Wake on wireless: an event driven energy saving strategy for battery operated devices
Proceedings of the 8th annual international conference on Mobile computing and networking
Multi-agent algorithms for solving graphical games
Eighteenth national conference on Artificial intelligence
Taming the underlying challenges of reliable multihop routing in sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems
Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems
Medium access control with coordinated adaptive sleeping for wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
Dynamic power management using on demand paging for networked embedded systems
Proceedings of the 2005 Asia and South Pacific Design Automation Conference
Etiquette protocol for ultra low power operation in energy constrained sensor networks
Etiquette protocol for ultra low power operation in energy constrained sensor networks
A high-throughput path metric for multi-hop wireless routing
Wireless Networks - Special issue: Selected papers from ACM MobiCom 2003
Routing techniques in wireless sensor networks: a survey
IEEE Wireless Communications
IEEE Communications Magazine
Decentralised reinforcement learning for energy-efficient scheduling in wireless sensor networks
International Journal of Communication Networks and Distributed Systems
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We present a game-theoretic self-organizing approach for scheduling the radio activity of wireless sensor nodes. Our approach makes each node play a win-stay lose-shift (WSLS) strategy to choose when to schedule radio transmission, reception and sleeping periods. The proposed strategy relies only on local interactions with neighboring nodes, and is thus fully decentralized. This behavior results in shorter communication schedules, allowing to not only reduce energy consumption by reducing the wake-up cycles of sensor nodes, but also to decrease the data retrieval latency. We implement this WSLS approach in the OMNeT++ sensor network simulator where nodes are organized in three topologies --- line, grid and random. We compare the performance of our approach to two state-of-the-art scheduling protocols, namely S-MAC and D-MAC, and show that the WSLS strategy brings significant gains in terms of energy savings, while at the same time reduces communication delays. In addition, we show that our approach performs particularly well in large, random topologies.