A blockchain-empowered authentication scheme for worm detection in wireless sensor network

Wireless Sensor Network(WSN)is a distributed sensor network composed a large number of nodes with low cost,low performance and self-management.The special structure of WSN brings both convenience and vulnerability.For example,a malicious participant can launch attacks by capturing a physical device.Therefore,node authentication that can resist malicious attacks is very important to network security.Recently,blockchain technology has shown the potential to enhance the security of the Internet of Things(IoT).In this paper,we propose a Blockchain-empowered Authentication Scheme(BAS)for WSN.In our scheme,all nodes are managed by utilizing the identity information stored on the blockchain.Besides,the simulation experiment about worm detection is executed on BAS,and the security is evaluated from detection and infection rate.The experiment results indicate that the proposed scheme can effectively inhibit the spread and infection of worms in the network.

Enabling Efficient Data Transmission in Wireless Sensor Networks-Based IoT Application

The use of the Internet of Things(IoT)is expanding at an unprecedented scale in many critical applications due to the ability to interconnect and utilize a plethora of wide range of devices.In critical infrastructure domains like oil and gas supply,intelligent transportation,power grids,and autonomous agriculture,it is essential to guarantee the confidentiality,integrity,and authenticity of data collected and exchanged.However,the limited resources coupled with the heterogeneity of IoT devices make it inefficient or sometimes infeasible to achieve secure data transmission using traditional cryptographic techniques.Consequently,designing a lightweight secure data transmission scheme is becoming essential.In this article,we propose lightweight secure data transmission(LSDT)scheme for IoT environments.LSDT consists of three phases and utilizes an effective combination of symmetric keys and the Elliptic Curve Menezes-Qu-Vanstone asymmetric key agreement protocol.We design the simulation environment and experiments to evaluate the performance of the LSDT scheme in terms of communication and computation costs.Security and performance analysis indicates that the LSDT scheme is secure,suitable for IoT applications,and performs better in comparison to other related security schemes.

A Novel Approach to Energy Optimization:Efficient Path Selection in Wireless Sensor Networks with Hybrid ANN

In pursuit of enhancing the Wireless Sensor Networks(WSNs)energy efficiency and operational lifespan,this paper delves into the domain of energy-efficient routing protocols.InWSNs,the limited energy resources of Sensor Nodes(SNs)are a big challenge for ensuring their efficient and reliable operation.WSN data gathering involves the utilization of a mobile sink(MS)to mitigate the energy consumption problem through periodic network traversal.The mobile sink(MS)strategy minimizes energy consumption and latency by visiting the fewest nodes or predetermined locations called rendezvous points(RPs)instead of all cluster heads(CHs).CHs subsequently transmit packets to neighboring RPs.The unique determination of this study is the shortest path to reach RPs.As the mobile sink(MS)concept has emerged as a promising solution to the energy consumption problem in WSNs,caused by multi-hop data collection with static sinks.In this study,we proposed two novel hybrid algorithms,namely“ Reduced k-means based on Artificial Neural Network”(RkM-ANN)and“Delay Bound Reduced kmeans with ANN”(DBRkM-ANN)for designing a fast,efficient,and most proficient MS path depending upon rendezvous points(RPs).The first algorithm optimizes the MS’s latency,while the second considers the designing of delay-bound paths,also defined as the number of paths with delay over bound for the MS.Both methods use a weight function and k-means clustering to choose RPs in a way that maximizes efficiency and guarantees network-wide coverage.In addition,a method of using MS scheduling for efficient data collection is provided.Extensive simulations and comparisons to several existing algorithms have shown the effectiveness of the suggested methodologies over a wide range of performance indicators.

A consensus time synchronization protocol in wireless sensor network

Time synchronization is one of the base techniques in wireless sensor networks(WSNs).This paper proposes a novel time synchronization protocol which is a robust consensusbased algorithm in the existence of transmission delay and packet loss.It compensates for transmission delay and packet loss firstly,and then,estimates clock skew and clock offset in two steps.Simulation and experiment results show that the proposed protocol can keep synchronization error below 2μs in the grid network of 10 nodes or the random network of 90 nodes.Moreover,the synchronization accuracy in the proposed protocol can keep constant when the WSN works up to a month.

