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For instance, wireless multimedia sensor networks, mobile wireless sensor networks, wireless underwater sensor networks, wireless underground sensor networks, and wireless sensor-actuator networks are being explored to extend WSNs for supporting rich-media sensing, mobile sensing, underwater/underground sensing, and closed-loop sensing and control. CWSN2012 serves as a forum for sensor network researchers, developers, and users to communicate the productions and experience of sensor network research and applications. The paper " I An adaptive opportunistic network coding mechanism in wireless multimedia sensor networks i " proposed an adaptive opportunistic network coding mechanism (AONC) to improve video communication performance in wireless multimedia sensor networks. [Extracted from the article]

Wireless ad hoc/sensor networks (WASN) have seen increased application in three-dimensional (3D) environments, such as underwater and aerial scenarios. However, WASN may be fragmented or unable to connect continuously due to the harsh surrounding environment or high mobility. Therefore, restoring the network connectivity and transmit data in real time is very important. This paper focuses on the critical task of restoring network connectivity in 3D WASN, a complex issue given that existing connectivity restoration algorithms for two-dimensional environments are not directly applicable or become overly complicated in 3D contexts. We present a comprehensive analysis of the current research landscape, summarizing key findings related to various aspects of 3D WASN connectivity restoration. These aspects include the application environment (underwater, in the sky, and recovery disaster), opportunities for restoration (active, passive, and active/passive), implementation strategies (clustering and sleep scheduling), and resource constraints (node deployment and movement control). Our study also proposes a classification of connectivity restoration solutions for 3D WASN, identifying existing gaps and suggesting potential future research directions. By providing specific insights and a structured overview of the field, we aim to contribute to the ongoing development of robust and resilient 3D WASN. [ABSTRACT FROM AUTHOR]

This paper introduces the development status of machine vision nondestructive testing technology and industrial IoT supervision mechanism. The study designs and implements a machine vision nondestructive testing system from two aspects: construction of industrial IoT supervision and detection model, and optimization of machine vision nondestructive testing algorithm. In this paper, the random deployment of dynamic and static nodes is adopted. The coverage rate after random deployment and the moving distance of dynamic nodes are two necessary research parameters. To improve the initial coverage and optimize the mobile path of dynamic nodes, this paper proposes a mobile deployment optimization scheme based on the supervisory mechanism model of industrial IoT, which improves the traversal of the quantum genetic algorithm by improving the genetic variation rules, thus improving the initial deployment of the network. The optimized machine vision nondestructive detection algorithm is used for mobile path optimization from dynamic nodes to target locations. Simulation results show that a random deployment of 100 static nodes and 20 dynamic nodes in a 400 m × 400 m factory area works best with a coverage rate of 6.719% and an average movement distance of 23.47 m, and the movement path avoids the obstacle area. The average accuracy of the modified machine vision nondestructive testing system is 1.59% higher than that before the modification, and the average detection accuracy of the final experiment reaches 95.46%. Not only is the coverage rate better than that of the cellular structure-based dynamic node optimization scheme, but also the monitoring range of the plant tends to be more comprehensive in the actual deployment environment. Through the analysis of test results, the system achieves the monitoring and display of data on the one hand and provides a natural information access and interaction experience for IoT managers on the other hand, which meets the requirements of real time, accuracy, and stability of industrial IoT information data to a certain extent. [ABSTRACT FROM AUTHOR]

One such problem is how to select an effective ML algorithm when there are a number of ML algorithms for a cyber-attack detection system for IoT security. Recently, the IoT security research community has endeavoured to build anomaly, intrusion, and cyber-attack traffic identification models using machine learning algorithms for IoT security analysis. Identifying attack traffic is very important for the security of Internet of Things (IoT) in smart cities by using machine learning (ML) algorithms. [Extracted from the article]

This paper establishes a unified perception information transmission model for the difference in the number of cognitive radio users in wireless communication network systems. The model can effectively improve the utilization of spectrum resources. At the same time, this paper introduces a cyclic delay full diversity sensing information coding transmission scheme for the security risks of wireless communication networks. We established a system simulation model to compare performance under different correlation coefficients. The study found that the total interference intensity in the cyclic delay diversity system is lower than that of the frequency division duplex and time division duplex. Its antijamming attack capability also becomes stronger accordingly. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has affected people's lives in all aspects. This pandemic has raised the usage of ubiquitous networks such as mobile ad hoc networks (MANETs) for information exchange in various domains. MANET is a group of versatile nodes that communicates with each other without relying on a fixed physical framework. One of the prominent features of MANET is its versatile topology. Because of this striking feature, MANETs are employed in various domains like defense and combat operations, disaster management, healthcare, and environmental monitoring. In this paper, we enlighten the significance of MANET in the smart healthcare system. The COVID-19 pandemic outbreak demanded the reshaping of the healthcare systems to combat the pandemic and similar cataclysms. Existing healthcare systems are proved inefficient in dealing with pandemic situations, because they are not fully automated and also vulnerable to various security attacks. Therefore, it is vital to empower the healthcare sectors by integrating ubiquitous networks and other emerging technologies. In this paper, we proposed a MANET-based secure healthcare system to exchange medical data among portable nodes. Ensuring secure communication in the MANET-based healthcare system is one of the challenging issues. Healthcare system demands the sharing of confidential medical data among mobile nodes. So it is essential to provide secure information exchange in healthcare system by using strong cryptographic schemes. In this paper, we proposed a hybrid cryptographic algorithm for secure medical information exchange among mobile healthcare nodes. The proposed cryptographic scheme uses logistic map for key generation. Logistic map exhibits high security with less computational power. Our simulation results show that the proposed hybrid cryptographic scheme exhibits better security against various attacks in MANET-based healthcare systems. [ABSTRACT FROM AUTHOR]

Since the low cost and high flexibility, wireless automatic meter reading network (WAMRN) is widely used by utility companies to realize automatic collection and transmission of remote energy consumption information. Considering that WAMRN is composed of several wireless communication nodes, the lifetime of the network will be affected by factors such as the changeable deployment environment and the limited energy of nodes. Thus, a novel niche quantum ant colony-based WAMRN clustering optimization method is proposed in this paper to address the problem of how to make full use of the limited energy to extend network lifetime and improve data transmission efficiency. In the proposed approach, a clustering model of WAMRN is defined; moreover, an improved Niche Quantum Ant Colony Optimization (NQACO) is proposed to optimize the model therefore to obtain an optimal clustering scheme, which can help WAMRN reduce unnecessary energy loss to achieve the purpose of extending the lifetime of the entire network. To verify the performance of the proposed method, NQACO is compared with some popular clustering methods, i.e., GA and SA, under different scenarios. The results show that under the premise of ensuring network communication, NQACO is superior to the other two methods in reducing the total energy consumption and prolonging the network lifetime. [ABSTRACT FROM AUTHOR]

