| To bridge the gap between the increasing demand of deploying sustainable sensor networks for practical applications and the limited energy supply of each low-profile sensor node, recent research studies suggest operating sensor nodes in a duty-cycling work mode to save energy. Although the duty-cycling technique turns out to notably increase the lifetime of sensor nodes, the network lifetime can still be largely limited due to the unevenly distributed network traffic load in many applications. In addition, excessive challenges are introduced for implementing a variety of basic operations with the duty-cycling technique, which could deteriorate the performances of a series of important network services, like information dissemination, data acquisition, end-to-end packet delivery, etc. In this thesis, we aim at studying fundamental challenges, and further achieving a sustainable and efficient communication design in duty-cycling sensor networks.;We first investigate the problem of controlling node sleep intervals so as to achieve the minmax energy fairness to maximize the network lifetime. We theoretically formulate the Sleep Interval Control (SIC) problem and find it a convex optimization problem. By utilizing the convex property, we decompose the original problem and propose a distributed algorithm, called GDSIC. In GDSIC, sensor nodes can tune sleep intervals through a local information exchange such that the maximum energy consumption rate in the network approaches to be minimized. After balancing the network-wide energy consumption, we further optimize the data collection service in duty-cycling networks. We propose a novel approach for collecting the network-wide data. The routing structure of data collection is additively updated with the movement of the user. With this approach, we only perform a local modification to update the routing structure while the routing performance is bounded and controlled compared to the optimal performance. Next, although the routing structure can be efficiently constructed, the routing structure formation process itself cannot completely ensure the system QoS in data transmissions. Due to limitations of the duty-cycling operation and interference, not all data transmissions tasks can be guaranteed to be scheduled within required delay deadlines. We thus investigate the multi-task schedulability problem to determine the maximum number of tasks that can be scheduled within their deadlines. We formulate the multi-task schedulability problem, prove its NP-Hardness, and propose an approximate algorithm. We further extend the proposed algorithm by explicitly altering duty cycles of certain sensor nodes so as to fully support applications with stringent delay requirements to accomplish all tasks. Finally, time synchronization is required to support many duty-cycling protocols and applications. We propose a novel synchronization approach called FLIGHT, which leverages the fact that the fluorescent light intensity changes with a stable period that equals half of the alternating current’s. By tuning to the light emitted from indoor fluorescent lamps, FLIGHT can intelligently extract the light period information and achieve network wide time calibration by referring to such a common time reference. FLIGHT can achieve tightly synchronized time with low energy consumption. In addition, FLIGHT does not occupy radio for the synchronization, which is greatly beneficial for a large number of indoor applications in duty-cycling sensor networks. |
