Mobile Cloud Computing Research Research Articles

Mobile Cloud Computing Research: Issues and Challenges

Mobile Cloud Computing Research: Issues and Challenges

Dynamic resource allocation for service in mobile cloud computing with Markov modulated arrivals

Mobile Cloud Computing (MCC) is a modern architecture that brings together cloud computing, mobile computing and wireless networks to assist mobile devices in storage, computing and communication. A cloud environment is developed to support a wide range of users that request the cloud resources in a dynamic environment with possible constraints. Burstiness in users service requests causes drastic and unpredictable increases in the resource requests that have a crucial impact on policies of resource allocation. How can the cloud system efficiently handle such burstiness when the cloud resources are limited? This problem becomes a hot issue in the MCC research area. In this paper, we develop a system model for the resource allocation based on the Semi-Markovian Decision Process (SMDP), able of dynamically assigning the mobile service requests to a set of cloud resources, to optimize the usage of cloud resources and maximize the total long-term expected system reward when the arrival process is a finite-state Markov-Modulated Poisson Process (MMPP). Numerical results show that our proposed model performs much better than the Greedy algorithm in terms of achieving higher system rewards and lower service requests blocking probabilities, especially when the burstiness degree is high, and the cloud resources are limited.

Mobile Cloud Computing Research – Issues, Challenges and Needs

With the rapid advance of mobile computing technology and wireless networking, there is a significant increase of mobile subscriptions. This drives a strong demand for mobile cloud applications and services for mobile device users. This brings out a great business and research opportunity in mobile cloud computing (MCC). This paper first discusses the market trend and related business driving forces and opportunities. Then it presents an overview of MCC in terms of its concepts, distinct features, research scope and motivations, as well as advantages and benefits. Moreover, it discusses its opportunities, issues and challenges. Furthermore, the paper highlights a research roadmap for MCC.

Explore virtual machine deployment to mobile cloud computing for multi-tenancy and energy conservation in wireless network

Mobile cloud computing (MCC) is becoming one of the primary applications and research directions of pervasive computing. Previous studies generally focuses on the following two kinds of paradigms. One is that mobile users offload computing tasks into traditional clouds to achieve collaboration processing. The other is that multiple mobile devices, as “helpers”, casually provide computing services for other mobile “requesters”. However, with the extraordinary development of mobile devices, new problems of resource utilization and multi-tenancy of mobile devices are emerging. Based on this, we propose a novel MCC paradigm combining virtual machine (VM) technologies to improve the resource utilization of mobile devices, achieve multi-tenancy and thereby obtain the more efficient MCC environment as well as a broader MCC research field. To achieve it, the VM deployment problem must be addressed firstly. The heuristic deployment approach VD-ABC based on an improved artificial bee colony algorithm is proposed. It combines with Boltzmann selection policy, to obtain the optimal solution of VM deployment. In terms of the traits of wireless network in MCC, the mapping from the obtained solution to the final VM deployment is achieved. Simulation results show that VD-ABC has a better energy saving performance while minimizing the service response latency.

Benchmark applications used in mobile cloud computing research: a systematic mapping study

Mobile cloud computing (MCC) integrates mobile computing and cloud computing aiming to extend the capabilities of mobile devices through offloading techniques. In MCC, many controlled experiments have been performed using mobile applications as benchmarks. Usually, these applications are used to validate proposed algorithms, architectures or frameworks. The task of choosing a specific benchmark to evaluate MCC proposals is difficult because there is no standard applications list. This paper presents a systematic mapping study for benchmarks used in MCC research. Taking 5 months of work, we have read 763 papers from MCC field. We catalogued the applications and characterized them considering three facets: category (e.g., games, imaging tools); evaluated resource (e.g., time, energy); and platform (e.g., Android, iPhone). The mapping study evidences research gaps and research trends. Providing a list of downloadable standardized benchmarks, this work can aid better choices to guide more reliable research studies since the same application could be used for different scientific purposes.

A Systematic Literature Review of Mobile Cloud Computing

Mobile cloud computing (MCC) is a relatively new concept that leverages the combination of cloud technology, mobile computing, and wireless networking to enrich the usability experiences of mobile users. Many fields of application such as mobile health, mobile learning, mobile commerce and mobile entertainment are now taking advantage of MCC technologies. Since MCC is new, there is need to advance research in MCC in order to deepen practice. Currently, what exist are mostly descriptive literature reviews in the area of MCC. In this paper, a systematic literature review (SLR), which offers a structured, methodical, and rigorous approach to the understanding of the trend of research in MCC, and the least and most researched issue is presented. The objective of the study is to provide a credible intellectual guide for upcoming researchers in MCC to help them identify areas in MCC research where they can make the most impact. The SLR was limited to peer-reviewed conference papers and journal articles published from 2002 to 2014. The study reveals that privacy, security and trust in MCC are the least researched, whereas issues of architecture, context awareness and data management have been averagely researched, while issues on operations, end users, service and applications have received a lot of attention in the literature.