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The huge advancement in the field of communication has pushed the innovation pace towards a new concept in the context of Internet of Things (IoT) named IoT for Financial Technology applications (IoT-FinTech). The main intention is to leverage the businesses’ income and reducing cost by facilitating the benefits enabled by IoT-FinTech technology. To do so, some of the challenging problems that mainly related to routing protocols in such highly dynamic, unreliable (due to mobility) and widely distributed network need to be carefully addressed. This paper therefore focuses on developing a new trustworthy and efficient routing mechanism to be used in routing data traffic over IoT-FinTech mobile networks. A new Non-linear Levy Brownian Generalized Normal Distribution Optimization (NLBGNDO) algorithm is proposed to solve the problem of finding an optimal path from source to destination sensor nodes to be used in forwarding FinTech’s related data. We also propose an objective function to be used in maintaining trustworthiness of the selected relay-node candidates by introducing a trust-based friendship mechanism to be measured and applied during each selection process. The formulated model also considering node’s residual energy, experienced response time, and inter-node distance (to figure out density/sparsity ratio of sensor nodes). Results demonstrate that our proposed mechanism could maintain very wise and efficient decisions over the selection period in comparison with other methods.

The advancement in the communication and services demand for better QoS, but in parallel the increase in network traffic demands for an effective and significant traffic controlling model to manage high network traffic and also reduce congestion. In case of MANET circumstances it is further difficult to control and manage due to high mobilizing nodes and limited resource restrictions. Even MANET’s dynamic mobility creates high maintenance overhead for effective communication. In the past most of the designed routing protocols utilize reactive routing mechanism, which are primary source driven. In case of a link failure and data failure it has to update the source node and source node only have to decide next course of action. This will generates an additional overhead in the network and may reduce throughput of the protocols. This paper aims to propose a novel Traffic Controlling Model (TCM) to efficiently manage the routing overhead in MANET. The TCM will handle heavy traffic, which is the main cause of network congestion and overhead. It first determines the network traffic and evaluates the probable Node Link Life (NLL) to recommend the TCM process. The analysis of the results generated through the experiment evaluation shows that the data routing has improved and substantiates the effectiveness of the proposal in compared to the existing routing approaches.

Routing protocol for Low Power Lossy Network (RPL) is a proactive network layer routing protocol. It is suitable for Internet of Things (IoT). It is also a source routing protocol. It works by creating a tree based network topology called Directed Acyclic Graph (DAG). Based on the position of the nodes from the root, rank value is allocated for each node. Rank is a unique value given to all the nodes in the DAG. It increases in the downward direction from the root. This value is used for prevention of loops, formation and maintenance of topology. Certain malignant nodes use this rank value and introduce a false routing by forcing the neighbors to route the packets through them. The consequences of this attack are more destructive in nature. It decreases throughput and increases delay in communication. Since the devices in IoT are resources constrained, there is an urge to address rank attack immediately. In this paper, a thorough review on the effects of rank attack and its countermeasures are presented.

Wireless networks are considered the best utilized network and in particular Mobile Ad-hoc NETworks (MANETs) have found many applications for its data transmission in real time applications. The accompanying challenges restrict the current protocols for the routing being specifically used in MANETs. The design issues in this network are to restrict the usage of energy while transmitting information and provide security to the nodes. In the existing routing protocols, route comes from a source where the source node seeks a way to the target node, by transmitting messages to its adjacent nodes, and the nodes use energy to do this. Mobile Ad-hoc network faces challenges in improving the energy efficiency and providing security for the routing protocol. This research work proposes the Enhanced Energy Efficient-Secure Routing (EEE-SR) protocol as a novel security algorithm to access secure data in hostile environment. In the proposed work, to secure data transmission in the network, the nodes associates with security policy. Under this policy, both the nodes have a common enforcing policy, and then they communicate with each other. The selection of the nodes for the transmission has to prove its authentication and then selection of the routing path built on the available energy threshold at the nodes in the set-up for forwarding packets in the network. The routing protocol implements the best shortest path in network and also checks for the nodes trustworthiness by evaluating the trust policies enforcement on it. The protocol enables a node to autonomously decide whether to select the neighboring node or based on the available energy threshold and security policy enforced. The algorithm evaluates increase network lifetime and low in the energy consumption, packet loss and end-to-end delay.

