DewSim: A trace‐driven toolkit for simulating mobile device clusters in Dew computing environments. (23rd April 2019)

• Record Type: Journal Article
• Authors: Hirsch, Matías; Mateos, Cristian; Rodriguez, Juan Manuel; Zunino, Alejandro
• Other Names: Ranjan Rajiv guestEditor.; Villari Massimo guestEditor.; Shen Haiying guestEditor.; Rana Omer guestEditor.; Buyya Rajkumar guestEditor.
• Is Part Of: Software, practice & experience. Volume 50:Number 5(2020)
• Page Start: 688
• Page End: 718
• Publication Date: 2019-04-23
• Subjects: android -- battery‐aware resource management policy -- discrete event simulation -- edge computing -- mobile devices -- trace‐based; Computer software -- Periodicals; Computer programming -- Periodicals; Computer programs -- Periodicals; 005.3
• DOI: 10.1002/spe.2696
• Languages: English
• ISSNs: 0038-0644

Abstract

Summary: Dew computing is an emerging computing paradigm, which aims at minimizing the dependency over existing internetwork back‐haul, ie, being dependent on processing resources offered by remote servers. Smartphones and tablets ubiquity and powerful computing hardware motivated researchers to investigate the way of providing Dew computing services by exploiting the aggregated capabilities of devices in a vicinity, a smart device cluster. Consequently, research on resource management is necessary to learn how to scavenge resources from such a cluster, deal with devices heterogeneity, limitations, and dynamic resource availability. Simulation is commonly practiced for studying resource management in other distributed computing research fields, specially due to the complexity involved in the set up of experiments. However, a free‐to‐use purpose specific toolkit for studying smart device clusters do not exist or have been documented. Current simulation efforts do not allow researchers to faithfully represent key singularities of such environment, which are energy depletion and nondedicated nature of computing resources. We propose a trace‐based toolkit built on modular software artifacts to speed up research in resource management techniques in Dew environments. A trace‐driven methodology is adopted to assure practical value of simulated scenarios. The toolkit comprises a device profiler application for Android to capture generic battery and CPU traces from real devices, a profile mixer to create user interaction baseline traces through generic ones, and an extensible engine to simulate the execution of workloads configurable via text files. Verification and validation tests were run to show correctness and reliability of our simulation approach.