Clustering of Mobile Ad Hoc Networks: An Adaptive Broadcast Period Approach

Organization, scalability and routing have been identified as key problems hindering viability and commercial success of mobile ad hoc networks. Clustering of mobile nodes among separate domains has been proposed as an efficient approach to address those issues. In this work, we introduce an efficient distributed clustering algorithm that uses both location and energy metrics for cluster formation. Our proposed solution mainly addresses cluster stability, manageability and energy efficiency issues. Also, unlike existing active clustering methods, our algorithm relieves the network from the unnecessary burden of control messages broadcasting, especially for relatively static network topologies. This is achieved through adapting broadcast period according to mobile nodes mobility pattern. The efficiency, scalability and competence of our algorithm against alternative approaches have been demonstrated through simulation results.Comment: 7 pages, 9 figures; IEEE International Conference on Communications, 2006. ICC '0

Distributed Clustering in Cognitive Radio Ad Hoc Networks Using Soft-Constraint Affinity Propagation

Absence of network infrastructure and heterogeneous spectrum availability in cognitive radio ad hoc networks (CRAHNs) necessitate the self-organization of cognitive radio users (CRs) for efficient spectrum coordination. The cluster-based structure is known to be effective in both guaranteeing system performance and reducing communication overhead in variable network environment. In this paper, we propose a distributed clustering algorithm based on soft-constraint affinity propagation message passing model (DCSCAP). Without dependence on predefined common control channel (CCC), DCSCAP relies on the distributed message passing among CRs through their available channels, making the algorithm applicable for large scale networks. Different from original soft-constraint affinity propagation algorithm, the maximal iterations of message passing is controlled to a relatively small number to accommodate to the dynamic environment of CRAHNs. Based on the accumulated evidence for clustering from the message passing process, clusters are formed with the objective of grouping the CRs with similar spectrum availability into smaller number of clusters while guaranteeing at least one CCC in each cluster. Extensive simulation results demonstrate the preference of DCSCAP compared with existing algorithms in both efficiency and robustness of the clusters

Efficient channel allocation and medium access organization algorithms for vehicular networking

Due to the limited bandwidth available for Vehicular Ad-hoc Networks (VANETs), organizing the wireless channel access to efficiently use the bandwidth is one of the main challenges in VANET. In this dissertation, we focus on channel allocation and media access organization for Vehicle-to-Roadside Units (V2R) and Vehicle-to-Vehicle (V2V) communications. An efficient channel allocation algorithm for Roadside Unit (RSU) access is proposed. The goal of the algorithm is to increase system throughput by admitting more tasks (vehicles) and at the same time reduce the risk of the admitted tasks. The algorithm admits the new requests only when their requirements can be fulfilled and all in-session tasks\u27 requirements are also guaranteed. The algorithm calculates the expected task finish time for the tasks, but allocates a virtual transmission plan for the tasks as they progress toward the edges of the RSU range. For V2V mode, we propose an efficient medium access organization method based on VANETs\u27 clustering schemes. In order to make this method efficient in rapid topology change environment like VANET, it\u27s important to make the network topology less dynamic by forming local strongly connected clustering structure, which leads to a stable network topology on the global scale. We propose an efficient cluster formation algorithm that takes vehicles\u27 mobility into account for cluster formation. The results of the proposed methods show that the wireless channel utilization and the network stability are significantly improved compared to the existing methods