Task allocation and scheduling in wireless distributed computing networks

Authors:
Dinesh Datla;Haris I. Volos;S. M. Hasan;Jeffrey H. Reed;Tamal Bose
Affiliations:
Bradley Department of Electrical and Computer Engineering, Wireless@Virginia Tech., Virginia Polytechnic Institute and State University, Blacksburg, USA 24061;Bradley Department of Electrical and Computer Engineering, Wireless@Virginia Tech., Virginia Polytechnic Institute and State University, Blacksburg, USA 24061;Bradley Department of Electrical and Computer Engineering, Wireless@Virginia Tech., Virginia Polytechnic Institute and State University, Blacksburg, USA 24061;Bradley Department of Electrical and Computer Engineering, Wireless@Virginia Tech., Virginia Polytechnic Institute and State University, Blacksburg, USA 24061;Bradley Department of Electrical and Computer Engineering, Wireless@Virginia Tech., Virginia Polytechnic Institute and State University, Blacksburg, USA 24061
Venue:
Analog Integrated Circuits and Signal Processing
Year:
2011

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Abstract

Wireless distributed computing (WDC) is an enabling technology that allows radio nodes to cooperate in processing complex computational tasks of an application in a distributed manner. WDC research is being driven by the fact that mobile portable computing devices have limitations in executing complex mobile applications, mainly attributed to their limited resource and functionality. This article focuses on resource allocation in WDC networks, specifically on scheduling and task allocation. In WDC, it is important to schedule communications between the nodes in addition to the allocation of computational tasks to nodes. Communication scheduling and heterogeneity in the operating environment make the WDC resource allocation problem challenging to address. This article presents a task allocation and scheduling algorithm that optimizes both energy consumption and makespan in a heuristic manner. The proposed algorithm uses a comprehensive model of the energy consumption for the execution of tasks and communication between tasks assigned to different radio nodes. The algorithm is tested for three objectives, namely, minimization of makespan, minimization of energy consumption, and minimization of both makespan and energy consumption.