The vehicular ad hoc network (VANET) has traditional routing protocols that evolved from mobile ad hoc networks (MANET). The standard routing protocols of VANET are geocast, topology, broadcast, geographic, and cluster-based routing protocols. They have their limitations and are not suitable for all types of VANET traffic scenarios. Hence, metaheuristics algorithms like evolutionary, trajectory, nature-inspired, and ancient-inspired algorithms can be integrated with standard routing algorithms of VANET to achieve optimized routing performance results in desired VANET traffic scenarios. This paper proposes integrating genetic algorithm (GA) in ant colony optimization (ACO) technique (GAACO) for an optimized routing algorithm in three different realistic VANET network traffic scenarios. The paper compares the traditional VANET routing algorithm along with the metaheuristics approaches and also discusses the VANET simulation scenario for experimental purposes. The implementation of the proposed approach is tested on the open-source network and traffic simulation tools to verify the results. The three different traffic scenarios were deployed on Simulation of Urban Mobility (SUMO) and tested using NS3.2. After comparing them, the results were satisfactory and it is found that the GAACO algorithm has performed better in all three different traffic scenarios. The realistic traffic network scenarios are taken from Dehradun City with four performance metric parameters including the average throughput, packet delivery ratio, end-to-end delay, and packet loss in a network. The experimental results conclude that the proposed GAACO algorithm outperforms particle swarm intelligence (PSO), ACO, and Ad-hoc on Demand Distance Vector Routing (AODV) routing protocols with an average significant value of 1.55%, 1.45%, and 1.23% in three different VANET network scenarios. [ABSTRACT FROM AUTHOR]

With the rapid deployment of 5G networks in recent years, the characteristics of high bandwidth, low latency, and low energy consumption of 5G networks have enabled the rapid development of IoT (Internet of things) technology. However, 5G networks cannot provide high-quality wireless coverage for many IoT devices in border areas and hotspots with a high signal density that lack fixed infrastructure. Therefore, this paper uses the UAV (unmanned aerial vehicle) to carry the communication platform to build the NTN (nonterrestrial network) to provide wireless coverage for terrestrial fixed and mobile IoT devices. Meanwhile, since the NTN needs to provide wireless coverage for many IoT devices, we use deep reinforcement learning to provide path planning for the UAV communication platform to improve the efficiency of wireless coverage. We build a simulation environment to evaluate the performance of the NTN network for wireless coverage of IoT devices in urban hotspot areas. Experimental results show that the method proposed in this paper can provide higher downlink rates for more IoT devices than NB-IoT (narrowband Internet of things). [ABSTRACT FROM AUTHOR]

Detecting 3D objects in a crowd remains a challenging problem since the cars and pedestrians often gather together and occlude each other in the real world. The Pointpillar is the leader in 3D object detection, its detection process is simple, and the detection speed is fast. Due to the use of maxpooling in the Voxel Feature Encode (VFE) stage to extract global features, the fine-grained features will disappear, resulting in insufficient feature expression ability in the feature pyramid network (FPN) stage, so the object detection of small targets is not accurate enough. This paper proposes to improve the detection effect of networks in complex environments by integrating attention mechanisms and the Pointpillar. In the VFE stage of the model, the mixed-attention module (HA) was added to retain the spatial structure information of the point cloud to the greatest extent from the three perspectives: local space, global space, and points. The Convolutional Block Attention Module (CBAM) was embedded in FPN to mine the deep information of pseudoimages. The experiments based on the KITTI dataset demonstrated our method had better performance than other state-of-the-art single-stage algorithms. Compared with another model, in crowd scenes, the mean average precision (mAP) under the bird's-eye view (BEV) detection benchmark increased from 59.20% of Pointpillar and 66.19% of TANet to 69.91 of ours, the mAP under the 3D detection benchmark was increased from 62% of TANet to 65.11% of ours, and the detection speed only dropped from 13.1 fps of Pointpillar to 12.8 fps of ours. [ABSTRACT FROM AUTHOR]

Artificial intelligence has recently been used in FANET-based routing strategies for decision-making, which is a unique paradigm. For effective communication in flying vehicles that use routing protocols to accomplish tasks collectively, aerial vehicles are used in both civic and military applications. Aerial ad hoc networks are wirelessly connected, and designing routing schemes is difficult due to the rapid mobility. Ground base stations and satellites are frequently used to interconnect UAV ad hoc networks. This paper developed a novel routing protocol with a focus on ant behavior routing, which assists in end-to-end security. For the first time in flying networks, the column mobility model is used to evaluate the performance of routing protocols. While merging with aerial ad hoc networks, AI-based networking is a relatively new field. In simulation results, AntHocNet shows better results in comparison with other contemporary routing algorithms. Pheromone update process is used for data encryption in AntHocNet. This research study is performed on network simulator-2. [ABSTRACT FROM AUTHOR]

For the severe impact of limited energy and network attacks caused by open transmission channels on data transmission, this paper presents a low-power and secure multihop routing mechanism based on the Markov state transition theory. The random selection of transmission paths enables the network to resist typical attacks such as interference and interception, thus ensuring the security of data transmission. Meanwhile, the proposed algorithm can reduce the overall energy consumption of the network and balance the load according to the residual energy of each path. Simulation results prove that the routing mechanism proposed in this paper can improve the energy efficiency and the security of the wireless ad hoc network. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) and cloud computing are well developed and applied in different services. Among these services, some of them take latency and overhead as the metrics to evaluate the quality of services. This paper introduces how an opportunistic routing (OR) protocol reduces latency and overhead when it is applied in wireless sensor network (WSN) application among lightweight devices. OR mitigates the delay problem and balances the energy consumption and delay of the nodes in WSNs. However, OR, with the nature of broadcasting, can easily cause heavy overhead such as redundant data and control packets in the forwarding process. In the current solution, the number of candidates (potential forwarders) is not limited by the dynamics of forwarding process. Also, the overhead of establishing the candidate sets is high due to global information calculation. Therefore, a low-delay OR protocol with reducing overhead which designs the dynamic candidate area (DCA) to establish candidate sets is first proposed in this paper. The main work is as follows. (a) The duty cycle of a node is adjusted according to the distance between the node and sink node in the initialized network. (b) A method to establish dynamic candidate sets is proposed based on the adaptive duty cycle. Before and during the forwarding process, the dynamic candidate area is adjusted in time. (c) According to the feature of the candidate area, the corresponding routing metric is proposed to complete the cooperative communication among candidates. Through further theoretical analysis and simulations, the results indicate that this protocol achieves better performance in terms of transmission delay, data and control overhead, and network lifetime compared to the state-of-the-art solutions. [ABSTRACT FROM AUTHOR]

