Delay-Efficient Data Collection with Dynamic Traffic Patterns in Wireless Sensor Networks

Data collection is one of the most important applications in Wireless Sensor Networks (WSNs), where the data are gathered from sensor nodes to the base station. To reduce energy consumption, the sensor node may not report every sensed data sample to the base station. Thus, the network traffic of continuous data collection application often varies unpredictably over different sampling intervals. In this paper, we propose an energy-efficient scheme, DelayEfficient Traffic Adaptive (DETA), for collecting data from sensor nodes with minimum delay according to the traffic load. The DETA scheme minimizes data collection delay by constructing a delay-efficient, collision-free schedule, and by using an adaptive mechanism to enable every node to self-adapt to the change of traffic. The simulation results show that our proposed solution could significantly decrease data collection delay and obtain reasonable values of energy consumption compared with other schemes.