Frank Comeau

An Energy Efficient Fuzzy Logic Cluster Formation Protocol in Wireless Sensor Networks

Despite significant advancements in wireless sensor networks (WSNs), energy conservation remains one of the most important research challenges. Researchers have investigated architectures and topologies that allow energy efficient operation of WSNs. One of the popular techniques in this regard is clustering. While many researchers have investigated cluster head selection, this paper investigates the cluster formation. In particular, we propose a novel scheme, the Fuzzy Logic Cluster Formation Protocol (FLCFP), which uses Fuzzy Logic Inference System (FIS) in the cluster formation process. We demonstrate that using multiple parameters in cluster formation reduces energy consumption. We compare our technique with the well known LEACH protocol to show that using a multi parameter FIS enhances the network lifetime significantly.

Energy Conserving Architectures and Algorithms for Wireless Sensor Networks

This paper derives an algorithm for minimizing energy spent by a hierarchical wireless sensor network in transmitting data to a sink, referred to as a base station. The network model considered is a single-hop multi-level clustered network. We draw on results from stochastic geometry to analytically determine the optimum number of clusters at each level. We show, both analytically and by simulation results, that a multi-level approach can significantly reduce the required network energy.

Energy conservation in clustered wireless sensor networks

In this paper, results from Walds equation and stochastic geometry are applied to the analysis of the energy expended in a homogeneous clustered Wireless Sensor Network (WSN). We determine the optimum number of clusterheads for minimising the energy expended by a single-hop clustered WSN in transmitting data to a sink using nonlinear and linear aggregation models, and include error control. Our model makes it possible to determine the optimum number of clusters given the node electronic energy expended, the type of aggregation employed, the propagation loss and the network geometry. The effect of these parameters on the optimum number of clusterheads is analysed. The analytical model is verified with simulations. We observe that, in some networks, clustering is not beneficial for minimising network energy.

Dynamic Fuzzy-Logic Based Path Planning for Mobility-Assisted Localization in Wireless Sensor Networks

Mobile anchor path planning techniques have provided as an alternative option for node localization in wireless sensor networks (WSNs). In such context, path planning is a movement pattern where a mobile anchor node’s movement is designed in order to achieve a maximum localization ratio possible with a minimum error rate. Typically, the mobility path planning is designed in advance, which is applicable when the mobile anchor has sufficient sources of energy and time. However, when the mobility movement is restricted or limited, a dynamic path planning design is needed. This paper proposes a novel distributed range-free movement mechanism for mobility-assisted localization in WSNs when the mobile anchor’s movement is limited. The designed movement is formed in real-time pattern using a fuzzy-logic approach based on the information received from the network and the nodes’ deployment. Our proposed model, Fuzzy-Logic based Path Planning for mobile anchor-assisted Localization in WSNs (FLPPL), offers superior results in several metrics including both localization accuracy and localization ratio in comparison to other similar works.

Analysis of LEACH Energy Parameters

Abstract The LEACH protocol is a popular protocol used in wireless sensor network analysis and simulation. This paper analyses the effect of varying the parameter values used in the LEACH protocol. In particular, we study the effect of the bit rate and operational frequency on the free space factor, and the effect of the antenna heights on the multipath factor. Simulation results are presented. We show that the parameters normally used apply to a specific network only. Network lifetime results obtained using one set of parameters are not easily generalized

New path planning model for mobile anchor-assisted localization in wireless sensor networks

As event detection is one of the main purposes of using wireless sensor networks (WSNs), the nodes location is essential to determine the location of that event when it occurs. Many localization models have been proposed in the literature. One of the solutions is to deploy a set of location-aware nodes, called anchors, to exchange information with the other nodes in order to help estimate their own location. Another promising proposal involves replacing these sets of anchors with only one mobile anchor. While this proposal seems to provide favorable results, it brings new challenges. The main challenge is to find an optimal path for the mobile anchor to follow while taking into account the need to provide highly accurate data and more localizable nodes in less time and with less energy. In this paper, we introduced a new static path planning model for mobile anchor-assisted localization in WSNs. Our proposed model guarantees that all nodes are able to receive the localization information, thus, estimate their own location with higher localization accuracy in comparison to similar static models. Moreover, this model overcomes the problem of collinearity and takes into account the metrics of precision and energy consumption as well as accuracy, localization ratio and the path length of the mobile anchor.

A Clustered Wireless Sensor Network Model Based on LogDistance Path Loss

Clustered wireless sensor network models typically assume that a clear line-of-sight path separates the transmitter and receiver within a cluster; an accurate assumption for relatively short distances. For longer distances, and in environments that are obstructed, the log-distance path loss model agrees better with measurements. In this paper, communication within a cluster is modeled using the free space propagation model for distances less than a crossover distance, d0, and the log-distance path loss model with loss exponent n > 2 for distances greater than d0. We determine the optimum number of clusters for minimizing the energy expended in the clustered WSN given the network geometry, the number of nodes in the network, the crossover distance d0, and the amount of data compression.

Using the DV-Hop technique to increase the localization ratio in static path planning models in wireless sensor networks

Localization is essential to consider in relation to wireless sensor networks issues. Establishing mobility in the localization process creates improvements in various regards. Static path planning is one of a number of mobility models that are used in localization in wireless sensor networks. Most static path planning models depend on trilateration or triangulation concepts in direct connection fashion between unknown nodes and anchors for successful node localization; however, such methods are insufficient in cases of mobility discontinuity. Considering scenarios where the mobile anchor has limited movement, in this paper we propose using the DV-Hop technique to increase the localization ratio in static path planning models in wireless sensor networks.

A scheme for using closest rendezvous points and Mobile Elements for data gathering in wireless sensor networks

A variety of wireless sensor network (WSN) applications have been proposed. However, the efficiency of WSNs, as well as their ability to interact with different environments, varies. Many challenges and problems to be solved remain. Overcoming these challenges requires a protocol that will design and provide a highly efficient system, thus helping the WSN to transmit data in a suitable time. In WSNs with Mobile Elements (MEs), the task is first to find an effective way to minimize the length of the tour that the ME follows for data gathering. However, the minimized tour length should still offer access to all nodes in the networks for data collection form the sensor nodes. In this paper, we propose a protocol that results in a shorter ME tour length than previously proposed protocols, using closest rendezvous points (CRPs) distributed throughout the network. Furthermore, this proposed protocol offers access to all nodes inside the network for the exchange of data with the MEs, as facilitated by the suggested CRP algorithm. One or more nodes can be represented by a single CRP that provides connectivity to all of the nodes within its wireless range. In cases where a greater number of MEs are used, less time is required to traverse the network for data gathering. This research demonstrates that the tour time can be reduced significantly by using more than one ME.

Data collection using rendezvous points and mobile actor in wireless sensor networks

In this paper we present a new data collection scheme using mobile actors in a large scale wireless sensor network (WSN). A mobile actor, or for convenience, M-actor is a mobile node that has powerful energy source, computation, and communication features. The mobile node is able to move freely through the sensor deployment, traversing through the radio transmission range of wireless sensor nodes to collect the sensed data. Once data from all sensors is collected, the M-actor returns to the base station to off-load the collected data. This paper makes two contributions. First, we present a heuristic to compute collection points, referred to as the rendezvous points (RPs). These points are computed such that full coverage is guaranteed. Second, the optimal path for the M-actor is modeled using a genetic algorithm (GA)based traveling salesman problem (TSP). The proposed scheme is evaluated through simulations. We demonstrate that the proposed scheme achieves significant improvement in reducing the tour length for the M-actor when compared with other schemes.