Neighbour Selection and Sensor Knowledge: Proactive Approach for the Frugal Feeding Problem in Wireless Sensor Networks

This paper examines new proactive solutions to the Frugal Feeding Problem (FFP) in Wireless Sensor Networks. The FFP attempts to find energy-efficient routes for a mobile service entity to rendezvous with each member of a team of mobile robots. Although the complexity of the FFP is similar to the Traveling Salesman Problem (TSP), we propose an efficient solution, completely distributed and localized for the case of a fixed rendezvous location (i.e., service facility with limited number of docking ports) and mobile capable sensors. Our proactive solution reduces the FFP to finding energy-efficient routes in a dynamic Compass Directed Gabriel Graph (CDGG) or Compass Directed Relative Neighbour Graph (CDRNG). The proposed graphs incorporate ideas from forward progress routing and the directionality of compass routing in an energy-aware graph. Navigating the CDGG or CDRNG guarantees that each sensor will reach the rendezvous location in a finite number of steps. The ultimate goal of our solution is to achieve energy equilibrium (i.e., no further sensor losses due to energy starvation) by optimizing the use of a shared recharge station. We also examine the impact of critical parameters such as transmission range, number of recharge ports and sensor knowledge for the two proposed graphs.