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Title: ENDA : embracing network inconsistency for dynamic application offloading in mobile cloud computing
Authors: Li, J
Bu, K
Liu, X
Xiao, B 
Keywords: Cloudlet
Mobile cloud computing
User track prediction
Issue Date: 2013
Source: MCC '13 Proceedings of the Second ACM SIGCOMM Workshop on Mobile Cloud Computing, Hong Kong, August 2013, p. 39-44 How to cite?
Abstract: Mobile Cloud Computing (MCC) enables smartphones to offload compute-intensive codes and data to clouds or cloudlets for energy conservation. Thus, MCC liberates smartphones from battery shortage and embraces more versatile mobile applications. Most pioneering MCC research work requires a consistent network performance for offloading. However, such consistency is challenged by frequent mobile user movements and unstable network quality, thereby resulting in a suboptimal offloading decision. To embrace network inconsistency, we propose ENDA, a three-tier architecture that leverages user track prediction, realtime network performance and server loads to optimize offloading decisions. On cloud tier, we first design a greedy searching algorithm to predict user track using historical user traces stored in database servers. We then design a cloud-enabled Wi-Fi access point (AP) selection scheme to find the most energy efficient AP for smartphone offloading. We evaluate the performance of ENDA through simulations under a real-world scenario. The results demonstrate that ENDA can generate offloading decisions with optimized energy efficiency, desirable response time, and potential adaptability to a variety of scenarios. ENDA outperforms existing offloading techniques that do not consider user mobility and server workload balance management.
ISBN: 978-1-4503-2180-8
DOI: 10.1145/2491266.2491274
Appears in Collections:Conference Paper

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