Dynamic distributed clustering in wireless sensor networks via Voronoi tessellation control

This paper presents two dynamic and distributed clustering algorithms for Wireless Sensor Networks (WSNs). Clustering approaches are used in WSNs to improve the network lifetime and scalability by balancing the workload among the clusters. Each cluster is managed by a cluster head (CH) node. The first algorithm requires the CH nodes to be mobile: by dynamically varying the CH node positions, the algorithm is proved to converge to a specific partition of the mission area, the generalised Voronoi tessellation, in which the loads of the CH nodes are balanced. Conversely, if the CH nodes are fixed, a weighted Voronoi clustering approach is proposed with the same load-balancing objective: a reinforcement learning approach is used to dynamically vary the mission space partition by controlling the weights of the Voronoi regions. Numerical simulations are provided to validate the approaches

Optimization strategies for two-tiered sensor networks.

Sensor nodes are tiny, low-powered and multi-functional devices operated by lightweight batteries. Replacing or recharging batteries of sensor nodes in a network is usually not feasible so that a sensor network fails when the battery power in critical node(s) is depleted. The limited transmission range and the battery power of sensor nodes affect the scalability and the lifetime of sensor networks. Recently, relay nodes, acting as cluster heads, have been proposed in hierarchical sensor networks. The placement of relay nodes in a sensor network, such that all the sensor nodes are covered using a minimum number of relay nodes is a NP-hard problem. We propose a simple strategy for the placement of relay nodes in a two-tiered network that ensures connectivity and fault tolerance. We also propose two ILP formulations for finding the routing strategy so that the lifetime of any relay node network may be maximized.Dept. of Computer Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2006 .B37. Source: Masters Abstracts International, Volume: 45-01, page: 0348. Thesis (M.Sc.)--University of Windsor (Canada), 2006

Integrated placement and routing of relay nodes for fault-tolerant hierarchical sensor networks

In two-tiered sensor networks, using higher-powered relay nodes as cluster heads has been shown to lead to further improvements in network performance. Placement of such relay nodes focuses on achieving specified coverage and connectivity requirements with as few relay nodes as possible. Existing placement strategies typically are unaware of energy dissipation due to routing and are not capable of optimizing the routing scheme and placement concurrently. We, in this thesis, propose an integrated integer linear program (ILP) formulation that determines the minimum number of relay nodes, along with their locations and a suitable communication strategy such that the network has a guaranteed lifetime as well as ensuring the pre-specified level of coverage (ks) and connectivity (kr). We also present an intersection based approach for creating the initial set of potential relay node positions, which are used by our ILP, and evaluate its performance under different conditions. Experimental results on networks with hundreds of sensor nodes show that our approach leads to significant improvement over existing energy-unaware placement schemes

Genetic-fuzzy based load balanced protocol for WSNs

Recent advancement in wireless sensor networks primarily depends upon energy constraint. Clustering is the most effective energy-efficient technique to provide robust, fault-tolerant and also enhance network lifetime and coverage. Selection of optimal number of cluster heads and balancing the load of cluster heads are most challenging issues. Evolutionary based approach and soft computing approach are best suitable for counter the above problems rather than mathematical approach. In this paper we propose hybrid technique where Genetic algorithm is used for the selection of optimal number of cluster heads and their fitness value of chromosome to give optimal number of cluster head and minimizing the energy consumption is provided with the help of fuzzy logic approach. Finally cluster heads uses multi-hop routing based on A*(A-star) algorithm to send aggregated data to base station which additionally balance the load. Comparative study among LEACH, CHEF, LEACH-ERE, GAEEP shows that our proposed algorithm outperform in the area of total energy consumption with various rounds and network lifetime, number of node alive versus rounds and packet delivery or packet drop ratio over the rounds, also able to balances the load at cluster head

Fuzzy logic-based guaranteed lifetime protocol for real-time wireless sensor networks

© 2015 by the authors; licensee MDPI, Basel, Switzerland. Few techniques for guaranteeing a network lifetime have been proposed despite its great impact on network management. Moreover, since the existing schemes are mostly dependent on the combination of disparate parameters, they do not provide additional services, such as real-time communications and balanced energy consumption among sensor nodes; thus, the adaptability problems remain unresolved among nodes in wireless sensor networks (WSNs). To solve these problems, we propose a novel fuzzy logic model to provide real-time communication in a guaranteed WSN lifetime. The proposed fuzzy logic controller accepts the input descriptors energy, time and velocity to determine each node’s role for the next duration and the next hop relay node for real-time packets. Through the simulation results, we verified that both the guaranteed network’s lifetime and real-time delivery are efficiently ensured by the new fuzzy logic model. In more detail, the above-mentioned two performance metrics are improved up to 8%, as compared to our previous work, and 14% compared to existing schemes, respectively

Quantized Routing Models for Clustering Scheme in Wireless Sensor Networks

AbstractClustering routing protocols are effective topology approaches which can increase the scalability of wireless sensor networks and efficiently utilize the limited energy resources of the sensors. However, the loading or energy consumption of sensors in networks is heterogeneous so that some sensors may die earlier than the others. In this case, data from sensors will not be delivered properly to the base station. Many previous studies have focused on energyefficient routing protocols to prolong the network lifetime without considering the influences of transmitting range or availability of compression. In this paper, we propose quantized models to simulate the operations of clustering routing protocols and evaluate the energy consumption of networks as well as the load distribution of sensors. Besides, the cluster head selection algorithm is developed correspondingly. The comparison of data reception rate for LEACH with our model in cases of different compression rates by simulations is also presented

Energy Aware Design Strategies for Heterogeneous Sensor Networks

A sensor network is an interconnection of sensor nodes, each equipped with sensor(s), a micro-processor, some memory, and a wireless transceiver. Data from sensor nodes are usually collected at a central entity known as the base station or sink. Sensor nodes are powered by lightweight batteries, and it is often not feasible to replace or recharge these batteries. Therefore, the lifetime of a sensor network is considered to be over as soon as the batteries of critical nodes are depleted. For scalability and efficient data gathering, a hierarchical two-tier architecture has been proposed in the literature, where the sensor nodes constitute the lower-tier. The network is organized as a number of clusters, and, in each cluster, one node is assigned the role of the cluster head. The cluster heads constitute the upper-tier of the network. Each cluster head receives data from the sensor nodes in the corresponding cluster and communicates the data to the base station. The cluster heads may communicate with the base station either directly, using single-hop communication, or by forming a network among themselves using multi-hop communication. In recent years, a special node, provisioned with higher initial energy and communication capabilities, called the relay node, has been proposed in the literature to act as a cluster head in hierarchical sensor networks. The three major sub-problems when designing this type of network are i) to find a suitable placement of the relay nodes within the network, using the minimal number of relay nodes, so that each sensor node can communicate effectively with its cluster head, and the upper-tier network can tolerate fault(s), ii) to assign sensor nodes to clusters in an energy efficient manner, and iii) to compute a routing scheme for the relay nodes, such that the network lifetime is maximized. In this dissertation, we present two strategies for the placement of relay nodes, and five energy-aware strategies for the clustering and routing in a hierarchical, heterogeneous, two-tiered sensor network using relay nodes as cluster heads