Data Aggregation for Increase Performance of Wireless Sensor Networks Using Learning Automata Approach

Wireless sensor networks, a new generation of networks, are composed of a large numbers of nodes and the communication between nodes takes place wirelessly. The main purpose of these networks is collecting information about the environment surrounding the network sensors. The sensors collect and send the required information. There are many challenges and research areas concerned in the literature, one of which is power consumption in network nodes. Nodes in these networks have limited energy sources and generally consume more energy in long communication distances and therefore run out of battery very fast. This results in inefficacy in the whole system. One of the proposed solutions is data aggregation in wireless networks which leads to improved performance. Therefore, in this study an approach based on learning automata is proposed to achieve data aggregation which leads to dynamic network at any hypothetical region. This approach specifies a cluster head in the network and nodes send their data to the cluster head and the cluster head sends the information to the main receiver. Also each node can change its sensing rate using learning automata. Simulation results show that the proposed method increases the lifetime of the network and more nodes will be alive.

     

大规模输电线路状态监测传感器网络的周期性低功耗通信技术方案

为了实现输电线路监测的功耗低、寿命长、绿色发展的目的，提出大规模输电线路状态监测传感器网络周期性低功耗通信技术方案。依据网络中传感器网络组网特征以及节点运行状态转换特点，设置睡眠定时器，以周期性运行方式使传感器网络通信节点在初始化、睡眠、激活状态间转换，通信节点在输电线路状态监测数据无传递需求时进入睡眠状态，节省通信功耗；传感器网络汇聚（sink）节点利用梯度创建上行路由，通过源路由的方式创建下行路由，以跳数和剩余能量为依据进行上、下行路由数据分组传递，降低节点功耗，延长通信运行时间。实验显示，大规模输电线路状态监测传感器网络应用该技术方案后，通信功耗明显降低，运行时间明显延长，且不会影响监测传感器网络的数据传输性能，延长了监测传感器网络的使用寿命。     

基于ZigBee的风电机组振动故障监测系统设计

：针对目前风电机组有线监测系统安装、维护不便和监测点有限等问题,设计了基于ZigBee的风电机组振动故障监测系统,由传感器节点、协调器节点、3G网络和监控中心组成。传感器节点采集机组各部位的振动参数并发送至协调器节点,经过协调器节点处理的信息通过3G网络发送至远程监控中心,此设计提高了系统的可靠性和实时性。测试结果表明系统节点间通信良好,系统工作稳定性高,数据传输实时性好,及时给出报警信息,故障诊断正确率达到95.5%。     

Mobile Malicious Node Detection Using Mobile Agent in Cluster-Based Wireless Sensor Networks

Many application domains require that sensor node to be deployed in harsh or hostile environments, such as active volcano area tracking endangered species, etc. making these nodes more prone to failures. The most challenging problem is monitoring the illegal movement within the sensor networks. Attacker prefers mobile malicious node because by making the diversity of path intruder maximize his impact. The emerging technology of sensor network expected Intrusion detection technique for a dynamic environment. In this paper, a defective mechanism based on three-step negotiation is performed for identifying the mobile malicious node using the mobile agent. In many approaches, the multi-mobile agents are used to collect the data from all the sensor nodes after verification. But it is inefficient to verify all the sensor nodes (SNs) in the network, because of mobility, energy consumption, and high delay. In the proposed system this can be solved by grouping sensor nodes into clusters and a single mobile agent performs verification only with all the cluster heads instead of verifying all the SNs. The simulation result shows the proposed system shows a better result than the existing system.

     

A new load balancing and data collection algorithm for energy saving in wireless sensor networks

Data gathering is a major function of many applications in wireless sensor networks. The most important issue in designing a data gathering algorithm is how to save energy of sensor nodes while meeting the requirements of special applications or users. Wireless sensor networks are characterized by centralized data gathering, multi-hop communication and many to one traffic pattern. These three characteristics can lead to severe packet collision, network congestion and packet loss, and even result in hot-spots of energy consumption thus causing premature death of sensor nodes and entire network. In this paper, we propose a load balance data gathering algorithm that classifies sensor nodes into different layers according to their distance to sink node and furthermore, divides the sense zone into several clusters. Routing trees are established between sensor node and sink depending on the energy metric and communication cost. For saving energy consumption, the target of data aggregation scheme is adopted as well. Analysis and simulation results show that the algorithm we proposed provides more uniform energy consumption among sensor nodes and can prolong the lifetime of sensor networks.     

