communication protocol for wireless sensor networks

Many wireless network applications, such as wireless computing on local area networks, employ data throughput as a primary performance metric. The data throughput on such networks has therefore been increasing in recent years. However, there are other potential wireless network applications, such as industrial monitoring and control, consumer home automation, and military remote sensing, that have relaxed throughput requirements, often measured in bits/day. Such networks have power consumption and cost as primary performance metrics, rather than data throughput, and have been called wireless sensor networks. This work describes a physical layer, a data link layer, and a network layer design suitable for use in wireless sensor networks. To minimize node duty cycle and therefore average power consumption, while minimizing the symbol rate, the proposed physical layer employs a form of orthogonal multilevel signaling in a direct sequence spread spectrum format. Results of Signal Processing Worksystem (SPW, Cadence, Inc.) simulations are presented showing a 4-dB sensitivity advantage of the proposed modulation method compared to binary signaling, in agreement with theory. Since the proposed band of operation is the 2.4 GHz unlicensed band, interference from other services is possible; to address this, SPW simulations of the proposed modulation method in the presence of Bluetooth interference are presented. The processing gain inherent in the proposed spread spectrum scheme is shown to require the interferer to be significantly stronger than the desired signal before materially affecting the received bit error rate. The proposed data link layer employs a novel distributed mediation device (MD) technique to enable networked nodes to synchronize to each other, even when the node duty cycle is arbitrarily low (e.g., <0.1%). This technique enables low-cost devices, which may employ only low-stability time bases, to remain asynchronous to one another, becoming synchronized only when communication is necessary between them. Finally, a wireless sensor network design is presented. A cluster-type architecture is chosen; the clusters are organized in a hierarchical tree to simplify the routing algorithm. Results of several network performance metrics simulations, including the effects of the distributed MD dynamic synchronization scheme, are presented, including the average message latency, node duty cycle, and data throughput. The architecture is shown to represent a practical alternative for the design of wireless sensor networks.