Energy management for time-critical energy harvesting wireless sensor networks
SSS'10 Proceedings of the 12th international conference on Stabilization, safety, and security of distributed systems
Cooperative energy management in distributed wireless real-time systems
Wireless Networks
Rolling-horizon scheduling for energy constrained distributed real-time embedded systems
Journal of Systems and Software
High performance dynamic voltage/frequency scaling algorithm for real-time dynamic load management
Journal of Systems and Software
Design exploration of energy-performance trade-offs for wireless sensor networks
Proceedings of the 49th Annual Design Automation Conference
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Performing end-to-end energy management for the data aggregation application poses certain unique challenges particularly when the computational demands on the individual nodes are significant. In this paper, we address the problem of minimizing the total energy consumption of data aggregation with an end-to-end latency constraint while taking into account both the computational and communication workloads in the network. We consider a model where individual nodes support both Dynamic Voltage Scaling (DVS) and Dynamic Modulation Scaling (DMS) power management techniques and explore the energy-time tradeoffs these techniques offer. Specifically, we make the following contributions in this paper. First, we present an analytical problem formulation for the ideal case where each node can scale its frequency and modulation continuously. Second, we prove that the problem is NP-Hard for practical scenarios where such continuity cannot be supported. We then present a Mixed Integer Linear Programming (MILP) formulation to obtain the optimal solution for the practical problem. Further, we present polynomial time heuristic algorithms which employ the energy-gain metric. We evaluated the performance of the proposed algorithms for a variety of scenarios and our results show that the energy savings obtained by the proposed algorithms are comparable to that of MILP.