Energy Performance of LDPC Scheme in Multi-Hop Wireless Sensor Network with Two base Stations Model

Conservation of the energy is one of the main design issues in wireless sensor networks. The limited battery power of each sensor node is a challenging task in deploying this type of network. The challenge is crucial in reliable wireless network when implementing efficient error correcting scheme with energy consuming routing protocol. In this work, we investigated the energy performance of LDPC code in multi-hop wireless sensor network. We proposed a model of two base stations to prolong the lifetime and build a reliable and energy-efficient network. Through performed MATLAB simulations, we examine the energy effectiveness of multiple base stations model on reliable wireless sensor network performance in different network dimensions

Efficient collection of sensor data via a new accelerated random walk

Motivated by the problem of efficiently collecting data from wireless sensor networks via a mobile sink, we present an accelerated random walk on random geometric graphs (RGG). Random walks in wireless sensor networks can serve as fully local, lightweight strategies for sink motion that significantly reduce energy dissipation but introduce higher latency in the data collection process. In most cases, random walks are studied on graphs like Gn,p and grid. Instead, we here choose the RGG model, which abstracts more accurately spatial proximity in a wireless sensor network. We first evaluate an adaptive walk (the random walk with inertia) on the RGG model; its performance proved to be poor and led us to define and experimentally evaluate a novel random walk that we call γ-stretched random walk. Its basic idea is to favour visiting distant neighbours of the current node towards reducing node overlap and accelerate the cover time. We also define a new performance metric called proximity cover time that, along with other metrics such as visit overlap statistics and proximity variation, we use to evaluate the performance properties and features of the various walks

Random Walk Based Routing Protocol for Wireless Sensor Networks

International audienceIn recent years, design of wireless sensor networks using methodologies and mechanisms from other disciplines has gained popularity for addressing many networking aspects and providing more flexible and robust algorithms. We address in this paper the problem of random walk to model routing for data gathering in wireless sensor networks. While at first glance, this approach may seem to be overly simplistic and highly inefficient, many encouraging results that prove its comparability with other approaches have been obtained over the years. In this approach, a packet generated from a given sensor node performs a random motion until reaching a sink node where it is collected. The objective of this paper is to give an analytical model to evaluate the performance of the envisioned routing scheme with special attention to two metrics: the mean system data gathering delay and the induced spatial distribution of energy consumption. The main result shows that this approach achieves acceptable performance for applications without too stringent QoS requirements provided that the ratio of sink nodes over the total number of sensor nodes is carefully tuned

Based on Regular Expression Matching of Evaluation of the Task Performance in WSN: A Queue Theory Approach

Due to the limited resources of wireless sensor network, low efficiency of real-time communication scheduling, poor safety defects, and so forth, a queuing performance evaluation approach based on regular expression match is proposed, which is a method that consists of matching preprocessing phase, validation phase, and queuing model of performance evaluation phase. Firstly, the subset of related sequence is generated in preprocessing phase, guiding the validation phase distributed matching. Secondly, in the validation phase, the subset of features clustering, the compressed matching table is more convenient for distributed parallel matching. Finally, based on the queuing model, the sensor networks of task scheduling dynamic performance are evaluated. Experiments show that our approach ensures accurate matching and computational efficiency of more than 70%; it not only effectively detects data packets and access control, but also uses queuing method to determine the parameters of task scheduling in wireless sensor networks. The method for medium scale or large scale distributed wireless node has a good applicability

Energy efficient organization and modeling of wireless sensor networks

With their focus on applications requiring tight coupling with the physical world, as opposed to the personal communication focus of conventional wireless networks, wireless sensor networks pose significantly different design, implementation and deployment challenges. Wireless sensor networks can be used for environmental parameter monitoring, boundary surveillance, target detection and classification, and the facilitation of the decision making process. Multiple sensors provide better monitoring capabilities about parameters that present both spatial and temporal variances, and can deliver valuable inferences about the physical world to the end user. In this dissertation, the problem of the energy efficient organization and modeling of dynamic wireless sensor networks is investigated and analyzed. First, a connectivity distribution model that characterizes the corresponding sensor connectivity distribution for a multi-hop sensor networking system is introduced. Based on this model, the impact of node connectivity on system reliability is analyzed, and several tradeoffs among various sleeping strategies, node connectivity and power consumption, are evaluated. Motivated by the commonality encountered in the mobile sensor wireless networks, their self-organizing and random nature, and some concepts developed by the continuum theory, a model is introduced that gives a more realistic description of the various processes and their effects on a large-scale topology as the mobile wireless sensor network evolves. Furthermore, the issue of developing an energy-efficient organization and operation of a randomly deployed multi-hop sensor network, by extending the lifetime of the communication critical nodes and as a result the overall network\u27s operation, is considered and studied. Based on the data-centric characteristic of wireless sensor networks, an efficient Quality of Service (QoS)-constrained data aggregation and processing approach for distributed wireless sensor networks is investigated and analyzed. One of the key features of the proposed approach is that the task QoS requirements are taken into account to determine when and where to perform the aggregation in a distributed fashion, based on the availability of local only information. Data aggregation is performed on the fly at intermediate sensor nodes, while at the same time the end-to-end latency constraints are satisfied. An analytical model to represent the data aggregation and report delivery process in sensor networks, with specific delivery quality requirements in terms of the achievable end-to-end delay and the successful report delivery probability, is also presented. Based on this model, some insights about the impact on the achievable system performance, of the various designs parameters and the tradeoffs involved in the process of data aggregation and the proposed strategy, are gained. Furthermore, a localized adaptive data collection algorithm performed at the source nodes is developed that balances the design tradeoffs of delay, measurement accuracy and buffer overflow, for given QoS requirements. The performance of the proposed approach is analyzed and evaluated, through modeling and simulation, under different data aggregation scenarios and traffic loads. The impact of several design parameters and tradeoffs on various critical network and application related performance metrics, such as energy efficiency, network lifetime, end-to-end latency, and data loss are also evaluated and discussed

An Enhanced Cluster-Based Routing Model for Energy-Efficient Wireless Sensor Networks

Energy efficiency is a crucial consideration in wireless sensor networks since the sensor nodes are resource-constrained, and this limited resource, if not optimally utilized, may disrupt the entire network's operations. The network must ensure that the limited energy resources are used as effectively as possible to allow for longer-term operation. The study designed and simulated an improved Genetic Algorithm-Based Energy-Efficient Routing (GABEER) algorithm to combat the issue of energy depletion in wireless sensor networks. The GABEER algorithm was designed using the Free Space Path Loss Model to determine each node's location in the sensor field according to its proximity to the base station (sink) and the First-Order Radio Energy Model to measure the energy depletion of each node to obtain the residual energy. The GABEER algorithm was coded in the C++ programming language, and the wireless sensor network was simulated using Network Simulator 3 (NS-3). The outcomes of the simulation revealed that the GABEER algorithm has the capability of increasing the performance of sensor network operations with respect to lifetime and stability period