Rapid Data Transmission Techniques in Wireless Sensor Network

Abstract

In this report we analyse and compare two algorithms for query based convergecast in WSNs and show that it’s possible to achieve better performances in terms of energy consumption and latency. Event aggregation in WSNs is a process of combining several low-level events into a high-level event to eliminate redundant information to be transmitted and thus save energy. Existing works on event aggregation consider either latency constraint or aggregation function, but not both. Moreover, existing works only consider optimal aggregation for single high level event, but many applications are composed of multiple high-level events. This studies the problem of aggregating multiple high-level events in WSNs with different latency constraints and aggregation functions. We propose relation matrix to define aggregation function, which describes the similarity among limited number of primitive events rather than the growing number of high-level events. Based on it, we propose an event aggregation algorithm jointly considering the two issues for single high-level event. This algorithm supports partial aggregation which is more general than fully aggregation and we focus on another important aspect of aggregation, i.e., delay performance. In conjunction with link scheduling, in-network aggregation can reduce the delay by lessening the demands for wireless resources and thus expediting data transmissions. We formulate the problem that minimizes the sum delay of sensed data, and analyse the performance of optimal scheduling with in-network aggregation in tree networks under the node-exclusive interference model. We provide a system wide lower bound on the delay and use it as a benchmark for evaluating different scheduling policies. We numerically evaluate the performance of myopic and non-myopic scheduling policies, where myopic one considers only the current system state for a scheduling decision while non-myopic one simulates future system states. We show that the one-step non-myopic policies can substantially improve the delay performance. In particular, the proposed non-myopic greedy scheduling achieves a good trade-offs between performances and implement ability. So we propose and efficient distributed method that produces a collision free schedule for data aggregation in WSNs. We theoretically prove that latency of data aggregation schedule generated by our algorithm is at most 16R + Δ - 14 timeslots. Here R is network radius and is the maximum node degree in the communication graph of the original network.