doi:10.1016/j.comcom.2006.11.008
Copyright © 2006 Elsevier B.V. All rights reserved.
Managing the power resources of sensor networks with performance considerations
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Khadija Stewarta, 
, 
and Spyros Tragoudasb,
aDePauw University, Greencastle, IN 46135, USA
bSouthern Illinois University Carbondale, IL 62901, USA
Received 7 December 2005;
revised 21 November 2006;
accepted 27 November 2006.
Available online 20 December 2006.
Abstract
A power management algorithm that schedules the time off intervals for nodes in sensor networks while maintaining network connectivity is proposed. The scheduling problem is formally formulated as a combinatorial optimization problem and is shown to be intractable. The performance of the proposed algorithm is compared to an optimum integer linear programming formulation. It is shown that its performance is very close to the optimum solutions for small instances. The experimental results also show that the proposed heuristic performs better than the ASAP and the sleep and listen component of the S-MAC protocol in terms of delay, throughput and energy savings.
Keywords: Sensor networks; Scheduling problem; Combinatorial optimization problem; Optimum solutions
Fig. 1. A sample cluster.
Fig. 2. The RSP schedule.
Fig. 3. The SSP schedule.
Fig. 4. A sample cluster.
Fig. 5. Latencies on the ISCAS 85 benchmarks. (a) C432 benchmark, (b) C499 benchmark, (c) C880 benchmark, (d) C2670 benchmark.
Fig. 6. Latencies on the networking benchmarks. (a) mulsol.i.1 bechmark, (b) mulsol.i.2 bechmark, (c) mulsol.i.3 bechmark, (d) mulsol.i.5 bechmark, (e) le450-5b bechmark, (f) inithx.1.2 benchmark.
Fig. 7. CPU times behavior of the Lp-solve on the ISCAS 85 benchmarks. (a) C432 benchmark, (b) C499 benchmark, (c) C880 benchmark, (d) C2670 benchmark.
Fig. 8. CPU times on the networking benchmarks. (a) mulsol.i.1 benchmark, (b) mulsol.i.2 benchmark, (c) mulsol.i.3 benchmark, (d) mulsol.i.5 benchmark, (e) le450-5b bechmark, (f) inithx.i.2 benchmarks.
Fig. 9. Average duration of time off of the motes as a function of the period of the base station.
Fig. 10. Message latency as a function of the period of the base station.
Fig. 11. AODV delay for the SSP and the ASAP algorithms.
Fig. 12. Network throughput for the SSP and the ASAP algorithms.
Fig. 13. Average latency overheads for the SSP and the sleep and listen component of the S-MAC with periods 0.5 and 0.65.
Table 1.
The ILP input file
Table 2.
Percentage of times a feasible schedule was obtained for the ISCAS85 benchmarks when using the SSP algorithm
Table 3.
Percentage of times a feasible schedule was obtained for the networking benchmarks when using the SSP algorithm
Corresponding author. Tel.: +1 812 2197192; fax: +1 765 6584732.
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