Abstract :
In contrast to the traditional wireless sensor network (WSN) applications that perform only data collection and aggregation, new generation of information processing applications, such as pursuit-evasion games, tracking, evacuation, and disaster relief applications, require in-network information storage and querying. Due to the resource limitations of WSNs, it is challenging to implement in-network information storage and querying in a resilient, energy-efficient, and distributed manner. To address these challenges, we exploit location information and geometry of the network and present an in-network querying infrastructure, namely distributed quad-tree (DQT) structure. DQT satisfies efficient in-network information storage as well as distance-sensitive querying: the cost of answering a query for an event is at most a constant factor (in our case 2radic2 ) of the distance "d" to the nearest event in the network. DQT construction is local and does not require any communication. Moreover, due to its minimalist infrastructure and stateless nature, DQT shows graceful resilience to the face of failures.
Keywords :
quadtrees; query processing; spatial data structures; wireless sensor networks; distributed quad-tree; in-network information querying infrastructure; in-network information storage; spatial querying; wireless sensor network; Application software; Communications Society; Computer science; Cost function; Delay; Energy efficiency; Information processing; Resilience; Road accidents; Wireless sensor networks;