دانلود رایگان مقاله انگلیسی محاسبات ابری سیار برای تخلیه محاسباتی: مسائل و چالش ها - الزویر 2018

Abstract

Despite the evolution and enhancements that mobile devices have experienced, they are still considered as limited computing devices. Today, users become more demanding and expect to execute computational intensive applications on their smartphone devices. Therefore, Mobile Cloud Computing (MCC) integrates mobile computing and Cloud Computing (CC) in order to extend capabilities of mobile devices using offloading techniques. Computation offloading tackles limitations of Smart Mobile Devices (SMDs) such as limited battery lifetime, limited processing capabilities, and limited storage capacity by offloading the execution and workload to other rich systems with better performance and resources. This paper presents the current offloading frameworks, computation offloading techniques, and analyzes them along with their main critical issues. In addition, it explores different important parameters based on which the frameworks are implemented such as offloading method and level of partitioning. Finally, it summarizes the issues in offloading frameworks in the MCC domain that requires further research.

Conclusion

 This paper discusses three main concepts: (1) cloud computing, (2) mobile cloud computing, and (3) computation offloading. More specifically, it presents existing frameworks for computa tion offloading along with the various techniques used to enhance the capabilities of smartphone devices based on the available cloud resources. The paper investigates the different issues in current offloading frameworks and highlights challenges that still obstruct these frameworks in MCC. Moreover, 880 the paper shows the different approaches that are used by the frameworks to achieve offloading. Some of these approaches use static offloading while others employ dynamic offloading. Even though there exist a variety of approaches, all of them 884 target the same objective which is the improvement of the smartphone device capabilities by saving energy, reducing response time, or minimizing the execution cost. We notice that current offloading frameworks are still facing some challenges and difficulties. For instance, lack of standard architectures. This shortage leads to more complications while developing and managing a proposed framework. Finally, it is important to come up with a lightweight paradigm or model that will help to overcome the difficulties and minimizing efforts while developing, deploying, and managing an offloading framework. We believe that exploring other alternatives, such as introducing a middleware based architecture using an optimizing offloading algorithm, could help better the available frame works and provide more efficient and more flexible solutions to the MCC users.