Cluster based node scheduling method for wireless sensor networks

By researching on the node scheduling problem of m-covered and connected sensor networks,a new concept of two-hops-cluster is proposed in this paper,and based on it,a new distributed node scheduling algorithm THCNS for allocating all nodes in the sensor network into k(k≤m) different groups {0,1,...,k 1} is designed,without requiring location information.Our algorithm guarantees that each group to be connected and maintains the coverage ratio with high possibility.Theoretical analysis and simulation results show that it has better performance than previous randomized scheduling scheme,and can prolong the lifetime of the sensor network effectively.     

Pareto-based evolutionary computational approach for wireless sensor placement

Wireless sensor networks (WSNs) have become increasingly appealing in recent years for the purpose of data acquisition, surveillance, event monitoring, etc. Optimal positioning of wireless sensor nodes is an important issue for small networks of relatively expensive sensing devices. For such networks, the placement problem requires that multiple objectives be met. These objectives are usually conflicting, e.g. achieving maximum coverage and maximum connectivity while minimizing the network energy cost. A flexible algorithm for sensor placement (FLEX) is presented that uses an evolutionary computational approach to solve this multiobjective sensor placement optimization problem when the number of sensor nodes is not fixed and the maximum number of nodes is not known a priori. FLEX starts with an initial population of simple WSNs and complexifies their topologies over generations. It keeps track of new genes through historical markings, which are used in later generations to assess two networks’ compatibility and also to align genes during crossover. It uses Pareto-dominance to approach Pareto-optimal layouts with respect to the objectives. Speciation is employed to aid the survival of gene innovations and facilitate networks to compete with similar networks. Elitism ensures that the best solutions are carried over to the next generation. The flexibility of the algorithm is illustrated by solving the device/node placement problem for different applications like facility surveillance, coverage with and without obstacles, preferential surveillance, and forming a clustering hierarchy.     

无线传感器网络中一种基于分簇的节点调度算法

本文研究m覆盖与连通的无线传感器网络中的节点调度问题,提出了一种两跳簇的概念,并在此基础上提出了一种新的节点调度算法.该算法可在不知道节点位置信息的情况下,将无线传感器网络中的所有节点较为均匀地指派到k(km)个不同的分组{0,1,...,k1}之中,且可同时保证每个分组中的节点具有全局连通性与较高的网络覆盖率.理论分析与实验结果表明,该算法具有比传统随机调度方法更好的节点调度性能,可更加有效地延长无线传感器网络的生命周期.     

无线传感网络中通用传感器节点硬件结构设计

无线传感网络是当前国内外传感器技术领域的热点研究课题。提出了一种构建无线传感网络节点实验平台的方法;基于该设计方案实现的无线传感网络节点可以有效地组建网络拓扑结构及多种传感数据采集传输。它还可以用于实现声音空间定位系统。关键词:无线传感网络;节点;拓扑结构;数据采集;声音空间定位     

A middleware architecture for disseminating delay-constrained information in wireless sensor networks

Data dissemination is a process where information is transmitted towards different destinations. In order to prevent accidents, coordinate rescue operations and warn people about critical events, this process imposes end-to-end delay constraints. Accordingly, the delay from each source to each destination should be monitored. For this purpose, a middleware is required between the network and the applications, offering the tracking capabilities of disseminated information. In this paper, we propose a middleware architecture for disseminating delay-constrained information in Wireless Sensor Networks (WSNs). In order to evaluate the feasibility of such architecture, a proof of concept of a real scenario is implemented. For performance evaluation, the end-to-end delay and the percentage of success related to the disseminated information are analyzed. Such analysis reveals that the middleware offers a percentage of success close to 98%, which is highly superior to the success of individual resources, such as Short Message Services (SMS), emailing and twitter.     

Survivability-oriented optimal node density for randomly deployed wireless sensor networks

The survivability is usually critical for wireless sensor networks,which are often deployed in the unattended harsh environment.Lots of technical schemes to improve the survivability depend on the redundant resources of the sensor networks.The amount of resources is usually determined by the node density during the deployment phase.For the random deployment and random node failures,the quantitative relation between the survivability and the node density is studied.Based on the conditional survivability,the node density to meet the required survivability level is presented.Finally,the survivability for unpredictable failures and the optimal node density to maximize the price–performance ratio are also discussed.     

Energy efficient coverage control in wireless sensor networks based on multi-objective genetic algorithm

Due to the constrained energy and computational resources available to sensor nodes, the number of nodes deployed to cover the whole monitored area completely is often higher than if a deterministic procedure were used. Activating only the necessary number of sensor nodes at any particular moment is an efficient way to save the overall energy of the system. A novel coverage control scheme based on multi-objective genetic algorithm is proposed in this paper. The minimum number of sensors is selected in a densely deployed environment while preserving full coverage. As opposed to the binary detection sensor model in the previous work, a more precise detection model is applied in combination with the coverage control scheme. Simulation results show that our algorithm can achieve balanced performance on different types of detection sensor models while maintaining high coverage rate. With the same number of deployed sensors, our scheme compares favorably with the existing schemes.     

Connectivity preserving localized coverage algorithm for area monitoring using wireless sensor networks

Efficient network coverage and connectivity are the requisites for most Wireless Sensor Network (WSN) deployments, particularly those concerned with area monitoring. Due to the resource constraints of the sensor nodes, redundancy of coverage area must be reduced for effective utilization of the available resources. If two nodes have the same coverage area in their active state, and if both the nodes are activated simultaneously, it leads to redundancy in network and wastage of precious sensor resources. In this paper, we address the problem of network coverage and connectivity and propose an efficient solution to maintain coverage, while preserving the connectivity of the network. The proposed solution aims to cover the area of interest (AOI), while minimizing the count of the active sensor nodes. The overlap region of two sensor nodes varies with the distance between the nodes. If the distance between two sensor nodes is maximized, the overall coverage area of these nodes will also be maximized. Also, to preserve the connectivity of the network, each sensor node must be in the communication range of at least one other node. Results of simulation of the proposed solution indicate up to 95% coverage of the area, while consuming very less energy of 9.44 J per unit time in the network, simulated in an area of 2500 m².     

A security policy language for wireless sensor networks

Authenticated computer system users are only authorized to access certain data within the system. In the future, wireless sensor networks (WSNs) will need to restrict access to data as well. To date, WSN security has largely been based on encryption and authentication schemes. The WSN Authorization Specification Language (WASL) is a mechanism-independent composable WSN policy language that can specify arbitrary and composable security policies that are able to span and integrate multiple WSN policies. Using WASL, a multi-level security policy for a 1000 node network requires only 60 bytes of memory per node.