Smart home is a building, network, communication, automation, set management, and service, as one of the efficient, comfortable, safe, and environmental protection of the living environment, and can provide personalized living space according to the needs of different users. Due to the advantages of wireless sensor network (WSN), such as strong expansion ability, strong communication ability, and strong self-organization ability, the smart home system based on WSN has become the main development direction in the field of smart home. This paper analyzes the different functions and features of wireless sensor network routing protocol and use scope, aiming at the application layer, using the MQ queue enhance server concurrent processing capacity and system scalability and design based on application layer gateway and terminal node "data matching list," which are introduced in the design of smart home system based on geographic information location energy-efficient routing protocols. The solution of routing void problem is improved by using information feedback mechanism and alternate nodes. Simulation results show that this method can improve the energy saving of energy-efficient routing protocol. Finally, the intelligent home system experiment platform was built to verify the overall function of the system, and the communication function of the WiFi network and ZigBee network was tested. Based on the analysis of the interference between ZigBee and WiFi network, frequency agility algorithm is used to solve the problem of the same frequency interference, so as to ensure the performance of the system to meet the needs of the smart home system. [ABSTRACT FROM AUTHOR]

Currently, many methods are available to improve the target network’s security. The vast majority of them cannot obtain an optimal attack path and interdict it dynamically and conveniently. Almost all defense strategies aim to repair known vulnerabilities or limit services in target network to improve security of network. These methods cannot response to the attacks in real-time because sometimes they need to wait for manufacturers releasing corresponding countermeasures to repair vulnerabilities. In this paper, we propose an improved Q-learning algorithm to plan an optimal attack path directly and automatically. Based on this path, we use software-defined network (SDN) to adjust routing paths and create hidden forwarding paths dynamically to filter vicious attack requests. Compared to other machine learning algorithms, Q-learning only needs to input the target state to its agents, which can avoid early complex training process. We improve Q-learning algorithm in two aspects. First, a reward function based on the weights of hosts and attack success rates of vulnerabilities is proposed, which can adapt to different network topologies precisely. Second, we remove the actions and merge them into every state that reduces complexity from O(N3) to O(N2). In experiments, after deploying hidden forwarding paths, the security of target network is boosted significantly without having to repair network vulnerabilities immediately. [ABSTRACT FROM AUTHOR]

This paper describes a parameterized approach to the Ad Hoc On-Demand Distance Vector (AODV) routing protocol using a network-simulator 2 (ns2). By utilizing two AODV’s protocol functions, which are HELLO messages and local route repair, we explore the more flexible approach on these two important functions, rather than a fixed setting within the default AODV protocol. HELLO message is used to detect the broken link, while the local route repair in AODV is used to fix and discover alternative routes in the event of route failure. In this paper, two functions to optimize AODV performance have been utilized. The first is link break detection time (Llb), using the HELLO message to detect link failure, and the second is link break position parameter (Lbp) for AODV’s local route repair. The results show that the default AODV setting does not yield the best results for most defined network scenarios. In some cases, improvement compared to the default setting can be as high as 38%, for local route repair strategies. This paper presents a potential flexible and parameterized approach for dealing with link breaks and route repairing strategies for AODV protocol. [ABSTRACT FROM AUTHOR]

The wide range of social hot news events on the Internet has made the Internet have a great impact on the public. However, there are few studies on Internet information. In order to improve the efficiency of user network information dissemination of Internet information based on complex network theory and model simulation, this paper makes a more in-depth study on information dissemination on the Internet, constructs a complex network of Internet information dissemination, and analyzes the static topology and dynamic evolution process of the network. Using the attention relationship between Internet users, the Internet information dissemination network, degree, and path were used to select multiple indicators. The static topology of the network is analyzed by using the complex network theory. The study found that the complex network of Internet information is different from other complex networks. The influencing factors of network dynamic evolution are studied from three aspects: overall structure, local structure, and time constraints. The evolution trend of different forms and overall network nodes in the evolution process was explored, and the network dynamic evolution process model was constructed. Practice shows that the model can better describe the evolution process of network information dissemination in complex networks. The degree values of the two networks are positively correlated with the corresponding average clustering coefficients, and the networks have a significant hierarchy. The correlation between news hot events and network nodes is not as good as users' attention to the network. [ABSTRACT FROM AUTHOR]

For the sensing layer of the Internet of Things, the mobile wireless sensor network has problems such as limited energy of the sensor nodes, unbalanced energy consumption, unreliability, and long transmission delay in the data collection process. It is proved by mathematical derivation and theory that this is a typical multiobjective optimization problem. In this paper, the optimization goal is to minimize the energy consumption and improve the reliability under time-delay constraints and propose a path optimization mechanism to optimize the mobile Sink of mobile wireless sensor networks based on the improved dragonfly optimization algorithm. The algorithm takes full advantage of the abundant storage space, sufficient energy, and strong computing power of the mobile Sink to ensure network connectivity and improve network communication efficiency. Through simulation comparison and analysis, compared with random movement method, artificial bee colony algorithm, and basic dragonfly optimization algorithm, the energy consumption of the network is reduced, the lifespan of the network is increased, and the connectivity and transmission delay of the network are improved. The proposed algorithm balances the energy consumption of the sensors nodes to meet the network service quality and improve the reliability of the network. [ABSTRACT FROM AUTHOR]

The energy problem and limited capacity of batteries have been fundamental constraints in many wireless sensor network (WSN) applications. For WSN, the wireless energy transmission technology based on magnetic resonance coupling is a promising energy transmission technology. To reduce the cost and energy consumption during charging in mobile wireless rechargeable sensor networks (MWRSNs), a cooperative mobile charging mechanism based on the Hamiltonian path is proposed in this paper. To improve the charging task interval, we study the use of a mobile charger (MC) as a mobile sink node to collect the data in this paper. Then, we used the sink and the charging sensors selected by the MC to construct the undirected complete graph. Finally, the Euclidean distance between nodes is used as the edge weight and a Hamiltonian loop is found by using the improved Clark–Wright (C-W) saving algorithm to solve the problem of charging a rechargeable sensor network. In addition to the energy usage efficiency (EUE) and the network lifetime, the average energy loss per unit time is considered as the evaluation index according to the impact of the MC on the energy consumption during charging. The simulation results show that the proposed scheme increases the average network lifetime, decreases the average energy loss per unit time, and improves the EUE. [ABSTRACT FROM AUTHOR]

