Indian Journal of Science and Technology
Year: 2017, Volume: 10, Issue: 28, Pages: 1-13
Imran Rafique1 *, Hina Gul2 , Salman Rafique3 , Syed Asad Raza Kazmi1 , Awais Qasim1 and Ilyas Fakhir1
1Department of Computer Science, GC University, Lahore – 54000, Pakistan; [email protected], [email protected], [email protected], [email protected] 2Department of Computer Science, Kinnaird College for Women, Lahore– 54000, Pakistan; [email protected] 3Department of Computer of Science and Engineering, University of Engineering and Technology, Lahore − 54890, Pakistan; [email protected]
*Author For Correspondence
Department of Computer Science, GC University, Lahore – 54000, Pakistan; [email protected]
Objectives: Recent technical advances have fueled the popularity of mobile grid computing. Mobile devices such as cellular phones and PDAs are becoming more common due to the diminution in their size and increase of computational power. In addition, wireless networks are also beginning to fill the environment. With these advances, mobile devices are becoming available to act as service providers in Grid. But the mobile environment presents a number of challenges. Analysis: The range of mobile execution platforms now available which introduces the problem of heterogeneity. Heavy weight checkpoints also provide hindrance to achieve this integration. At present, Grid Computing standards, neither state any load sharing architecture and model that integrates mobile devices in Grid computing nor does it provide any policy that hides heterogeneity and overcome memory limitations of mobile devices thus it is still an open research problem. Findings: Mobile Grid computing solutions must be developed that are lightweight, independent of specific platform and a load sharing model for mobile grid computing that distributes computational tasks on heterogeneous mobile devices. Our simulation results show the effectiveness of data optimization techniques for mobile devices, interoperability and proxy performance in heterogeneous mobile environment. Novelty: We propose a novel layered architecture that adjusts the data size of checkpoints at the minimum possible level and a load sharing Mobile Proxy algorithm.
Keywords: Broker, Checkpointing, Control Flow Graph, Data Liveliness, Heterogeneity, Interoperability, Proxy, Web Service
Subscribe now for latest articles and news.