phd topics in mobile computing

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Mobile Computing

Computer scientists introduce innovative new work at annual conferences.  The Mobile Computing research community expands the state of the art at these, the field's most prestigious and selective conferences:

ACM Annual International Conference on Mobile Computing and Networking (MobiCom)

ACM Conference on Embedded Networked Sensor Systems (SenSys)

ACM International Conference on Mobile Systems, Applications, and Services (MobiSys)

ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc)

Mobile systems research focuses on the design and implementation of next-generation systems for mobile devices.  Research topics include mobile data management, wireless networks, sensing systems, static analysis and instrumentation for mobile apps, mobile image and video analytics, and secure and low-power hardware for mobile devices.

CSE Research Labs and Groups

Affiliated faculty.

113I Davis Hall

Phone: (716) 645-1590

[email protected]

Research Topics: Wireless systems; mobile computing; Internet of Things (IoT); wireless sensing; machine learning

106 Davis Hall

Phone: (716) 645-2670

[email protected]

Research Topics: Mobile sensor networks; robot networks; networked embedded systems; mobile computing; wireless networks; embedded operating systems

336 Davis Hall

Phone: (716) 645-1601

[email protected]

Research Topics: Emerging biometrics; human-computer interaction and cognitive science; cyber-physical security; neuromorphic computing; mobile and wearable computing; low-power sensing

211 Capen Hall

Phone: (716) 645-1597

[email protected]

Research Topics: Databases; programming languages; user interfaces for data science; scalable compilers; managing uncertainty in data; data structures; healthy and equitable food systems

332 Davis Hall

Phone: (716) 645-4754

[email protected]

Research Topics: Optimization; deep learning; foundation models; computer vision and machine learning

312 Davis Hall

Phone: (716) 645-4751

[email protected]

Research Topics: Future generation communication systems; optical networks; survivable/resilient protocols; wireless and mobile networks (including sensor networks)

338K Davis Hall

Phone: (716) 645-3186

[email protected]

Research Topics: Computer architecture; embedded technologies; VLSI circuits and systems; wireless networks and security

330 Davis Hall

Phone: (716) 645-4748

[email protected]

Research Topics: Embedded and cyber-physical systems; body sensor networks; biomedical signal analytics; telemedicine; human-computer interaction

338B Davis Hall

Phone: (716) 645-1595

[email protected]

Research Topics: Hardware-assisted security; system security; usable security; cybercrime analysis

Research Ranking

UB's institutional reputation in the field of computer science has improved dramatically over the last decade.  By the most valid measure, our national ranking has risen from 50th to 29th .

The Computing Research Association (CRA) is a leading computer science advocacy organization whose mission is to unite industry, academia, and government.  The CRA recommends CSRankings: Computer Science Rankings as the best institutional ranking agency, preferring it over the traditional standard, the US News and World Report Best Graduate Schools report.

The CRA supports the CSRankings report because its evaluative criteria meet the ' GOTO ' standard:

Good data .  Data have been cleaned and curated.

Open .  Data available, regarding attributes measured, at least for verification.  

Transparent .  Process and methodologies are entirely transparent.

Objective .  Based on measurable attributes.

For more details, see Department Rankings , by H.V. Jagadish .

According to CSRankings (2008-2018) , UB's 10-year computer science institutional ranking is #50 in the nation, tied with the University of Central Florida and the University of North Carolina .

According to CSRankings (2015-2018) , UB's three-year computer science institutional ranking is #34 in the nation, making our peer institution the University of Virginia .

According to CSRankings (2017-2018) , UB's one-year computer science institutional ranking is #29 in the nation, putting us in company with Harvard , Johns Hopkins , Ohio State , and Penn State .

Research Highlights

Wenyao Xu leads an NSF-funded program that detects 3D printing data security vulnerabilities by using smart phones to analyze electromagnetic and acoustic waves.  Kui Ren and Chi Zhou are co-authors.

Ken Regan develops algorithms that detect cheating in chess games.  His software compares a player's moves to a database of the player's typical gameplay, then makes an assessment of the statistical likelihood of cheating.  Dr. Regan frequently consults at international chess matches.

Professor and Chair Chunming Qiao leads Instrument for Connected and Autonomous Vehicle Evaluation and Experimentation (iCAVE2) —a multidisciplinary academic-industrial partnership that's helping to make self-driving cars safer, cleaner, and more efficient.

An article on PhysOrg reports UB has received a $584,469 grant from the National Science Foundation to create a tool designed to work with the existing computing infrastructure to boost data transfer speeds by more than 10 times, and quotes Tevfik Kosar , associate professor of computer science.

Karthik Dantu owns the vision component of the RoboBee Initiative , led by the National Science Foundation and Harvard University.  The "eyes" that Dr. Dantu is integrating are laser-powered sensors that enable the mechanical bees to orient themselves in space.

Proposed software solution could extend battery life, reduce energy consumption.

Wenyao Xu created AutoDietary — software that tracks the unique sounds produced by food as people chew it.  AutoDietary, placed near the throat by a necklace delivery system developed at China's Northeastern University, helps users measure their caloric intake.

Recognitions

Deborah Chung and Venu Govindaraju will receive the UB President’s Medal,   recognizing extraordinary service to the university.

Jinjun Xiong, SUNY Empire Innovation Professor in the Department of Computer Science and Engineering, has been elevated to fellow in the Institute of Electrical and Electronics Engineers. 

Awards acknowledge and provide system-wide recognition for consistently superior professional achievement and the ongoing pursuit of excellence.

Atri Rudra has been named the first Katherine Johnson Chair in Artificial Intelligence, which was established by a generous gift from computer science alums D. Sivakumar, PhD ’96, and Uma Mahadevan, PhD ’98.

Siwei Lyu, SUNY Empire Innovation Professor in the Department of Computer Science and Engineering, is one of the world’s leading experts on deepfakes.

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Phd project topics in mobile computing.

Mobile computing is a generic term referring to a variety of devices that enable people to access data from everywhere at any time with or without the Internet. It allows people to exchange data, voice, and video over the Internet using a mobile device. With the continuous growth of smartphone application usage, the threat of malware has increased in terms of abusing the premium service, private information theft, device fingerprinting, and rooting the smartphone to launch the attacks. With the increased utilization of financial service-based mobile applications on smartphones, security and privacy become significant constraints. Hence, smartphone users demand potential defense mechanisms for privacy and security concerns while accessing third-party applications. Moreover, the tremendous increase of the mobile applications in the application market, such as Google Play and the Apple App store, significantly increase the application discovery for mobile users. It is essential to build systems for facilitating the discovery of mobile applications from the immense amount of choices. 5G wireless technology has significantly improved the performance and efficiency by delivering high-speed data, very ultra-low latency, high reliability, increased availability, massive network capacity, and user experience.

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PhD in Computer Science

The PhD in Computer Science is a small and selective program at Pace University that aims to cultivate advanced computing research scholars and professionals who will excel in both industry and academia. By enrolling in this program, you will be on your way to joining a select group at the very nexus of technological thought and application.

Learn more about the PhD in Computer Science .

Forms and Research Areas

General forms.

• PhD Policies and Procedures Manual – The manual contains all the information you need before, during, and toward the end of your studies in the PhD program.
• Advisor Approval Form (PDF) – Completed by student and approved by faculty member agreeing to the role as advisor.
• Committee Member Approval Form (PDF) – Completed by student with signatures of each faculty member agreeing to be on dissertation committee.
• Change in Advisor or Committee Member Approval Form (PDF) – Completed by student with the approval of new advisor or committee member. Department Chair approval needed.
• Qualifying Exam Approval Form (PDF) – Complete and return form to the Program Coordinator no later than Week 6 of the semester.

