Relay node placement in structurally damaged wireless sensor networks via triangular steiner tree approximation

Wireless sensor networks (WSNs) have many applications which operate in hostile environments. Due to the harsh surroundings, WSNs may suffer from a large scale damage that causes many nodes to fail simultaneously and the network to get partitioned into multiple disjoint segments. In such a case, restoring the network connectivity is very important in order to avoid negative effects on the applications. In this paper, we pursue the placement of the least number of relay nodes to re-establish a strongly connected network topology. The problem of finding the minimum count and the position of relay nodes is NP-hard and hence we pursue heuristics. We present a novel three-step algorithm called FeSTA which is based on steinerizing appropriate triangles. Each segment is represented by a terminal. Each subset of 3 terminals forms a triangle. Finding the optimal solution for a triangle (i.e. connecting 3 segments) is a relatively easier problem. In the first step, FeSTA finds the best triangles and form islands of segments by establishing intra-triangle connectivity. Then in the second, disjoint islands of segment are federated. In the final step, the steinerized edges are optimized. The performance of FeSTA is validated through simulation.     

基于安全连通性检测的随机密钥预分配方案

近年来,无线传感器网络的安全研究越来越受到关注,研究者们相继提出了许多解决方案。其中的随机密钥预分配方案基于概率模型,因此网络中可能存在着一些安全孤立节点,从而可能会降低整个网络的安全连通性。针对此问题,提出在节点布置比较稀疏的无线传感器网络的初始化阶段以及网络在运行过程中,定期对网络进行安全连通性检测,以发现网络中存在的安全孤立节点,然后增大这些孤立节点的通信半径,从而动态地调整网络中某个局部区域的安全连通性,以使得整个网络获得更高的安全连通性。     

Recovery from multiple simultaneous failures in wireless sensor networks using minimum Steiner tree

In some applications, wireless sensor networks (WSNs) operate in very harsh environments and nodes become subject to increased risk of damage. Sometimes a WSN suffers from the simultaneous failure of multiple sensors and gets partitioned into disjoint segments. Restoring network connectivity in such a case is crucial in order to avoid negative effects on the application. Given that WSNs often operate unattended in remote areas, the recovery should be autonomous. This paper promotes an effective strategy for restoring the connectivity among these segments by populating the least number of relay nodes. Finding the optimal count and position of relay nodes is NP-hard and heuristics are thus pursued. We propose a Distributed algorithm for Optimized Relay node placement using Minimum Steiner tree (DORMS). Since in autonomously operating WSNs it is infeasible to perform a network-wide analysis to diagnose where segments are located, DORMS moves relay nodes from each segment toward the center of the deployment area. As soon as those relays become in range of each other, the partitioned segments resume operation. DORMS further model such initial inter-segment topology as Steiner tree in order to minimize the count of required relays. Disengaged relays can return to their respective segments to resume their pre-failure duties. We analyze DORMS mathematically and explain the beneficial aspects of the resulting topology with respect to connectivity, and traffic balance. The performance of DORMS is validated through extensive simulation experiments.     

Handling large-scale node failures in mobile sensor/robot networks

In Wireless Sensor Networks (WSNs), maintaining connectivity with the sink node is a crucial issue to collect data from sensors without any interruption. While sensors are typically deployed in abundance to tolerate possible node failures, a large number of simultaneous node failures within the same region may result in partitioning the network which may disrupt the network operation significantly. Given that WSNs are deployed in inhospitable environments, such node failures are very likely due to storms, fires, floods, etc. The self-recovery of the network from these large-scale node failures is challenging since the nodes will not have any information about the location and span of the damage. In this paper, we first present a distributed partition detection algorithm which quickly makes the sensors aware of the partitioning in the network. This process is led by the sensors whose upstream nodes fail due to damages. Upon partition detection, sensors federate the partitions and restore data communication by utilizing the former routing information stored at each sensor to the sink node and exploiting sensor mobility. Specifically, the locations of failed sensors on former routes are used to assess the span of the damage and some of the sensors are relocated to such locations to re-establish the routes with the sink node. Relocation on such former routes is performed in such a way that the movement overhead on sensors is also minimized. Our proposed approach solely depends on the local information to ensure autonomicity, timeliness and scalability. The effectiveness of the proposed federation approach is validated through realistic simulation experiments and has been shown to provide the mentioned features.     

