Cellular automaton-based algorithms for the dispersion of mobile wireless sensor networks

Due to the advent of sensor technology and its applications, mobile wireless sensor networks (MWSNs) have gained a significant amount of research interest. In a typical MWSN, sensors can move within the network. We develop a set of probabilistic and deterministic cellular automaton (CA)-based algorithms for motion planning problems in MWSNs. First, we consider a scenario where a group of sensors are deployed and they need to disperse in order to maximise the area covered by the network. In this variant of the problem we do not explicitly consider that the sensors should maintain the connectivity of the network while they move. Second, we consider a scenario where the sensors are initially randomly distributed and they need to disperse autonomously to both maximise the coverage of the network and maintain its connectivity. We carry out extensive simulations of both deterministic and randomised variants of the algorithms. For the first variant of the problem we compare our algorithms with one previous algorithm and find that our algorithm yields better network coverage than the earlier algorithm. We also find that probabilistic algorithms have better overall performance for the second variant. CA algorithms rely only on local information about the network and, hence, they can be used in practice for MWSN problems. On the other hand, locality of the algorithm implies that maintaining connectivity becomes a non-trivial problem.     

无线传感器网络部分覆盖算法及连通性研究

研究了无线传感器网络在部分覆盖下的节点配置及网络连通性问题。首先,基于最优正六边形拓扑架构,给出了节点密集分布条件下的覆盖率与相邻工作节点间距的解析关系,并在已有的最优完全覆盖算法OGDC的基础上进行了扩展和改进,从而得到了一种新的网络节点配置算法EGDC（Extended OGDC Algorithm）。该算法可以有效地选择出合适的工作节点以达到任意给定覆盖率下的部分覆盖。此外,还给出了一种检验和评价网络连通性的方法,通过该方法可以对网络的连通性进行量化分析,并给出了一项评价网络连通性的指标。仿真表明,EGDC可以有效地实现任意期望覆盖率下的网络配置并保持网络的连通。     

Connected K-target coverage problem in wireless sensor networks with different observation scenarios

In this paper, we consider the problem of scheduling sensor activities to maximize network lifetime while maintaining both discrete K-target coverage and network connectivity. In K-target coverage, it is required that each target should be simultaneously observed by at least K sensors. The data generated by the sensors will be transmitted to the sink node via single or multiple hop communications. As maintaining discrete target coverage cannot guarantee the network connectivity, we consider both target coverage and connectivity issues. Further, by adopting a more realistic energy consumption model, we consider the sensor activity scheduling problem and routing problem jointly. We study the problem with two observation scenarios depending on whether a sensor can distinguish the targets in its sensing area or not. For the first scenario, a more general scenario where each sensor can simultaneously observe multiple targets is considered and we develop a polynomial-time algorithm which can achieve optimal solution based on linear programming and integer theorem. For the second scenario, we show that the problem is NP-complete and develop an approximation algorithm for solving it. As the protocol cost of the optimal solution and the approximation algorithm may be high in practice, we develop a low-cost heuristic algorithm which can be implemented in a distributed fashion for both scenarios. We demonstrate the effectiveness of the heuristic algorithm through extensive simulations.     

Connectivity and coverage maintenance in wireless sensor networks

One of the main design challenges for wireless sensor networks (WSNs) is to obtain long system lifetime without sacrificing system original performance such as communication connectivity and sensing coverage. A large number of sensor nodes are deployed in redundant fashion in dense sensor networks, which lead to higher energy consumption. We propose a distributed framework for energy efficient connectivity and coverage maintenance in WSNs. In our framework, each sensor makes self-scheduling to separately control the states of RF and sensing unit based on dynamic coordinated reconstruction mechanism. A novel energy-balanced distributed connected dominating set algorithm is presented to make connectivity maintenance; and also a distributed node sensing scheduling is brought forward to maintain the network coverage according to the surveillance requirements. We implemented our framework by C++ programming, and the simulation results show that our framework outperforms several related work by considerably improving the energy performance of sensor networks to effectively extend network lifetime.     

无线传感网络的非分簇拓扑控制方法研究

无线传感网络通常由能量受限、通信半径较小的传感器节点构成,其中拓扑控制是重要的工程问题。提出了一种基于元胞自动机的非分簇的拓扑控制算法,与传统分簇方法的区别在于本方法试图通过牺牲小部分拓扑连通度和覆盖度来换取更长的系统生存时间。基于元胞自动机模型的研究表明,节点的状态转移规则对系统整体性能起决定作用,在一些规则下系统拓扑呈现稳定变化,符合对无线传感网络拓扑控制的要求。进一步探讨了该机制在工程上的具体实现问题,并与LEACH算法进行了对比,验证了以拓扑性能换取生存时间的设想。     