Dissertation Proposal of Defense Forms

• Application for the Dissertation Proposal of Defense Form (PDF) – Completed by student with the approval of committee members that dissertation proposal is sufficient to defend. Completed form and abstract and submitted to program coordinator for scheduling of defense.
• Dissertation Proposal Defense Evaluation Form (PDF) – To be completed by committee members after student has defended his dissertation proposal.

Final Dissertation Defense Forms

• Dissertation Pre- Defense Approval Form (PDF) – Committee approval certifying that the dissertation is sufficiently developed for a defense.
• Dissertation Defense Evaluation Form (PDF) – Completed by committee members after student has defended his dissertation.

All completed forms submitted to the program coordinator.

Research Areas

The Seidenberg School’s PhD in Computer Science covers a wealth of research areas. We pride ourselves on engaging with every opportunity the computer science field presents. Check out some of our specialties below for examples of just some of the topics we cover at Seidenberg. If you have a particular field of study you are interested in that is not listed below, just get in touch with us and we can discuss opportunities and prospects.

Some of the research areas you can explore at Seidenberg include:

Algorithms And Distributed Computing

Algorithms research in Distributed Computing contributes to a myriad of applications, such as Cloud Computing, Grid Computing, Distributed Databases, Cellular Networks, Wireless Networks, Wearable Monitoring Systems, and many others. Being traditionally a topic of theoretical interest, with the advent of new technologies and the accumulation of massive volumes of data to analyze, theoretical and experimental research on efficient algorithms has become of paramount importance. Accordingly, many forefront technology companies base 80-90% of their software-developer hiring processes on foundational algorithms questions. The Seidenberg faculty has internationally recognized strength in algorithms research for Ad-hoc Wireless Networks embedded in IoT Systems, Mobile Networks, Sensor Networks, Crowd Computing, Cloud Computing, and other related areas. Collaborations on these topics include prestigious research institutions world-wide.

Machine Learning In Medical Image Analysis

Machine learning in medical imaging is a potentially disruptive technology. Deep learning, especially convolutional neural networks (CNN), have been successfully applied in many aspects of medical image analysis, including disease severity classification, region of interest detection, segmentation, registration, disease progression prediction, and other tasks. The Seidenberg School maintains a research track on applying cutting-edge machine learning methods to assist medical image analysis and clinical data fusion. The purpose is to develop computer-aided and decision-supporting systems for medical research and applications.

Pattern recognition, artificial intelligence, data mining, intelligent agents, computer vision, and data mining are topics that are all incorporated into the field of robotics. The Seidenberg School has a robust robotics program that combines these topics in a meaningful program which provides students with a solid foundation in the robotics sphere and allows for specialization into deeper research areas.

Cybersecurity

The Seidenberg School has an excellent track record when it comes to cybersecurity research. We lead the nation in web security, developing secure web applications, and research into cloud security and trust. Since 2004, Seidenberg has been designated a Center of Academic Excellence in Information Assurance Education three times by the National Security Agency and the Department of Homeland Security and is now a Center of Academic Excellence in Cyber Defense Education. We also secured more than $2,000,000 in federal and private funding for cybersecurity research during the past few years.

Pattern Recognition And Machine Learning

Just as humans take actions based on their sensory input, pattern recognition and machine learning systems operate on raw data and take actions based on the categories of the patterns. These systems can be developed from labeled training data (supervised learning) or from unlabeled training data (unsupervised learning). Pattern recognition and machine learning technology is used in diverse application areas such as optical character recognition, speech recognition, and biometrics. The Seidenberg faculty has recognized strengths in many areas of pattern recognition and machine learning, particularly handwriting recognition and pen computing, speech and medical applications, and applications that combine human and machine capabilities.

A popular application of pattern recognition and machine learning in recent years has been in the area of biometrics. Biometrics is the science and technology of measuring and statistically analyzing human physiological and behavioral characteristics. The physiological characteristics include face recognition, DNA, fingerprint, and iris recognition, while the behavioral characteristics include typing dynamics, gait, and voice. The Seidenberg faculty has nationally recognized strength in biometrics, particularly behavioral biometrics dealing with humans interacting with computers and smartphones.

Big Data Analytics

The term “Big Data” is used for data so large and complex that it becomes difficult to process using traditional structured data processing technology. Big data analytics is the science that enables organizations to analyze a mixture of structured, semi-structured, and unstructured data in search of valuable information and insights. The data come from many areas, including meteorology, genomics, environmental research, and the internet. This science uses many machine learning algorithms and the challenges include data capture, search, storage, analysis, and visualization.

Business Process Modeling

Business Process Modeling is the emerging technology for automating the execution and integration of business processes. The BPMN-based business process modeling enables precise modeling and optimization of business processes, and BPEL-based automatic business execution enables effective computing service and business integration and effective auditing. Seidenberg was among the first in the nation to introduce BPM into curricula and research.

Educational Approaches Using Emerging Computing Technologies

The traditional classroom setting doesn’t suit everyone, which is why many teachers and students are choosing to use the web to teach, study, and learn. Pace University offers online bachelor's degrees through NACTEL and Pace Online, and many classes at the Seidenberg School and Pace University as a whole are available to students online.

The Seidenberg School’s research into new educational approaches include innovative spiral education models, portable Seidenberg labs based on cloud computing and computing virtualization with which students can work in personal enterprise IT environment anytime anywhere, and creating new semantic tools for personalized cyber-learning.

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PhD in Computing & Data Sciences

For more information and to get in touch, please visit the Faculty of Computing & Data Sciences website .

The PhD program in Computing & Data Sciences (CDS) at Boston University prepares its graduates to make significant contributions to the art, science, and engineering of computational and data-driven processes that are woven into all aspects of society, economy, and public discourse, leading to solution of problems and synthesis of knowledge related to the methodical, generalizable, and scalable extraction of insights from data as well as the design of new information systems and products that enable actionable use of those insights to advance scholarly as well as practical pursuits in a wide range of application domains.

Applicants to the PhD program in CDS are expected to have earned a bachelor’s or master’s degree in one of the methodological or applied disciplines relating to the computational and data-driven areas of scholarship in CDS. They are expected to possess basic mathematical and computational competencies, and demonstrable propensity for cross-disciplinary work. To accommodate a diversity of student backgrounds and preparations, a holistic admission review is utilized. As such, GRE tests and scores are not required, but could be optionally provided and considered as part of the applicant’s portfolio, which may also include evidence of prior, relevant preparation, including creative works, software code repositories, etc. Special attention will be paid to applicants from underrepresented minorities in computing and data science disciplines.

Completion of the PhD degree in CDS requires coursework covering breadth and depth topics spanning the foundational, applied, and sociotechnical dimensions of computing and data science; completion of research rotations that expose students to ongoing projects; completion of a cohort-based training on ethical and responsible computing; and successful proposal and defense of a doctoral thesis.

For their thesis work, and in preparation for careers in academia, industry, and government, CDS PhD students are expected to pursue theoretical, applied, or empirical studies leading to solution of new problems and synthesis of new knowledge in a topic area determined in consultation with their mentors and collaborators, which may include external researchers and practitioners in industrial and academic research laboratories.

Upon completion of the program, students will be prepared to pursue careers in which they lead independent cutting-edge research and development agendas, whether in academia (by teaching, mentoring, and supervising teams of students engaged in scholarly pursuits) or in industry (by collaborating, directing, and effectively managing diverse teams of practitioners working at the forefront of industrial R&D).

