Enhanced Metaheuristics with Trust Aware Route Selection for Wireless Sensor Networks

Recently, a trust system was introduced to enhance security and cooperation between nodes in wireless sensor networks (WSN). In routing, the trust system includes or avoids nodes related to the estimated trust values in the routing function. This article introduces Enhanced Metaheuristics with Trust Aware Secure Route Selection Protocol (EMTA-SRSP) for WSN. The presented EMTA-SRSP technique majorly involves the optimal selection of routes in WSN. To accomplish this, the EMTA-SRSP technique involves the design of an oppositional Aquila optimization algorithm to choose safe routes for data communication. For the clustering process, the nodes with maximum residual energy will be considered cluster heads (CHs). In addition, the OAOA technique gets executed to choose optimal routes based on objective functions with multiple parameters such as energy, distance, and trust degree. The experimental validation of the EMTA-SRSP technique is tested, and the results exhibited a better performance of the EMTA-SRSP technique over other approaches.     

Blockchain Enabled Metaheuristic Cluster Based Routing Model for Wireless Networks

With recent advancements made in wireless communication techniques, wireless sensors have become an essential component in both data collection as well as tracking applications. Wireless Sensor Network (WSN) is an integral part of Internet of Things (IoT) and it encounters different kinds of security issues. Blockchain is designed as a game changer for highly secure and effective digital society. So, the current research paper focuses on the design of Metaheuristic-based Clustering with Routing Protocol for Blockchain-enabled WSN abbreviated as MCRP-BWSN. The proposed MCRP-BWSN technique aims at deriving a shared memory scheme using blockchain technology and determine the optimal paths to reach the destination in clustered WSN. In MCRP-BWSN technique, Chimp Optimization Algorithm (COA)-based clustering technique is designed to elect a proper set of Cluster Heads (CHs) and organize the selected clusters. In addition, Horse Optimization Algorithm (HOA)-based routing technique is also presented to optimally select the routes based on fitness function. Besides, HOA-based routing technique utilizes blockchain technology to avail the shared memory among nodes in the network. Sensor nodes are treated as coins whereas the ownership handles the sensor nodes and Base Station (BS). In order to validate the enhanced performance of the proposed MCRP-BWSN technique, a wide range of simulations was conducted and the results were examined under different measures. Based on the performance exhibited in simulation outcomes, the proposed MCRP-BWSN technique has been established as a promising candidate over other existing techniques.     

车联网环境下基于机会网络的可信路由模型

由于车联网中的节点多为快速移动的车辆,因此节点的移动性使得车联网网络拓扑的结构变得更加复杂,节点的分布范围变得更加广泛,恶意节点对路由的潜在威胁也逐渐增加.这些不确定因素都使车载节点间通讯的安全性与节点的空间信任值受到了的影响.本文主要研究的内容是构建出一种基于反馈节点信任度的信任评估模型,与经典的机会路由模型相结合,提出一个优于现有、且更适合目前车联网复杂多变的环境所需要的可信路由模型,进而提高节点间通信的安全性与准确性.仿真实验结果表明:各个路由模型的性能在不同预设值下差异明显.其中FB-SF模型在提高数据传输准确度的同时尽可能的提高了恶意节点检测比.     

一种多向链路感知的车载Ad Hoc网络传播协议

为了提高车辆自组织网络（Vehicular Ad Hoc Network,VANET）的数据传输效率,并使车辆间的数据通信能够持续进行,提出一种多向链路感知的车载Ad Hoc网络传播协议。为了保证车辆节点在执行通信任务的过程中实现数据的持续传输,防止通信链路频繁断连影响传输质量,提出了车辆网络的时间关联模型来讨论车辆间的速度差与通信持续时间的关系。为了缩短VANET中用于数据传输任务的总时间,协议基于改进蚁群的方法进行了多向链路感知,从而寻找在保证通信需求时间下的最短传输路径。实验结果分析表明,相比基于改进地理信息路由和基于优化链路状态路由的VANET数据传输算法,该算法的数据传输任务完工时间分别缩短了38.4%和27.3%,平均传输延迟分别降低了25.5%和12.1%。     