Wireless Sensor Security Issues on Data Link Layer:A Survey

A computer network can be defined as many computing devices connected via a communication medium like the internet.Computer network development has proposed how humans and devices communicate today.These networks have improved,facilitated,and made conventional forms of communication easier.However,it has also led to uptick in-network threats and assaults.In 2022,the global market for information technology is expected to reach$170.4 billion.However,in contrast,95%of cyber security threats globally are caused by human action.These networks may be utilized in several control systems,such as home-automation,chemical and physical assault detection,intrusion detection,and environmental monitoring.The proposed literature review presents a wide range of information on Wireless Social Networks(WSNs)and Internet of Things(IoT)frameworks.The aim is first to be aware of the existing issues(issues with traditional methods)and network attacks on WSN and IoT systems and how to defend them.The second is to review the novel work in the domain and find its limitations.The goal is to identify the area’s primary gray field or current research divide to enable others to address the range.Finally,we concluded that configuration.Message Rapid Spanning Tree Protocol(RSTP)messages have higher efficiency in network performance degradation than alternative Bridge Data Unit Protocol(BPDU)forms.The research divides our future research into solutions and newly developed techniques that can assist in completing the lacking component.In this research,we have selected articles from 2015 to 2021 to provide users with a comprehensive literature overview.

A Novel Negative Multinomial Distribution Based Energy-Efficient Reputation Modeling for Wireless Sensor Networks(WSNs)

In wireless sensor networks(WSNs),nodes are usually powered by batteries.Since the energy consumption directly impacts the network lifespan,energy saving is a vital issue in WSNs,especially in the designing phase of cryptographic algorithms.As a complementary mechanism,reputation has been applied to WSNs.Different from most reputation schemes that were based on beta distribution,negative multinomial distribution was deduced and its feasibility in the reputation modeling was proved.Through comparison tests with beta distribution based reputation in terms of the update computation,results show that the proposed method in this research is more energy-efficient for the reputation update and thus can better prolong the lifespan of WSNs.

Sensors Dynamic Energy Management in WSN

A wireless sensor node is typically battery operated and energy constrained. Therefore, it is apparent that optimal energy management is one of the most important challenges in WSN development. However, energy management requires in-depth knowledge and detailed insight concerning specific scenarios. After Carrying out a large number of experiments in precision agriculture, we find that it is the sensors that have never been concerned consuming the most energy of the node. In order to conserve energy and prolong the lifetime of WSN, we design and carry out a dynamic energy management strategy for sensors. The basic idea is to shut down all sensors’ power when not needed and wake them up when necessary. Valuable conclusions are extracted and analyzed.

WSN Mobile Target Tracking Based on Improved Snake-Extended Kalman Filtering Algorithm

A wireless sensor network mobile target tracking algorithm(ISO-EKF)based on improved snake optimization algorithm(ISO)is proposed to address the difficulty of estimating initial values when using extended Kalman filtering to solve the state of nonlinear mobile target tracking.First,the steps of extended Kalman filtering(EKF)are introduced.Second,the ISO is used to adjust the parameters of the EKF in real time to adapt to the current motion state of the mobile target.Finally,the effectiveness of the algorithm is demonstrated through filtering and tracking using the constant velocity circular motion model(CM).Under the specified conditions,the position and velocity mean square error curves are compared among the snake optimizer(SO)-EKF algorithm,EKF algorithm,and the proposed algorithm.The comparison shows that the proposed algorithm reduces the root mean square error of position by 52%and 41%compared to the SOEKF algorithm and EKF algorithm,respectively.

Effective data transmission through energy-efficient clustering and Fuzzy-Based IDS routing approach in WSNs

Wireless sensor networks(WSN)gather information and sense information samples in a certain region and communicate these readings to a base station(BS).Energy efficiency is considered a major design issue in the WSNs,and can be addressed using clustering and routing techniques.Information is sent from the source to the BS via routing procedures.However,these routing protocols must ensure that packets are delivered securely,guaranteeing that neither adversaries nor unauthentic individuals have access to the sent information.Secure data transfer is intended to protect the data from illegal access,damage,or disruption.Thus,in the proposed model,secure data transmission is developed in an energy-effective manner.A low-energy adaptive clustering hierarchy(LEACH)is developed to efficiently transfer the data.For the intrusion detection systems(IDS),Fuzzy logic and artificial neural networks(ANNs)are proposed.Initially,the nodes were randomly placed in the network and initialized to gather information.To ensure fair energy dissipation between the nodes,LEACH randomly chooses cluster heads(CHs)and allocates this role to the various nodes based on a round-robin management mechanism.The intrusion-detection procedure was then utilized to determine whether intruders were present in the network.Within the WSN,a Fuzzy interference rule was utilized to distinguish the malicious nodes from legal nodes.Subsequently,an ANN was employed to distinguish the harmful nodes from suspicious nodes.The effectiveness of the proposed approach was validated using metrics that attained 97%accuracy,97%specificity,and 97%sensitivity of 95%.Thus,it was proved that the LEACH and Fuzzy-based IDS approaches are the best choices for securing data transmission in an energy-efficient manner.