Learning Outcomes

The following learning outcomes explain what you will be able to do at the end of your time as a CDS PhD candidate, as a result of earning your degree.

• Exhibit a strong grasp of the principles governing the design and implementation of the methodological approaches for computational and data-driven inquiry.
• Identify the literature and demonstrate mastery of the compendium of works relevant to a well-defined area of research inquiry in computing and data sciences.
• Show capacity to engage meaningfully in and materially contribute to multidisciplinary research and development endeavors.
• Evidence a strong sense of social and professional responsibility for decisions related to the development and deployment of computational and data-driven technologies.
• Assess and argue the merits, limitations, and possibilities of new research work in a specialized area at the level commensurate with standards of scholarly venues in that area.
• Formulate and pursue a research agenda leading to solution of new problems and to synthesis of new knowledge shared through peer-reviewed publications.

Course Requirements

Sixteen semester courses (64 credits) are required for post-BA/BS students and 12 semester courses (48 credits) are required for post-MA/MS students. Students with prior graduate work (including master’s degrees) may be able to transfer up to two courses (8 credits) as long as these credits were not used to fulfill matriculation requirements, upon the recommendation of the student’s academic advisor, and subject to approval by the Associate Provost for CDS.

Of the 16 courses, up to 3 undergraduate courses (12 credits) may be counted as background courses, selected in consultation with the student’s academic advisor and subject to approval by the Associate Provost for CDS. Other than these remedial courses, all other courses must be graduate-level courses or directed studies offered by CDS or by other BU departments in order to satisfy the following degree requirements.

The methodology core requirement ensures that students possess foundational knowledge and competencies in a subset of the following eight methodological areas of CDS:

• Mathematical Foundations of Data Science
• Statistical Modeling and Inference
• Efficient and Scalable Algorithms
• Predictive Analytics and Machine Learning
• Combinatorial Optimization and Algorithms
• Computational Complexity
• Programming and Software Design
• Large-scale Data Management

A list of courses that can be used to satisfy these competencies will be maintained on the website for CDS. Students who start their PhD program in CDS are expected to satisfy at least six of these competencies. Students who complete the course requirement for the PhD program in a cognate discipline are expected to satisfy at least four of these competencies.

The subject core requirement ensures that students establish depth in one area of inquiry that is aligned with either the methodological or applied dimensions of CDS. Subject areas are defined by groups of CDS faculty members working in related disciplinary and/or interdisciplinary areas of research who expect their prospective students to have enough depth in the subset of topics to enable them to tackle doctoral-level research in these topics. The set of subject areas as well as a list of preapproved graduate-level courses offered in CDS or elsewhere at BU that can be used to satisfy each subject area will be maintained on the website for CDS.

During the first two years in the program, all PhD candidates in CDS must complete three cohort-based requirements; namely, a two-semester training course (4 credits) covering various aspects of the responsible and ethical conduct of computational and data-driven research, a two-semester doctoral seminar (4 credits) that introduces them to the research portfolios of CDS faculty members as well as to the skills and capacities needed for success as scholars, and at least two research or lab rotations (8 credits) that expose them to real-world computational and data-driven applications that must be tackled through effective multidisciplinary teamwork.

A cumulative GPA not less than 3.3 must be maintained for all non-Pass/Fail courses taken to satisfy the methodology core requirement and the subject core requirement of the degree, excluding any background courses and excluding any transferred credits. Students who receive grades of B– or lower in any three courses taken at BU will be withdrawn from the program.

Language Requirement

There is no foreign language requirement for the PhD degree in CDS.

Qualifying Examinations

No later than the end of the sixth semester (third year), all PhD candidates in CDS must pass a public oral examination administered by a committee of three faculty members, chaired by the student’s research (and presumptive thesis) advisor or coadvisors. The oral area exam is meant to establish the student mastery of a well-defined area of scholarship and preparedness to pursue original research in that area. The oral area examination may require completion of a survey paper or completion of a pilot project ahead of the examination. The scope as well as any additional requirements needed for the examination should be developed in consultation with and approval of the research advisor(s), at least one semester prior to the exam.

Dissertation and Final Oral Examination

Candidates shall demonstrate their abilities for independent study in a dissertation representing original research or creative scholarship. A prospectus for the dissertation must be successfully defended no later than the end of the eighth semester (fourth year) of study.

Candidates must undergo a final oral examination no later than the end of the 10th semester (fifth year) of study in which they defend their dissertation as a valuable contribution to knowledge in their field and demonstrate a mastery of their field of specialization in relation to their dissertation.

Both the prospectus and final dissertation must be administered by a dissertation committee of at least three readers (including the dissertation advisor or coadvisors) and chaired by a CDS faculty member who is not one of the readers.

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• Data Science for Good
• Impact Labs & Co-Labs
• BS in Data Science
• MS in Data Science
• PhD in Computing & Data Sciences
• Minor in Data Science

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Home » PhD Research Topics in Mobile Computing

PhD Research Topics in Mobile Computing

           Are you guys excited to know about the significant research topics in the field of mobile computing? Then stay tuned with this article!!! Our technical professionals have enlisted the notable research notions based on mobile computing for your reference in the following.

• SDN / NFV mobile communication
• Physical layer mobile communication
• Quantum mobile communication
• Containerized mobile services
• Mobile VNFs orchestration

Mobile Computing Projects

       For your ease, we have addressed some research projects based on mobile computing which are implemented in recent times.

• Resource allocation and path planning in mobile edge computing using joint optimization
• Equilibrium model for elasticity debt analytics exploitation in green mobile cloud computing
• Image retrieval in mobile edge computing using cloud based feature extraction technique
• Enhancing mobile cloud computing cloudlets using resource scheduling and robust computation offloading
• Resourceful social networks in mobile edge computing through fuzzy reasoning routing forwarding algorithm
• Energy efficient mobile cooperative computing for exploitation non causal CPU state information
• Mobile edge computing based NOMA for reduction of transaction time difference
• Development of energy and delay constrained mobile edge computing environments using multi objective computation sharing
• Execution of mobile edge computing systems using cost effective data accumulation approach
• Service placement and joint network selection in mobile edge computing using online framework
• Provision of QoS in mobile cloud computing through crowdsourcing technique
• Resilient access management in mobile IoT for leveraging edge computing
• UAV assisted mobile edge computing based computing resource allocation strategy using biological evolutionary algorithm
• Two phase game theoretical approach for NOMA mobile edge computing
• Mobile to wired offloading computing execution for edge computing system
• Enhancement of mobile edge computing using interference aware game theoretic device allocation
• Design of mobile computing devices & deep leaning based handwritten character recognition system
• Three tier mobile computing networks using cooperative task offloading
• Heterogeneous network based three tier computing in energy efficient mobile edge computing

         The research scholars can make call to us to clarify your doubts and our research professionals will provide the appropriate guidance

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Cloud computing has suddenly seen a spike in employment opportunities around the globe with tech giants like Amazon, Google, and Microsoft hiring people for their cloud infrastructure. Before the onset of cloud computing, companies and businesses had to set up their own data centers, allocate resources and other IT professionals thereby increasing the cost. The rapid development of the cloud has led to more flexibility, cost-cutting, and scalability. 

The Cloud Computing market its an all-time high with the current market size at USD 371.4 billion and is expected to grow up to USD 832.1 billion by 2025! It’s quickly evolving and gradually realizing its business value along with attracting more and more researchers, scholars, computer scientists, and practitioners. Cloud computing is not a single topic but a composition of various techniques which together constitute the cloud. Below are 10 the most demanded research topics in the field of cloud computing:

1. Big Data

Big data refers to the large amounts of data produced by various programs in a very short duration of time. It is quite cumbersome to store such huge and voluminous amounts of data in company-run data centers. Also, gaining insights from this data becomes a tedious task and takes a lot of time to run and provide results, therefore cloud is the best option. All the data can be pushed onto the cloud without the need for physical storage devices that are to be managed and secured. Also, some popular public clouds provide comprehensive big data platforms to turn data into actionable insights. 

