Duty cycling is a technique for saving energy in resource-limited wireless networks such as sensor networks. With duty cycling, each node periodically switches between active and sleeping states, for example being active for only 1 to 10 percent of the time. Wireless duty-cycling networks face many challenges such as maintaining high energy efficiency, efficient packet delivery under dynamic channel conditions, and effective route discovery. This thesis presents a series of protocols to address these challenges.
The first part of this thesis presents a new single-channel energy-efficient MAC protocol, called the Predictive-Wakeup MAC (PW-MAC). The key idea behind PW-MAC is to allow each node to wake up asynchronously at randomized times, while enabling senders to predict receiver wakeup times to save energy.
Extending the randomized predictive wakeup mechanism of PW-MAC, the second part of this thesis presents a new multichannel energy-efficient MAC protocol, called the Efficient-Multichannel MAC (EM-MAC). EM-MAC enables each node to dynamically optimize the selection of wireless channels it utilizes based on the channel conditions it senses. By adapting to changing channel conditions, EM-MAC achieves high packet delivery performance. EM-MAC also achieves high energy efficiency through its predictive multichannel wakeup mechanism.
Although duty cycling saves energy, I found that, in asynchronous duty-cycling networks, existing on-demand routing protocols tend to discover routes much worse than the optimal routes. The last part of this thesis presents four optimization techniques to improve the routes discovered in such networks. These optimizations are fully distributed and work on different route metrics, such as hop-count and ETX.
Implemented in TinyOS on a testbed of MICAz sensor nodes, PW-MAC achieved the lowest energy consumption and delivery latency among the single-channel protocols, while EM-MAC significantly outperformed all other protocols tested. EM-MAC maintained the lowest duty cycles, the lowest packet delivery latency, and 100% packet delivery ratio across all experiments, including those with concurrent multihop traffic flows, and those with heavy ZigBee and Wi-Fi interference. Finally, in simulations on the ns-2 network simulator, compared with the conventional on-demand route discovery, the presented route discovery optimizations substantially improved the routes discovered in asynchronous duty-cycling networks.