Bipartivity Index based Link Selection Strategy to Determine Stable and Energy-Efficient Data Gathering Trees for Mobile Sensor Networks

摘要: Bipartivity Index (BPI) has been used in complex network analysis to quantify the extent of partitioning vertices a graph into two disjoint partitions; edges between within same partition are called frustrated edges. The BPI values for ranges from 0 1 (the that is truly bipartite and no 1). Our hypothesis this research end nodes short distance link significantly smaller than transmission range per node) mobile sensor (MSN) more likely share significant fraction their neighbors such links be stable. We introduce notion egocentric an edge (adapted comprising (as vertices) incident on edges). claim whose lower score stable link, with relatively larger shared neighborhood, could preferred inclusion while determining data gathering trees MSNs. Through extensive simulations, we show BPI-based DG energy-efficient compared determined using predicted expiration time (LET), currently best known strategy.