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Abstract-Opportunistic routing [2], [3] has been shown to improve the network throughput, by allowing nodes that overhear the transmission and closer to the destination to participate in forwarding packets, i.e., in forwarder list. The nodes in forwarder list are prioritized and the lower priority forwarder will discard the packet if the packet has been forwarded by a higher priority forwarder. One challenging problem is to select and prioritize forwarder list such that a certain network performance is optimized. In this paper, we focus on selecting and prioritizing forwarder list to minimize energy consumption by all nodes. We study both cases where the transmission power of each node is fixed or dynamically adjustable. We present an energy-efficient opportunistic routing strategy, denoted as EEOR. Our extensive simulations in TOSSIM show that our protocol EEOR performs better than the well-known ExOR protocol (when adapted in sensor networks) in terms of the energy consumption, the packet loss ratio, and the average delivery delay.

Abstract-Motivated by the needs of precise carbon emission measurement and real-time surveillance for CO2 management in cities, we present CitySee, a real-time CO2-monitoring system using sensor networks for an urban area (around 100 square kilometers). In order to conduct environment monitoring in a real-time and long-term manner, CitySee has to address the following challenges, including sensor deployment, data collection, data processing, and network management. In this discussion, we mainly focus on the sensor deployment problem so that necessary requirements like connectivity, coverage, data representability are satisfied. We also briefly go through the solutions for the remaining challenges. In CitySee, the sensor deployment problem can be abstracted as a relay node placement problem under hole-constraint. By carefully taking all constraints and real deployment situations into account, we propose efficient and effective approaches and prove that our scheme uses additional relay nodes at most twice of the minimum. We evaluate the performance of our approach through extensive simulations resembling realistic deployment. The results show that our approach outperforms previous strategies. We successfully apply this design into CitySee, a large-scale wireless sensor network consisting of 1096 relay nodes and 100 sensor nodes in Wuxi City, China.