Composite Fault Diagnosis in Wireless Sensor Networks Using Neural Networks

Wireless sensor networks (WSNs) are spatially distributed devices to support various applications. The undesirable behavior of the sensor node affects the computational efficiency and quality of service. Fault detection, identification, and isolation in WSNs will increase assurance of quality, reliability, and safety. In this paper, a novel neural network based fault diagnosis algorithm is proposed for WSNs to handle the composite fault environment. Composite fault includes hard, soft, intermittent, and transient faults. The proposed fault diagnosis protocol is based on gradient descent and evolutionary approach. It detects, diagnose, and isolate the faulty nodes in the network. The proposed protocol works in four phases such as clustering phase, communication phase, fault detection and classification phase, and isolation phase. Simulation results show that the proposed protocol performs better than the existing protocols in terms of detection accuracy, false alarm rate, false positive rate, and detection latency.

     

Rule‐Based Anomaly Detection Technique Using Roaming Honeypots for Wireless Sensor Networks

Because the nodes in a wireless sensor network (WSN) are mobile and the network is highly dynamic, monitoring every node at all times is impractical. As a result, an intruder can attack the network easily, thus impairing the system. Hence, detecting anomalies in the network is very essential for handling efficient and safe communication. To overcome these issues, in this paper, we propose a rule‐based anomaly detection technique using roaming honeypots. Initially, the honeypots are deployed in such a way that all nodes in the network are covered by at least one honeypot. Honeypots check every new connection by letting the centralized administrator collect the information regarding the new connection by slowing down the communication with the new node. Certain pre‐defined rules are applied on the new node to make a decision regarding the anomality of the node. When the timer value of each honeypot expires, other sensor nodes are appointed as honeypots. Owing to this honeypot rotation, the intruder will not be able to track a honeypot to impair the network. Simulation results show that this technique can efficiently handle the anomaly detection in a WSN.     

LoRa-Based WSNs Construction and Low-Power Data Collection Strategy for Wetland Environmental Monitoring

The wetland that known as "the kidney of the earth" is an ecological system with many resources. Monitoring of wetland environment includes the monitoring of water quality, air and soil. The parameters of temperature, pH value, turbidity, dissolved oxygen (DO), water level, conductivity of water, illuminance, PM2.5, harmful gas, and soil moisture is particularly important for the survival of animals in wetland. Real-time monitoring wetland environment is conducive to understanding the causes and trends of environmental change in the whole region, so as to make environmental change emergency strategies timely. The author introduces a real-time monitoring system based on Multi-sensor Combination Module (MSCM) and LoRa. This system has two types of MSCM, one is for water and the other is for air. The MSCM for water consists of six sensors, such as water temperature sensor, pH sensor, turbidity sensor, dissolved oxygen sensor, conductivity sensor, and water level sensor, and stm32 core processor, which has the advantages of low power consumption and high speed. The data collection node uploads the collected data to the base station through a LoRa module with low power consumption, high speed and wide coverage. The base station and the collection node are connected in a star. The LoRaWan protocol is used to realize the communication between acquisition nodes and sink. In the case of code rate is 4/5, bandwidth is 500 kHz and spreading factor is 12, the effective throughput of the system can reach 1172 bps. At the same time, a data fusion algorithm based on fuzzy decision is designed for data processing on the acquisition nodes to reduce the amount of uploaded data, reduce power consumption and improve network throughput. Experiments show that the system has strong stability, flexible networking, low power consumption, long communication distance, and is suitable for wetland environmental monitoring.