F-Ant: an effective routing protocol for ant colony optimization based on fuzzy logic in vehicular ad hoc networks

Vehicular ad hoc networks (VANETs) are a subset of mobile ad hoc networks that provide communication services between nearby vehicles and also between vehicles and roadside infrastructure. These networks improve road safety and accident prevention and provide entertainment for passengers of vehicles. Due to the characteristics of VANET such as self-organization, dynamic nature and fast-moving vehicles, routing in this network is a considerable challenge. Swarm intelligence algorithms (nature-inspired) such as ant colony optimization (ACO) have been proposed for developing routing protocols in VANETs. In this paper, we propose an enhanced framework for ACO protocol based on fuzzy logic for VANETs. To indicate the effectiveness and performance of our proposed protocol, the network simulator NS-2 is used for simulation. The simulation results demonstrate that our proposed protocol achieves high data packet delivery ratio and low end-to-end delay compared to traditional routing algorithms such as ACO and ad hoc on-demand distance vector (AODV).

     

An Optimized Novel Trust-Based Security Mechanism Using Elephant Herd Optimization

Routing strategies and security issues are the greatest challenges in Wireless Sensor Network (WSN). Cluster-based routing Low Energy adaptive Clustering Hierarchy (LEACH) decreases power consumption and increases network lifetime considerably. Securing WSN is a challenging issue faced by researchers. Trust systems are very helpful in detecting interfering nodes in WSN. Researchers have successfully applied Nature-inspired Metaheuristics Optimization Algorithms as a decision-making factor to derive an improved and effective solution for a real-time optimization problem. The metaheuristic Elephant Herding Optimizations (EHO) algorithm is formulated based on elephant herding in their clans. EHO considers two herding behaviors to solve and enhance optimization problem. Based on Elephant Herd Optimization, a trust-based security method is built in this work. The proposed routing selects routes to destination based on the trust values, thus, finding optimal secure routes for transmitting data. Experimental results have demonstrated the effectiveness of the proposed EHO based routing. The Average Packet Loss Rate of the proposed Trust Elephant Herd Optimization performs better by 35.42%, by 1.45%, and by 31.94% than LEACH, Elephant Herd Optimization, and Trust LEACH, respectively at Number of Nodes 3000. As the proposed routing is efficient in selecting secure routes, the average packet loss rate is significantly reduced, improving the network’s performance. It is also observed that the lifetime of the network is enhanced with the proposed Trust Elephant Herd Optimization.     

移动边缘计算环境下基于改进GPSR的VANET路由算法

针对车辆自组织网络(VANET,vehicular ad-hoc network)中现有路由协议存在的路由选择错误、丢包率较高、服务质量低等问题,提出了移动边缘计算环境下,结合改进贪婪周边无状态路由(GPSR,greedy perimeter stateless routing)和自适应链路质量评估的VANET路由算法;首先,结合边缘计算构建了VANET通信模型,对其车辆位置和速度进行系统的理论分析;将边缘计算架构应用于VANET能够有效缓解计算量大、与车辆有限且不均的资源分布之间的矛盾;然后,提出了基于节点移动速度和节点间距离的改进GPSR协议,通过自适应链路稳定性和链路传递速率评估来选择合适的中继节点,动态更新链路;通过SUMO仿真平台对路由算法的性能进行评估,实验结果表明,相对于其他算法,所提算法受车辆密度、交通流以及车辆相对速度的影响较小,且提高了分组传送率(车辆数为300时传送率达到92%),减少端到端延迟(交通流为5时延迟降低到1.5 s),从而降低了通信开销。     

Optimal phase searching of PTS using modified genetic algorithm for PAPR reduction in OFDM systems

