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

Pentaho and Jaspersoft: A Comparative Study of Business Intelligence Open Source Tools Processing Big Data to Evaluate Performances

Regardless of the recent growth in the use of “Big Data” and “Business Intelligence” (BI) tools, little research has been undertaken about the implications involved. Analytical tools affect the development and sustainabi...

Feature Weight Optimization Mechanism for Email Spam Detection based on Two-step Clustering Algorithm and Logistic Regression Method

This research proposed an improved filtering spam technique for suspected emails, messages based on feature weight and the combination of two-step clustering and logistic regression algorithm. Unique, important features...

Automatic Rotation Recovery Algorithm for Accurate Digital Image and Video Watermarks Extraction

Research in digital watermarking has evolved rapidly in the current decade. This evolution brought various different methods and algorithms for watermarking digital images and videos. Introduced methods in the field vari...

A Global Convergence Algorithm for the Supply Chain Network Equilibrium Model

In this paper, we first present an auxiliary problem method for solving the generalized variational inequalities problem on the supply chain network equilibrium model (GVIP), then its global convergence is also establish...

Cross Site Scripting: Detection Approaches in Web Application

Web applications have become one of the standard platforms for service releases and representing information and data over the World Wide Web. Thus, security vulnerabilities headed to various type of attacks in web appli...

Download PDF file
  • EP ID EP258810
  • DOI 10.14569/IJACSA.2017.080547
  • Views 82
  • 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