Mobile ad hoc networks (MANETs) have rapidly expanded in recent years, mostly as a result of the mobile devices' obvious low cost, heterogeneity, and flexibility. When communication networks are down or inaccessible, sensors can quickly create a reliable network that can be used as a rescue data system. Industrial mobile communication has developed into a significant study area for both industry and academia in recent years. The need for data interchange between various smart devices with various latency flows is enormous. Nevertheless, there has not been as much research done in this area. The suggested work suggests a fuzzy-based improved PSO optimized in MANET to alleviate the drawbacks of the conventional routing approach. The suggested study offers a numerical modelling that can be used to carry out adaptive transmission optimization with a variety of programmable module structures and guarantee cost-effective route establishment with greater throughput, goodput, and lowest delay requirements. To find the best route, the proposed approach combines energy-optimized route construction with data-driven cluster head (CH) selection based on swarm intelligence. Particle swarm optimization- (PSO-) based clustering achieves improved delay, goodput, throughput, and path difference degree as compared to other conventional approaches, according to the extensive simulation results. The energy efficiency of a network that is decentralized is more important. The MANET device's energy efficiency helps to extend battery life and improve network performance. This research demonstrates how the fuzzy-based improved PSO optimized in MANET helps to raise the network's energy efficiency. As a result, network energy conservation improves network performance and battery life. Additionally, this method enhances the quality of service methodology. End-to-end delay, energy consumption, packet delivery ratio, and normalized routing overhead are measured and compared between the simulation and conventional routing protocols. [ABSTRACT FROM AUTHOR]

The vehicle-mounted self-organizing network is a part of the MANET network. It is placed between the roadside vehicle and the fixed communication equipment. It can serve as a hub for road vehicles and can enable multihorsepower wireless mechanisms to exchange data between vehicles. This article is aimed at studying the DTN routing protocol based on machine learning in the vehicle self-organizing network. When data is forwarded, the node will determine the forwarding route selection according to its own coordinate information, the coordinate information of neighboring nodes, and the coordinate information of the destination node. Usually, the purpose is for the geographic coordinates of the node to be stored in the data packet. And data packets are periodically transmitted between nodes on each network. So that when you publish your own coordinate nodes, you can update the location information of nearby nodes at any time. This paper proposes that routing technology has become one of the most important challenges in vehicle self-organization, and there are many reasons for this. These reasons include frequent changes in the network topology and fast-moving mobile nodes. The experimental results in this paper show that more than 67% of the network data is obtained through the Gawk data extraction tool to quantify GPSR performance indicators and obtain the average driving speed of the current vehicle node. When increasing, the average end-to-end transmission delay of the GPSR routing protocol increases, and the average transmission rate decreases. [ABSTRACT FROM AUTHOR]

The Internet of Things allows vehicles to communicate with their surroundings and send various traffic and road conditions to other vehicles, making driving better. Data received from other vehicles sometimes need to be processed. In this state, the data should be sent to the Roadside unit for processing and fog if necessary. The source and destination must know each other's identities to send and receive information, and various attacks can threaten source and destination authentication. The paper presents secure authentication scheme based on fog-cloud for the Internet of Vehicles. Formal and informal security analyses verify that the SAIFC demonstrates resistance to famous attacks. The SAIFC is compared with another scheme regarding security features, computing, and communication costs. The SAIFC simulated with the NS3 tool and compared several routing protocols in packet loss, packet delivery, end-to-end delay, throughput, and MAC/PHY overhead. [ABSTRACT FROM AUTHOR]

IPv6 routing protocol for low-power and lossy networks (RPL) has been developed as a routing agent in low-power and lossy networks (LLN), where nodes' resource constraint nature is challenging. This protocol operates at the network layer and can create routing and optimally distribute routing information between nodes. RPL is a low-power, high-throughput IPv6 routing protocol that uses distance vectors. Each sensor-to-wire network router has a collection of fixed parents and a preferred parent on the path to the Destination-oriented directed acyclic graph (DODAG) graph's root in steady-state. Each router part of the graph sends DODAG information object (DIO) control messages and specifies its rank within the graph, indicating its position within the network relative to the root. When a node receives a DIO message, it determines its network rank, which must be higher than all its parents' rank, and then continues sending DIO messages using the trickle timer. As a result, DODAG begins at the root and eventually extends to encompass the whole network. This paper is the first review to study intrusion detection systems in the RPL protocol based on machine learning (ML) techniques to the best of our knowledge. The complexity of the new attack models identified for RPL and the efficiency of ML in intelligent and collaborative threats detection, and the issues of deploying ML in challenging LLN environments underscore the importance of research in this area. The analysis is done using research sources of "Google Scholar," "Crossref," "Scopus," and "Web of Science" resources. The evaluations are assessed for studies from 2016 to 2021. The results are illustrated with tables and figures. [ABSTRACT FROM AUTHOR]

Recently, vehicular ad hoc networks (VANETs) got much popularity and are now being considered as integral parts of the automobile industry. As a subclass of MANETs, the VANETs are being used in the intelligent transport system (ITS) to support passengers, vehicles, and facilities like road protection, including misadventure warnings and driver succor, along with other infotainment services. The advantages and comforts of VANETs are obvious; however, with the continuous progression in autonomous automobile technologies, VANETs are facing numerous security challenges including DoS, Sybil, impersonation, replay, and related attacks. This paper discusses the characteristics and security issues including attacks and threats at different protocol layers of the VANETs architecture. Moreover, the paper also surveys different countermeasures. [ABSTRACT FROM AUTHOR]

In wireless networks, a change in network state is unpredictable because of the movement of network nodes, which is not conducive to the stability of the network and poses an especially serious challenge to network routing technology. To adapt to the flexibility of business, consider the impact of environmental changes on the bottom layer of a network, and improve the utilization of network resources, this paper proposes a multipath routing decision strategy restricted by multiple QoS attributes based on an intuitionistic fuzzy set of entropy weights. Cross-layer technology is applied to minimally meet the QoS needs based on multipath routing to discover and maintain multiple transmission paths. Moreover, intuitionistic fuzzy set theory is utilized to reflect the performance indexes of these multiple paths through fuzzy normalization to create a multiparameter multipath routing decision matrix. The weight of each parameter is objectively computed according to information entropy theory. The performance ranking of the multiple paths is determined with the TOPSIS method. As reflected by the results, the TOPSIS decision method based on an intuitionistic fuzzy set of entropy weights effectively solves the optimization problem for multiple paths in mobile ad hoc networks restricted by multiple parameters, and the resulting network is suitable for sensitive network applications involving multiple businesses in mobile environments. According to the simulation results, the proposed routing scheme reduces average network delay by 17% and routing overhead by 21% when compared to the current routing protocols. [ABSTRACT FROM AUTHOR]

