An Energy-efficiency Node Scheduling Game Based on Task Prediction in WSNs

Abstract

For wireless sensor networks, unbalanced task load will decrease the lifetime of network. In this paper, we investigate how to schedule the sensor nodes to sleep or wakeup according to the dynamically changing task load. We first demonstrate that for a sensor network with uniform node distribution and constant data reporting, balancing the task load of the whole network cannot be realized. Then we define the concept of state transition and design a state transition model for sensor nodes. By introducing Markov chain, we further propose a task prediction method to predict the local task load in the next time period. Finally, we propose an energy-efficiency node scheduling algorithm based on game theory (ENSG) for WSNs. To obtain better performance, the residual energy of sensor nodes and local task load are both considered into the payoff function of our game. Our simulation results show that ENSG can guarantee the real-time task completion and prolong the lifetime of network.

An Energy-Efficient Coverage Enhancement Strategy for Wireless Sensor Networks Based on a Dynamic Partition Algorithm for Cellular Grids and an Improved Vampire Bat Optimizer

“…The sensors are dispatched to each cluster of events to reduce and balance energy consumption during movement, and it greatly extends the lifetime. Aimed at guaranteeing the task completion instantaneously and extending the life-cycle of network, the authors in [30] presented an energy-efficiency node scheduling algorithm based on game theory for WSNs, and the payoff function includes both the residual energy and local task load of the sensor nodes. A Hungarian algorithm (HA) [31] is used to solve the NP-hard problem of deterministic coverage enhancement with small time complexity [32], that is, the shortest moving scheme between the initial position of each sensor node and the position to be deployed is determined by the maximum matching algorithm of bipartite graph [33,34].…”

Blind RSSD-Based Indoor Localization with Confidence Calibration and Energy Control

“…Energy control is another important issue in WSN applications without a fixed supplement of electricity [ 23 , 24 , 25 ]. The majority of energy control procedures are based on task scheduling [ 26 , 27 ], topology optimization [ 28 , 29 ] and smart clustering [ 30 , 31 ] but do not focus on reducing energy consumption by unnecessary nodes. Several anchor nodes are necessary in current position estimation, whereas others can be set to sleep to save energy.…”