Selvadurai Selvakennedy

An overview of Channel Assignment methods for multi-radio multi-channel wireless mesh networks

Channel Assignment (CA) is an active research area due to the proliferating deployments of multi-radio multi-channel wireless mesh networks. This paper presents an in-depth survey of some of the CA approaches in the literature. First, the key design issues for these approaches are identified, laying down the basis for discussion. Second, a classification that captures their essentials is proposed. Third, the different CA approaches are examined individually, with their advantages and limitations highlighted; furthermore, categorical and overall comparisons for them are given in detail, clarifying their sameness and differences. Finally, the future research directions for CA are discussed at length.

A biologically-inspired clustering protocol for wireless sensor networks

Lately, wireless sensor networks are garnering a lot of interests, as it is feasible to deploy them in many ad hoc scenarios such as for earthquake monitoring, tsunami monitoring and battlefield surveillance. As sensor nodes may be deployed in hostile areas, these battery-powered nodes are mostly expected to operate for a relatively long period. Clustering is an approach actively pursued by many groups in realizing more scalable data gathering and routing. However, it is rather challenging to form an appropriate number of clusters with well balanced memberships. To this end, we propose a novel application of collective social agents to guide the formation of these clusters. In order to counter the usual problems of such meta-heuristics, we propose a novel atypical application that allows our protocol to converge fast with very limited overhead. An analysis is performed to determine the optimal number of clusters necessary to achieve the highest energy efficiency. In order to allow for a realistic evaluation, a comprehensive simulator involving critical components of the communication stack is used. Our protocol is found to ensure a good distribution of clusterheads through a totally distributed approach. To quantify certain clustering properties, we also introduced two fitness metrics that could be used to benchmark different clustering algorithms.

T-ANT: A Nature-Inspired Data Gathering Protocol for Wireless Sensor Networks

There are many difficult challenges ahead in the design of an energy-efficient communication stack for wireless sensor networks. Due to the severe sensor node constraints, protocols have to be simple yet scalable. To this end, collective social insects’ behavior could be adopted to guide the design of these protocols. We exploit the simple heuristics of ant colony in foraging and brood sorting to design a hierarchical and scalable data gathering protocol. Also, we demonstrate how it could exploit data correlations in sensor readings to minimize communications cost in the data gathering process towards the sink. This approach selects only a subset of sensor nodes to reconstruct data for the entire network. A distributed variance estimation algorithm is introduced to capture data correlations with negligible state maintenance. It is shown that this algorithm is able to predict the values rather accurately. Due to the general robustness of any nature-inspired algorithm, our data gathering protocol is reliable. It is fully distributed, and promises scalability and substantial energy savings.

An Adaptive Data Dissemination Strategy for Wireless Sensor Networks

Future large-scale sensor networks may comprise thousands of wirelessly connected sensor nodes that could provide an unimaginable opportunity to interact with physical phenomena in real time. However, the nodes are typically highly resource-constrained. Since the communication task is a significant power consumer, various attempts have been made to introduce energy-awareness at different levels within the communication stack. Clustering is one such attempt to control energy dissipation for sensor data dissemination in a multihop fashion. The Time-Controlled Clustering Algorithm (TCCA) is proposed to realize a network-wide energy reduction. A realistic energy dissipation model is derived probabilistically to quantify the sensor networks energy consumption using the proposed clustering algorithm. A discrete-event simulator is developed to verify the mathematical model and to further investigate TCCA in other scenarios. The simulator is also extended to include the rest of the communication stack to allow a comprehensive evaluation of the proposed algorithm.

An Energy-Efficient Clustering Algorithm for Multihop Data Gathering in Wireless Sensor Networks

Wireless sensor networks afford a new opportunity to observe and interact with physical phenomena at an unprecedented fidelity. To fully realize this vision, these networks have to be self-organizing, self-healing, economical and energy-efficient simultaneously. Since the communication task is a significant power consumer, there are various attempts to introduce energy-awareness within the communication stack. Node clustering, to reduce direct transmission to the base station, is one such attempt to control energy dissipation for sensor data gathering. In this work, we propose an efficient dynamic clustering algorithm to achieve a network-wide energy reduction in a multihop context. We also present a realistic energy dissipation model based on the results from stochastic geometry to accurately quantify energy consumption employing the proposed clustering algorithm for various sensor node densities, network areas and transceiver properties.

A Configurable Time-Controlled Clustering Algorithm for Wireless Sensor Networks

Future large-scale sensor networks may comprise thousands of wirelessly connected sensor nodes that could provide an unimaginable opportunity to interact with physical phenomena in real time. These nodes are typically highly resource-constrained. Since the communication task is a significant power consumer, there are various attempts to introduce energy-awareness at different levels within the communication stack. Clustering is one such attempt to control energy dissipation for sensor data routing. Here, we propose the time-controlled clustering algorithm to realise a network-wide energy reduction by the rotation of clusterhead role, and the consideration of residual energy in its election. A realistic energy model is derived to accurately quantify the networks energy consumption using the proposed clustering algorithm

The time-controlled clustering algorithm for optimized data dissemination in wireless sensor network

As the communication task is a significant power consumer, there are many attempts to improve energy efficiency. Node clustering, to reduce direct transmission to the base station, is one such attempt to control data dissemination. Here, we derived the optimal number of clusters for TCCA clustering algorithm based on a realistic energy model using results in stochastic geometry

A Geometric Deployment and Routing Scheme for Directional Wireless Mesh Networks

This paper first envisions the advent of the wireless mesh networks with multiple radios and directional antennas in future. Then, based on the observation that simplicity induces efficiency and scalability, the paper proposes a joint geometric deployment and routing strategy for such mesh networks, and also gives a concrete approach under this strategy. The main idea of this strategy is to deploy mesh networks in certain kind of geometric graph, and then design a geometric routing protocol by exploiting the routing properties of this graph. The proposed concrete approach comprises two parts: (1) a topology generation algorithm based on Delaunay triangulations and (2) a geometric routing protocol based on the greedy forwarding algorithm. Both parts are characterized by simplicity and appealing properties, with formal proofs provided when possible. The simulation results validate our proposed approach.

A Position-Based Deployment and Routing Approach for Directional Wireless Mesh Networks

Observing that simplicity implies efficiency and scalability, this paper proposes a position-based deployment and routing strategy, and then gives a concrete approach under this strategy, for the emerging wireless mesh networks with multiple radios and directional antennas. The main idea of this strategy is to deploy the mesh network in certain kind of geometric graph and then design a position-based routing protocol by exploiting the routing properties of this graph. The proposed concrete approach comprises two parts: (1) a topology generation algorithm based on Delaunay triangulations and (2) a routing protocol based on the greedy forwarding algorithm. Both parts have appealing properties for deployment or routing, with formal proofs provided when applicable. Our simulation results strongly support this proposed approach.