Cognitive radio networks need stringent and secure group communication as nodes dynamically access the free portions of radio frequency spectrum to solve the spectrum scarcity in wireless networks. The cognitive radio ad hoc networks can use group key agreement to achieve security in group communication and tree topology to organize the group members in order to reduce the complexity of group operations. This paper proposes a ternary key tree model for tree-based group key agreement in cognitive radio ad hoc networks, and it considers batch rekeying scheme. The range of ids for member, nonmember and pruned nodes in the ternary key tree are analysed in this paper. This paper proposes the analysis of two types of leave operations in the key tree, and the concept of subtree structure is used to analyse the total number of internal nodes that are pruned during leave operations in the key tree through mathematical expressions. This pruned nodes analysis can be used in finding the total number of renewed nodes in the key tree during rekeying process to measure the communication complexity of tree-based group key agreement protocol. [ABSTRACT FROM AUTHOR]

MANET (mobile ad-hoc network) is a wireless ad-hoc network made up of mobile devices that use peer-to-peer routing to provide network access instead of using a preexisting network infrastructure. Despite the network infrastructure's simplicity, it faces issues such as changeable connection capacity, dynamic topology, node battery power exhaustion, and inadequate physical security. Broadcasting is a standard MANET approach for sending messages from a source node to all other nodes in the network. Flooding is a frequent method for broadcasting route request (RREQ) packets, which is susceptible to broadcast storms. The high retransmission rate is caused by the standard flooding technique, which causes media congestion and packet collisions, which can drastically reduce throughput and network performance. In a mobile ad-hoc network, efficient broadcasting focuses on selecting a compact forward node set while assuring broadcast coverage. The goal is to find a limited number of forward nodes that will provide complete coverage. In this paper, we propose an optimized and energy-efficient routing protocol for MANET (mobile ad-hoc network) based on dynamic forwarding probability in general and AODV (ad hoc on-demand distance vector) in particular, in which the route request packets are randomly controlled to increase the network lifetime and reduce packet loss in the flooding algorithm. We tested and assessed the results of our proposed solution using various network performance factors after implementing and integrating it into NS-2. According to simulation findings, our proposed technique effectively reduced route request propagation messages (RREQ). The suggested technique is more efficient, has a longer network lifetime, and uniformly utilizes node residual energy, enhancing network throughput and minimizing routing overhead when compared to regular and modified AODV protocols. [ABSTRACT FROM AUTHOR]

This paper studies the throughput capacity and delay scaling laws in a three-dimensional mobile ad hoc network (3D-MANET) under different routing schemes. Previous work generally assumed that nodes follow a uniform distribution or a power-law distribution to move in the network. From the perspective of the entire network, it is difficult for this network model to reflect communication entities' distribution in real 3D space. Moreover, the research results of analyzing network performance using different routing schemes are limited, and the research work is insufficient. With formerly related studies different,we propose a cell-gridded network model that considers the actual environment with cells of the node aggregation degree, which follows Zipf's law with exponent γ. And our model can cover a variety of distribution scenarios with changes in the γ value. The packet delivery rate, network capacity, and delay performance of 3D-MANET adopting the traditional two-hop nonredundant and redundant relay routing scheme are examined utilizing theoretical tools such as probability theory, random process, and queuing theory. We propose a wireless access point- (WAP-) enabled multihop relay routing scheme. By deploying WAP in cells with a high γ , nodes can access WAP and broadcast packets, which accelerates the delivery of packets, and the results obtained by applying this scheme indicate that compared with the two-hop relay scheme, the WAP multihop relay effectively improves the delay performance and the transmission efficiency with less loss of capacity performance. Additionally, a better delay-capacity trade-off performance is achieved. Finally, we discuss the influence of parameters such as the number of network nodes n , the number of network cells m , the redundancy r , and γ on the capacity and delay. The analysis results confirm that exploiting the users' distribution status information and dividing the cells reasonably will save deployment costs and further improve network performance. [ABSTRACT FROM AUTHOR]

Intelligent Transportation System (ITS) is a critical factor for Vehicular Ad hoc Networks (VANET). Even though VANET belongs to the class of Mobile Ad hoc Network (MANET), none of the MANET routing protocol applies to VANET. VANET network is dynamic, due to increased vehicle speed and mobility. Vehicle mobility of VANET affects conventional routing algorithm performance, which deals with the dynamicity of the network node. The evaluation of the existing research stated that Ad hoc On-Demand Distance Vector (AODV) is an effective MANET protocol to adopt network changes for significant resource utilization and also provides effective adaptation in the network change. Due to the effective performance of the AODV protocol, it is considered as an effective routing protocol for VANET. This paper proposed an ad hoc TROPHY (TAD-HOC) routing protocol for the VANET network for increasing efficiency and effective resource utilization of the network. To improve the overall performance, ad hoc network is combined with Trustworthy VANET ROuting with grouP autHentication keYs (TROPHY) protocol. The proposed TAD-HOC protocol transmits data based on time demand in the VANET network with the desired authentication. Results of the proposed approach show the increased performance of the VANET network with packet delay, transmission range, and end-to-end delay. The comparative analysis of the proposed approach with I-AODV, AODV-R, and AODV-L shows that the proposed TAD-HOC exhibited effective performance. [ABSTRACT FROM AUTHOR]

In a wireless ad hoc network, the size of the virtual backbone (VB) is an important factor for measuring the quality of the VB. The smaller the VB is, the less the overhead caused by the VB. Since ball graphs (BGs) have been used to model 3-dimensional wireless ad hoc networks and since a connected dominating set can be used to represent a VB undertaking routing-related tasks, the problem of finding the smallest VB is transformed into the problem of finding a minimum connected dominating set (MCDS). Many research results on the MCDS problem have been obtained for unit disk graphs and unit ball graphs, in which the transmission ranges of all nodes are identical. In some situations, the node powers can vary. One can model such a network as a graph with different transmission ranges for different nodes. In this paper, we focus on the problem of minimum strongly connected dominating and absorbing sets (MSCDASs) in a strongly connected directed ball graph with different transmission ranges, which is also NP-hard. We design an algorithm considering the construction of a strongly connected dominating and absorbing set (SCDAS), whose size does not exceed 319 / 15 k 3 + 116 / 5 k 2 + 29 / 5 k opt + 29 / 3 k 3 + 116 / 5 k 2 + 87 / 5 k + 13 / 15 , where opt is the size of an MCDAS and k denotes the ratio of r max to r min in the ad hoc network with transmission range r min , r max . Our simulations show the feasibility of the algorithm proposed in this paper. [ABSTRACT FROM AUTHOR]