     

Efficient and distributed access control for sensor networks

Sensor networks are a promising computing paradigm for monitoring the physical environment and providing observations for various uses. In hostile situations, it is critical to enforce network access control to ensure the integrity, availability, and at times confidentiality of the sensor data. A natural idea is to adopt a centralized design where every access request from users goes through a trusted base station. However, this idea is not practical due to the cost and efficiency issues. This paper proposes two efficient and distributed access control methods, uni-access query and multi-access query. The uni-access query uses only symmetric cryptographic operations; it allows (1) a user to directly access the data on any sensor node in the network without going through the base station and (2) a sensor to protect its data so that only authorized users can access. Compared to existing solutions, this scheme is much more flexible and efficient. In addition, this scheme can also support privilege delegation, which allows a user to delegate all or part of its privilege to others without using the base station. The multi-access query applies public key cryptography to provide an additional feature, which allows a user to access the data on many sensor nodes via a single query. Compared to existing solutions that require a user to send at least one request for every sensor node to be queried, the multi-access query reduces the communication overhead significantly. The theoretical analysis and simulation evaluation show that the proposed schemes are practical for access control in sensor networks.     

Lifetime analysis of wireless sensor nodes in different smart grid environments

Wireless sensor networks (WSNs) can help the realization of low-cost power grid automation systems where multi-functional sensor nodes can be used to monitor the critical parameters of smart grid components. The WSN-based smart grid applications include but not limited to load control, power system monitoring and control, fault diagnostics, power fraud detection, demand response, and distribution automation. However, the design and implementation of WSNs are constrained by energy resources. Sensor nodes have limited battery energy supply and accordingly, power aware communication protocols have been developed in order to address the energy consumption and prolong their lifetime. In this paper, the lifetime of wireless sensor nodes has been analyzed under different smart grid radio propagation environments, such as 500 kV substation, main power control room, and underground network transformer vaults. In particular, the effects of smart grid channel characteristics and radio parameters, such as path loss, shadowing, frame length and distance, on a wireless sensor node lifetime have been evaluated. Overall, the main objective of this paper is to help network designers quantifying the impact of the smart grid propagation environment and sensor radio characteristics on node lifetime in harsh smart grid environments.     

无线传感器网络的新进展与应用

为完成实时监测、感知和采集各种监测环境或对象的信息,将智能传感器组成分布式信息测控网络。无线传感器网络是传感器智能化发展的趋势。它是以数据获取与数据管理为核心的全新网络,综合了传感器技术、嵌入式计算技术、分布式信息处理技术和无线通信技术。介绍了无线传感器网络节点、无线传感器网络、无线传感器网络的最新进展,并给出了无线传感器网络的应用。     

基于移动中继站的无线传感器网络设计

WSN（无线传感器网络）是由大量分布式的不同规格和功能的具有感知、计算和通信能力的微型传感器节点通过自组织的方式构成的一个小范围的无线网络。为了解决无线传感器的远距离通信中继问题,能够将网络信息通过中继顺利地传送到远程终端,设计了基于移动螃蟹的传感器网络。它以机器螃蟹作为中继,进行数据的本地化处理和融合,实现分布式数据采集和监控。本系统应用于大规模的无线网络,增加了设备状态数据采集与通信的距离,有效地增强了系统的健壮性。     

The n-Hop Multilateration Primitive for Node Localization Problems

The recent advances in MEMS, embedded systems and wireless communication technologies are making the realization and deployment of networked wireless microsensors a tangible task. In this paper we study node localization, a component technology that would enhance the effectiveness and capabilities of this new class of networks. The n-hop multilateration primitive presented here, enables ad-hoc deployed sensor nodes to accurately estimate their locations by using known beacon locations that are several hops away and distance measurements to neighboring nodes. To prevent error accumulation in the network, node locations are computed by setting up and solving a global non-linear optimization problem. The solution is presented in two computation models, centralized and a fully distributed approximation of the centralized model. Our simulation results show that using the fully distributed model, resource constrained sensor nodes can collectively solve a large non-linear optimization problem that none of the nodes can solve individually. This approach results in significant savings in computation and communication, that allows fine-grained localization to run on a low cost sensor node we have developed.     

