Ubiquitous wireless sensor networks (WSNs) are expected to play an important role in the future society for various applications. As a result, carefully managing the network resources to improve the network performance becomes a hot research topic. In this thesis, we study the perfonnance ofWSNs with a cluster tree topology, where all the cluster heads (CHs) fonn a tree topology. The sensor nodes transmit data to their directly associated CHs, which forward the traffic to the sink through other CHs in the cluster tree.
We first study the associations between sensor nodes and the cluster heads (CHs). In a WSN where there is a strong overlapping coverage area between the CHs, associating the sensor nodes to different CHs may result in different network performance. As the sensor node associations affect the traffic load within each cluster and that between the clusters, timeline of the CHs should be allocated accordingly. We formulate three optimization problems by jointly considering the sensor node associations and CH timeline allocations. The objectives are maximizing the throughput per sensor node, balancing the energy consumption among the CHs, and maximizing the network level throughput, respectively. Conesponding to each of the objectives, a heuristic association scheme is designed and the timeline allocations of the CHs are calculated. Numerical results based on computer simulation demonstrate that the proposed schemes achieve close-to-optimum performance.
In the second part of the thesis we study the end-to-end transmission delay for traffic at different levels of a WSN with the cluster tree topology. The end-to-end delay includes both local transmission delay between the sensor nodes and their directly associated CHs and inter-CH transmission delay between the forwarding CHs along the path to the sink. Given the timeline allocations of each CH for local and inter-cluster traffic transmissions, we find the distribution of the local traffic transmission delay and that of the inter-CH transmission delay. Based on these results, we then derive the distribution of the end-to end transmission delay and the packet drop rate due to excessive delay. The results provide important guidelines for allocating the CH time resources in order to achieve certain delay or packet drop rate performance. By appropriately allocating the CH time resources, it is possible that traffic traversing more hops to the sink experiences better delay performance than that traversing a fewer number of hops.