With the recent advancements in the field of wireless networks or Mobile Ad-hoc networks (MANETs), mobile computing is the most powerful use for network communication and connectivity. Effective networks come across with numerous difficulties. Networks need to be able to transmit data with acceptable precision from one system to another. A framework must ensure that the retrieved data is consistent with the transmitted data for most applications. If the frame between the two nodes is distorted in the data-link layer, it must be corrected before having driven to other nodes. However, most protocols with the link-layer simply dismiss the frame and allow the high-layer protocols to pass down the frame. In other words, information is a valuable commodity, since asset information must be protected from threats. Some applications require a network mechanism for detecting and preventing these attacks in MANETs. An important challenge in MANET is building the secure intrusion detection system in network providing security to the nodes and route paths in network. The attacks in network can threaten the security issues which have been identified in the intrusion detection system engine, later it is prevented by intrusion prevention engine in the network. A henceforth new technique to implement the security goals and prevent attacks is implemented by introducing the Secure-Intrusion Detection System (S-IDS) in the network. The research work introduced the Secure Energy Routing (SER) protocol for the MANETs. The protocol solves the issue of security in network by detecting the attacks and preventing them in the network. The simulation results show the higher packet delivery ratio and low end-to-end delay with and without attacks. The protocol performance is good in terms of its packet delivery ratio and low end-to-end delay respectively.

Wireless Sensor Network (WSN) has the characteristics limited computing, memory and energy, so a routing protocol that supports WSN network performance is needed. Routing protocols based Ant Colony Optimization (ACO) are very suitable for use in WSN for routing data packets. In this report, we will try out several kinds of parameter values that bear on the pheromone evaporation (ρ) on the ACO algorithms applied to the WSN routing protocol with grid topology on the number of nodes variables in the WSN network. Where this can increase the number of delivery packets on a busy WSN network and each node transmits a packet continuously. From the results, the value of ρ 0.75 makes WSN performance on the grid topology with the number of nodes 12 and 30 very good in terms of the delivery packet, but with the number of nodes 70 the value of ρ 0.70 makes WSN performance better than the delivery packet side.

The Mobile Edge Computing (MEC) mitigates the bandwidth limitation between the edge server and the remote cloud by directly processing the large amount of data locally generated by the network of the internet of things (IoT) at the edge. To reduce redundant data transmission, this paper proposes a data collection scheme that only gathers the necessary data from IoT devices along a trajectory. Instead of using and transmitting location information (to preserve location anonymity), a virtual coordinate system called "distance vector of hops to anchors" (DV-Hop) is used. The proposed trajectory encoding algorithm uses ellipse and hyperbola constraints to encode the position of interest (POI) and the trajectory route to the POI. Sensors make routing decisions only based on the geometric constraints and the DV-Hop information, both of which are stored in their memory. The proposed DV-Hop updating algorithm enables the users to collect data in an IoT network with mobile nodes. The experiments show that in heterogeneous IoT networks, the proposed data collection scheme outperforms two other state-of-the-art topology-based routing protocols, called ring routing, and nested ring. The results also show that the proposed scheme has better latency, reliability, coverage, energy usage, and provide location privacy compared to state-of-the-art-schemes.

One of the operational challenges in the Internet of Things (IoT) is load balancing, which is the focus of interest of this paper. We propose a three-phase enhanced ad hoc on-demand distance vector (enhanced-AODV) routing protocol for multi wireless sensor networks (multi-WSNs). The three phases are categorized based on traffic priority, namely: high priority, low priority, and ordinary network traffic. The network architecture is divided into chains, i.e. local and public chains, where the cluster heads (CHs) and base stations (BSs) are used respectively to manage network traffic based on priority information with alternative route allocation. Moreover, our three-phase enhanced-AODV protocol provides traffic categorization with alternatives route allocation to minimize energy consumption and prolong the lifetime of participating devices in the network. The proposed model is implemented in the simulation environment to overview results statistics in terms of network lifetime, prioritize traffic, computation and communication costs, latency, and packet lost ratio (PLR). Findings from the simulation suggest that our scheme achieves 15% improvement in network lifetime, 17% latency, 22% PLR, and approximately 10% in the computation and communication costs of the network, in comparison to three other similar protocols.