Deterministic K‐means secure coverage clustering with periodic authentication for wireless sensor networks

Innovative and emerging developments in sensor networks are proven to be the backbone for real‐time applications such as satellite communications, military and border area surveillance systems, health care systems, traffic monitoring systems, seismic and underwater monitoring systems, and agriculture and habitat environment systems. Coverage and clustering techniques enable the sensor network to operate in group‐based and region‐based communication and thus save the node energy. Energy‐efficient protocols save the node energy and increase the network life cycle in a resource‐constrained sensor network. Cluster head (CH) node manages and controls the operations such as network topology, coverage area, and routing paths (multi‐paths and fault‐tolerant paths) of the network. In this paper, we present deterministic K‐means secure coverage clustering (K‐SCC) with periodic authentication. The proposed protocol uses coverage clustering technique with periodic authentication between the CH node and sensor nodes to establish the secure channel in the network. Maximum cover of K nodes is maintained in the secure coverage cluster to achieve authenticated communication between the sensor nodes in the network. The proposed K‐SCC protocol is compared with the existing protocols such as deterministic‐SCC and random‐SCC protocols. Simulation results indicate that the proposed K‐SCC protocol achieves an average of 84% coverage ratio (cluster/sensor node ratio) as compared with 62% coverage ratio in the existing SCC protocols. Simulations also indicate that the proposed K‐SCC protocol consumes 20% less energy as compared with the existing SCC protocol. Copyright © 2015 John Wiley & Sons, Ltd.     

TDMA scheduling algorithms for wireless sensor networks

Algorithms for scheduling TDMA transmissions in multi-hop networks usually determine the smallest length conflict-free assignment of slots in which each link or node is activated at least once. This is based on the assumption that there are many independent point-to-point flows in the network. In sensor networks however often data are transferred from the sensor nodes to a few central data collectors. The scheduling problem is therefore to determine the smallest length conflict-free assignment of slots during which the packets generated at each node reach their destination. The conflicting node transmissions are determined based on an interference graph, which may be different from connectivity graph due to the broadcast nature of wireless transmissions. We show that this problem is NP-complete. We first propose two centralized heuristic algorithms: one based on direct scheduling of the nodes or node-based scheduling, which is adapted from classical multi-hop scheduling algorithms for general ad hoc networks, and the other based on scheduling the levels in the routing tree before scheduling the nodes or level-based scheduling, which is a novel scheduling algorithm for many-to-one communication in sensor networks. The performance of these algorithms depends on the distribution of the nodes across the levels. We then propose a distributed algorithm based on the distributed coloring of the nodes, that increases the delay by a factor of 10–70 over centralized algorithms for 1000 nodes. We also obtain upper bound for these schedules as a function of the total number of packets generated in the network.     

The Impact of Deployment Pattern and Routing Scheme on the Lifetime in Multi-Sink Wireless Sensor Network

Extensive use of sensor and actuator networks in many real-life applications introduced several new performance metrics at the node and network level. Since wireless sensor nodes have significant battery constraints, therefore, energy efficiency, as well as network lifetime, are among the most significant performance metrics to measure the effectiveness of given network architecture. This work investigates the performance of an event-based data delivery model using a multipath routing scheme for a wireless sensor network with multiple sink nodes. This routing algorithm follows a sink initiated route discovery process with the location information of the source nodes already known to the sink nodes. It also considers communication link costs before making decisions for packet forwarding. Carried out simulation compares the network performance of a wireless sensor network with a single sink, dual sink, and multi sink networking approaches. Based on a series of simulation experiments, the lifetime aware multipath routing approach is found appropriate for increasing the lifetime of sensor nodes significantly when compared to other similar routing schemes. However, energy-efficient packet forwarding is a major concern of this work; other network performance metrics like delay, average packet latency, and packet delivery ratio are also taken into the account.

     

Joint Routing and Resource Allocation for Cluster Based Isolated Nodes in Cognitive Radio Wireless Sensor Networks

