ACM Transactions on Sensor Networks (TOSN)
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Wireless sensor networks are often battery-powered, and hence extending the network lifetime is one of the primary concerns in the ubiquitous deployment of wireless sensor networks. One approach to efficiently utilize the limited energy supplies of the sensors is to have the medium access control (MAC) protocol duty-cycle the sensors, periodically putting the sensors to sleep and waking them up to reduce idle listening, which is energy intensive. Among duty-cycled MAC protocols, some protocols are synchronized so that nodes wake up at the same time in each cycle, and other protocols are asynchronous, where nodes have arbitrary offsets to start their cycles. For protocol designers, it is important to understand which type of duty-cycled MAC protocol should be chosen (synchronized or asynchronous), as well as what values should be assigned to the protocol parameters under a given network scenario in order to achieve a desirable performance for throughput, delay, or energy consumption. However, previous work to analyze the performance of different duty-cycled MAC protocols is either protocol-specific, or limited to one aspect of the performance metric. In this paper, we propose a Markov queuing model to analyze the throughput, delay, and energy consumption of both synchronized and asynchronous duty-cycled MAC protocols with applications to S-MAC and X-MAC. Our contributions include: 1) proposing a Markov queuing model to describe the queuing behavior of both synchronous and asynchronous duty-cycled nodes, 2) modeling the queue dynamics and the stationary probability of packet transmissions for S-MAC, a synchronized duty-cycled MAC protocol, to analyze its performance, 3) modeling the queue dynamics and the stationary probability of packet transmissions for X-MAC, an asynchronous duty-cycled MAC protocol, to analyze its performance, 4) providing comprehensive performance estimation and comparison for different duty-cycled MAC protocols, and 5) providing flexibility to tradeoff different performance metrics by optimizing the protocol parameters. Our model results are validated by comparing with NS-2 and Matlab simulations.