Wireless networks face security problems compared with traditional wired networks. In wireless networks such as wireless sensor networks (WSNs), mobile ad hoc networks (MANETs), vehicular ad hoc networks (VANETs), and the internet of things (IoT), nodes have limited radio bandwidth and power supply then. They require cooperation in sending messages. It increases the motivation of nodes not to cooperate in such networks. This paper reviews different methods for identifying and stimulating nodes for focused cooperation. The performance of each method, its advantages, and its disadvantages have been reviewed and functionally categorized and compared with the metrics of false positive/negative rate and detection accuracy, throughput, and other metrics. [ABSTRACT FROM AUTHOR]

Today, intelligent transportation systems (ITS) have received a lot of attention due to their significant impact on increasing the safety, efficiency, and convenience of transportation. One of the main applications of ITS is vehicular ad hoc networks (VANETs). In particular, a more flexible, reliable, real-time, and scalable routing scheme across the large urban areas is one of the most critical issues for VANETs. Past VANET routing methods have various technical issues with VANET evolutions. On the other hand, clustering improves the reliability and scalability of routing schemes in VANETs. In this paper, a cluster-based, Traffic-aware and Low-Latency Routing Schema (TaLAR) is proposed for VANETs. In the proposed scheme, the Harris hawks optimization (HHO) algorithm is used to select cluster head (CH) nodes by considering appropriate parameters such as intracluster distance, link reliability, and relative speed of vehicles. The path between source and destination CH nodes is identified by using the HHO algorithm; it chooses the appropriate route based on link reliability and intercluster distance. Also, in the interconnection area, a traffic-aware and reliable route is identified by using a digital map of the streets and the Dijkstra algorithm. The performance evaluation of the proposed scheme is analyzed in terms of packet delivery rate (PDR), average end-to-end delay, and throughput. The output of the proposed scheme is compared with the Clustering Routing Based on PSO (Particle Swarm Optimization) (CRBP) and Grey Wolf Optimization Based Clustering in Vehicular Ad Hoc Network (GWOCENT) methods. Simulation results show that the proposed scheme improves PDR (22 and 19%), throughput (25 and 21%), and average end-to-end delay (23 and 18%). [ABSTRACT FROM AUTHOR]

Wireless networks with a large number of peer nodes are known as mobile ad hoc networks (MANETs). In MANETs, the mobility of nodes causes a number of challenges, including path preservation, battery life, safety, dependability, and unexpected connection characteristics. As a result, the network's quality of service (QoS) would be compromised (QoS). For the discovery and maintenance of pathways in MANETs, the routing protocol is critical. By implementing the multicast routing protocol, the MANET network's reliability may be improved significantly. Evaluation of multicast routing for quality of service (QoS) is the primary goal of this study. In multicasting, data packets from one node are transmitted to a set of receiver nodes at a time, simultaneously. Multicasting reduces transmission costs. Cluster head selection is one of the challenges in MANET. This proposed research paper optimal route selection (ORS) provides the cluster head selection and alternate cluster head selection for avoiding the failure of the cluster head, generation of the optimal path between the cluster head and member node based on reliability pair factor and node's energy, and establishment of the path based on maximum energy and number of hops between the nodes (minimum number of hops). In comparison to existing methods, ORS is more effective in the energy-efficient path between base station and cluster head, and member node is provided by an ORS route. Results show that the proposed ORSMAN has higher throughput, minimum latency, minimum jitter, and maximum packet delivery ratio, when compared to the existing methodologies. [ABSTRACT FROM AUTHOR]

Vehicular Ad hoc Networks (VANETs) are the industrial cornerstone of intelligent transportation system (ITS), which are widely used in traffic management, automatic driving, and road optimization. With the expansion of the scale of the mobile ad hoc networks (MANETs) and smart vehicles (SV), VANETs will produce a large amount of data. In the open access environment of VANETs, the security of information transmission and the authenticity of user identity need to be considered when different vehicles communicate. In order to solve the cybersecurity risks of large-scale deployment of VANET, this paper proposes a trusted blockchain-based signcryption protocol and data management (TB-SCDM) for authentication and authorization (A&A) in VANETs. In the existing attack model, TB-SCDM can ensure the confidentiality and undeniability of information, as well as can effectively resist 51% attacks, eclipse attacks and double-spending attacks, etc. Through benchmark analysis, this scheme has higher computing efficiency and lower storage cost compared with other existing schemes. [ABSTRACT FROM AUTHOR]

The new IoT apps will not be able to inspire people to utilize them and may ultimately lose all their potential if an interoperable and trustworthy ecosystem is not provided. IoT has its extra security difficulties such as information storage, administration, privacy concerns, and authentication. The presently deployed IoT apps have encountered various security and privacy assaults globally. Due to being less secure and low powered, the IoT devices present a simple entryway to the adversaries to obtain access to the corporate networks, leading to giving easy control over all of the data of the users. The objective of this doctorate proposed work will be to solve the security associated difficulties in multiple IoT domains like the e-commerce, vehicular ad hoc networks (VANET), mobile ad hoc networks (MANET), and Internet of Drones (IoD). The proposed study focuses on the development of a distributed framework for IoT based on blockchain. The framework includes the usage of Ethereum-based smart contracts and auction models to increase the income and QoS for both the seller and the buyer and the development of a DAG chain-based distributed framework for parking lot allocation in a network of automobiles. The suggested model includes the requirement of obtaining agreement among the nodes with probability one in such a circumstance. The suggested model demonstrates to be predictable as typical voting-based consensus protocols like Practical Byzantine Fault Tolerance (PBFT) and at the same time can accommodate a high number of nodes even in an asynchronous setting. Research on Byzantine fault-tolerant systems has been ongoing for more than four decades, and although the solutions were shown to be feasible early on, they remained unworkable for a long time. With PBFT, the first feasible solution was provided in 1999, and this sparked fresh research that has resulted in unique applications that are still being developed today employing this technology. Despite the fact that the safety and liveness properties of PBFT-type protocols have been thoroughly investigated, when it comes to practical performance, only empirical results—often obtained in artificial environments—are known, and imperfections in the communication channels are not explicitly considered. It is our goal in this paper to propose the first performance model for PBFT that takes into account the effect of unreliable channels as well as the usage of alternative transport protocols across those channels. We also performed a large number of simulations to test the model and acquire a better understanding of the influence of different deployment factors on the total transaction timeframe. [ABSTRACT FROM AUTHOR]

