Abstract
Fueled by the advances in the Internet of Things, and the growing capacity of smart mobile devices at the edge of the Internet, we have witnessed a growing trend in research and development for edge computing and edge storage, which extends the abilities of single mobile device on the edge through on-demand collaboration among multiple geographically distributed mobile devices. In this article, we address several technical challenges that are unique for collaborative storage at the edge due to the unique characteristics of mobile devices. First, we formalize the collaborative storage problem as an optimization problem. Second, we design an Acceleration Algorithm for Collaborative Storage, called A2CS, based on the architecture of Alternating Direction Method of Multipliers (ADMM). Specifically, we use the Nesterov’s Acceleration strategy and the step size rules in the process of updating variables and determining the optimal speed of convergence. We develop a novel collaborative storage policy in order to guide the whole lifecycle of collaborative storage. Finally, we conduct a series of experiments for acceleration performance analysis and validation. We show that A2CS delivers a better convergence performance with different step size rules, compared with two existing approaches: the ADMM baseline and the ADMM-OR (ADMM with Over-Relaxation), achieving the acceleration percentage by at least 25.33 percent and at most 64.01 percent. In addition, by conducting the utility performance comparison analysis with the existing Average Distribution Strategy (ADS) and the existing Distance Preferred Distribution Strategy (DPDS), we show the advantage of A2CS over both ADS and DPDS with respect to the total utility and energy consumption.
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