Optimization of depth-based routing for underwater wireless sensor networks through intelligent assignment of initial energy

Underwater Wireless Sensor Networks (UWSNs) are extensively used to explore the diverse marine environment. Energy efficiency is one of the main concerns regarding performance of UWSNs. In a cooperative wireless sensor network, nodes with no energy are known as coverage holes. These coverage holes are created due to non-uniform energy utilization by the sensor nodes in the network. These coverage holes degrade the performance and reduce the lifetime of UWSNs. In this paper, we present an Intelligent Depth Based Routing (IDBR) scheme which addresses this issue and contributes towards maximization of network lifetime. In our proposed scheme, we allocate initial energy to the sensor nodes according to their usage requirements. This idea is helpful to balance energy consumption amongst the nodes and keep the network functional for a longer time as evidenced by the results provided

Load Balancing Techniques for Lifetime Maximizing in Wireless Sensor Networks

International audienceEnergy consumption has been the focus of many studies on Wireless Sensor Networks (WSN). It is well recognized that energy is a strictly limited resource in WSNs. This limitation constrains the operation of the sensor nodes and somehow compromises the long term network performance as well as network activities. Indeed, the purpose of all application scenarios is to have sensor nodes deployed, unattended, for several months or years.This paper presents the lifetime maximization problem in “many-to-one” and “mostly-off” wireless sensor networks. In such network pattern, all sensor nodes generate and send packets to a single sink via multi-hop transmissions. We noticed, in our previous experimental studies, that since the entire sensor data has to be forwarded to a base station via multi-hop routing, the traffic pattern is highly non-uniform, putting a high burden on the sensor nodes close to the base station.In this paper, we propose some strategies that balance the energy consumption of these nodes and ensure maximum network lifetime by balancing the traffic load as equally as possible. First, we formalize the network lifetime maximization problem then we derive an optimal load balancing solution. Subsequently, we propose a heuristic to approximate the optimal solution and we compare both optimal and heuristic solutions with most common strategies such as shortest-path and equiproportional routing. We conclude that through the results of this work, combining load balancing with transmission power control outperforms the traditional routing schemes in terms of network lifetime maximization

CLUSTERING SOLUTION TO MAXIMIZE LIFETIME OF WIRELESS SENSOR NETWORK: A SURVEY

ABSTRACT Wireless sensor networks consist of small nodes with sensing, computation, and wireless communications capabilities. The purpose of the network is to sense the environment and report what happens in the area it is deployed in. The sensor networks can be used for various application areas (e.g., health, military, home) Moreover, most of the Wireless Sensor Network (WSN) applications render it impossible to charge or replace the battery of sensor nodes. Therefore, optimal use of node energy is a major challenge in wireless sensor networks to enhance the lifetime of whole network. Clustering of sensor nodes is an effective method to use the node energy optimally and prolong the lifetime of energy constrained wireless sensor network. .In the paper we give out the survey of clustering solution to lifetime maximization in wireless sensor network. In this paper we also points out the open research issues and intends to spark new interests and developments in this field

Optimal power control in green wireless sensor networks with wireless energy harvesting, wake-up radio and transmission control

Wireless sensor networks (WSNs) are autonomous networks of spatially distributed sensor nodes which are capable of wirelessly communicating with each other in a multi-hop fashion. Among different metrics, network lifetime and utility and energy consumption in terms of carbon footprint are key parameters that determine the performance of such a network and entail a sophisticated design at different abstraction levels. In this paper, wireless energy harvesting (WEH), wake-up radio (WUR) scheme and error control coding (ECC) are investigated as enabling solutions to enhance the performance of WSNs while reducing its carbon footprint. Specifically, a utility-lifetime maximization problem incorporating WEH, WUR and ECC, is formulated and solved using distributed dual subgradient algorithm based on Lagrange multiplier method. It is discussed and verified through simulation results to show how the proposed solutions improve network utility, prolong the lifetime and pave the way for a greener WSN by reducing its carbon footprint

