Abstract
Sleep scheduling, which is putting some sensor nodes into sleep mode without harming network functionality, is a common method to reduce energy consumption in dense wireless sensor networks. This paper proposes a distributed and energy efficient sleep scheduling and routing scheme that can be used to extend the lifetime of a sensor network while maintaining a user defined coverage and connectivity. The scheme can activate and deactivate the three basic units of a sensor node (sensing, processing, and communication units) independently. The paper also provides a probabilistic method to estimate how much the sensing area of a node is covered by other active nodes in its neighborhood. The method is utilized by the proposed scheduling and routing scheme to reduce the control message overhead while deciding the next modes (full-active, semi-active, inactive/sleeping) of sensor nodes. We evaluated our estimation method and scheduling scheme via simulation experiments and compared our scheme also with another scheme. The results validate our probabilistic method for coverage estimation and show that our sleep scheduling and routing scheme can significantly increase the network lifetime while keeping the message complexity low and preserving both connectivity and coverage.
Highlights
In recent years, advances in wireless communications and electronics have enabled the development of low-power and small size sensor nodes
This paper proposes a distributed and energy efficient sleep scheduling and routing scheme that can be used to extend the lifetime of a sensor network while maintaining a user defined coverage and connectivity
We investigated the sleep scheduling problem for energy conservation in wireless sensor networks
Summary
Advances in wireless communications and electronics have enabled the development of low-power and small size sensor nodes. A common technique is to put some sensor nodes into sleep and use only a necessary set of active nodes for sensing and communication This technique is called sleep scheduling or density control. The method assumes that a large number of sensor nodes are deployed uniformly and randomly to target region Based on this assumption and by just knowing the number of neighbors of a node, the expected amount of overlapping coverage is computed, without requiring to know the exact locations of nodes. Our scheme assumes a static sensor network where nodes are densely, randomly and uniformly distributed It works with local interactions only, reduces the energy consumption in the network, and works with low control messaging overhead while each node is learning about the status of the neighborhood nodes and deciding its mode for the round.
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