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Proceedings ArticleDOI

Max-min d-cluster formation in wireless ad hoc networks

TLDR
A heuristic to form d-clusters in a wireless ad hoc network that tends to re-elect existing clusterheads even when the network configuration changes and has a tendency to evenly distribute the mobile nodes among the clusterheads, and evently distribute the responsibility of acting as clusterheads among all nodes.
Abstract
An ad hoc network may be logically represented as a set of clusters. The clusterheads form a d-hop dominating set. Each node is at most d hops from a clusterhead. Clusterheads form a virtual backbone and may be used to route packets for nodes in their cluster. Previous heuristics restricted themselves to 1-hop clusters. We show that the minimum d-hop dominating set problem is NP-complete. Then we present a heuristic to form d-clusters in a wireless ad hoc network. Nodes are assumed to have a non-deterministic mobility pattern. Clusters are formed by diffusing node identities along the wireless links. When the heuristic terminates, a node either becomes a clusterhead, or is at most d wireless hops away from its clusterhead. The value of d is a parameter of the heuristic. The heuristic can be run either at regular intervals, or whenever the network configuration changes. One of the features of the heuristic is that it tends to re-elect existing clusterheads even when the network configuration changes. This helps to reduce the communication overheads during transition from old clusterheads to new clusterheads. Also, there is a tendency to evenly distribute the mobile nodes among the clusterheads, and evently distribute the responsibility of acting as clusterheads among all nodes. Thus, the heuristic is fair and stable. Simulation experiments demonstrate that the proposed heuristic is better than the two earlier heuristics, namely the LCA and degree-based solutions.

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Journal ArticleDOI

Size-restricted cluster formation and cluster maintenance technique for mobile ad hoc networks

TL;DR: A size‐restricted, distributed clustering strategy (cluster formation and cluster maintenance) for mobile ad hoc networks and uses a weight‐based cluster head election strategy which results in less change in cluster head and higher cluster head lifetime when compared to the Least Cluster Head Changes (LCC) with lowest ID algorithm.
Journal ArticleDOI

Performance analysis of decode-and-forward relaying with partial relay selection for multihop transmission over Rayleigh fading channels

TL;DR: This paper proposes a cluster-based multihop wireless network that makes use of the advantages ofMultihop relaying, i.e., path loss gain, and partial relay selection in each hop, and the probability of SNR gain over direct transmission is investigated for different environments.
Proceedings ArticleDOI

Address Borrowing In Wireless Personal Area Network

TL;DR: A unified address borrowing scheme which can be easily applied to grow the network beyond 16 hops and overcome the address exhaustion problem by borrowing address is provided.
Proceedings ArticleDOI

Detecting DoS attacks in WSN based on clustering technique

TL;DR: This paper proposes an energy-preserving solution to detect compromised nodes in WSNs based on hierarchical clustering technique which elect Controlled nodes that analyze the traffic inside a cluster and to send warnings to the cluster-head whenever an abnormal behavior is detected.
Proceedings ArticleDOI

Cluster-based routing overhead in networks with unreliable nodes

TL;DR: A mathematical framework for quantifying the overhead of a cluster-based routing protocol and shows that clustering does not change the traffic requirement for infinite scalability compared to flat protocols, but reduces the overhead by a factor of O(1/M) where M is the cluster size.
References
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