Modeling Data-Aggregation within Wireless Sensor Networks as Scheduling of Super Task-Flow-Graph

摘要

The paper examines the resources needed to carry on all the tasks within wireless sensor networks (WSN) by modeling the data-aggregation within WSN as a scheduling problem. A typical sensor executes three tasks periodically, which are mainly sensing, processing and transmitting. We have modeled the sensorpsilas three tasks as a task-flow graph (TFG), and then we have combined all TFGs for all sensors within WSN as a super task-flow-graph (STFG). Three scheduling algorithms (as soon as possible (ASAP), as late as possible (ALAP) and branch-and-bound (BB)) are utilized to order all tasks within STFG, subject to the concurrency of executions among the sensorspsila tasks. The computational results have provided excellent bounds on the number of gateways, which are needed to retrieve the collected data by the sensors.