Algorithms for Fault-Tolerant Topology in Heterogeneous Wireless Sensor Networks

This paper addresses fault-tolerant topology control in a heterogeneous wireless sensor network consisting of several resource-rich supernodes, used for data relaying, and a large number of energy-constrained wireless sensor nodes. We introduce the k-degree anycast topology control (fc-ATC) problem, with the objective of selecting each sensor's transmission range such that each sensor is k-vertex supernode connected and the total power consumed by sensors is minimized. Such topologies are needed for applications that support sensor data reporting, even in the event of failures of up to k - 1 sensor nodes. We propose three solutions for the k-ATC problem: a k-approximation algorithm, a greedy centralized algorithm that minimizes the maximum transmission range between all sensors, and a distributed and localized algorithm that incrementally adjusts sensors' transmission range such that the k-vertex supernode connectivity requirement is met. Extended simulation results are presented to verify our approaches.     

CROSS: A probabilistic constrained random sensor selection scheme in wireless sensor networks

Due to the application-specific nature of wireless sensor networks, the sensitivity to coverage and data reporting latency varies depending on the type of applications. In light of this, algorithms and protocols should be application-aware to achieve the optimum use of highly limited resources in sensors and hence to increase the overall network performance. This paper proposes a probabilistic constrained random sensor selection (CROSS) scheme for application-aware sensing coverage with a goal to maximize the network lifetime. The CROSS scheme randomly selects in each round (approximately) k data-reporting sensors which are sufficient for a user/application-specified desired sensing coverage (DSC) maintaining a minimum distance between any pair of the selected k sensors. We exploit the Poisson sampling technique to force the minimum distance. Consequently, the CROSS improves the spatial regularity of randomly selected k sensors and hence the fidelity of satisfying the DSC in each round, and the connectivity among the selected sensors increase. To this end, we also introduce an algorithm to compute the desired minimum distance to be forced between any pair of sensors. Finally, we present the probabilistic analytical model to measure the impact of the Poisson sampling technique on selecting k sensors, along with the optimality of the desired minimum distance computed by the proposed algorithm.     

An Integrated Optimization Enabled Sensor Deployment Model in Wireless Sensor Network

ABSTRACT

Target coverage (TCOV) and network connectivity (NCON) are the most basic problems affecting robust data communication and environmental sensing in a wireless sensor network (WSN) application. This article proposes an intelligent Context Aware Sensor Network (CASN) for the process of sensor deployment in WSNs. Accordingly, the process is sub-divided into two phases. In the initial phase, optimal TCOV is performed; whereas, in the second phase, the proposed algorithm establishes NCON among the sensors. The objective model that meets both TCOV and NCON is evaluated as the minimization problem. This problem is solved by a new method that hybridizes the Artificial Bee Colony (ABC) algorithm and the Whale Optimization Algorithm (WOA) together, which is known as the Onlooker Probability-based WOA (OP-WOA) for the determination of optimal sensor locations. In addition, the adopted OP-WOA model is compared with the Genetic Algorithm (GA), the Particle Swarm Optimization (PSO), the ABC algorithm, Differential Evolution (DE), FireFly (FF), the WOA, and the Evolutionary Algorithm (EA)-based TCOV and NCON models. Finally, the results attained from the execution demonstrate the enhanced performance of the implemented OP-WOA technique.     

Energy Efficient Monitoring in Sensor Networks

We study a set of problems related to efficient battery energy utilization for monitoring applications in a wireless sensor network with the goal to increase the sensor network lifetime. We study several generalizations of a basic problem called Set k-Cover. The problem can be described as follows: we are given a set of sensors, and a set of targets to be monitored. Each target can be monitored by a subset of the sensors. To increase the lifetime of the sensor network, we would like to partition the sensors into k sets (or time-slots), and activate each set of sensors in a different time-slot, thus extending the battery life of the sensors by a factor of k. The goal is to find a partitioning that maximizes the total coverage of the targets for a given k. This problem is known to be NP-hard. We develop an improved approximation algorithm for this problem using a reduction to Max k-Cut. Moreover, we are able to demonstrate that this algorithm is efficient, and yields almost optimal solutions in practice.     

