A major concern in designing and operating WSNs is their energyefficiency. Cross-layer optimization is widely accepted as an effective technique to ameliorate this concern. The basic idea is to share information across different system layers and to enable tradeoffs involving multiple layers, which provides a larger optimization space for system design. Crosslayer optimization in the context of collaborative information processing and routing is the motivation of this book.
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Posted: October 26th, 2008, 6:41am CET
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Wireless sensor networks (WSNs) have become an important technology in the realization of many applications, including both simple event/phenomena monitoring applications and heavy-duty data streaming applications. While many systems are being developed, we focus on two fundamental operations: information processing and information routing. In the data-centric operating paradigm of WSNs, these two operations are tightly related and must be performed in a collaborative fashion.
A major concern in designing and operating WSNs is their energyefficiency. Cross-layer optimization is widely accepted as an effective technique to ameliorate this concern. The basic idea is to share information across different system layers and to enable tradeoffs involving multiple layers, which provides a larger optimization space for system design. Crosslayer optimization in the context of collaborative information processing and routing is the motivation of this book.
A major concern in designing and operating WSNs is their energyefficiency. Cross-layer optimization is widely accepted as an effective technique to ameliorate this concern. The basic idea is to share information across different system layers and to enable tradeoffs involving multiple layers, which provides a larger optimization space for system design. Crosslayer optimization in the context of collaborative information processing and routing is the motivation of this book.
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