In this paper,a novel genetic algorithm assisted partial transmit sequence(NGA-PTS)is proposed to reduce the peak-to-average power ratio(PAPR)of orthogonal frequency division multiplexing(OFDM).However,the search complexity of the optimum PTS(OPTS)scheme is too large for the typical number of sub-blocks.Therefore,some artificial intelligence methods,such as genetic algorithm technique,and particle swarm optimization,are introduced to reduce the complexity.As traditional GA-PTS(TGA-PTS)technique risks finding a suboptimal solution,how to avoid this disadvantage of TGA-PTS is an interest topic.In order to obtain a better suboptimal solution,a phase factor optimal pair technique and an abandon/introduction new chromosome technique are proposed in GA here.Simulation results show that the proposed scheme achieves a significant improvement over the TGA-PTS scheme in PAPR.Furthermore,by use of the inherent diversity of constellation for each OFDM candidate,in the receiver part,the proposed scheme enables data recovery without any side information.Simulation results show the efficiency of the proposed scheme.     

基于车载自组网通信终端和运动信息的容忍时延网络分簇路由算法

针对复杂战场环境下用户终端间缺少稳定的端到端通信路径的问题,提出一种基于车载自组网（VANET）通信终端和运动信息的容忍时延网络（DTN）分簇路由算法——CVCTM。首先,完成了基于簇头选举的分簇算法研究;然后,根据跳数、转发方式和地理位置信息开展了簇内源车辆路由选择算法研究;其次,通过引入等待时间、重发次数阈值和下游簇头,实现了异簇间源车辆路由选择;最后,通过车载自组网的通信终端选择与上级指挥所通信的最佳方式。ONE仿真的实验结果表明,CVCTM与无线自组网按需平面距离向量路由协议（AODV）相比,消息投递率增加了近5%,网络开销减少了近10%,簇结构重组次数减少了近25%;与基于传统分簇路由（CBRP）算法和动态源路由（DSR）协议相比,消息投递率增加了近10%,网络开销减少了近25%,簇结构重组次数减少了近40%。CVCTM能够有效减少网络开销和簇结构重组次数,同时增加消息投递率。     

VANET中基于WSN节点感知的高效路由协议设计方案

在车载自组网(VANET)中,当网络密度较低时,VANETs不能保证及时发现危险的路况或保持通信连通性,这可能对驾驶安全构成风险。为解决该问题,提出一种VANET中基于WSN节点感知的高效路由协议设计方案。该方案将VANET和WSN相结合,使用WSN节点沿着路边部署,以感知道路状况,并向车辆传递关于危险状况的信息,忽略VANET的密度和连通性。同时根据VANET中常用的被动式带宽估算方法,提出一种基于CORNER传播模型的带宽评估策略,实现链路可用带宽和信道容量的准确估计。仿真结果表明,该路由协议可以减少端到端延迟和能耗,合理地利用有限的网络带宽资源,减少丢包率。     

ALCA: agent learning–based clustering algorithm in vehicular ad hoc networks

Vehicular ad hoc network (VANET) is an emerging technology which can be used in various applications such as intelligent transport technology, safety applications, etc. But one of the major issues in VANETs is how to cluster the vehicles on the road for efficient operations such as routing, mobility management and generating safety alarms. Clustering of vehicles has been widely used for routing and data dissemination in VANETs. But due to the high mobility of the vehicles/nodes on the road, it is quite difficult to find the exact route in VANETs. Keeping in view of the above issue, in this paper, we propose a new agent learning–based clustering and routing in VANETs. Agents learn from the environment in which they are deployed, and accordingly, their action performed is rewarded or penalized with certain values. Each agent performs its task in collaboration with the other agents, i.e. agents communicate with each other in collaborative manner for information sharing. The deployed agents estimate the mobility of the vehicles, and based upon their learning, clustering of vehicles is performed. An Agent Learning–based Algorithm for Clustering is proposed. The performance of the proposed scheme is evaluated using extensive simulation with respect to the various metrics such as message transmission ratio, percentage of connectivity, node participation, cluster head duration, and connectivity preservation ratio. The results obtained show that the proposed scheme is effective in performing fast clustering and converges quickly to the final solution.     