无线传感器网络中能耗均衡的覆盖控制算法

覆盖控制作为无线传感器网络的一个基本问题,对网络的生存时间、部署策略、通信协议和组网等问题的解决具有重要影响。在传感器节点随机冗余部署方式下,传统的方式 是在保证覆盖要求和通信连通的前提下仅将最少量的节点投入活跃工作状态,从而降低网络能耗。但是,若频繁地激活同一批节点,会造成这些节点由于能耗过快而较早失效效,使整个网络的冗余程度降低。然而,冗余度是传感器网络在单个节点性能有限的情况下提高整个网络的可靠性、容错性、精确性等的基础。为此,本文提出了一个能耗均衡ECB的覆盖问题,指出它是NP完全的,并给出了一个集中式近似算法。该算法根据节点的剩余能量赋于每个节点非负权,再基于Voronoi划分和贪心边方法,在保证覆盖要求的同时选择权和最小的节点激活。仿真实验结果表明,ECB算法求得的活跃节点集小,可以达到有效覆盖,并且可以保持网络的冗余度。     

带时延约束的连通目标覆盖最大化生命周期问题

在无线传感器网络中,如何确保网络服务质量（如覆盖、连通）同时最大化网络生命周期是研究的热点和难点.在延时敏感的应用（如火灾、爆炸等灾害监测）中,传感器节点必须在有限的时间内传送它们的数据到汇聚节点.为了研究这种应用下的连通目标覆盖,提出了一种带时延约束的连通目标覆盖问题(DCCTC).首先,将DCCTC建模成为限高的最大覆盖树问题(HLMCT),并证明它是NP-Complete的.然后,设计了一种快速启发式算法HLCWGC求解HLMCT问题.仿真实验和理论证明,HLCWGC在时延约束下获得的网络生命周期比已有的算法要好.具有较高的应用价值和理论意义.     

C3: an energy-efficient protocol for coverage,connectivity and communication in WSNs

The lower layer of ubiquitous and pervasive systems consists of wireless ad hoc and sensor networks. In wireless sensor networks (WSNs), sensors consume most of their energy in data transmission and idle listening. Hence, efficient usage of energy can be ensured by improved protocols for topology control (i.e., coverage and connectivity), sleep scheduling, communication, and aggregation and compression of data. Though several protocols have been proposed for this purpose, they are not energy-efficient. We propose an integrated and energy-efficient protocol for Coverage, Connectivity, and Communication (C3) in WSNs. The C3 protocol uses received signal strength indicator to divide the network into virtual rings, defines clusters with clusterheads more probably at alternating rings, defines dings that are rings inside a cluster and uses triangular tessellation to identify redundant nodes, and communicates data to sink through clusterheads and gateways. The proposed protocol strives for near-optimal deployment, load balancing, and energy-efficient communication. Simulation results show that the C3 protocol ensures partial coverage of more than 90 % of the total deployment area, ensures one connected network, and facilitates energy-efficient communication while expending only one-fourth of the energy compared to other related protocols such as the coverage and connectivity protocol, and the layered diffusion-based coverage control.     

一种移动无线视频传感器节点的覆盖算法

在现有的无线传感器网络覆盖算法的研究中,缺乏对移动节点路径规划的研究,而针对具有视频传感器节点的网络仍使用普通传感器圆形覆盖区域的测量方法来计算覆盖面积,并不完全符合实际情况.基于这两方面的原因,本文提出了一种适用于无线视频传感器节点的最大覆盖算法,并提出一种对于视频传感器节点覆盖面积的计量方法.该算法能够使节点在保证网络连通性的前提下,达到最大的有效监测范围.此外,本文建立了相应的仿真实验模型,对该算法的有效性和覆盖面积进行了实验与分析.结果表明,本算法的节点监测面积大约为使用随机运动算法的节点监测面积的1.5倍左右,并可以保证网络的连通性.     

Impact of sensor nodes scaling and velocity on handover mechanisms for healthcare wireless sensor networks with mobility support

Health promotion in hospital environments can be improved using the most recent information and communication technologies. The Internet connectivity to small sensor nodes carried by patients allows remote access to their bio-signals. To promote these features the healthcare wireless sensor networks (HWSN) are used. In these networks mobility support is a key issue in order to keep patients under real-time monitoring even when they move around. To keep sensors connected to the network, they should change their access points of attachment when patients move to a new coverage area along an infirmary. This process, called handover, is responsible for continuous network connectivity to the sensors. This paper presents a detailed performance evaluation study considering three handover mechanisms for healthcare scenarios (Hand4MAC, RSSI-based, and Backbone-based). The study was performed by simulation using several scenarios with different number of sensors and different moving velocities of sensor nodes. The results show that Hand4MAC is the best solution to guarantee almost continuous connectivity to sensor nodes with less energy consumption.     

基于功率控制的成簇优化算法

在无线传感器网络中,高效、节能的自组织成簇算法,有助于拓扑结构控制与优化,有助于提高传感器网络的服务质量,延长整个网络的生命周期.针对成簇算法中没有考虑工作节点的功率控制问题,本文从理论上对节点覆盖、连通与有效通信半径之间的关系进行分析,提出一种节点有效通信半径的计算方法,应用于传统的成簇算法进行优化,并通过仿真计算对优化算法进行了性能分析.仿真结果表明,优化算法的网络覆盖度、网络生存期及节点失效等方面都有明显提高.     

