Hierarchical Agglomerative Aggregation Scheduling in Directional Wireless Sensor Networks

In this paper, we study the Minimum Latency Aggregation Scheduling (MLAS) problem in Wireless Sensor Networks (WSNs). The MLAS problem targets to attain data aggregation schedules that satisfy the two desirable properties: minimum latency and no collisions. Most existing works explored the problem under the uniform power model with no power control in omnidirectional WSNs. However, we investigate it under a more realistic non-uniform power model with power control in directional WSNs. To the best of our knowledge, addressing the MLAS problem in directional WSNs under non-uniform power model with power control is unprecedented. Unlike existing works that schedule nodes based on trees, our proposed scheduling algorithm does not create trees. Specifically, our algorithm employs multilevel divide-and-conquer steps, where a whole network is repeatedly partitioned into smaller networks and the smaller networks are systematically agglomerated to achieve the two desirable properties. We assess the performance of the proposed algorithm in terms of latency and power level for simulated networks.