An energy-efficient geographic routing protocol design in vehicular ad-hoc network

The combination of vehicles and wireless communication has resulted in a promising future for vehicular ad hoc networks (VANETs). The VANET is a kind of network that can be built randomly, quickly and temporarily without any infrastructure. The routing of data in a VANET is a challenging task due to the high dynamics, unstable connection environments and transfer direction limit (real road planning) involved. However, it has been discussed that radio obstacles, as found in urban areas, have a significant negative impact on the performance of location based routing. Therefore, the design of a suitable routing protocol for VANETs is an important issue, especially in regard to inter-vehicle communication applications. This paper proposes a energy-efficient geographic routing algorithm that uses the direction, density and distance between nodes in the crossroad routing strategy, to improve the link stability. We compare the novel scheme, ad hoc on-demand distance vector, and dynamic source routing (DSR) for packet loss rate and average end-to-end delay in VANETs to reduce the power consumptions. The simulation results are obtained which demonstrate the power effectiveness of our proposed routing strategy.     

基于区块链的车联网安全通信策略

为完善车联网信任评估机制并建立车辆间的信任关系,提出一种基于区块链技术的车联网安全通信策略。利用椭圆曲线加密算法进行车辆身份注册与验证,结合基于Beta分布的直接信任值与基于PageRank算法的推荐信任值求得车辆综合信任值。通过智能合约技术对车辆综合信任值及交互信息进行管控,实现车辆综合信任值的上链、更改与更新。仿真结果表明,该策略能够有效抵御车联网内部与外部攻击,保证数据传输的安全性,且满足车联网车辆在高速移动环境下的高吞吐量及低时延通信需求。     

VANET路由协议与安全问题分析

随着车载自主式网络（VANET）的快速发展,VANET涉及的技术与安全问题成为行业研究的热点。车载自主式网络是没有固定框架的多跳式网络,它包含互相通信的交通工具和路边基础设施。为VANET设计一个有效的路由协议成为VANET研究的难点。讨论不同的路由协议和面临的安全问题。     

Profile based routing in vehicular ad-hoc networks

One of the main problems in the VANET(vehicular ad-hoc network)routing algorithms is how to establish the stable routes.The link duration in these networks is often very short because of the frequent changes in the network topology.Short link duration reduce the network efficiency.Different speeds of the vehicles and choosing different directions by the vehicles in the junctions are the two reasons that lead to link breakage and a reduction in link duration.Several routing protocols have been proposed for VANET in order to improve the link duration,while none of them avoids the link breakages caused by the second reason.In this paper,a new method for routing algorithms is proposed based on the vehicles trips history.Here,each vehicle has a profile containing its movement patterns extracted from its trips history.The next direction which each vehicle may choose at the next junction is predicted using this profile and is sent to other vehicles.Afterward each vehicle selects a node the future direction of which is the same as its predicted direction.Our case study indicates that applying our proposed method to ROMSGP(receive on most stable group-path)routing protocol reduces the links breakages and increases the link duration time.     

LESPP: lightweight and efficient strong privacy preserving authentication scheme for secure VANET communication

Authentication in vehicular ad-hoc network (VANET) is still a research challenge, as it requires not only secure and efficient authentication, but also privacy preservation. In this paper, we proposed a lightweight and efficient authentication scheme (LESPP) with strong privacy preservation for secure VANET communication. The proposed scheme utilizes self-generated pseudo identity to guarantee both privacy preservation and conditional traceability, and it only requires a lightweight symmetric encryption and message authentication code (MAC) generation for message signing and a fast MAC re-generation for verification. Compared with currently existing public key based schemes, the proposed scheme significantly reduces computation cost by \(10^2\)–\(10^3\) times and decreases communication overhead by 41.33–77.60 %, thus achieving resilience to denial of service (DoS) attack. In LESPP, only key management center can expose a vehicle’s real identity from its pseudo identity, therefore, LESPP provides strong privacy preservation so that the adversaries cannot trace any vehicles, even if all roadside units are compromised. Furthermore, vehicles in LESPP need not maintain certificate revocation list (CRL), so any CRL related overhead is avoided. Extensive simulations reveal that the novel scheme is feasible and has an outstanding performance of nearly 0 ms network delay and 0 % packet loss ratio, which are especially appropriate for realtime emergency event reporting applications.     

