Power-Aware Wireless Sensor Networks

Hać, Anna

doi:10.1002/0470867388.ch3

Cited by 1 publication

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“…In section 4, the power consumption issues in continuous time Markov model and semi Markov model have been analyzed in detailed case studies 1 & 2 respectively. It also provides some background about existing stochastic models for dynamic power management as described in the literature, aiming at their stiff and weak points in wireless sensor network applications [8]. Apart from this, it highlights the important key areas, challenges and lacuna in managing the power dynamically using power aware stochastic modelling techniques, which gives future direction for research in the WSN area.…”

Section: Introductionmentioning

confidence: 99%

A review on stochastic approach for dynamic power management in wireless sensor networks

Pughat

Sharma

2015

Hum. Cent. Comput. Inf. Sci.

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Wireless sensor networks (WSNs) demand low power and energy efficient hardware and software. Dynamic Power Management (DPM) technique reduces the maximum possible active states of a wireless sensor node by controlling the switching of the low power manageable components in power down or off states. During DPM, it is also required that the deadline of task execution and performance are not compromised. It is seen that operational level change can improve the energy efficiency of a system drastically (up to 90%). Hence, DPM policies have drawn considerable attention. This review paper classifies different dynamic power management techniques and focuses on stochastic modeling scheme which dynamically manage wireless sensor node operations in order to minimize its power consumption. This survey paper is expected to trigger ideas for future research projects in power aware wireless sensor network arenas.

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Section: Introductionmentioning

confidence: 99%