Distributed Optimal Rate-Reliability-Lifetime Tradeoff in Wireless Sensor Networks

The transmission rate, delivery reliability and network lifetime are three fundamental but conflicting design objectives in energy-constrained wireless sensor networks. In this paper, we address the optimal rate-reliability-lifetime tradeoff with link capacity constraint, reliability constraint and energy constraint. By introducing the weight parameters, we combine the objectives at rate, reliability, and lifetime into a single objective to characterize the tradeoff among them. However, the optimization formulation of the rate-reliability-reliability tradeoff is neither separable nor convex. Through a series of transformations, a separable and convex problem is derived, and an efficient distributed Subgradient Dual Decomposition algorithm (SDD) is proposed. Numerical examples confirm its convergence. Also, numerical examples investigate the impact of weight parameters on the rate utility, reliability utility and network lifetime, which provide a guidance to properly set the value of weight parameters for a desired performance of WSNs according to the realistic application's requirements.Comment: 27 pages, 10 figure

Network Lifetime Maximization With Node Admission in Wireless Multimedia Sensor Networks

Wireless multimedia sensor networks (WMSNs) are expected to support multimedia services such as delivery of video and audio streams. However, due to the relatively stringent quality-of-service (QoS) requirements of multimedia services (e.g., high transmission rates and timely delivery) and the limited wireless resources, it is possible that not all the potential sensor nodes can be admitted into the network. Thus, node admission is essential for WMSNs, which is the target of this paper. Specifically, we aim at the node admission and its interaction with power allocation and link scheduling. A cross-layer design is presented as a two-stage optimization problem, where at the first stage the number of admitted sensor nodes is maximized, and at the second stage the network lifetime is maximized. Interestingly, it is proved that the two-stage optimization problem can be converted to a one-stage optimization problem with a more compact and concise mathematical form. Numerical results demonstrate the effectiveness of the two-stage and one-stage optimization frameworks

On Lifetime Maximization and Fault Tolerance Measurement in Wireless Ad Hoc and Sensor Networks

In this dissertation we study two important issues in wireless ad hoc and sensor networks: lifetime maximization and fault tolerance. The first part investigates how to maximally extend the lifetime of randomly deployed wireless sensor networks under limited resource constraint, and the second part focuses on how to measure the fault tolerance and attack resilience of wireless ad hoc networks. We take the approach of adaptive traffic distribution and power control to maximize the lifetime of randomly deployed wireless sensor networks. After abstracting the network into multiple layers, we model the lifetime maximization problem as a linear program. We study both scenarios where receiving/processing power consumption is ignored and receiving/processing is included. In both cases, we have a similar observation: for each packet to be sent, the sender should either transmit it using the transmission range with the highest energy efficiency per bit per meter, or transmit it directly to the sink. We then prove it is true in general. Finally, we propose a fully distributed algorithm to adaptively split traffic and adjust transmission power. Extensive simulation studies demonstrate that the network lifetime can be dramatically extended by applying the proposed approach in various scenarios. Besides studying the lifetime extension problem for fully deployed wireless sensor networks, we also investigate how to extend the network lifetime via joint relay node deployment and adaptive traffic distribution. We formulate this problem as a mixed-integer nonlinear-program problem, which is NP-hard in general. We then propose a greedy heuristic to attack it. Both numerical and simulation results show that significant network lifetime extension can be achieved. In the second part of this dissertation, we investigate how to measure the fault tolerance and attack resilience for randomly deployed wireless ad hoc networks. We first propose two new metrics to measure the average case of network service quality: average pairwise connectivity and pairwise connected ratio. We then propose the fault tolerance and attack resilience metric: alpha-p-resilience, where a network is alpha-p-resilient if at least alpha portion of nodes pairs remain connected as long as no more than p fraction of nodes is removed from the network