DevOps is an amalgamation of two terms, Development and Operations. It has led to Continuous Delivery, Integration, and Deployment and therefore reducing boundaries between the development team and the operations team. Heavy applications and software need elaborate and complex tech stacks that demand extensive labor to develop and configure which can easily be eliminated by cloud computing. It offers a wide range of tools and technologies to build, test, and deploy applications with a few minutes and a single click. They can be customized as per the client requirements and can be discarded when not in use hence making the process seamless and cost-efficient for development teams.

3. Cloud Cryptography

Data in the cloud is needed to be protected and secured from foreign attacks and breaches. To accomplish this, cryptography in the cloud is a widely used technique to secure data present in the cloud. It allows users and clients to easily and reliably access the shared cloud services since all the data is secured using either the encryption techniques or by using the concept of the private key. It can make the plain text unreadable and limits the view of the data being transferred. Best cloud cryptographic security techniques are the ones that do not compromise the speed of data transfer and provide security without delaying the exchange of sensitive data. 

4. Cloud Load Balancing

It refers to splitting and distributing the incoming load to the server from various sources. It permits companies and organizations to govern and supervise workload demands or application demands by redistributing, reallocating, and administering resources between different computers, networks, or servers. Cloud load balancing encompasses holding the circulation of traffic and demands that exist over the Internet. This reduces the problem of sudden outages, results in an improvement in overall performance, has rare chances of server crashes, and also provides an advanced level of security. Cloud-based servers farms can accomplish more precise scalability and accessibility using the server load balancing mechanism. Due to this, the workload demands can be easily distributed and controlled.

5. Mobile Cloud Computing

It is a mixture of cloud computing, mobile computing, and wireless network to provide services such as seamless and abundant computational resources to mobile users, network operators, and cloud computing professionals. The handheld device is the console and all the processing and data storage takes place outside the physical mobile device. Some advantages of using mobile cloud computing are that there is no need for costly hardware, battery life is longer, extended data storage capacity and processing power improved synchronization of data and high availability due to “store in one place, accessible from anywhere”. The integration and security aspects are taken care of by the backend that enables support to an abundance of access methods. 

6. Green Cloud Computing

The major challenge in the cloud is the utilization of energy-efficient and hence develop economically friendly cloud computing solutions. Data centers that include servers, cables, air conditioners, networks, etc. in large numbers consume a lot of power and release enormous quantities of Carbon Dioxide in the atmosphere. Green Cloud Computing focuses on making virtual data centers and servers to be more environmentally friendly and energy-efficient. Cloud resources often consume so much power and energy leading to a shortage of energy and affecting the global climate. Green cloud computing provides solutions to make such resources more energy efficient and to reduce operational costs. This pivots on power management, virtualization of servers and data centers, recycling vast e-waste, and environmental sustainability. 

7. Edge Computing

It is the advancement and a much more efficient form of Cloud computing with the idea that the data is processed nearer to the source. Edge Computing states that all of the computation will be carried out at the edge of the network itself rather than on a centrally managed platform or the data warehouses. Edge computing distributes various data processing techniques and mechanisms across different positions. This makes the data deliverable to the nearest node and the processing at the edge. This also increases the security of the data since it is closer to the source and eliminates late response time and latency without affecting productivity.

8. Containerization

Containerization in cloud computing is a procedure to obtain operating system virtualization. The user can work with a program and its dependencies utilizing remote resource procedures. The container in cloud computing is used to construct blocks, which aid in producing operational effectiveness, version control, developer productivity, and environmental stability. The infrastructure is upgraded since it provides additional control over the granular activities over the resources. The usage of containers in online services assists storage with cloud computing data security, elasticity, and availability. Containers provide certain advantages such as a steady runtime environment, the ability to run virtually anywhere, and the low overhead compared to virtual machines. 

9. Cloud Deployment Model

There are four main cloud deployment models namely public cloud, private cloud, hybrid cloud, and community cloud. Each deployment model is defined as per the location of the infrastructure. The public cloud allows systems and services to be easily accessible to the general public. Public cloud could also be less reliable since it is open to everyone e.g. Email. A private cloud allows systems and services to be accessible inside an organization with no access to outsiders. It offers better security due to its access restrictions. Hybrid cloud is a mixture of private and public clouds with the critical activities being performed using private cloud and non-critical activities being performed using the public cloud. Community cloud allows system and services to be accessible by a group of an organization.

10. Cloud Security

Since the number of companies and organizations using cloud computing is increasing at a rapid rate, the security of the cloud is a major concern. Cloud computing security detects and addresses every physical and logical security issue that comes across all the varied service models of code, platform, and infrastructure. It collectively addresses these services, however, these services are delivered in units, that is, the public, private, or hybrid delivery model. Security in the cloud protects the data from any leakage or outflow, theft, calamity, and removal. With the help of tokenization, Virtual Private Networks, and firewalls data can be secured. 

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Mobile Cloud Computing PhD Thesis

              Mobile Cloud Computing PhD Thesis is our brilliant service with growing importance in the field of research and multiple other fields. Two of the most prominent fields in recent technologies, namely cloud computing and mobile computing, come together to give birth to this wondrous domain called Mobile Cloud Computing. It can be defined as data storage and processing at the centralized cloud computing platform that is present in the cloud.

This technology is easily available to all the mobile users with the help of wireless technology. Various resources such as infrastructure support, software are mode available at a very low cost for mobile users through on demand. It minimises the cost and maximise the performance and energy. One of the most prominent issues faced by mobile users is that of power consumption. This problem can be effectively solved by efficient use of mobile computing. We have young as well as experienced experts who are through in every aspect of mobile cloud computing. Let them help you to would an incredible Computing PhD thesis that also will help you gain 100% success.

            Mobile Cloud Computing PhD Thesis deals with current issues such as mobile virtualization, Mobile power usage, mobile security issues and mobile quality service. Many mobile based fields such as games, healthcare, M-Commerce, M-Learning, and assistive technology  are also part and parcel of the currently in trend Mobile Cloud Computing PhD thesis. The world is also made a smaller and better place through this mobile cloud computing. Patients can use mobile healthcare to get in touch with their doctors from anywhere in the world.

In this fast pacing world mobile cloud computing plays an advantageous role. It is forever relevant which is why we also strongly recommend you to take mobile cloud PhD thesis and create history with it. Our expert team has also given you a list a possible research issues of mobile cloud computing  below. Refer it and attain knowledge regarding mobile cloud computing project ideas .

                      …” Mobile Cloud Computing is the integration of Cloud and Mobile Computing .  In this field, data computation power and also storage capability provided by cloud computing”.

