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A chromosome represents a mapping of tasks to sensor nodes.
These constraint satisfaction approaches neither address mapping of tasks to sensor nodes nor discuss the resource consumption/performance trade-off.
This generic role assignment approach does consider the energy consumption but not the ordering of tasks to sensor nodes.
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We also plan to investigate the fairness in the energy consumption of the sensors, and strategies that assign testing tasks to sensors with more residual energy.
In the literature on task allocation for WSNs [7 9, 12, 13], given a directed acyclic graph (DAG) and initial available resources, the set of tasks is assigned to sensor nodes based on a known static energy model.
The tasks are queued for assignment to sensor nodes based on LST.
Thus, the cost of a test executed by sensor v i on sensor v j is equal to the sum of the energy spent sending a test task from sensor v i to sensor v j plus the test reply by the tested sensor v j back to sensor v i.
Solving this problem results in execution sequence of tasks and assignment of tasks to the sensor nodes.
Furthermore, the WSN task may be shared among multiple sensors due to sensor overlaps as a result of less collisions and packet drops.
For determining the next task to execute, sensor nodes need to consider the available energy and the energy required for executing that task.
The task graph is shown, along with the mapping of tasks to nodes in the wireless sensor network.
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