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Task allocation to actors in wireless sensor actor networks: an energy and time aware technique
Author(s) -
Morteza Okhovvat,
Mohsen Sharifi,
Hossein Momeni
Publication year - 2011
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2010.12.082
Subject(s) - computer science , wireless sensor network , task (project management) , latency (audio) , distributed computing , wireless , job shop scheduling , scheduling (production processes) , energy (signal processing) , load balancing (electrical power) , queueing theory , efficient energy use , computer network , real time computing , mathematical optimization , telecommunications , statistics , routing (electronic design automation) , mathematics , management , geometry , engineering , electrical engineering , economics , grid
Task allocation is a critical issue in proper engineering of cooperative applications in embedded systems with latency and energy constraints, as in wireless sensor and actor networks (WSANs). Existing task allocation algorithms are mostly concerned with energy savings and ignore time constraints and thus increase the makespan of tasks in the network as well as the probability of malfunctioning of the network. In this paper we take both energy awareness and reduction of actor tasks’ times to completion in WSANs into account and propose a two-phase task allocation technique based on Queuing theory. In the first phase, tasks are equally assigned to actors just to measure the capability of each actor to perform the assigned tasks. Tasks are then allocated to actors according to their measured capabilities in such a way to reduce the total completion times of all tasks in the network. The results of simulations on typical scenarios shows 45% improvement in the makespan of tasks in a network compared to the wellknown opportunistic load balancing (OLB) task allocation algorithm that is generally used in distributed systems. It is shown that our algorithms provide better tradeoffs between load balancing and completion times of all tasks in a WSAN compared to OLB

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