This paper was aimed at discussing the information monitoring of animal husbandry based on the Internet of Things and wireless communication system. The breeding and health of animals in the breeding industry has always been a topic that people talk about. The advent of the wireless communication system has made monitoring and positioning technologies more and more simple. The wireless communication network technology is applied to the environmental monitoring of animal breeding farms, and a real-time reporting system is designed to pay attention to animal health in real time. This article focuses on the connection between the two. First, this article briefly describes the state of the wireless communication network and the aquaculture industry, furthermore explains the research methods, such as the livestock breeding environment monitoring system model, which needs to have the characteristics of humanization, fast and simple, easy to maintain, high reliability, compatibility, scalability, and intelligence, and designs related monitoring systems and hardware systems to integrate carbon dioxide, ammonia, and other gas sensors with temperature and humidity sensors to sense the environment. Next, this article shows the wireless communication network monitoring and positioning algorithm, namely, the TOA-based wireless communication positioning algorithm and the LTE prediction algorithm. The predicted time is used as the link weight, and the weight within the wide link cluster is defined according to the time threshold, making the link maintain stability for a short time to enhance the network topology. Then, this article conducts experiments based on ZigBee wireless communication network sensor combined with improved genetic algorithm in the temperature and humidity test of farms, designs the environmental monitoring system, improves the algorithm, and cooperates with experiments and analysis to verify the feasibility and apply it to the temperature and humidity test of the livestock farm. The results are good, and the temperature and humidity errors are reduced by 88.28% and 84.21%, respectively. It has a certain degree of guidance. Finally, it is discussed and summarized. It can be seen that the system and algorithm designed in this paper have a good prospect in the development of animal husbandry. However, this algorithm takes a long time and has a broader research space. [ABSTRACT FROM AUTHOR]

Vehicular ad hoc networks (VANETs) are eminent class of mobile ad hoc networks due to their applications. However, mobility management and network scalability are still addressable problems in VANETs. In the current paper, a hierarchical approach has been designed for handling significantly large VANETs by providing better mobility management. The formation of multiple overlapped clusters from large VANETs using k-means algorithm is major characteristics of this approach. Additionally, an addressing architecture has been introduced using two data registers. The derived algorithm allows preparing an appropriate route between source and destination vehicles. Correctness and performance of the approach have been discussed. [ABSTRACT FROM AUTHOR]

Recently, vehicular ad hoc networks (VANETs) embark a great deal of attention in the area of wireless and communication technology and are becoming one of the prominent research areas in the intelligent transportation system (ITS) because they provide safety and precautionary measures to the drivers and passengers, respectively. VANETs are quite different from the mobile ad hoc networks (MANETs) in terms of characteristics, challenges, system architecture, and their application. In this paper, we summarize the recent state-of-the-art methods of VANETs by discussing their architecture, security, and challenges. Secondly, we discuss the detailed analysis of security schemes and the possible measures to provide secure communication in VANETs. Then, we comprehensively cover the authentication schemes, which is able to protect the vehicular network from malicious nodes and fake messages. Thus, it provides security in VANETs. Thirdly, we cover the mobility and network simulators, as well as other simulation tools, followed by the performance of authentication schemes. Finally, we discuss the comfort and safety applications of VANETs. In sum, this paper comprehensively covers the entire VANET system and its applications by filling the gaps of existing surveys and incorporating the latest trends in VANETs. [ABSTRACT FROM AUTHOR]

Spectrum sensing is of the utmost importance to the workings of a cognitive radio network (CRN). The spectrum has to be sensed to decide whether the cognitive radio (CR) user can transmit or not. Transmitting on unoccupied spectrum becomes a hard task if energy-constrained networks are considered. CRNs are ad hoc networks, and thus, they are energy-limited, but energy harvesting can ensure that enough energy is available for transmission, thus enabling the CRN to have a theoretically infinite lifetime. The residual energy, along with the sensing decision, determines the action in the current time slot. The transmission decision has to be grounded on the sensing outcome, and thus, a combined sensing–transmission framework for the CRN has to be considered. The sensing–transmission framework forms a Markov decision process (MDP), and solving the MDP problem exhaustively through conventional methods cannot be a plausible solution for ad hoc networks such as a CRN. In this paper, to solve the MDP problem, an actor–critic-algorithm-based solution for optimizing the action taken in a sensing–transmission framework is proposed. The proposed scheme solves an optimization problem on the basis of the actor–critic algorithm, and the action that brings the highest reward is selected. The optimal policy is determined by updating the optimization problem parameters. The reward is calculated by the critic component through interaction with the environment, and the value function for each state is updated, which then updates the policy function. Simulation results show that the proposed scheme closely follows the exhaustive search scheme and outperforms a myopic scheme in terms of average throughput achieved. [ABSTRACT FROM AUTHOR]

A Mobile Ad-Hoc Network (MANET) is a convenient wireless infrastructure which presents many advantages in network settings. With Mobile Ad-Hoc Network, there are many challenges. These networks are more susceptible to attacks such as black hole and man-in-the-middle (MITM) than their corresponding wired networks. This is due to the decentralized nature of their overall architecture. In this paper, ANN classification methods in intrusion detection for MANETs were developed and used with NS2 simulation platform for attack detection, identification, blacklisting, and node reconfiguration for control of nodes attacked. The ANN classification algorithm for intrusion detection was evaluated using several metrics. The performance of the ANN as a predictive technique for attack detection, isolation, and reconfiguration was measured on a dataset with network-varied traffic conditions and mobility patterns for multiple attacks. With a final detection rate of 88.235%, this work not only offered a productive and less expensive way to perform MITM attacks on simulation platforms but also identified time as a crucial factor in determining such attacks as well as isolating nodes and reconfiguring the network under attack. This work is intended to be an opening for future malicious software time signature creation, identification, isolation, and reconfiguration to supplement existing Intrusion Detection Systems (IDSs). [ABSTRACT FROM AUTHOR]

Request route flooding attack is one of the main challenges in the security of Mobile Ad Hoc Networks (MANETs) as it is easy to initiate and difficult to prevent. A malicious node can launch an attack simply by sending an excessively high number of route request (RREQ) packets or useless data packets to nonexistent destinations. As a result, the network is rendered useless as all its resources are used up to serve this storm of RREQ packets and hence unable to perform its normal routing duty. Most existing research efforts on detecting such a flooding attack use the number of RREQs originated by a node per unit time as the threshold to classify an attacker. These algorithms work to some extent; however, they suffer high misdetection rate and reduce network performance. This paper proposes a new flooding attacks detection algorithm (FADA) for MANETs based on a machine learning approach. The algorithm relies on the route discovery history information of each node to capture similar characteristics and behaviors of nodes belonging to the same class to decide if a node is malicious. The paper also proposes a new flooding attacks prevention routing protocol (FAPRP) by extending the original AODV protocol and integrating FADA algorithm. The performance of the proposed solution is evaluated in terms of successful attack detection ratio, packet delivery ratio, and routing load both in normal and under RREQ attack scenarios using NS2 simulation. The simulation results show that the proposed FAPRP can detect over 99% of RREQ flooding attacks for all scenarios using route discovery frequency vector of sizes larger than 35 and performs better in terms of packet delivery ratio and routing load compared to existing solutions for RREQ flooding attacks. [ABSTRACT FROM AUTHOR]

