APDA: Adaptive pruning & data aggregation algorithms for query based wireless sensor networks

TLDR: The research contribution presents data reporting using the adaptive dynamic pruning and data aggregation algorithms for query based wireless sensor network called as APDA to prolong the network lifetime and reduce query latency while reducing the communication runtime overheads.

Abstract: The research contribution presents data reporting using the adaptive dynamic pruning and data aggregation algorithms for query based wireless sensor network called as APDA. The aim of APDA is to reduce the network communication overheads through dynamic sub-network pruning to save the energy, minimize the unnecessary extra non relevant data transmissions. We construct tree rooted at base station BS. Mainly, proposed work includes three algorithms: 1) network formation using MST, 2) data aggregation using normalization, and 3) pruning technique with multi-cast communication. Aggregation tree includes dominator nodes (DN) which perform certain operations like data aggregation, multicast communication and pruning the sub network using normalized values in the range of 0 to 1 and at lower layer i.e. Inferior nodes (IN) sense the requested information and reports to its upstream DN nodes. The objective of APDA is to prolong the network lifetime and reduce query latency while reducing the communication runtime overheads. The solutions are well demonstrated through extensive simulations to prove the validity of proposed approaches to minimize the query response time and to get in time delivery of requested data.