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Mobile agent itinerary planning for WSN data fusion: considering multiple sinks and heterogeneous networks
Author(s) -
Gavalas Damianos,
Venetis Ioannis E.,
Konstantopoulos Charalampos,
Pantziou Grammati
Publication year - 2016
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.3184
Subject(s) - computer science , scalability , wireless sensor network , distributed computing , sensor fusion , reliability (semiconductor) , field (mathematics) , mobile agent , efficient energy use , middleware (distributed applications) , computer network , database , machine learning , power (physics) , physics , mathematics , quantum mechanics , pure mathematics , electrical engineering , engineering
Summary Mobile agent (MA)‐based middleware has been thoroughly investigated in the past few years as a means to address the efficiency, scalability, and reliability issues of data fusion applications on wireless sensor networks. Deriving an efficient itinerary for each MA to follow is of high importance, because itineraries determine to a large extent the overall performance of data fusion tasks. In this article, we present a novel algorithmic approach for efficient itinerary planning of MA objects undertaking data fusion tasks. We adopt a method based on iterated local search to construct the itineraries (ie, visiting sequences of source nodes) assigned to multiple traveling MAs. We apply alternative optimization criteria which aim either at minimizing the overall energy expenditure over all derived MA itineraries or prolonging the network lifetime. Furthermore, we propose algorithmic solutions for 2 realistic settings which have not been investigated in the past: firstly, the employment of multiple sinks that share the responsibility of MA‐based data fusion tasks across the sensor field, and secondly, the consideration of heterogeneous sensor networks comprising nodes powerful enough to host the runtime environment required to execute MA code as well as “ordinary” nodes which lack these resources. Simulation tests verify the performance gain attained by our algorithmic methods against alternative itinerary planning approaches which involve multiple MAs. Copyright © 2016 John Wiley & Sons, Ltd.