This document summarizes a paper on distributed processing of probabilistic top-k queries in wireless sensor networks. It introduces the concepts of sufficient and necessary sets, which can facilitate localized data pruning in clusters. It then describes three algorithms - sufficient set-based, necessary set-based, and boundary-based - for intercluster query processing with bounded communication rounds. Finally, it presents an adaptive algorithm that dynamically switches between the three algorithms to minimize transmission cost, and experimental results showing the algorithms significantly reduce data transmission with small constant communication rounds, with the adaptive algorithm performing near-optimally under various conditions.

1. ECWAY TECHNOLOGIES
IEEE PROJECTS & SOFTWARE DEVELOPMENTS
OUR OFFICES @ CHENNAI / TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE
CELL: +91 98949 17187, +91 875487 2111 / 3111 / 4111 / 5111 / 6111
VISIT: www.ecwayprojects.com MAIL TO: ecwaytechnologies@gmail.com
DISTRIBUTED PROCESSING OF PROBABILISTIC TOP-K QUERIES IN
WIRELESS SENSOR NETWORKS
ABSTRACT:
In this paper, we introduce the notion of sufficient set and necessary set for distributed
processing of probabilistic top-k queries in cluster-based wireless sensor networks. These two
concepts have very nice properties that can facilitate localized data pruning in clusters.
We develop a suite of algorithms, namely, sufficient set-based (SSB), necessary set-based
(NSB), and boundary-based (BB), for intercluster query processing with bounded rounds of
communications in responding to dynamic changes of data distribution in the network.
We develop an adaptive algorithm that dynamically switches among the three proposed
algorithms to minimize the transmission cost. We show the applicability of sufficient set and
necessary set to wireless sensor networks with both two-tier hierarchical and tree-structured
network topologies.
Experimental results show that the proposed algorithms reduce data transmissions significantly
and incur only small constant rounds of data communications. The experimental results also
demonstrate the superiority of the adaptive algorithm, which achieves a near-optimal
performance under various conditions.