Clustering is an effective way to increase network lifetime but it leads to formation of isolated nodes in the wireless sensor network. These isolated sensor nodes forward data directly to sink and consume more energy which significantly reduces the network lifetime. In this article, we present how to maximize the network lifetime through joint routing and resource allocation with isolated nodes technique (JR-IN) between cluster head and isolated nodes in a cognitive based wireless sensor networks. In JR-IN technique the network area is divided into different layers and cluster size is formulated in each layer such that the size of the cluster remains unequal when it moves towards sink. Hence the cluster size is lager in the outermost layer compared to the cluster size in the inner most layer. To avoid inter cluster collision, we proposed different fixed channel to all the cluster heads in the network. For the intra cluster communication, the cluster member (sensor nodes) will lease the spectrum from the cluster head and forward data to their respective cluster head using TDMA technique. The periodical data gathering of cluster heads and forwarding the data to one hop cluster head may tend to lose energy faster and dies out quickly. We also propose in the JR-IN technique, the isolated nodes in the layer will take charge as a cluster head node and utilizes the resource allocated to the respective cluster head and forward the data to next hop cluster head. Simulation result shows that JR-IN outperforms the existing techniques, maximizes network lifetime and throughput and reduces the end to end delay.

     

A distributed reinforcement learning based sensor node scheduling algorithm for coverage and connectivity maintenance in wireless sensor network

The fundamental challenge for randomly deployed resource-constrained wireless sensor network is to enhance the network lifetime without compromising its performance metrics such as coverage rate and network connectivity. One way is to schedule the activities of sensor nodes and form scheduling rounds autonomously in such a way that each spatial point is covered by at least one sensor node and there must be at least one communication path from the sensor nodes to base station. This autonomous activity scheduling of the sensor nodes can be efficiently done with Reinforcement Learning (RL), a technique of machine learning because it does not require prior environment modeling. In this paper, a Nash Q-Learning based node scheduling algorithm for coverage and connectivity maintenance (CCM-RL) is proposed where each node autonomously learns its optimal action (active/hibernate/sleep/customize the sensing range) to maximize the coverage rate and maintain network connectivity. The learning algorithm resides inside each sensor node. The main objective of this algorithm is to enable the sensor nodes to learn their optimal action so that the total number of activated nodes in each scheduling round becomes minimum and preserves the criteria of coverage rate and network connectivity. The comparison of CCM-RL protocol with other protocols proves its accuracy and reliability. The simulative comparison shows that CCM-RL performs better in terms of an average number of active sensor nodes in one scheduling round, coverage rate, and energy consumption.

     

Energy Attentive and Pre-fault Recognize Mechanism for Distributed Wireless Sensor Network Using Fuzzy Logic Approach

Wireless sensor networks (WSNs) have been transforming over recent years with development in the design of smart real-time applications. However, it presents numerous challenges in terms of fault-tolerant communication, low latency, scalability, and transmission efficiency. It is extremely difficult for WSNs to detect runtime faults since they're unaware of the internal processes at work within the sensor node. As a result, valuable sensed information cannot reach its destination and performance starts degrading. Towards this objective, the proposed mechanism applies a novel pre-fault detection mechanism based on a fuzzy rule-based method for multilevel transmission in distributed sensor networks. The proposed mechanism uses a fuzzy rule set to make routing decisions. A fuzzy decision rule set is proposed to perform routing based on the fuzzy fault count status of a node. The proposed mechanism assists in identifying the fault in advance and determining the optimal routing path to save energy and improve network performance. In accordance with the node fault status, the data transmission rate is finalized to prevent further energy consumption. The results demonstrated that the proposed mechanism performed well on judgment evaluation metrics like the energy dissipation ratio, throughput, packet loss rate and communication delay.

     

Partial Relay Selection in Energy Harvesting Based NOMA Network with Imperfect CSI

The wireless body area network (WBAN) can effectively modify the health and lifestyle monitoring specifically where multiple body parameters are measured using biomedical sensor devices. However, power consumption and reliability are crucial issues in WBAN. Cooperative Communication usually prolongs the network lifetime of WBAN and allows reliable delivery of bio-medical packets. Hence, the main aim of this investigation is to propose a novel protocol Cooperative Energy efficient and Priority based Reliable routing protocol with Network coding (CEPRAN) to enhance the reliability and energy efficiency of WBAN using cooperative communication method. Firstly, to identify a relay node from the group of sensor nodes for data forwarding, an enhanced Cuckoo search optimization algorithm is proposed. Secondly, Cooperative Random Linear Network Coding approach is incorporated into the relay node to improve the packet transfer rate. CEPRAN is implemented in Ns-3 simulator and the experimental results prove that the proposed protocol outperforms the existing SIMPLE Protocol.