Major Issues in Mobile Cloud Computing

• Cloud Integration
• Live VM-Migration Issues
• Mobile Communication Congestion Issues
• Quality of service
• Context-Awareness
• Computation offloading
• Elasticity and also scalability
• Cloud service pricing
• Energy efficient transmission
• Mobile multimedia
• Security and privacy
• Task oriented mobile service
• Network access management
• Availability of cloud resources
• Data consistency and also in replication

Development Tools and Software

• Kony Studio’s
• AWS Mobile Hub
• Agile tools
• And also in Code anywhere

Description of the Tools and Software

• Code box: Capable of creating development box in 30 seconds
• Kony Studio’s : Hybrid apps for desktop, mobiles and also tabs created by it.
• AWS Mobile Hub: AWS mobile apps can be built using it.
• Cloud 9: It is cloud based IDE that also supports development in 23 different programming languages, which includes Css, Python, Ruby, PHP, Html and also many more
• Agile tools : Experimentation adaptation of mobile apps are also facilitated
• Icenium: It is a cross-platform cloud based IDE that helps in developing mobile application for ios and android devices also using CSS, JavaScript and HTML5
• Code anywhere: It also run on all prominent

Other Cloud Simulators

• WorkflowSim
• RealCloudSim

Protocols/Algorithms used in MCC

• Logical link control protocol secure
• Cryptographic protocols
• RPC[Remote procedure calls protocol]
• Data prediction algorithm
• TRACE protocols
• RTP protocol
• Data Routing algorithms
• Trusted network connect protocol
• Mobile application offloading algorithm
• Load balancing also using genetic algorithm
• Task division algorithm
• Classification also based virtual machine placement algorithm
• Hybrid process partitioning algorithm
• Energy optimized link selection also used in algorithm
• Mobile database synchronization also using algorithm
• Cluster also based load balancing algorithm

         Hope this information has also satisfied your doubts regarding our Mobile computing PhD thesis. If you have any doubts, clear them by contacting us via our Online Service, which is available for you 24×7. Take out your hands to build an amazing platform for you.  We are also the sculptures of your beautiful future…

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Top 9 Edge Computing Research Topics

In simple terms, the distributed computing model that performs local computations for a particular geographical location is mainly referred to as edge computing . It focuses on both data computation and storage at endpoints . Majorly, it has the objective to enhance response time, bandwidth, and resource provisioning . 

Through this article, you can know the latest Edge Computing Research Topics, challenges, applications, technologies, etc.!!!

What is meant by edge computing?

A new distributed technique called edge computing is introduced to replace the centralized data processing techniques . It has several in-built features and open-space architecture. Further, it guarantees enhanced performance by utilizing the internet of things and mobile computing technologies . Overall, it distributes the services and resources to edge devices at high speed .   

How does edge computing works?

Generally, the majority of computation works are performed at edge devices (PCs/servers). In the traditional system, the computation works are performed at data centres. Some of the edge computing works in a distributed environment are computing power reduction, data fragmentation, pushing data , etc. It particularly focuses on users that currently using commercial internet application services . For better understanding, here we have given you a few main reasons for edge computing utilization . 

Why edge computing?

• Edge computing securely process sensitive data with the help of the security layer 
• It does not process the data in the public cloud for security reasons and fast accessibility
• It allows the acceleration of real-time data streaming without delay
• It cut-offs the waiting time and enable fast replies in smart applications
• It minimizes the cost of application accessibility from a remote area
• It minimizes the utilization of internet bandwidth
• It enables large-scale data processing in generated source place itself

Now, we can see the important properties to craft edge computing research topics . These properties play a significant role in edge computing developments. Also, these properties need extra concern while developing edge computing projects. Our research team has a strong basement in edge computing to support you in every edge of the edge computing. Similarly, our developers know all smart approaches to enhance the below properties in any edge computing project for improvised results. 

What are the unique properties of edge computing?

• It frequently keep record of connected entities locations due to mobility
• It effectively collect and process the large-scale data at edge devices through edge infrastructure
• It enables to incorporate with service control system
• It is able to work continuously and create alert to respective edges in the case of issues
• It also provide alter service in the case of insecurity over edge network
• It uses single and trustable source to monitor the edges to keep record of their actions / events
• It maintains the actions in schedule basis for remote monitoring
• It allows to sense and manage the environment
• It enables to monitor and track the locations of edge devices from remote place
• It generates live video in edge devices through edge facility
• It enables to identify the physical entity accessibility, environ conditions, entity mobility, etc.
• It supports accessibility of edge network for remote control and maintenance
• It provides architecture that handle network asserts, distributed environ, different data type while large-scale data collection and processing
• It allows users to track the frequent changing asserts movements
• It enables to monitor the whole large-scale edge environ
• It ensures no cost and no impact on monitoring while new devices are deployed to network
• It offers cooling data, abstraction layer, environmental power in regardless of edge device type
• It incorporates best service management. For instance: When SLA is agreed, it provide complete edge infrastructure view to DCIM products
• It reduces the storage that automatically created while monitoring edge devices based on its vendor / type
• It holds the edge locations with data throughout the network functioning. Further, it do comparative study among good and bad performing locations
• It helps to track the environmental changes from normal state which may cause problems
• It uses SLA to manage the impact of environmental changes and controls the negative impact of environmental changes

Next, we can see the significant classification of the edge computing models . In this classification, we majorly covered research essentials for the edge computing field. As well, the classifications are computing devices, main objectives, communication technologies, computational order, computing models, applications, and supportive technologies . For your reference, we have given you only a few instances. Likewise, we facilitate you in other technologies. 

Taxonomy of Edge Computing Models

• Base Stations
• Switch / Routers
• End Users / Devices
• Edge Servers
• Main Cloud Servers
• Delay Reduction
• Carbon Footprint Reduction
• Bandwidth Preservation
• Backhaul Traffic Minimization
• Utility Improvisation
• Increasing Number of Executed Tasks          
• 3G / 4G / 5G / 5G Beyond
• Mobile Edge Computing

Fog Computing

• Health Care and Medical Analysis
• IoT Smart Grids
• Smart Farming
• Smart Transportation
• Supply Chain Management
• Renewable Energy Saving System
• Web-based Retail Shopping
• Smart Gas and Oil Industries
• Software Development Networking
• Network Function Virtualization
• Smart Mobile Technologies
• Enriched Network Entities and Resources

Edge computing has so many advantages compared to other computing technologies . Since it generates data and performs the computation in edge devices without using main servers/datacenters . As a result, it enables fast data accessibility and high performance . So, it is widely spread in several research fields as follows, 

• Internet Of Things
• Vehicular Networks
• Image Processing

Once you connect with us, we provide more real-time application Edge Computing Research Topics in your interested edge computing areas.        

Applications and Use cases for Edge Computing

• Global Positioning System
• VoIP and Video
• Cryptography
• Video Transmission
• Video-to-Text
• Speech-to-Text
• Language Translation
• Text-to-Speech
• Environmental Monitoring
• Vehicle-to-Everything Communication
• Vehicle-to-Vehicle Communication
• Face Recognition
• Bandwidth Signaling
• Augmented Reality
• Direct Routing
• Dedicated Enterprise Networks
• Social Events

Next, we can see the current research challenges of edge computing . Although this field is technically advancing fast, it has some research challenges in real-world development and deployment. The below challenges are collected from our recent edge computing review. We are good not only in collecting recent challenges but also in generating suitable research solutions . When you connect with us, we provide you best-fitting research solutions for these challenges and others. 

Top 9 Interesting Edge Computing Research Topics

• Infrastructure and Application Level Designing
• End Nodes Mobility Management
• Geolocation-Aware Data Distribution
• Batch Processing with Real-Time Processing Comparison
• Mobility and Resource Management
• Edge Network Expandability and Scalability
• Context-Aware Edge Computing in Low Delay
• End Points Interoperability, Heterogeneity and Functionalities
• Cloud and Fog Layer Interaction through Edge Network

In traditional computing infrastructure, the increasing demands of heterogeneous endpoints fail to satisfy. At the same time, it satisfies the demand for quality of service at all levels. When the computing complexities of edge nodes increase, it makes it a hard choice for an infrastructure provider to allocate resources for edges .