A testbed for coverage control using mixed wireless sensor networks

Wireless sensor networks (WSNs) is a relatively new technology that has been proposed for several applications including wide area monitoring. Such applications may include stationary or mobile sensor platforms or they may include several stationary and some mobile-robotic sensor nodes that can move in the area in order to achieve certain objectives, e.g., monitor areas that are not adequately covered or assist in the transfer of data to prevent the energy depletion of certain critical nodes. Such networks that consist of both stationary and mobile nodes are referred to as mixed WSNs. This paper presents the development of an experimental testbed for mixed WSNs consisting of stationary and mobile sensor nodes that collaborate to improve the sensing coverage and event detection of the network in a given deployment area. The paper describes the hardware and infrastructure of the testbed as well as a case study for coverage control that was investigated using the testbed. We point out that the developed testbed can be used for the evaluation and validation of different algorithms for coverage control that involve collaboration between stationary and mobile sensors to improve the WSN's monitoring capabilities. In addition, it can also be used to investigate other objectives as well as other concepts (e.g., network control).     

A survey on coverage and connectivity issues in wireless sensor networks

A wireless sensor network (WSN) is composed of a group of small power-constrained nodes with functions of sensing and communication, which can be scattered over a vast region for the purpose of detecting or monitoring some special events. The first challenge encountered in WSNs is how to cover a monitoring region perfectly. Coverage and connectivity are two of the most fundamental issues in WSNs, which have a great impact on the performance of WSNs. Optimized deployment strategy, sleep scheduling mechanism, and coverage radius cannot only reduce cost, but also extend the network lifetime. In this paper, we classify the coverage problem from different angles, describe the evaluation metrics of coverage control algorithms, analyze the relationship between coverage and connectivity, compare typical simulation tools, and discuss research challenges and existing problems in this area.     

Energy-aware node placement,topology control and MAC scheduling for wireless sensor networks

In the WSNs, the nodes closer to the sink node have heavier traffic load for packet forwarding because they do not only collect data within their sensing range but also relay data for nodes further away. The unbalanced power consumption among sensor nodes may cause network partition. This paper proposes efficient node placement, topology control, and MAC scheduling protocols to prolong the sensor network lifetime, balance the power consumption of sensor nodes, and avoid collision. Firstly, a virtual tree topology is constructed based on Grid-based WSNs. Then two node-placement techniques, namely Distance-based and Density-based deployment schemes, are proposed to balance the power consumption of sensor nodes. Finally, a collision-free MAC scheduling protocol is proposed to prevent the packet transmissions from collision. In addition, extension of the proposed protocols are made from a Grid-based WSN to a randomly deployed WSN, enabling the developed energy-balanced schemes to be generally applied to randomly deployed WSNs. Simulation results reveal that the developed protocols can efficiently balance each sensor node’s power consumption and prolong the network lifetime in both Grid-based and randomly deployed WSNs.     

基于WSNs的部分覆盖应用的节点唤醒机制

无线传感网络WSNs(Wireless Sensor Networks)已广泛应用于各类领域.然而,由于能量有限,提高传感节点能效是一项挑战工作.休眠调度策略是保存能量、延长网络寿命的有效策略.此外,多数WSNs应用并不要求100％的覆盖.为此,提出面向部分覆盖应用的节点唤醒机制,且标记为PCLA.PCLA机制引用学习自动机去合理地唤醒节点,而其他节点休眠,进而延长网络寿命.首先,唤醒部分节点构成主干网,然后,再利用这些节点的邻居去满足网络覆盖要求.实验数据表明,与同类机制相比,提出的PCLA机制能够有效地满足部分覆盖要求,并且在活动节点数和网络寿命方面也具有较好的性能.     

