Selective forwarding or dropping of packets is a serious threat to multi hop communication in a Wireless Sensor Network (WSN). There are various schemes to induce cooperation in a WSN to overcome this problem. In this paper, we have introduced a novel adversary model and have proposed an incentive based scheme to inspire cooperation among nodes in a Geometric Structure based WSN. The scheme has been formally analyzed. The efficacy of the scheme is also established through various simulation experiments.
Nodes in mobile ad-hoc networks are arbitrarily deployed without relying on any fixed network infrastructure. In a multi-hop wireless network, many ...view middle of the document...
One way to support efficient communication between nodes is to develop wireless backbone architecture.
In all these papers, nodes are classified in two categories: TRUSTED those who forward packets and MALICIOUS, those who do not like to forward others’ packets. Moreover, malicious nodes, according to these papers are content by dropping packets to conserve their resources. In this paper, we have introduced two further dimensions to this misbehavior model. First, we introduced a ‘rational adversary’ category of nodes. ‘Rational adversary nodes’ do not mind dropping packets if they are not penalized for that. Second, we have incorporated an idea by which ‘malicious’ nodes inspire their neighboring nodes to drop packets.
In order to design backbone network Trusted nodes are elected to form the backbone. These nodes are called clusterheads and gateways. Clusterheads are nodes that are vested with the responsibility of routing messages for all the nodes within their cluster. Cluster heads may form a second tier network, i.e. making another level of hierarchy or they may just pass on the data to the base station. Gateway nodes are nodes at the fringe of a cluster and typically communicate with gateway nodes of other clusters. The wireless backbone can be used either to route packets, or to disseminate routing information, or both. Due to the mobility of nodes in an ad hoc network, the backbone must be continuously reconstructed in a timely fashion, as the nodes move away from their associated clusterheads.
For Leader election algorithm, I want to use generalized clustering heuristics like “Max-Min D-Cluster Formation” made cluster head formation with nodes at most D hops away from a cluster head. These were distributed leader election heuristic for an ad hoc network, guaranteeing that no node is more than D hops away from a leader, where D is a value selected for the heuristic. Thus, this heuristic extends the notion of cluster formation. Existing 1-hop clusters are an instance of the generic D-hop clusters. The proposed heuristic provides load balancing among clusterheads to insure a fair distribution of load among clusterheads. Additionally, the heuristic elects clusterheads in such a manner as to favor their re-election in future rounds,...