Particle Swarm Optimization Based Placement of Data Acquisition Points in a Smart Water Metering Network

A Particle Swarm Optimization (PSO) algorithm for the placement of Data Acquisition Points (DAPs) in a Smart Water Metering Networks is investigated. The PSO algorithm generates particles, which denote the coordinates of the DAPs and creates the topology file by appending these coordinates to the smart meter topology file. It then invokes the Java LinkLayerModel, which generates the link gain file of the network. Once that is done, the TOSSIM Python script is invoked to simulate the network and the packet delivery ratio (PDR) is calculated and designated as the fitness value for the particle. Updates of global best solution are carried out if necessary. This process continues until 50 iterations are reached. Results show that the PDR for 10 DAPs (0.97) in the PSO placement mechanism is better than that of the meter density based placement for 25 DAPs (0.96). It is, therefore, possible to deploy fewer DAPs while achieving even better PDR values. The PSO mechanism also shows more consistency as the meter density based has a higher relative error. In future, some distance based constraints will be incorporated in PSO approach to prevent the problem of smart meters. Multi-core software development techniques will be employed in order to speed up computation on multi-core architectures.