Towards augmenting federated wireless sensor networks in forestry applications

Environmental Monitoring (EM) has witnessed significant improvements in recent years due to the great utility of wireless sensor networks (WSNs). Nevertheless, due to harsh operational conditions in such applications, WSNs often suffer large-scale damage in which nodes fail concurrently and the network gets partitioned into disjoint sectors. Thus, reestablishing connectivity between the sectors, via their remaining functional nodes, is of utmost importance in EM, especially in forestry. In this regard, considerable work has been proposed in the literature tackling this problem by deploying Relay Nodes (RNs) aimed at reestablishing connectivity. Although finding the minimum relay count and positions is NP-Hard, efficient heuristic approaches have been anticipated. However, the majority of these approaches ignore the surrounding environment characteristics and the infinite 3-dimensional (3-D) search space that significantly degrades network performance in practice. Therefore, we propose a 3-D grid-based deployment for RNs in which the relays are efficiently placed on grid vertices. We present a novel approach, named fixing augmented network damage intelligently, based on a minimum spanning tree construction to re-connect the disjointed WSN sectors. The performance of the proposed approach is validated and assessed through extensive simulations, and comparisons with two main stream approaches are presented. Our protocol outperforms the related work in terms of the average relay node count and distribution, the scalability of the federated WSNs in large-scale applications, and the robustness of the topologies formed.     

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.     

A fault tolerant optimal relay node selection algorithm for Wireless Sensor Networks using modified PSO

Wireless Sensor Networks (WSNs) have energy-constraints that restricts to achieve prolonged network lifetime. To optimize energy consumption of sensor nodes, clustering is one of the efficient techniques for minimization of energy conservation in WSNs. This technique sends the collected data towards the SINK based on cluster head (CH) nodes that leads to the saving of energy. WSNs have been faced a crucial issue of fault tolerance and the overall data communication is collapsed due to the failure of cluster head. Various fault-tolerance clustering methods are available for WSNs, but they are not selected the backup nodes properly. The backup nodes’ closeness or location to the other remaining nodes is not considered in these methods. They may increase network overhead with the backup nodes accessibility. A fault-tolerance cluster-based routing method is presented in this paper that aims on providing fault tolerance for relay selection in addition to the data aggregation method for clustered WSNs. The proposed method utilizes backup mechanism & the Particle Swarm Optimization (PSO) to achieve this. Based on the distance from sink, residual energy, and link delay parameters, the CHs are chosen and the network is categorized into the clusters. The Backup CHs are selected by estimating the centrality among the nodes. As a part of intra-cluster communication for reducing the aggregation overhead among CHs, the Aggregator (AG) nodes are deployed in every cluster. So that they act as the bridge between the member nodes and CHs. These AG nodes aggregates the information from member nodes and deliver it to the CHs. The PSO with modified fitness function is used to identify the best relays between AG and member nodes. The proposed mechanism is compared with existing techniques such as EM-LEACH AI-Sodairi and Ouni (2018), QEBSR Rathee et al. (2019), QOS-IHC Singh and Singh (2019), and ML-SEEP Robinson et al. (2019). The simulation results proved that the proposed mechanism reduces overhead by 55% and improve the energy consumption & throughput by 40% & 60% respectively.     

