TY - JOUR
T1 - Quality-of-service trade-off analysis for wireless sensor networks.
AU - Hoes, R.J.H.
AU - Basten, A.A.
AU - Tham, C.K.
AU - Geilen, M.C.W.
AU - Corporaal, H.
PY - 2009
Y1 - 2009
N2 - Quality of Service (QoS) support for wireless sensor networks (WSN) is a fairly new topic that is gaining more and more interest. This paper introduces a method for determining the node configurations of a WSN such that application-level QoS constraints are met. This is a complex task, since the search space is typically extremely large. The method is based on a recent algebraic approach to Pareto analysis, that we use to reason about QoS trade-offs. It features an algorithm that keeps the working set of possible configurations small, by analysing parts of the network in a modular fashion, and meanwhile discarding configurations that are inferior to other configurations. Furthermore, we give WSN models for two different applications, spatial mapping and target tracking, in which QoS trade-offs are made explicit. Test results for these applications and a heterogeneous WSN combining these two applications show that the models are accurate and that the method is scalable and thus practically usable for WSN, even with large numbers of nodes. Details are given on how to efficiently implement the algorithm.
AB - Quality of Service (QoS) support for wireless sensor networks (WSN) is a fairly new topic that is gaining more and more interest. This paper introduces a method for determining the node configurations of a WSN such that application-level QoS constraints are met. This is a complex task, since the search space is typically extremely large. The method is based on a recent algebraic approach to Pareto analysis, that we use to reason about QoS trade-offs. It features an algorithm that keeps the working set of possible configurations small, by analysing parts of the network in a modular fashion, and meanwhile discarding configurations that are inferior to other configurations. Furthermore, we give WSN models for two different applications, spatial mapping and target tracking, in which QoS trade-offs are made explicit. Test results for these applications and a heterogeneous WSN combining these two applications show that the models are accurate and that the method is scalable and thus practically usable for WSN, even with large numbers of nodes. Details are given on how to efficiently implement the algorithm.
U2 - 10.1016/j.peva.2008.10.007
DO - 10.1016/j.peva.2008.10.007
M3 - Article
SN - 0166-5316
VL - 66
SP - 191
EP - 208
JO - Performance Evaluation
JF - Performance Evaluation
IS - 3-5
ER -