Now, we can see in what way the edge computing model is enhanced to meet current technological advancements . A good edge computing model is required to solve maintenance complexities, bandwidth constraints, security threats, delay , etc. Further, a good edge computing model should enable you to perform the following, 

How to design an effective edge computing model?

• Ensure system security and privacy
• Enable scalability for adapting system requirements
• Handle workloads of all connected nodes in cloud
• Smoothly install the applications in all edge devices

In addition, we have also given you a few vital design techniques. From our experience, we found that the following techniques give the best result in designing an effective edge computing model. When you confirm your research problem/challenge on edge computing, then we provide suitable research solutions (techniques and algorithms) for your handpicked research problem. In the case of complexity, we smartly design our algorithm to crack the issues. 

Edge Computing Modelling Techniques

• Markov Chains
• Reliability Block Diagrams
• Reliability Graphs

Furthermore, we have listed you faster-growing technologies of edge computing . Currently, our handhold scholars are requesting project topics on these technologies. This list represents the current research areas of edge computing . We have an infinite number of edge computing research topics in the following areas. All our research topics are up-to-date with future scope . If you are curious to know about our innovations in the edge computing field , then contact us

Edge Computing Research Topics

• Edge computing with 5G
• Vehicular Networks (IoCV, IoV, V2X, VANET)
• Cellular and Heterogeneous Networks (LTE, 5G, 5G beyond and 6G)
• Internet of Things / Internet of Everything
• Cloud Computing, Grid Computing, Volunteer Computing, and Fog Computing

Software Defined Networks

Wireless sensor networks.

• Wireless Body Area Networks
• Augmented and Virtual Reality
• Robotics Monitoring and Control

Network Security

• Wireless Communications 

For your add-on benefits, here we have also given you the few most important research topics of edge computing . All these topics are acquired from our emerging technologies of edge computing . As well, we encourage our handhold scholars to bring to their creative research ideas. Further, we also provide you with more edge computing research topics and ideas in your interesting research areas . 

Latest Project Topics in Edge Computing

• Task Offloading and Scheduling
• Task Queue Management
• Resource (power and energy) management
• Security and Privacy of Devices and Edge Users
• Routing / Data Transmission
• Best Forwarder Selection
• Network Topology Management
• Optimum Edge Node Selection
• Clustering / Classification of Edge Nodes
• Network Management and Overhead Reduction 

When you have selected your research topic (i.e., problem and solutions), the next step is to select suitable development tools and technologies. All these tools are suggested by our experts to gain the best results in your edge computing project. Here, each tool has some special characteristics and purposes. So, it is necessary to analyze the tool before confirming your developing cloud computing simulation tools . When do your project with us, our developers will suggest to you appropriate development tools and technologies after a thorough project requirements examination? 

Simulation Tools for Edge Computing

• PureEdgeSim
• FogNetSim++
• EdgeCloudSim simulator

To sum up, we support you in the code implementation and thesis/dissertation phases of your edge computing study . Additionally, we provide novel Edge Computing Research Topics , proposal writing, report writing, paper writing, and paper publication services . Same as edge computing, we also extend our support in other related fields such as cloud computing, fog computing, mobile computing , grid computing, pervasive computing, fog-edge computing, cloud-edge computing, mobile edge computing, mobile cloud computing projects , cloud-fog computing,etc. We hope that you smartly use this opportunity to create a bond with us. 

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• Mobile Computing Thesis

Mobile computing is a method or methodology for developing, deploying, and hosting software products employing cloud computing services. A wireless strategy provides developers applications tailored to mobile customers without becoming constrained by the device’s operating system, processing, or storage capability. This article provides a complete picture of the mobile computing thesis where you will find all the essential research data related to mobile computing which are both automatic and updated. We will first start with an introduction to mobile computing  

Introduction of mobile computing

• Mobile Computing seems to be a broad word that describes the human ability to innovate ‘untethered,’ such that, when you are not actually attached to it, or when you are in a distant or movable (non-static) setting.
• In contemporary terms, the word has developed to mean that portable computing activities must be linked securely to and through the Internet or other networks.
• By the use of rechargeable batteries, transportable, and mobile communication and computing equipment, this connectivity integrates the smartphone to centralized data and mobile applications.
• Computers with wireless LAN or wireless WAN technologies, smartphones, wearable computers, and Personal Digital Assistants (PDAs) with Bluetooth and IRDA connections are all examples of this.
• We concentrate on strategy, development, execution, assessment, modeling, programming, and analytics in the context of mobile and social networking.
• The discipline of mobile computing encompasses communication services and portable computers, like laptop computers.
• In some aspects, the mobile computing subject emerged from work that began in the modern computing sector.

Usually, we provide complete data with regard to the basics and advanced theoretical and developmental aspects of mobile computing in the format and way that you prefer. In this regard, the following here are some of the trending areas of research in mobile computing in which we have delivered ample projects

• Ubiquitous and mobile computing
• Edge computing technology based on blockchain
• Mobile grid computing (middleware)
• Internet of things assisted by mobile computing technology
• Mobile cloud technology (on demand)
• Mobile computing based on machine learning
• Fog computing which is cloud-aware
• Mobile computing based on artificial intelligence

These are the most important topics of research in mobile computing . By choosing one of which as your mobile computing thesis you can have a better career. The opportunities are always wide in mobile computing as the technology is fast growing in recent years. Our experts are here to help you understand all major aspects of mobile computing. What are the important mobile computing issues?

Major issues in mobile computing

• Quality of service and cloud integration
• Context-aware system and mobile multimedia
• Offloading computation and migration issues in virtual machines
• Cost of cloud Service and efficiency of Energy transmission
• Congestion issues in mobile computing
• Scalability, privacy, integrity, and elasticity
• Mobile computing security and the network stability
• Constraints in protection and interoperability issues
• Network connection losses and inefficiency in bandwidth transmission
• Persistent interference shielding and constraints in energy consumption
• Replication and consistency in data management
• Cloud resource availability and management of network access
• Mobile services based on different tasks

These are the issues that we have handled in mobile computing more efficiently. In order to find the solutions to the mobile computing research problems that you are facing, get in touch with us through any means. Our technical support team will guide you in solving all the issues. What are the latest mobile computing technologies?

Latest mobile computing technologies

• Mobile system algorithm and models
• Analyzing the behavior of users in mobile computing applications
• Mobile system economics, incentives, and reputation
• Social network privacy and security
• Scalability and usability of mobile systems
• Mobile system applications and implementations
• Crowdsourcing, artificial and virtual reality
• Payment and advertisements displayed online using mobile computing technology
• Wearable computing and mobile networking (fog and edge computing)
• Mobile centric and location-based social networking services

Technically we help you in writing better codes and implementing them in real-time more effectively. Advanced project ideas and mobile computing thesis topics are available on our website. The recent mobile computing project topics that we have guided are available at your disposal. Check out the quality and standard of our services at any time. In this regard, we will now list out the major demands of quality thesis work.

Quality demands in thesis writing

• Strict adherence to technical terms usage
• Accuracy of data and updated references
• Usage of punctuation marks
• Avoiding grammatical and typo errors
• Following the standard format
• Style of writing and thesis structure

Generally, when you look at a successfully completed standard thesis in mobile computing , you can get a better idea and picture on developing the best one for you. For this purpose, you can reach out to our expert at any time. We will support you in all aspects of thesis writing efficiently. The following section describes how we support thesis writing.

