Error Control and Energy Consumption in Communications for Nomadic Computing
IEEE Transactions on Computers - Special issue on mobile computing
Understanding packet delivery performance in dense wireless sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Link-level measurements from an 802.11b mesh network
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Temporal properties of low power wireless links: modeling and implications on multi-hop routing
Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing
On stochastic learning in predictive wireless ARQ
Wireless Communications & Mobile Computing
Improving packet delivery ratio estimation for indoor ad hoc and wireless sensor networks
CCNC'09 Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference
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Energy constrained Wireless Sensor Networks (WSNs) challenge traditional protocols in many aspects. One such challenge is the requirement of energy efficiency in the Automatic Repeat Request (ARQ) protocols. Although traditional ARQ protocols are optimized for a better throughput, they fail to minimize the energy consumption. In some applications in sensor networks, delay can be tolerated. Using this aspect, we propose a link quality aware ARQ (LQ-ARQ) protocol which only retransmits packets from a buffer when the link from the sender to the receiver is relatively good. The link quality is judged by checking the Received Signal Strength (RSS) of the data packets, thus no extra overhead is introduced. To avoid using an inflexible threshold of RSS to judge a good or bad link, which is hard to decide in practise, we propose a machine learning mechanism to decide the threshold softly depending on link quality. Our protocol is able to deliver packets reliably with least amount of retransmissions. Thus energy consumption is reduced. Moreover, usage of limited resources such as memory is minimized in the protocol. We compared our protocol with traditional ARQ protocols with real field experimental data. Results show significant improvements.