Intelligent transport systems are the future in matters of safe roads and comfortable driving. Integration of vehicles into a unified intelligent network leads to all kinds of security issues and cyber threats common to conventional networks. Rapid development of mobile ad hoc networks and machine learning methods allows us to ensure security of intelligent transport systems. In this paper, we design an authentication scheme that can be used to ensure message integrity and preserve conditional privacy for the vehicle user. The proposed authentication scheme is designed with lightweight cryptography methods, so that it only brings little computational and communication overhead. We also conduct experiments on vehicular ad hoc network segment traffic generation in OMNeT++ tool and apply up-to-date machine learning methods to detect malicious behavior in a given simulated environment. The results of the study show high accuracy in distributed denial-of-service attack detection. [ABSTRACT FROM AUTHOR]

In energy-constrained networks, designing an energy-efficient MAC protocol is crucial since the MAC protocol controls the access of the nodes to the shared wireless medium. Indeed, an efficient MAC protocol should reduce or even mitigate the consumption of the main sources of energy wastage, namely, overhearing, collision, and idle listening, and hence the network lifetime will be improved. One of the most efficient solutions is designing a MAC protocol that utilizes the quorum concept to increase energy efficiency by reducing idle listening and overhearing. Researchers have proposed several quorum-based MAC protocols to conserve energy. This paper presents a detailed overview and classification of several existing quorum-based sleep/wakeup scheduling MAC protocols. We classify these quorum-based MAC protocols into homogeneous and heterogeneous based on their quorum system characteristics. Moreover, we further classify these protocols according to the guaranteed intersection between any two quorums into fixed and limited. Furthermore, we compare these protocols in terms of their quorum system characteristics, limitations, and performance. Finally, a guide for future research directions is presented. [ABSTRACT FROM AUTHOR]

The vehicular ad hoc networks (VANETs) are an example of mobile networks, which utilizes dedicated short-range communication (DSRC) to establish a wireless connection between cars, and their primary purpose is to provide more security and comfort for passengers. These networks utilize wireless communications and vehicular technology to collect and disseminate traffic information, and it is required to be delivered to all vehicles on the network reliably and quickly. One of the major challenges raised in VANETs is that the communication path between the source and destination nodes is disconnected due to the dynamic nature of the nodes in this network, and the reconnection process of nodes through the new path reduces the performance of network. This paper presents a highway routing protocol to overcome some of the challenges of these networks including routing cost, delay, packet delivery rate, and overhead. The NS2 is used for simulation, and the performance of the proposed protocol is compared with the VMaSC-LTE and DBA-MAC protocols. The results of the simulation indicated that the proposed protocol outperforms the other two protocols in terms of delay, packet delivery rate, and routing overhead. [ABSTRACT FROM AUTHOR]

Wireless communication systems have evolved and offered more smart and advanced systems like ad hoc and sensor-based infrastructure fewer networks. These networks are evaluated with two fundamental parameters including data rate and spectral efficiency. To achieve a high data rate and robust wireless communication, the most significant task is channel equalization at the receiver side. The transmitted data symbols when passing through the wireless channel suffer from various types of impairments, such as fading, Doppler shifts, and Intersymbol Interference (ISI), and degraded the overall network performance. To mitigate channel-related impairments, many channel equalization algorithms have been proposed for communication systems. The channel equalization problem can also be solved as a classification problem by using Machine Learning (ML) methods. In this paper, channel equalization is performed by using ML techniques in terms of Bit Error Rate (BER) analysis and comparison. Radial Basis Functions (RBFs), Multilayer Perceptron (MLP), Support Vector Machines (SVM), Functional Link Artificial Neural Network (FLANN), Long-Short Term Memory (LSTM), and Polynomial-based Neural Networks (NNs) are adopted for channel equalization. [ABSTRACT FROM AUTHOR]

With the development of the mobile Internet, e-commerce has become one of the important ways of daily consumption, but how to effectively use e-commerce for interactive marketing and increase sales is an important research direction. Mobile ad hoc distributed algorithms are introduced in this paper. Through sorting out the mode of e-commerce interaction influence, process marketing is performed from two-dimensional code, short message, business district, mobile search, Bluetooth, wireless network, and other methods, and interactive marketing is tried in various industries such as education, tourism, agriculture, catering, finance, and publishing, and simulation experiments are used to verify them. The simulation experiment results show that the mobile ad hoc distributed algorithms are effective and can support the e-commerce interactive marketing model. [ABSTRACT FROM AUTHOR]

The recent advancements in embedded and wireless systems have led to a new class of pervasive technologies, such as Radio Frequency Identification (RFID) Networks, Ad-Hoc Networks, and Wireless Sensor Networks (WSNs). These networks have presented promising solutions for a wide range of technological applications. However, privacy and security concerns in these systems have remained a matter of great concern. The privacy and security concerns in these networks become more serious when the networks are integrated. In this paper, simulation of relay attacks is presented on the commonly used ISO/IEC 14443 standard. A mobile phone and an RFID tag emulator have been used. The emulator and the phone are set to share RFID communication through a Bluetooth channel. The results of the relay attacks are then presented. Finally, the paper suggests possible solutions that can be implemented to protect against the attacks. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper proposes a new two round authenticated contributory group key agreement (ACGKA) protocol based on elliptic curve Diffie-Hellman (ECDH) with integrated signature. In this technique, one node is picked up as the group controller, and this node runs an authenticated ECDH with the rest of the nodes to generate an authenticated shared key per each two-party. It then merges these keys in another round in such a way that every member obtains the identical authenticated group key. Further, ACGKA is extended to dynamic ACGKA protocol. The dynamic ACGKA, being elliptic curve decisional Diffie Hellman-based, is less expensive and well suited for resource constrained networks such as mobile ad-hoc networks, and wireless sensor network. Also, we demonstrate that all the protocols proposed in this paper are provably secure in the standard model under ECDDH assumption and moreover secure against most of the active and passive attacks. Finally, the proposed protocol is compared with other prevalent ECDH and Diffie Hellman based group key agreement protocols, and results are found to be satisfactory. Copyright © 2015 John Wiley & Sons, Ltd [ABSTRACT FROM AUTHOR]