Our Thesis Writing Support

• Selection of topic and data collection from standard literature sources
• Literature review and determining the research gaps
• Analyzing the problem statement
• Deriving proper methodologies and experimentation techniques
• Analysis and complete discussion about results
• Thesis inscription and correction

With separate teams of experts, developers, writers, and researchers, we are offering one of the most reliable, trusted, and authentic research guidance in mobile computing across the world. By providing a proper explanation of all aspects of the thesis we support you ultimately. The following are the major points about the thesis statement

• Exact description of the thesis topic
• Complete information of your essay
• Methods in which the claim is supported and developed
• Specifies your topic claim

Thus as a result a thesis statement should focus on the subject, claim, and points of support. We will help you in meeting all the requirements of a thesis statement. 

• Before you begin writing your thesis, check over all of the prerequisites with your supervisors.
• If the quantity of the final paper is specified, you’ll have to figure out the thesis’s other prerequisites.
• Fonts and spacing are likely to be relevant as well.
• Produce and maintain a list of references from the beginning and don’t leave any queries unresolved

While writing a thesis you need to remember some points. Through your teases, you need to tell your readers about your essay. With a proper introduction and a categorically developed essay, chronologically arranged points are especially useful. Creation, narration, and the structure of your essay must be academically acceptable. Finally, the conclusion must reiterate your thesis objective and address the issues in discussion. Since resolving the research issues is the major idea of any thesis. Here at the mobile computing thesis, you can get guidance on all these aspects. What are the technologies to be used in mobile computing?   

Technologies to be used in mobile computing

The following is a note on different aspects of Mobile edge computing and mobile cloud Computing

• Small scale moderate data-centric resources is the server hardware
• Wireless gateway technology, LTE , and Wi-Fi are the integrated cloud server locations
• The deployment is highly dense for use by enterprises, individuals, and vendors
• Requirement of planning and lightweight configuration is demanded
• Short distance between end-users
• Rare usage and congestion alleviation are the backhaul usages
• Hierarchy based control management of systems which are centralized and distributed
• It supports up to 10 MS latency
• Applications that have used computations and latency used Mobile edge computing which for instance include interactive gaming and autonomous driving
• Large scale high capacity data centers are the server hardware
• The server is installed at dedicated fields and buildings
• With proper planning and configuration mobile cloud Computing is utilized by IT companies
• The distance between end-users is usually very large
• Condition may arise due to frequent and backhaul usage
• Centralized control system management
• It supports more than 100 Ms latency
• Applications involving intensive calculations and latency tolerant which include mobile-based learning, commerce and health, and online social networking

More detailed explanations on the mobile computing technologies and various other technologies under the purview of mobile computing are available on our website on the mobile computing thesis. Also, check out our services on practical explanations and demonstrations in mobile computing. We have been supporting students and Research scholars from all top world universities in producing the best mobile computing works . What are the latest mobile computing concepts?

Latest concepts in mobile computing

• Compression of data and task offloading
• Clustering mobile networks and reducing data dimensionality
• Lightweight algorithms and encryption techniques
• Deduplication of data and distributed data storage systems

All of the strategies mentioned above are utilized to increase the energy efficiency of mobile computing. Each technique also includes a number of different methods and algorithms.

• Deduplication, for example, is a strategy for reducing the storage capacity required by an organization to save its content.
• Compression of data, on the other hand, is the process of lowering the size of a file by using specific methods.
• A study on efficient energy mobile computing, on the other hand, must include two or maybe more approaches in order to demonstrate its efficacy.

As a result, we constantly combine several techniques for a single thesis with separate crew assignments for mobile computing is one of our additional strategies. We also focus on integrating many systems without disrupting the thesis process. A thorough examination of the proposed approaches and their consequences is made by our experts. This has gained a huge reputation among researchers. We also provide the following facilities

• Mathematical derivation of the energy model, mobility mode, and workload model for the mobile computing environment under consideration.
• Experimentation with a variety of experimental settings (with more than one scenario)

Therefore you can reach out to our experts for all your research needs and thesis support in mobile computing. Get in touch with us to know more about the services that we offer. What are the recent mobile computing thesis and project topics?

Recent Project Topics in Mobile Computing

• An original methodology for Cost-Driven Method to Caching-as-a-Service in Web cloud on 5G Mobile Communications
• A novel strategy for Online Edge Server Dispatching from UAV-Mounted Edge Servers focused at Mobile-to-Mobile Edge Computing
• An effective functionality for Clustered VNs Functions Resource Allocation built on Context-Aware Grouping in 5G Edge Networks
• Mobile Cloudization Storytelling with an Innovative Mechanism: Contemporary Problems from an Optimization Perspective
• Current procedure for Efficient and Easy Offloading through Deep Reinforcement Learning built for Mobile Edge Video Computers
• A revolutionary innovation for Computation and Relaying based on Using Mobile Edge Computing intended at P2P Communications
• A modern function for Dynamic Response Scheduling Optimizing in Mobile Edge Computing architecture for the Internet of things based devices
• Modern functionality for Efficient Computing Sharing Resources aimed at MECCNs
• A useful function for Collaboration Task Offloading in SCNs that is meant for overburdened mobile edge computing.

Currently, we are offering all the essential Research and thesis writing support in all the topics mentioned here. You can completely depend on us with more confidence and get your thesis developed and evaluated by top mobile computing researchers and analysts of the world. Reach out to us for all your research queries in the mobile computing thesis.

MILESTONE 1: Research Proposal

Finalize journal (indexing).

Before sit down to research proposal writing, we need to decide exact journals. For e.g. SCI, SCI-E, ISI, SCOPUS.

Research Subject Selection

As a doctoral student, subject selection is a big problem. Phdservices.org has the team of world class experts who experience in assisting all subjects. When you decide to work in networking, we assign our experts in your specific area for assistance.

Research Topic Selection

We helping you with right and perfect topic selection, which sound interesting to the other fellows of your committee. For e.g. if your interest in networking, the research topic is VANET / MANET / any other

Literature Survey Writing

To ensure the novelty of research, we find research gaps in 50+ latest benchmark papers (IEEE, Springer, Elsevier, MDPI, Hindawi, etc.)

Case Study Writing

After literature survey, we get the main issue/problem that your research topic will aim to resolve and elegant writing support to identify relevance of the issue.

Problem Statement

Based on the research gaps finding and importance of your research, we conclude the appropriate and specific problem statement.

Writing Research Proposal

Writing a good research proposal has need of lot of time. We only span a few to cover all major aspects (reference papers collection, deficiency finding, drawing system architecture, highlights novelty)

MILESTONE 2: System Development

Fix implementation plan.

We prepare a clear project implementation plan that narrates your proposal in step-by step and it contains Software and OS specification. We recommend you very suitable tools/software that fit for your concept.

Tools/Plan Approval

We get the approval for implementation tool, software, programing language and finally implementation plan to start development process.

Pseudocode Description

Our source code is original since we write the code after pseudocodes, algorithm writing and mathematical equation derivations.

Develop Proposal Idea

We implement our novel idea in step-by-step process that given in implementation plan. We can help scholars in implementation.

Comparison/Experiments

We perform the comparison between proposed and existing schemes in both quantitative and qualitative manner since it is most crucial part of any journal paper.

Graphs, Results, Analysis Table

We evaluate and analyze the project results by plotting graphs, numerical results computation, and broader discussion of quantitative results in table.

Project Deliverables

For every project order, we deliver the following: reference papers, source codes screenshots, project video, installation and running procedures.

MILESTONE 3: Paper Writing

Choosing right format.

We intend to write a paper in customized layout. If you are interesting in any specific journal, we ready to support you. Otherwise we prepare in IEEE transaction level.

Collecting Reliable Resources

Before paper writing, we collect reliable resources such as 50+ journal papers, magazines, news, encyclopedia (books), benchmark datasets, and online resources.

