Context-Aware Mobile Application Task Offloading to the Cloud

Abstract

One of the benefits of mobile cloud computing is the ability to offload mobile applications to the cloud for many reasons including performance enhancement and reduced resource consumption. This paper is concerned with offloading of context-aware mobile applications, in which actions or tasks are executed in certain contexts and offloading those tasks needs to be itself context-aware to be advantageous. The paper investigates candidate techniques and development models in the literature to identify suitable ones. Accordingly, the paper proposes the practical Context-Aware Mobile applications Offloading (CAMO) development model, which we developed in Java for the Android platform. Programmers can exploit the independency of the tasks of a typical context-aware mobile application and use CAMO to profile each task in isolation on the mobile and the cloud. The paper introduces the concept of a task-offloading plan in which programmers specify a criterion and/or an objective for offloading a task in a specific context. Offloading criteria allow rapid offloading in case the mobile environment does not change frequently. Based on the profiling results, programmers can use the classes and methods of CAMO to develop one or more custom offloading plans for each task or use pre-specified plans, criterion and objectives. We provide three example tasks with details of their profiling and analysis for developing corresponding offloading plans. CAMO is general and flexible enough for offloading any application partitioned into independent modules. Empirical evaluation shows extreme satisfaction of mobile application developers with its capabilities.

Authors and Affiliations

Hanan Elazhary, Saja Aloraini, Roa’a Aljuraid

Keywords

Related Articles

Energy Efficient Algorithm for Wireless Sensor Network using Fuzzy C-Means Clustering

Energy efficiency is a vital issue in wireless sensor networks. In this paper, an energy efficient routing algorithm has been proposed with an aim to enhance lifetime of network. In this paper, Fuzzy C-Means clustering h...

Development of Dynamic Real-Time Navigation System

This study aimed to develop a system that considers dynamic real-time situations to provide effective support for tourist activities. The conclusions of this study are summarized in the following three points: (1) The sy...

Crowd Mobility Analysis using WiFi Sniffers

Wi-fi enabled devices such as today’s smart-phones are regularly in-search for connectivity. They continuously send management frames called Probe Requests searching for previ-ously accessed networks. These frames contai...

Aggregation Operator for Assignment of Resources in Distributed Systems

In distributed processing systems it is often necessary to coordinate the allocation of shared resources that should be assigned to processes in the modality of mutual exclusion; in such cases, the order in which the sha...

RGBD Human Action Recognition using Multi-Features Combination and K-Nearest Neighbors Classification

In this paper, we present a novel system to analyze human body motions for action recognition task from two sets of features using RGBD videos. The Bag-of-Features approach is used for recognizing human action by extract...

Download PDF file
  • EP ID EP258810
  • DOI 10.14569/IJACSA.2017.080547
  • Views 97
  • Downloads 0

How To Cite

Hanan Elazhary, Saja Aloraini, Roa’a Aljuraid (2017). Context-Aware Mobile Application Task Offloading to the Cloud. International Journal of Advanced Computer Science & Applications, 8(5), 381-390. https://europub.co.uk/articles/-A-258810