Weighted fairness guaranteed data aggregation scheduling algorithm in wireless sensor networks

Data aggregation from a set of sensors to a common sink over a tree-based routing topology is a fundamental traffic pattern in wireless sensor networks (WSNs). The time division multiple access (TDMA)-based scheduling protocols are suitable for such data aggregation applications. Most of the previously proposed TDMA schemes focus on a particular objective, such as minimizing schedule delay, latency, and energy consumption etc. In this paper, we investigate another important aspect of aggregation, i.e., weighted fairness, and propose a novel weighted fairness guaranteed aggregation scheduling algorithm (WAS) under the protocol interference model. We use node weight to reflect the importance of each node, and introduce the weighted delay as the weighted fairness guaranteed metric. Then the problem of weighted fairness guaranteed can be translated into minimizing the weighted delay. In order to achieve this purpose, WAS utilizes the approximate maximum weighted set to allocate time slots for each node according to different accumulative weight. The results of simulation demonstrate that the weighted fairness of WAS is much better than the existing TDMA scheduling algorithm. In particular, the proposed scheduling scheme can achieve a good trade-off between weighted fairness guarantee and aggregation delay.