Wireless Sensor Network (WSN) plays a vital role in dealing with the challenging tasks of information management in Intelligent Transportation Systems (ITS). Current research has shown that the ever growing number of vehicles on the roads is making congestion worse, and many safety concerns are being addressed comprehensively by the WSN-based ITS. However, the energy consumed by sensor nodes, their operational period, and `security compromise' are ever growing concerns. Cluster-based routing strategies have potentially contributed in reducing the energy expenditure of sensor nodes, besides the selection of energy-efficient and secure Cluster Head (CH) is still seeking an optimized approach for acquiring the proliferated performance of WSN. To address these concerns, we propose an Intelligent Clustering approach for ITS (ICITS) which selects CHs based on a hybrid optimization method called GABAT that integrates the strengths of Genetic Algorithm (GA) and BAT Algorithm (BA). The proposed framework (ICITS) is targeted primarily to road transport in military areas due to their stringent requirements in terms of security and reliability while collecting the data from the deployed sensor nodes. The simulation results obtained with ICITS demonstrate that it performs well for various performance metrics that include stability period, network survival period and `number of packets sent', which are improved by 54.7%, 19.6%, and 40.5%, respectively as compared to recently proposed Cluster-based Intelligent Routing Protocol (CIRP).

With the growing utilization of intelligent unmanned aerial vehicle (UAV) clusters in both military and civilian domains, the routing protocol of flying ad-hoc networks (FANETs) has promised a crucial role in facilitating cluster communication. However, the highly dynamic nature of the network topology, owing to the rapid movement and changing direction of aircraft nodes, as well as frequent accesses and exits from the network, has resulted in an increased interruption rate of FANETs links. While traditional protocols can satisfy basic network service quality (QoS) requirements in mobile ad-hoc networks (MANETs) with relatively fixed topology changes, they may fail to achieve optimal routes and consequently restrict information dissemination in FANETs with topology changes, which ultimately leads to elevated packet loss and delay. This paper undertakes an in-depth investigation of the challenges faced by current routing protocols in high dynamic topology scenarios, such as delay and packet loss. It proposes a Q-learning empowered highly dynamic, and latency-aware routing algorithm for flying ad-hoc networks (QEHLR). Traditional routing algorithms are unable to effectively route packets in highly dynamic FANETs; hence, this paper employs a Q-learning method to learn the link status in the network and effectively select routes through Q-values to avoid connection loss. Additionally, the remaining time of the link or path lifespan is incorporated into the routing protocol to construct the routing table. QEHLR can delete predicted failed links based on network status, thereby reducing packet loss caused by failed route selection. Simulations show that the enhanced algorithm significantly improves the packet transmission rate, which addresses the challenge of routing protocols’ inability to adapt to various mobility scenarios in FANETs with dynamic topology by introducing a calculation factor based on the QEHLR protocol. The experimental results indicate that the improved routing algorithm achieves superior network performance.

Traditional methods for wildlife monitoring are labor-intensive and time-consuming. Therefore, advanced technologies and remote monitoring methods are becoming increasingly popular. This paper presents a study on wireless technologies for wildlife monitoring. In the study, a review of the literature was done to identify the most commonly used wireless technologies. Various technologies were explored including unmanned aerial vehicles (UAVs), Internet of Things (IoT), wireless sensor networks (WSNs), artificial intelligence (AI), global positioning system (GPS), and very high frequency (VHF) radio. Then, a more detailed study was done on WSN technology. Investigations were done to observe the performance of routing protocols in WSNs. The use of source location privacy (SLP) routing protocols was considered for secure wildlife monitoring in areas such as game reserves. In such areas, sensor node energy consumption minimization and battery lifetime maximization are crucial. Hence, energy-efficient SLP protocols are more suitable for deployment. Using MATLAB simulation environment, performance analysis of various phantom-based SLP protocols was done to identify effective and energy-efficient SLP protocols. Simulation results show that two-level phantom with a backbone route protocol (TBP) and phantom with angle protocol (PAP) exhibit advantageous performance features in terms of SLP protection, energy efficiency, effective long-term SLP protection, and scalability. Thus, TBP and PAP are suitable for deployment in wildlife monitoring WSNs.

