Energy Efficiency enhancement using firefly algorithm in wireless sensor network

Energy Efficiency enhancement using firefly algorithm in wireless sensor network

The hybrid approach consisting of two algorithms: Genetic Algorithm (GA) and Fireflies Algorithm (FA) will be used to analyse the network performance. The parameters that will be considered in our project are energy efficiency, network life span and coverage.

We propose to apply this hybrid approach on WSN and then compare their results when they are individually applied on WSN, as well as with the other approaches.

In firefly approach the movement of a firefly i is attracted to another, more attractive (brighter) firefly j, as determined by

where β0 is the attractiveness at zero distance r = 0, α is the randomization parameter, and

is a vector of random numbers drawn from a Gaussian distribution at time t. Position of a particle is represented by x.

In this project, residual energy nodes will be considered population set. In Wireless Sensor Network if each node sends data to the sink then it will consume more energy so if we make clusters and then appoint a Head, this head selection will be done using firefly more intensity (Bright) node will be considered as most residual energy node. The brightness of firefly can simply be proportional to the value of the objective function. Many other forms of brightness can be defined in a similar way to the fitness function in genetic algorithms. Basically, there are two important issues in Fireflies algorithm: first one is the Light intensity and another one is attractiveness. So, for simplicity this is assumed that the attractiveness is directly promotional to the Brightness of the firefly.