Heuristic algorithm for finding boundary cycles in location-free low density wireless sensor networks

Wireless sensor networks (WSNs) comprise a large number of sensor nodes, which are spread out within a region to be monitored and communicate using wireless links. In some WSN applications, recognizing boundary nodes is important for topology discovery, geographic routing, tracking and guiding. In this paper, we study the problem of identifying the boundary nodes of a WSN. In a WSN, close-by nodes can establish direct communications with their neighbors and have the ability to estimate distances to nearby nodes, but not necessarily the true distances. Our objective is to find the boundary nodes by using only the connectivity relation and neighbor distance information without any other knowledge of node locations. Moreover, our main aim is to design a distributed algorithm that works even when the average degree is low. We propose a heuristic algorithm to find the boundary nodes which are connected in a boundary cycle of a location-free, low density (average degree 5–6), randomly deployed WSN. We develop the key ideas of our boundary detection algorithm in the centralized scenario and extend these ideas to the distributed scenario. The distributed implementation is more realistic for real WSNs, especially for sparse networks when all local information cannot be collected very well due to sparse connectivity. In addition, the distributed implementation can tolerate faults by recomputing the boundary locally when a boundary node is faulty. Simulations in ns-2 show that the distributed implementation outperforms the centralized one with higher quality of boundaries.     

Power Consumption Analysis of Maximum A Posterior Classifier Using LU Decomposition and Jacobi Iterations

In tracking applications of wireless sensor networks (WSNs), classification of an object or event of interest is considred one of the most computationally intensive tasks that recur frequently over the lifetime of the network. It is imperative that the implementations of such tasks be power-efficient and computationally feasible for resource-constrained WSNs. Existing implementations of the best known classifiers, such as Maximum A Posterior (MAP) classifier, are computationally infeasible for WSNs. The focus of this paper is to investigate computational techniques to realize power efficient distributed implementation of the MAP classifier in WSNs. In the MAP classifier, one of the most computationally challenging steps is the computation of the inverse of the covariance matrices. In this paper, we study computationally efficient methods for realizing the inverse of a matrix. We present a detailed discussion of one-sided Jacobi Iterations and LU Decomposition for approximating and computing the inverse of the covariance matrices. For LU Decomposition based solutions, we also apply folding techniques to ensure equal power dissipation among the sensor network nodes We show that MAP with one-sided Jacobi Iterations greatly simplifies classification process and makes it more feasible and efficient choice for sensor network applications.     

Reliable networks with unreliable sensors

Wireless sensor networks (WSNs) deployed in hostile environments suffer from a high rate of node failure. We investigate the effect of such failure rate on network connectivity. We provide a formal analysis that establishes the relationship between node density, network size, failure probability, and network connectivity. We show that large networks can maintain connectivity despite a significantly high probability of node failure. We derive mathematical functions that provide lower bounds on network connectivity in WSNs. We compute these functions for some realistic values of node reliability, area covered by the network, and node density, to show that, for instance, networks with over a million nodes can maintain connectivity with a probability exceeding 95% despite node failure probability exceeding 53%.     

无线传感器网络中基于关联度的多查询优化

无线传感器网络是一种以数据为中心的网络,用户通过基站向网络提出查询请求获取所需数据。如何通过多查询的优化来减少传感器节点的能耗以延长网络生命期是无线传感器网络中需要解决的关键问题之一。提出了基于关联度的多查询优化算法,其基本思想是节点通过节点与候选父亲节点之间的关联度来选择父节点,从而被相同查询覆盖的节点聚集成一个组,多个查询间共享组中节点的数据,在网络中对查询数据进行有效的融合,充分减少了网络的数据传输量,延长了网络的生命期。理论分析和模拟实验表明该算法可以充分减少数据传输量,从而达到节能的目的。     

Machine learning algorithms for wireless sensor networks: A survey

Wireless sensor network (WSN) is one of the most promising technologies for some real-time applications because of its size, cost-effective and easily deployable nature. Due to some external or internal factors, WSN may change dynamically and therefore it requires depreciating dispensable redesign of the network. The traditional WSN approaches have been explicitly programmed which make the networks hard to respond dynamically. To overcome such scenarios, machine learning (ML) techniques can be applied to react accordingly. ML is the process of self-learning from the experiences and acts without human intervention or re-program. The survey of the ML techniques for WSNs is presented in [1], covering period of 2002–2013. In this survey, we present various ML-based algorithms for WSNs with their advantages, drawbacks, and parameters effecting the network lifetime, covering the period from 2014–March 2018. In addition, we also discuss ML algorithms for synchronization, congestion control, mobile sink scheduling and energy harvesting. Finally, we present a statistical analysis of the survey, the reasons for selection of a particular ML techniques to address an issue in WSNs followed by some discussion on the open issues.     

