Energy-efficient content retrieval in mobile cloud

Authors:
You Lu;Biao Zhou;Lung-Chih Tung;Mario Gerla;Ashwin Ramesh;Lohith Nagaraja
Affiliations:
University of California, Los Angeles, Los Angeles, CA, USA;Electronic Arts, Redwood City, CA, USA;University of California, Los Angeles, Los Angeles, CA, USA;University of California, Los Angeles, Los Angeles, CA, USA;University of California, Los Angeles, Los Angeles, CA, USA;University of California, Los Angeles, Los Angeles, CA, USA
Venue:
Proceedings of the second ACM SIGCOMM workshop on Mobile cloud computing
Year:
2013

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Abstract

Mobile cloud computing (MCC) has recently been drawing increased attention in academia as well as industry. Content retrieval is a critical service, for many mobile cloud applications and in turns relies on other resources and tools, e.g., internal storage, content searching and sharing, etc. Previous studies have shown that conventional ICN interest query schemes and content searching architectures, if not properly designed, can cause significant performance degradation and energy consumption, especially for large scale MANETs. In this paper, we specifically address the scalability and energy efficiency of the content retrieval scheme in mobile cloud computing. We propose a direction-selective forwarding scheme for the content query method that decreases traffic overhead and energy cost caused by duplicate copies of the query packets. We also advocate the parallel search method of multiple caches to increase the hit rate. Simulation experiments show that the proposed scheme yields significant improvements in efficiency and scalability for the content retrieval in large scale MANETs.