EFFORT: Energy efficient framework for offload communication in mobile cloud computing. (31st May 2020)

• Record Type: Journal Article
• Authors: Malik, Saif U. R.; Akram, Hina; Gill, Sukhpal Singh; Pervaiz, Haris; Malik, Hassan
• Other Names: Ilager Shashikant guestEditor.; Stankovski Vlado guestEditor.; Pallickarar Shrideep guestEditor.; Buyya Rajkumar guestEditor.
• Is Part Of: Software, practice & experience. Volume 51:Number 9(2021)
• Page Start: 1896
• Page End: 1909
• Publication Date: 2020-05-31
• Subjects: cloud computing -- cloud service providers -- energy consumption -- IoT -- Internet spoofing -- offload communication; Computer software -- Periodicals; Computer programming -- Periodicals; Computer programs -- Periodicals; 005.3
• DOI: 10.1002/spe.2850
• Languages: English
• ISSNs: 0038-0644

Abstract

Summary: There is an abundant expansion in the race of technology, specifically in the production of data, because of the smart devices, such as mobile phones, smart cards, sensors, and Internet of Things (IoT). Smart phones and devices have undergone an enormous evolution in a way that they can be used. More and more new applications, such as face recognition, augmented reality, online interactive gaming, and natural language processing are emerging and attracting the users. Such applications are generally data intensive or compute intensive, which demands high resource and energy consumption. Mobile devices are known for the resource scarcity, having limited computational power and battery life. The tension between compute/data intensive application and resource constrained mobile devices hinders the successful adaption of emerging paradigms. In the said perspective, the objective of this article is to study the role of computation offloading in mobile cloud computing to supplement mobile platforms ability in executing complex applications. This article proposes a systematic approach (EFFORT) for offload communication in the cloud. The proposed approach provides a promising solution to partially solve energy consumption issue for communication‐intensive applications in a smartphone. The experimental study shows that our proposed approach outperforms its counterparts in terms of energy consumption and fast processing of smartphone devices. The battery consumption was reduced to 19% and the data usage was reduced to 16%.