改进猎人猎物优化算法在WSN覆盖中的应用

针对传统无线传感器网络(WSN)节点部署覆盖盲区大、分布不均等问题,提出一种改进的猎人猎物优化(IHPO)算法优化网络覆盖。首先,在猎物位置更新阶段,引入差分进化(DE)思想并借助动态比例因子进行交叉变异,从而增强种群信息交流;其次,在全局最优位置更新阶段,由α稳定分布提出自适应α变异对全局最优位置进行扰动,从而平衡不同时期算法的性能需求;最后,利用自适应α变异扰动的全局最优位置引导种群完成动态反向学习,从而增加种群的全局搜索能力和多样性。在WSN覆盖问题中,使用IHPO优化的网络节点分布更均匀、覆盖率更高,在传感器感知能力不足时能达到92.56%的覆盖率,对比原始HPO算法优化的节点提高了25.74%,对比改进粒子群优化(IPSO)算法、改进灰狼优化算法(IGWO)优化的节点分别提高了13.98%、16.41%。同时,IHPO算法优化的节点能耗更均衡,在路由测试中的网络工作时间可以延长至2500轮次。

Hybrid Marine Predators Optimization and Improved Particle Swarm Optimization-Based Optimal Cluster Routing in Wireless Sensor Networks(WSNs)

Wireless Sensor Networks(WSNs)play an indispensable role in the lives of human beings in the fields of environment monitoring,manufacturing,education,agriculture etc.,However,the batteries in the sensor node under deployment in an unattended or remote area cannot be replaced because of their wireless existence.In this context,several researchers have contributed diversified number of cluster-based routing schemes that concentrate on the objective of extending node survival time.However,there still exists a room for improvement in Cluster Head(CH)selection based on the integration of critical parameters.The meta-heuristic methods that concentrate on guaranteeing both CH selection and data transmission for improving optimal network performance are predominant.In this paper,a hybrid Marine Predators Optimization and Improved Particle Swarm Optimizationbased Optimal Cluster Routing(MPO-IPSO-OCR)is proposed for ensuring both efficient CH selection and data transmission.The robust characteristic of MPOA is used in optimized CH selection,while improved PSO is used for determining the optimized route to ensure sink mobility.In specific,a strategy of position update is included in the improved PSO for enhancing the global searching efficiency of MPOA.The high-speed ratio,unit speed rate and low speed rate strategy inherited by MPOA facilitate better exploitation by preventing solution from being struck into local optimality point.The simulation investigation and statistical results confirm that the proposed MPOIPSO-OCR is capable of improving the energy stability by 21.28%,prolonging network lifetime by 18.62%and offering maximum throughput by 16.79%when compared to the benchmarked cluster-based routing schemes.

基于WSN+UWB的室内人员定位系统设计

随着社会发展,家长对幼儿安全越来越重视,幼儿园环境安全与否直接关系到儿童的健康及生命。为保障园区内幼儿状况及安全,文章提出了一种室内人员定位系统设计,该系统在满足基本定位需求的同时,采用了超宽带(Ultra Wide Band,UWB)技术,具有穿透性强、抗干扰和功耗低等优势,其性能表现已超过蓝牙和Wi-Fi,并以UWB技术作为主要技术依据,将无线传感网络(Wireless Sensor Network,WSN)技术与UWB技术相结合,设计了一款智能化的人员看护及定位系统,测试结果证明了该系统设计可满足园区内人员监测及定位警报的需求。

基于IPSO-BP神经网络的WSNs数据融合算法

针对无线传感器网络(WSNs)数据融合算法中反向传播(BP)神经网络存在对初值敏感、收敛速度慢、易陷入局部最优解等问题,提出基于改进粒子群优化BP(IPSO-BP)神经网络的WSNs数据融合算法。首先,用细菌觅食算法的趋化、迁徙算子对粒子群优化(PSO)算法进行改进;然后,用IPSO算法优化BP神经网络的权值和阈值,再引入到WSNs数据融合中,簇成员节点负责采集监测数据,在簇首节点通过优化后的BP神经网络对数据进行特征提取,并将融合结果发送至汇聚节点。仿真结果表明:IPSO-BP算法能有效提高融合精度和收敛速度,减少冗余数据传输,延长网络生命周期。

