TY - GEN
T1 - Comparing design of experiments and evolutionary approaches to multi-objective optimisation of sensornet protocols
AU - TATE, Jonathan
AU - WOOLFORD-LIM, Benjamin
AU - BATE, Iain
AU - YAO, Xin
PY - 2009/5
Y1 - 2009/5
N2 - The lifespan, and hence utility, of sensornets is limited by the energy resources of individual motes. Network designers seek to maximise energy efficiency while maintaining an acceptable network Quality of Service. However, the interactions between multiple tunable protocol parameters and multiple sensornet performance metrics are generally complex and unknown. In this paper we address this multi-dimensional optimisation problem by two distinct approaches. Firstly, we apply a Design Of Experiments approach to obtain a generalised linear interaction model, and from this derive an estimated near-optimal solution. Secondly, we apply the Two- Archive evolutionary algorithm to improve solution quality for a specific problem instance. We demonstrate that, whereas the first approach yields a more generally applicable solution, the second approach yields a broader range of viable solutions at potentially lower experimental cost. © 2009 IEEE.
AB - The lifespan, and hence utility, of sensornets is limited by the energy resources of individual motes. Network designers seek to maximise energy efficiency while maintaining an acceptable network Quality of Service. However, the interactions between multiple tunable protocol parameters and multiple sensornet performance metrics are generally complex and unknown. In this paper we address this multi-dimensional optimisation problem by two distinct approaches. Firstly, we apply a Design Of Experiments approach to obtain a generalised linear interaction model, and from this derive an estimated near-optimal solution. Secondly, we apply the Two- Archive evolutionary algorithm to improve solution quality for a specific problem instance. We demonstrate that, whereas the first approach yields a more generally applicable solution, the second approach yields a broader range of viable solutions at potentially lower experimental cost. © 2009 IEEE.
UR - http://www.scopus.com/inward/record.url?scp=70449752082&partnerID=8YFLogxK
U2 - 10.1109/CEC.2009.4983074
DO - 10.1109/CEC.2009.4983074
M3 - Conference paper (refereed)
SN - 9781424429592
SP - 1137
EP - 1144
BT - 2009 IEEE Congress on Evolutionary Computation, CEC 2009
ER -