Vehicle Ad-hoc network (VANET) can provide technical support and solutions for the construction of intelligent and efficient transportation systems, and the routing protocol directly affects the efficiency of VANET. The rapid movement of nodes and uneven density distribution affect the routing stability and data transmission efficiency in VANET. To improve the local optimality and routing loops of the path-aware greedy perimeter stateless routing protocol (PA-GPSR) in urban sparse networks, a weight-based path-aware greedy perimeter stateless routing protocol (W-PAGPSR) is proposed. The protocol is divided into two stages. Firstly, in the routing establishment stage, the node distance, reliable node density, cumulative communication duration, and node movement direction are integrated to indicate the communication reliability of the node, and the next hop node is selected using the weight greedy forwarding strategy to achieve reliable transmission of data packets. Secondly, in the routing maintenance stage, based on the data packet delivery angle and reliable node density, the next hop node is selected for forwarding using the weight perimeter forwarding strategy to achieve routing repair. The simulation results show that compared to the greedy peripheral stateless routing protocol (GPSR), for the maximum distance–minimum angle greedy peripheral stateless routing (MM-GPSR) and PA-GPSR protocols, the packet loss rate of the protocol is reduced by an average of 24.47%, 25.02%, and 14.12%, respectively; the average end-to-end delay is reduced by an average of 48.34%, 79.96%, and 21.45%, respectively; and the network throughput is increased by an average of 47.68%, 58.39%, and 20.33%, respectively. This protocol improves network throughput while reducing the average end-to-end delay and packet loss rate.

The internet of things (IoT) based on a network layer perspective includes low-power and lossy networks (LLN) that are limited in terms of power consumption, memory, and energy usage. The routing protocol used in these networks is called routing over low-power and lossy networks (RPL). Therefore, the IoT networks include smart objects that need multiple routing for their interconnections which makes traffic load balancing techniques indispensable to RPL routing protocol. In this paper, we propose a method based on fuzzy logic and the technique for the order of prioritization by similarity to the ideal solution (TOPSIS) as a well-known multi-criteria decision-making method to solve the load balancing problem by routing metrics composition. For this purpose, a combination of both link and node routing metrics namely hop count, expected transmission count, and received signal strength indicator is used. The results of simulations show that this method can increase the quality of services in terms of packet delivery ratio and average end-to-end delay.

A little change in the environment that goes unnoticed in an underwater communication network might lead to calamity. A little alteration in the environment must also be adequately analyzed in order to deal with a potential crisis. A priority-based routing protocol is required to ensure that the vital data perceived by the sensor about the environment changes. The priority-based routing system guarantees that vital data packets are delivered at a quicker pace to the destination or base station for further processing. In this work, we present a priority-based routing protocol based on the energy efficient hybrid cluster routing protocol (EEHRCP) algorithm. The suggested approach keeps two distinct queues for lower and higher priority data packets. In order to ensure that these packets get at their destination without any information loss and at a quicker rate, all of the crucial sensed data is passed through a higher priority queue. Test findings show that the suggested technique increases throughput, delivery percentage, and reduces latency for the crucial data packets.

Scientific, commercial, exploration, and monitoring applications of underwater sensor networks have drawn the attention of researchers toward the investigation of routing protocols that are robust, scalable, and energy efficient. This has brought significant research in network layer routing protocols. Irrespective of the field of application it is desirable to increase network lifetime by reducing energy consumed by sensor nodes in the network or by balancing energy in the entire network. Energy balancing refers to the uniform distribution of the network’s residual energy such that all nodes remain alive for a long time. It requires uniform energy consumption by each sensor node in the network instead of the same node being involved in every transmission. In this paper, we discuss two routing methods for three-dimensional environments in which the water region under monitor is divided into subregions of equal height and each subregion has a sink. Nodes in the subregion send data to the sink designated for that subregion. The first method called static multi-sink routing uses static sinks and the second method called horizontal trajectory-based mobile multi-sink routing (HT-MMR) uses mobile sinks with a horizontal trajectory. Simulation results show that the proposed HT-MMR reduces average energy consumption and average energy tax by 16.69% and 16.44% respectively. HT-MMR is energy efficient as it enhances network lifetime by 11.11%.

