Page 2 Lecture Notes in Computer Science 2865 Edited by G. Goos ...

IDEA: An Iterative-Deepening Algorithm for Energy-Efficient Querying 209maintained by the transmitter after transmitting to the new nodes. [4] also usesthe concept of elimination set based on the tuple of location co-ordinates andneighbor nodes for a particular node; it also uses a negative acknowledgementscheme for retransmissions. Algorithm in this paper does not keep the state ofthe broadcast either for the IDEA search or for the token-based, T-IDEA search,since it scales robustly to any change in the topology.Many approaches use the topological information of the ad hoc network.[10] selects a set of neighbors called multipoint relays (MPR), based on thetopological information such that each node covers the same network region,which the complete set of neighbors does. The computation of this minimal setis NP-Complete problem. The iterative-deepening search in this work does notexploit any topology information, but tries to exploit tokens received from theneighbor nodes (in case of T-IDEA).Several works use the concept of dominating set to optimally broadcast thepackets, which are different from the approach addressed by this paper whichdoes an optimal flooding based on a policy(s). [9] proposed a distributed deterministicalgorithm, which defined a set as dominating if all nodes in that graphare either the neighbor nodes belonging to the set or in the set of neighbors.Two rules are proposed to reduce the number of internal nodes.Another genre of solutions was the cluster-based approach, where nodes organizethemselves in clusters and nominate cluster heads to do the routing. [6],[12], [13] perform clustering for a hierarchical routing scheme, but not mainlyfor efficient flooding. This scheme depends on the complete neighbor informationand incurs an overhead due to exchange of ‘HELLO’ messages. These classicalclustering approaches focus on forming clusters but do not have an optimal connectedset with least number of clusters. More recent work like [5] is based onself-pruning methods that makes local decisions on the forwarding status. Thisdepends on small clustered topology creation which changes dynamically. However,this work forms a topology of nodes involved in the searching, but does nothave clustering, it is completely granular to single node level.8 ConclusionThis paper examined a novel approach for efficient searching in ad-hoc sensornetworks. The results in section 7 show the trade-off(s) involved in the IDEAalgorithm(s),described in this paper, compared to classical search and queryalgorithms. This paper includes several contributions. First, IDEA algorithmis probably the first algorithm (to the best of author’s knowledge) to use theiterative-deepening algorithm to efficiently control the flooding in a ad-hoc sensornetwork. Second, the token-based algorithm T-IDEA, gives a self-stabilizingapproach to dynamically adapt to the constraints of individual nodes in thenetwork. Unlike previous approaches, this does not use any complex algorithmbut is based on the local decisions, based on per-node characteristics, made bythe nodes individually in the sensor network. Finally simulations show that theIDEA algorithm (s) perform better that the classical approaches in an energyconstrainednetwork environment. IDEA and T-IDEA reduce the aggregate en-