Delay-Sensitive Optimization Models and Distributed Routing Algorithms for Mobile Wireless Sensor Networks
Author(s) -
Germán A. Montoya,
Yezid Donoso
Publication year - 2016
Publication title -
international journal of computers communications and control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.422
H-Index - 33
eISSN - 1841-9844
pISSN - 1841-9836
DOI - 10.15837/ijccc.2016.6.2745
Subject(s) - computer science , node (physics) , wireless sensor network , computer network , routing (electronic design automation) , path (computing) , geographic routing , algorithm , wireless network , distributed computing , wireless , routing protocol , telecommunications , link state routing protocol , structural engineering , engineering
Communication disruptions caused by mobility in wireless sensor networks introduce undesired delays which affect the network performance in delay sensitive applications in MWSN. In order to study the negative effects caused by mobility, we propose two mathematical models to find the minimum cost path between a source node and a destination node considering the nodes position changes across time. Our mathematical models consider the usage of buffers in the nodes to represent the fact of storing a message if there is not an appropriate forwarding node for transmitting it. In order to contrast our mathematical models results we have designed two kinds of algorithms: the first one takes advantage of the closest neighbours to the destination node in order to reach it as fast as possible from the source node. The second one simply reaches the destination node if a neighbour node is precisely the destination node. Finally, we compare the delay performance of these algorithms against our mathematical models to show how efficient they are for reaching a destination node. This paper is an extension of [10].a The mathematical model proposed in [10] is improved by adding two new binary variables with the aim of make it more readable and compact mathematically. This means a post-processing algorithm is added only for evaluating if a solution is at the first network state.
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