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.     

A routing protocol for vehicular ad hoc networks using simulated annealing algorithm and neural networks

Vehicular ad hoc network (VANET) is special type of mobile ad hoc networks which establish communications between adjacent vehicles and also between vehicles and roadside units. Thanks to their dynamic and fast topology changes, inter-vehicular ad hoc networks are like dynamic networks without organizations. Hence, developing a reliable routing algorithm is regarded as a notable challenge in these networks. In this paper, a clustering-based reliable routing algorithm was proposed for VANETs with reliable applications. In this way, simulated annealing was used for appropriate clustering of nodes and the parameters of node degree, coverage and ability were considered in the proposed method. For selecting cluster head, radial basis function neural network was used and a suitable fitness function with velocity and free buffer size parameters was used. Each cluster has two gateway nodes which are used as the communication interface for transmitting data from one cluster to another cluster. The simulation results indicated the efficiency of the proposed method in terms of route discovery rate and packet delivery rate.     

Secure clustering and routing for heterogeneous mobile wireless sensor networks with dynamic key management

In mobile wireless sensor networks, the process of offering security to the network after computing dynamic key may result in misuse of information by malicious node. All the messages exchanged during the inter-cluster routing also need to be protected by providing integrity and confidentiality. The proposed architecture includes heterogeneous backbone nodes (BNs) deployed in the network using particle swarm optimisation technique. They perform secure clustering process using exclusion basis system. The cluster head is chosen based on weight value that is estimated using parameters such as the node degree (ND), distance to BN, node velocity and virtual battery power. Once the clusters are formed, the cluster members estimate the cost value based on location, ND and virtual battery power. This cost value is used by the member nodes to calculate the dynamic key for its data communication. Since the parameters used for clustering are further used during dynamic key generation, security has to be provided to the clustering phase. When the node moves from one cluster to another, secure cluster maintenance is performed and when the data need to be transmitted from source to sink, secure route discovery is executed within the clusters. By simulation results, we show that the proposed technique is more secured and minimises the communication and storage overhead.     

Internet of Things Enabled Energy Aware Metaheuristic Clustering for Real Time Disaster Management

Wireless Sensor Networks (WSNs) are a major element of Internet of Things (IoT) networks which offer seamless sensing and wireless connectivity. Disaster management in smart cities can be considered as a safety critical application. Therefore, it becomes essential in ensuring network accessibility by improving the lifetime of IoT assisted WSN. Clustering and multihop routing are considered beneficial solutions to accomplish energy efficiency in IoT networks. This article designs an IoT enabled energy aware metaheuristic clustering with routing protocol for real time disaster management (EAMCR-RTDM). The proposed EAMCR-RTDM technique mainly intends to manage the energy utilization of nodes with the consideration of the features of the disaster region. To achieve this, EAMCR-RTDM technique primarily designs a yellow saddle goatfish based clustering (YSGF-C) technique to elect cluster heads (CHs) and organize clusters. In addition, enhanced cockroach swarm optimization (ECSO) based multihop routing (ECSO-MHR) approach was derived for optimal route selection. The YSGF-C and ECSO-MHR techniques compute fitness functions using different input variables for achieving improved energy efficiency and network lifetime. The design of YSGF-C and ECSO-MHR techniques for disaster management in IoT networks shows the novelty of the work. For examining the improved outcomes of the EAMCR-RTDM system, a wide range of simulations were performed and the extensive results are assessed in terms of different measures. The comparative outcomes highlighted the enhanced outcomes of the EAMCR-RTDM algorithm over the existing approaches.