In Internet of Things (IoT) applications with multihop networking, not only traditional energy efficiency but also many distinct features should be considered when designing routing protocols, including different security requirements, heterogeneity, and scalability. In this paper, an energy efficient multi-level secure routing (EEMSR) protocol in IoT networks is proposed. Considering that clustering is a reasonable solution of conserving energy, a cluster-based multi-hop routing protocol is utilized to reduce the high communication overhead due to the scalability of IoT networks. In particular, more reasonable analytic hierarchy process and genetic algorithms are adopted to assign accurate weight and optimize inter-cluster routing in which heterogeneous IoT networks are considered to support large amount of heterogeneous IoT entities and services. Moreover, multiple trust levels are adopted to defend the different attacks by calculating the trust factor on the clustering and routing, including data perception trust, data fusion trust, and communication trust. It is shown that the proposed algorithm outperforms the existing algorithms in terms of network lifetime, throughput, packet delivery ratio, network energy balance, and adaptability.

The area of intelligent transport systems (ITS) is attracting growing attention because of the integration of the smart IoT with vehicles that improve user safety and overall travel experience. Vehicular ad hoc network (VANET) is the part of ITS; that deals with the routing protocols and security of smart vehicles. However, due to the rapid increase in the number of smart vehicles, the existing network technology's resources unable to handle the traffic load. It expects that the 6G communication system has the ability to fulfill the requirements of VANETs. Only a few studies explore this area, but they also overlooked the security aspect of VANETs in 6G communications networks. In this paper, we present an approach to address authentication and security issues for vehicles in VANET. By authenticating cars in the VANET and identifying various cyber assaults such as DDoS, our method significantly contributes to the intelligent transport communication network. Our approach uses the concepts of identity-based encryption to provide access control to the vehicles and deep learning-based techniques for filtering malicious packets. Our identity-based encryption technique is IND-sID-CCA secure, and a state-of-the-art deep learning algorithm detects malicious packets with an accuracy of 99.72%. These results emphasize the validity of our proposed approach for VANETs in 6G communication systems.

The Internet of Things (IoT) is an emerging technology that has earned a lot of research attention and technical revolution in recent years. Significantly, IoT connects and integrates billions of devices and communication networks around the world for several real-time IoT applications. On the other hand, cybersecurity attacks on the IoT are growing at an alarming rate since these devices are vulnerable because of their limited battery life, global connectivity, resource-constrained nature, and mobility. When attacks on IoT networks go undetected within a speculated period, such security attacks may prompt severe threats and disruptive behavior inside the network and make the network unavailable to the end-user. Hence, it is quintessential to design an intelligent and robust security approach that promptly detects potential attack surfaces in a dynamic IoT network. This paper investigates a comprehensive survey of machine learning, deep learning, and reinforcement learning-based intelligent intrusion detection techniques for securing IoT. Also, this paper thoroughly illustrates the implementation of various categories of security threats in IoT with a neat diagram. Significantly, we classify the threats into two broad categories: Wireless Sensor networks (WSN) inherited security attacks and Routing Protocol for Low Power and Lossy Networks (RPL) specific security attacks in IoT. Finally, we present potential research opportunities and challenges in intelligent intrusion detection approaches in future IoT security.

