Architectures and methods for energy-efficient querying and indexing in wireless sensor networks.

摘要

Wireless sensor networks have been an active research area for about a decade due to their adaptability to applications involving long-term environmental monitoring. Recent technologies make it possible that a small device equipped with multi-purposed sensors, small CPU and memory, wireless transmitter and receiver, and software can form a network, measure some quantitative phenomena and communicate with each other seamlessly. In wireless sensor networks, one of the basic applications is to monitor events and measure values at places that people cannot reach easily or where a long term sensing task is required. In this case, we need to know the properties of diverse types of sensor network queries and data that are different from traditional ones. Also, we need to solve the intrinsic sensor network problem, energy saving, since users want to gather data for a long term and it is generally not feasible to replace batteries in sensor devices after the sensors are deployed.;In order to solve this problem, first, we classify sensor network queries and find a suitable network system that includes different routing and storage types for each type of query. Second, energy efficient indexing and data gathering methods for sensor networks are studied. In energy efficient indexing, we propose a sectioned tree index, which divides the network area into several squares and each square has a local index subtree organized within that square. Local trees are interconnected to form one big tree in the network. Local trees are also built based on any algorithm that is energy consumption aware at each sub-root node in a locally centralized way. In energy efficient data gathering, we create energy-efficient data gathering routing tree when we consider two-way communication for reliable transmission and collision prevention. This makes the problem intractable, and we prove our problem is NP-complete by showing that a known NP-complete problem is a special case of our problem. In order to get an energy-efficient routing tree, we propose several heuristic techniques that backtrack one or two steps (BT1 and BT2). We give various values as parameters in measuring energy equation and simulate our proposed algorithms in diverse conditions.