An Effective Context Sensitive Offloading System for Mobile Cloud Environments using Support Value-based Classification

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Mostafa Abdulghafoor Mohammed
Aya Ahkam Kamil
Raed Abdulkareem Hasan
Nicolae Tapus

Abstract

Mobile cloud computing (MCC) has drawn significant research attention recently due to the popularity and capability of portable devices. This paper presents an MCC offloading system based on internet offloading choices. This system guarantees the conservation of battery life and reduced execution time. The proposed effective context sensitive offloading approach using support value-based classification is processed in different steps. Initially, the context data of the input tasks is extracted through the energy consumption model, cost model, execution model, communication model and stored. Then, the support value-based classification approach classifies the tasks based on the context information. This classification creates the information about the tasks and finally, a decision is made at the right time to achieve better offloading. The result indicates the presented offloading framework can choose reasonable cloud assets depending on various contexts of the mobile devices and achieve significant performance enhancement.

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Section
Research Reports