The implementation of the optimal Huffman coding technique for achieving proficient data compression, lower information redundancy and minimal utilization of the scarce bandwidth is essential to handle the effective processing of massive network data. In this paper, we employ cross-layer design technique among the data link, network and presentation layers of the traditional protocol stack to develop the improved DSDV routing protocol based on n-ary Huffman coding procedure. The entropy-based adaptive prefix codewords with variable length are assigned to the probability of packet successful delivery across the ad-hoc wireless network. Several coding and network efficiency parameters are deployed to assess the performance of the proposed routing scheme under three distinctive IPv4 network scenarios. These investigated network protocols include the default IPv4, multi IPv4 and dynamic IPv4 routing methodologies. Diversified simulation settings are employed with deviating network size to measure the multitude of essential wireless network characteristics incorporating the average delay, packet error rate, packet delivery fraction, data rate, ping loss rate, entropy rate, and reception cache hit. In addition, the set of key data compression/coding indicators are examined through comprehensive numerical analysis such as codeword length, source information rate, mean redundancy, and coding efficiency. Beyond, we significantly compare the performance of our developed cross-layer coded mobile routing model with several previous algorithms to validate its enhanced feasibility and superiority in terms of crucial network operation metrics such as throughput, packet drop rate, mean delay and packet delivery ratio.

An excellent routing protocol is important for wireless sensor network construction and efficient data transmission. With continuous expansion of the application scenarios and scopes of the Internet of Things, the existing wireless sensor network routing protocols are no longer suitable for the complex network structure and the huge demands of communications. Aiming at these issues of existing routing protocols, such as short network lifetime caused by high energy consumption and uneven distribution of surviving nodes, this paper proposes an energy saving clustering protocol based on adaptive Voronoi dividing, named ESCVAD (Energy Saving Clustering by Voronoi Adaptive Dividing) protocol. The innovation of ESCVAD protocol lies in the adaptive clustering algorithm based on Voronoi dividing and cluster head election optimization algorithm based on distance and energy comprehensive weighting. The advantage of proposed algorithms is effectively to balance the energy consumption between cluster head nodes and cluster member nodes. The simulation results show that, compared with the traditional routing protocols, such as LEACH (Low Energy Adaptive Clustering Hierarchy) protocol and SEP (Stable Energy Protocol), the proposed ESCVAD protocol can effectively reduce the clustering frequency and cluster head electing frequency, so as to reduce signaling interaction frequency, finally result in the energy consumption down and the network lifetime up. Among the six protocols for comparation, ESCVAD has the best network lifetime and energy efficiency.

With the rapid development of the Internet of vehicles (IoV), routing in vehicular ad hoc networks (VANETs) has become a popular research topic. Due to the features of the dynamic network structure, constraints of road topology and variable states of vehicle nodes, VANET routing protocols face many challenges, including intermittent connectivity, large delay and high communication overhead. Location-based geographic routing is the most suitable method for VANETs, and such routing performs well on paths with an appropriate vehicle density and network load. We propose an intersection-based V2X routing protocol that includes a learning routing strategy based on historical traffic flows via Q-learning and monitoring real-time network status. The hierarchical routing protocol consists of two parts: a multidimensional Q-table, which is established to select the optimal road segments for packet forwarding at intersections; and an improved greedy strategy, which is implemented to select the optimal relays on paths. The monitoring models can detect network load and adjust routing decisions in a timely manner to prevent network congestion. This method minimizes the communication overhead and latency and ensures reliable transmission of packets. We compare our algorithm with three benchmark algorithms in an extensive simulation. The results show that our algorithm outperforms the existing methods in terms of network performance, including packet delivery ratio, end-to-end delay, and communication overhead.

Internet of Things (IoT) is a wireless network of various battery-powered sensing units. Due to the limited battery capacity, the non-accessible/abandoned nodes demand more energy to be reached or re-integrated to keep the network connected. When a specific tree topology for routing, called Destination Oriented Directed Acyclic Graphs (DODAG) is used, isolated nodes spend maximum energy on the assigned task during data transformation from the sensor field to the DODAG root. The nodes closer to the DODAG root need to rely on faraway nodes and resource-burden constrained nodes to lead to the quick energy drain. It brings an idea of IoT network nodes in which an extra amount of energy provide to the longer-time alive nodes. This paper proposes an ARFOR-Adaptive ranking fuzzy-based energy-efficient opportunistic routing protocol for sustainable IoT applications. The proposed protocol consists of Parent Node (PN) that acts as a head node in a cluster to aggregate the packets to DODAG root; and Volunteer Node (VN) acts as a forwarder to transfer the packets to PN with threshold energy limits to increase network lifetime during transmission cycle. The proposed VN selection is based on fuzzy parameters such as Canberra distance, residual energy, and threshold. The simulation outcomes depict that the ARFOR fairly justifies the network timeline requirement with maximum percentage area coverage. The percentage gain in terms of network lifetime is comparatively significant for a lower number of VN.