Maximizing connected coverage via controlled actor relocation in wireless sensor and actor networks

Wireless sensor and actor networks (WSANs) have recently emerged with the idea of combining wireless sensor networks (WSNs) and mobile ad hoc networks (MANETs). In addition to resource constrained sensors, resource rich and mobile actor nodes are employed in WSANs. These actors can collect data from the sensors and perform appropriate actions as a result of processing such data. To perform the actions at all parts of the region in a timely manner, the actors should be deployed in such a way that they might be able to communicate with each other and cover the whole monitored area. This requires that the actors should be placed carefully prior to network operation in order to maximize the coverage and maintain the inter-actor connectivity. In this paper, we propose a distributed actor deployment algorithm that strives to maximize the coverage of actors without violating the connectivity requirement. The approach applies repelling forces between neighboring actors and from the sensors that sit on the boundaries in order to spread them in the region. The spreading of the nodes is done using a tree of actors which can provide more freedom for the movement of the nodes but at the same time maintain the required connectivity among the nodes. We present two techniques for creation of such an actor tree which are based on local pruning of the actor links and spanning tree of the inter-actor network. The performance of our approach is validated both analytically and experimentally.     

Robotic data mules for collecting data over sparse sensor fields

We present a robotic system for collecting data from wireless devices dispersed across a large environment. In such applications, deploying a network of stationary wireless sensors may be infeasible because many relay nodes must be deployed to ensure connectivity. Instead, our system utilizes robots that act as data mules and gather the data from wireless sensor network nodes. We address the problem of planning paths of multiple robots so as to collect the data from all sensors in the shortest time. In this new routing problem, which we call the data gathering problem (DGP), the total download time depends on not only the robots' travel time but also the time to download data from a sensor and the number of sensors assigned to the robot. We start with a special case of DGP in which the robots' motion is restricted to a curve that contains the base station at one end. For this version, we present an optimal algorithm. Next, we study the two‐dimensional version and present a constant factor approximation algorithm for DGP on the plane. Finally, we present field experiments in which an autonomous robotic data mule collects data from the nodes of a wireless sensor network deployed over a large field. © 2011 Wiley Periodicals, Inc.     

基于概率探测模型的传感器结点配置研究

无线传感器网络结点配置是传感器网络研究的核心问题之一,它反映出无线传感器网络的代价和探测能力.主要研究了基于一种更为实用化概率检测模型(引入x%-RS 的概念)的无线传感器网络覆盖优化配置问题.在严格确保无线传感器网络连通性的条件下,优化了传感器结点配置数目并达到要求的覆盖度,获得具体的传感器结点配置方案.为提高算法的效率,在分步优化算法的基础上尝试一次循环配置多个传感器结点.最后,通过模拟计算给出配置算法的性能.     

基于能量均衡的最大化覆盖目标算法

目标覆盖问题是无线传感网络WSNs(Wireless sensor networks)最重要的问题之一.每个目标至少被一个传感节点覆盖,为此提出基于能量均衡的最大化覆盖目标EMNL(Energy-balance-based Maximizing Network Lifetime)算法.EMNL算法将所有传感节点划分不同的传感节点覆盖区SC(Sensor Cover),致使每个SC能够维持对所有目标监测一个固定时间.通过有选择性选择一个SC活动,而其他SC休眠,进而提高能量利用率,延长了网络寿命.EMNL算法构建了不同不相邻SC,进而最大化网络寿命.最后,建立仿真环境,并进行性能仿真.此环境下的数据表明,在EMNL算法有效地扩延生存时间,也提升了覆盖率.     

EQOWSN: Evolutionary-based query optimization over self-organized wireless sensor networks

In this paper, a new approach has been introduced that integrates an evolutionary-based mechanism with a distributed query sensor cover algorithm for optimal query execution in self-organized wireless sensor networks (WSN). An algorithm based on an evolutionary technique is proposed, with problem-specific genetic operators to improve computing efficiency. Redundancy within a sensor network can be exploited to reduce the communication cost incurred in execution of spatial queries. Any reduction in communication cost would result in an efficient use of battery energy, which is very limited in sensors. Our objective is to self-organize the network, in response to a query, into a topology that involves an optimal subset of sensors that is sufficient to process the query subject to connectivity, coverage, energy consumption, cover size and communication overhead constraints. Query processing must incorporate energy awareness into the system by reducing the total energy consumption and hence increasing the lifetime of the sensor cover, which is beneficial for large long running queries. Experiments have been carried out on networks with different sensors Transmission radius, different query sizes, and different network configurations. Through extensive simulations, we have shown that our designed technique result in substantial energy savings in a sensor network. Compared with other techniques, the results demonstrated a significant improvement of the proposed technique in terms of energy-efficient query cover with lower communication cost and lower size.