Writing Rough Draft

We create an outline of a paper at first and then writing under each heading and sub-headings. It consists of novel idea and resources

Proofreading & Formatting

We must proofread and formatting a paper to fix typesetting errors, and avoiding misspelled words, misplaced punctuation marks, and so on

Native English Writing

We check the communication of a paper by rewriting with native English writers who accomplish their English literature in University of Oxford.

Scrutinizing Paper Quality

We examine the paper quality by top-experts who can easily fix the issues in journal paper writing and also confirm the level of journal paper (SCI, Scopus or Normal).

Plagiarism Checking

We at phdservices.org is 100% guarantee for original journal paper writing. We never use previously published works.

MILESTONE 4: Paper Publication

Finding apt journal.

We play crucial role in this step since this is very important for scholar’s future. Our experts will help you in choosing high Impact Factor (SJR) journals for publishing.

Lay Paper to Submit

We organize your paper for journal submission, which covers the preparation of Authors Biography, Cover Letter, Highlights of Novelty, and Suggested Reviewers.

Paper Submission

We upload paper with submit all prerequisites that are required in journal. We completely remove frustration in paper publishing.

Paper Status Tracking

We track your paper status and answering the questions raise before review process and also we giving you frequent updates for your paper received from journal.

Revising Paper Precisely

When we receive decision for revising paper, we get ready to prepare the point-point response to address all reviewers query and resubmit it to catch final acceptance.

Get Accept & e-Proofing

We receive final mail for acceptance confirmation letter and editors send e-proofing and licensing to ensure the originality.

Publishing Paper

Paper published in online and we inform you with paper title, authors information, journal name volume, issue number, page number, and DOI link

MILESTONE 5: Thesis Writing

Identifying university format.

We pay special attention for your thesis writing and our 100+ thesis writers are proficient and clear in writing thesis for all university formats.

Gathering Adequate Resources

We collect primary and adequate resources for writing well-structured thesis using published research articles, 150+ reputed reference papers, writing plan, and so on.

Writing Thesis (Preliminary)

We write thesis in chapter-by-chapter without any empirical mistakes and we completely provide plagiarism-free thesis.

Skimming & Reading

Skimming involve reading the thesis and looking abstract, conclusions, sections, & sub-sections, paragraphs, sentences & words and writing thesis chorological order of papers.

Fixing Crosscutting Issues

This step is tricky when write thesis by amateurs. Proofreading and formatting is made by our world class thesis writers who avoid verbose, and brainstorming for significant writing.

Organize Thesis Chapters

We organize thesis chapters by completing the following: elaborate chapter, structuring chapters, flow of writing, citations correction, etc.

Writing Thesis (Final Version)

We attention to details of importance of thesis contribution, well-illustrated literature review, sharp and broad results and discussion and relevant applications study.

How PhDservices.org deal with significant issues ?

1. novel ideas.

Novelty is essential for a PhD degree. Our experts are bringing quality of being novel ideas in the particular research area. It can be only determined by after thorough literature search (state-of-the-art works published in IEEE, Springer, Elsevier, ACM, ScienceDirect, Inderscience, and so on). SCI and SCOPUS journals reviewers and editors will always demand “Novelty” for each publishing work. Our experts have in-depth knowledge in all major and sub-research fields to introduce New Methods and Ideas. MAKING NOVEL IDEAS IS THE ONLY WAY OF WINNING PHD.

2. Plagiarism-Free

To improve the quality and originality of works, we are strictly avoiding plagiarism since plagiarism is not allowed and acceptable for any type journals (SCI, SCI-E, or Scopus) in editorial and reviewer point of view. We have software named as “Anti-Plagiarism Software” that examines the similarity score for documents with good accuracy. We consist of various plagiarism tools like Viper, Turnitin, Students and scholars can get your work in Zero Tolerance to Plagiarism. DONT WORRY ABOUT PHD, WE WILL TAKE CARE OF EVERYTHING.

3. Confidential Info

We intended to keep your personal and technical information in secret and it is a basic worry for all scholars.

• Technical Info: We never share your technical details to any other scholar since we know the importance of time and resources that are giving us by scholars.
• Personal Info: We restricted to access scholars personal details by our experts. Our organization leading team will have your basic and necessary info for scholars.

CONFIDENTIALITY AND PRIVACY OF INFORMATION HELD IS OF VITAL IMPORTANCE AT PHDSERVICES.ORG. WE HONEST FOR ALL CUSTOMERS.

4. Publication

Most of the PhD consultancy services will end their services in Paper Writing, but our PhDservices.org is different from others by giving guarantee for both paper writing and publication in reputed journals. With our 18+ year of experience in delivering PhD services, we meet all requirements of journals (reviewers, editors, and editor-in-chief) for rapid publications. From the beginning of paper writing, we lay our smart works. PUBLICATION IS A ROOT FOR PHD DEGREE. WE LIKE A FRUIT FOR GIVING SWEET FEELING FOR ALL SCHOLARS.

5. No Duplication

After completion of your work, it does not available in our library i.e. we erased after completion of your PhD work so we avoid of giving duplicate contents for scholars. This step makes our experts to bringing new ideas, applications, methodologies and algorithms. Our work is more standard, quality and universal. Everything we make it as a new for all scholars. INNOVATION IS THE ABILITY TO SEE THE ORIGINALITY. EXPLORATION IS OUR ENGINE THAT DRIVES INNOVATION SO LET’S ALL GO EXPLORING.

Client Reviews

I ordered a research proposal in the research area of Wireless Communications and it was as very good as I can catch it.

I had wishes to complete implementation using latest software/tools and I had no idea of where to order it. My friend suggested this place and it delivers what I expect.

It really good platform to get all PhD services and I have used it many times because of reasonable price, best customer services, and high quality.

My colleague recommended this service to me and I’m delighted their services. They guide me a lot and given worthy contents for my research paper.

I’m never disappointed at any kind of service. Till I’m work with professional writers and getting lot of opportunities.

- Christopher

Once I am entered this organization I was just felt relax because lots of my colleagues and family relations were suggested to use this service and I received best thesis writing.

I recommend phdservices.org. They have professional writers for all type of writing (proposal, paper, thesis, assignment) support at affordable price.

You guys did a great job saved more money and time. I will keep working with you and I recommend to others also.

These experts are fast, knowledgeable, and dedicated to work under a short deadline. I had get good conference paper in short span.

Guys! You are the great and real experts for paper writing since it exactly matches with my demand. I will approach again.

I am fully satisfied with thesis writing. Thank you for your faultless service and soon I come back again.

Trusted customer service that you offer for me. I don’t have any cons to say.

I was at the edge of my doctorate graduation since my thesis is totally unconnected chapters. You people did a magic and I get my complete thesis!!!

- Abdul Mohammed

Good family environment with collaboration, and lot of hardworking team who actually share their knowledge by offering PhD Services.

I enjoyed huge when working with PhD services. I was asked several questions about my system development and I had wondered of smooth, dedication and caring.

I had not provided any specific requirements for my proposal work, but you guys are very awesome because I’m received proper proposal. Thank you!

- Bhanuprasad

I was read my entire research proposal and I liked concept suits for my research issues. Thank you so much for your efforts.

- Ghulam Nabi

I am extremely happy with your project development support and source codes are easily understanding and executed.

Hi!!! You guys supported me a lot. Thank you and I am 100% satisfied with publication service.

- Abhimanyu

I had found this as a wonderful platform for scholars so I highly recommend this service to all. I ordered thesis proposal and they covered everything. Thank you so much!!!

Related Pages

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