基于WSN的流程行业安全生产数据多优先级多路径传输方法

为区分基于无线传感网络(wireless sensor network,WSN)的流程行业安全生产监测数据的优先级,保证关键安全生产决策数据的高质量、低时延传输,减少监测系统对生产事故的误判或漏判现象发生,通过建立实现多层级数据融合的分簇监测网络架构,划分流程安全生产过程中3个级别的数据类型,并提出数据多优先级多路径传输方法。研究结果表明:与传统基于WSN的传输方法相比,本文提出的基于WSN的流程行业安全生产数据多优先级多路径传输方法能够提升高优先级数据传输的及时性和可靠性,有利于安全生产的准确决策。研究结果可为基于WSN的流程行业安全生产监测提供参考。

Comparison of Energy Harvesting Systems for Wireless Sensor Networks

Wireless sensor networks (WSNs) offer an attractive solution to many environmental,security,and process monitoring problems.However,one barrier to their fuller adoption is the need to supply electrical power over extended periods of time without the need for dedicated wiring.Energy harvesting provides a potential solution to this problem in many applications.This paper reviews the characteristics and energy requirements of typical sensor network nodes,assesses a range of potential ambient energy sources,and outlines the characteristics of a wide range of energy conversion devices.It then proposes a method to compare these diverse sources and conversion mechanisms in terms of their normalised power density.

Chain-type wireless sensor network node scheduling strategy

In order to reduce power consumption of sensor nodes and extend network survival time in the wireless sensor network （WSN）, sensor nodes are scheduled in an active or dormant mode. A chain-type WSN is fundamental y different from other types of WSNs, in which the sensor nodes are deployed along elongated geographic areas and form a chain-type network topo-logy structure. This paper investigates the node scheduling prob-lem in the chain-type WSN. Firstly, a node dormant scheduling mode is analyzed theoretical y from geographic coverage, and then three neighboring nodes scheduling criteria are proposed. Sec-ondly, a hybrid coverage scheduling algorithm and dead areas are presented. Final y, node scheduling in mine tunnel WSN with uniform deployment （UD）, non-uniform deployment （NUD） and op-timal distribution point spacing （ODS） is simulated. The results show that the node scheduling with UD and NUD, especial y NUD, can effectively extend the network survival time. Therefore, a strat-egy of adding a few mobile nodes which activate the network in dead areas is proposed, which can further extend the network survival time by balancing the energy consumption of nodes.

Clustering routing algorithm of wireless sensor networks based on Bayesian game

To avoid uneven energy consuming in wireless sen- sor networks, a clustering routing model is proposed based on a Bayesian game. In the model, Harsanyi transformation is introduced to convert a static game of incomplete information to the static game of complete but imperfect information. In addition, the existence of Bayesian nash equilibrium is proved. A clustering routing algorithm is also designed according to the proposed model, both cluster head distribution and residual energy are considered in the design of the algorithm. Simulation results show that the algorithm can balance network load, save energy and prolong network lifetime effectively.

Optimal distributed resource allocation in a wireless sensor network for control systems

Wireless technology is applied increasingly in networked control systems. A new form of wireless network called wireless sensor network can bring control systems some advantages, such as flexibility and feasibility of network deployment at low costs, while it also raises some new challenges. First, the communication resources shared by all the control loops are limited. Second, the wireless and multi-hop character of sensor network makes the resources scheduling more difficult. Thus, how to effectively allocate the limited communication resources for those control loops is an important problem. In this paper, this problem is formulated as an optimal sampling frequency assignment problem, where the objective function is to maximize the utility of control systems, subject to channel capacity constraints. Then an iterative distributed algorithm based on local buffer information is proposed. Finally, the simulation results show that the proposed algorithm can effectively allocate the limited communication resource in a distributed way. It can achieve the optimal quality of the control system and adapt to the network load changes.

TDOA-based Sybil attack detection scheme for wireless sensor networks

As wireless sensor networks （WSN） are deployed in fire monitoring, object tracking applications, security emerges as a central requirement. A case that Sybil node illegitimately reports messages to the master node with multiple non-existent identities （ID） will cause harmful effects on decision-making or resource allocation in these applications. In this paper, we present an efficient and lightweight solution for Sybil attack detection based on the time difference of arrival （TDOA） between the source node and beacon nodes. This solution can detect the existence of Sybil attacks, and locate the Sybil nodes. We demonstrate efficiency of the solution through experiments. The experiments show that this solution can detect all Sybil attack cases without missing.