基于协作传输的大范围WSNs能耗均衡分簇算法

由于大范围无线传感器网络（WSNs）节点的数量巨大,网络的能量消耗极不均,提出一种基于协作传输的分簇算法—EBBMCC—LS算法。该算法在保证网络均匀分簇的前提下,能保证网络中簇头节点的均匀分布,在簇间通信时加入协作传输策略,传感器节点之间通过协作传输构成虚拟多天线系统,改善系统性能,解决了大范围WSNs中的能耗不均现象。实验验证：该算法能够均衡大范围WSNs中的能耗,延长网络寿命,可促进大范围WSNs应用的推广。     

A survey of game-theoretic approaches in wireless sensor networks

Wireless sensor networks (WSNs) comprising of tiny, power-constrained nodes are gaining popularity due to their potential for use in a wide variety of environments like monitoring of environmental attributes, intrusion detection, and various military and civilian applications. While the sensing objectives of these environments are unique and application-dependent, a common performance criteria for wireless sensor networks is prolonging network lifetime while satisfying coverage and connectivity in the deployment region. Security is another important performance parameter in wireless sensor networks, where adverse and remote environments pose various kinds of threats to reliable network operation. In this paper, we look at the problems of security and energy efficiency and different formulations of these problems based on the approach of game theory. The potential applicability of WSNs to intruder detection environments also lends itself to game-theoretic formulation of these environments, where pursuit-evasion games provide a relevant framework to model detection, tracking and surveillance applications.The suitability of using game theory to study security and energy efficiency problems and pursuit-evasion scenarios using WSNs stems from the nature of strategic interactions between nodes. Approaches from game theory can be used to optimize node-level as well as network-wide performance by exploiting the distributed decision-making capabilities of WSNs. The use of game theory has proliferated, with a wide range of applications in wireless sensor networking. In the wake of this proliferation, we survey the use of game-theoretic approaches to formulate problems related to security and energy efficiency in wireless sensor networks.     

无线传感器网络中基于异构节点的覆盖控制算法

研究了无线传感器网络中基于异构节点的优化覆盖控制问题.异构无线传感器网络由两类能力不同的节点组成,包括普通节点和超级节点.对普通节点采用基于状态轮转的覆盖控制算法,对超级节点采用基于路由表的转发策略.通过两类节点的协作使得网络达到覆盖与连通的目的.模拟结果表明,在具有相同初始能量的情况下,该算法与SHHN-HS算法相比能够延长网络生命期.     

A novel gossip-based sensing coverage algorithm for dense wireless sensor networks

Wireless sensor networks (WSNs) have been widely studied and usefully employed in many applications such as monitoring environments and embedded systems. WSNs consist of many nodes spread randomly over a wide area; therefore, the sensing regions of different nodes may overlap partially. This is called the “sensing coverage problem”. In this paper, we define a maximum sensing coverage region (MSCR) problem and present a novel gossip-based sensing-coverage-aware algorithm to solve the problem. In the algorithm, sensor nodes gossip with their neighbors about their sensing coverage region. In this way, nodes decide locally to forward packets (as an active node) or to disregard packets (as a sleeping or redundant node). Being sensing-coverage-aware, the redundant node can cut back on its activities whenever its sensing region is k-covered by enough neighbors. With the distributed and low-overhead traffic benefits of gossip, we spread energy consumption to different sensor nodes, achieve maximum sensing coverage with minimal energy consumption in each individual sensor node, and prolong the whole network lifetime. We apply our algorithm to improve LEACH, a clustering routing protocol for WSNs, and develop a simulation to evaluate the performance of the algorithm.