QoS-aware adaptive data collection in wireless sensor networks

Abstract

Designing a unified data collection scheme working for multiple sensing tasks is challenging when the tasks require different types and levels of quality of services (QoS). This paper proposes a QoS-aware data report scheduling (QRS) scheme for class-based adaptive data collection in a wireless sensor network possibly running multiple sensing tasks with different QoS demands. The main contributions of this work include two aspects. First, a sensor node competes with other nodes only when the nodes are transmitting the sensing result in the same class; in other words, sensor nodes do not compete with each other for data report in different classes. Second, sensor nodes reporting different types of sensing results in different classes can have differentiated channel access opportunity depending on the QoS level and this enables adaptive data collection. The simulation results show that the proposed scheme can provide stable throughput performance regardless of the network size. Copyright 2014 ACM.