Various routing protocols have been developed for wireless ad hoc networks to shift from infrastructure-based networks to self-controlling and self-configurable networks. These ad hoc networks are easy to implement and have plenty of application in the fields of healthcare, transportation, smart cities, etc. Although almost all of the routing protocols work on the Open Systems Interconnection (OSI) model’s network layer, a few routing protocols support routing on the data link layer of the OSI model rather than the conventional one. One of these routing protocols include the Better Approach To Mobile Ad Hoc Networking (BATMAN). Though BATMAN is a comparably new routing protocol and included in the Linux kernel, it suffers from performance deterioration and latency issues that need to be addressed especially in the Internet of Things (IoT). This paper presents a symmetry-based split hop penalty for BATMAN version 4 to improve the network’s performance in multi-hop scenarios. Split hop penalty defines two different sets of penalties to accommodate the routing protocol metric based on the interface media type. The experiments were conducted within the campus building of the university with physical nodes, and the obtained results highlight that overall performance is improved in terms of throughput, latency, and jitter while no performance gain is measured in packet loss and routing loops that are still present.

In the current digital era, video streaming services are increasingly popular and have become one of the most widely used services by the public. The quality of video streaming services is the key to providing a good user experience. However, unstable networks and suboptimal Quality of Service (QoS) can affect the quality of video streaming services, resulting in buffering or poor picture quality. To overcome these problems, reliable networks and optimal QoS settings are needed. OSPF and EIGRP are routing protocols used in computer networks to optimize the user experience when using video streaming services. The aim of this study is to compare the QoS performance of video streaming services on OSPF and EIGRP networks with measured parameters including delay, jitter, packet loss, and throughput. Additionally, this study aims to determine which routing protocol is better at supporting video streaming services with good quality. The final result of the study is a comparison of the QoS performance of OSPF and EIGRP networks. Overall, the OSPF network has better performance compared to the EIGRP network, with a difference in performance values of 13.3%.

Dynamic source routing protocol (DSR) is a common routing protocol in wireless network without infrastructure, called ad-hoc network, DSR used just above internet protocol (IP) at the network layer. The upper transport layer provides reliability by transmission control protocol (TCP) and user datagram protocol (UDP). The choice between DSR/TCP and DSR/UDP is an actual issue for network designers and engineers. The question arises: which one provides better quality of service (QoS) parameters, less delay and jitter, greater throughput, and data rates. This paper focuses on the study and analysis of DSR and comparison of DSR/TCP and DSR/UDP by simulation in network simulator (NS2) environment. Another comparison of DSR and ad hoc on-demand distance vector (AODV) is provided. Design and simulation of the protocols in ad hoc network accurately describe the behavior in real system and QoS parameters are obtained.

Optimized Link State Routing protocol, an ad-hoc routing protocol, has been popular in wireless devices running on Linux operating system for quite some time. In this project we have outlined the process of preparing Android devices for ad-hoc networking, a way to overcome limitations of the OS for continuous UDP communication, ensure all devices communicate on the same wireless Wi-Fi SSID, Cell-ID, subnet and finally implement the Optimized Links State Routing (OLSR) in Android Operating System using Google Nexus 7 devices. Using the code base from ProjectSPAN, an open source project, OLSR protocol has been ported to Android Nexus 7 devices. The core application is divided into two major sections, MANET and OLSR. Mobile Ad-hoc Network portion of the code takes care of setting up the device for ad-hoc mode communication, firewall and peripheral setup while OLSR portion of the code maintains the neighbor tables, MPRs and routing. The project also describes the process by which a device is prepared to run low level custom codes in Android operating system. The OLSR implementation has been successfully tested with three nodes test bed, demonstrating the multi-hop ad-hoc networking capabilities of this wireless routing protocol. With the aid of the Android’s graphical interface the application is able to exhibit the dynamic nature of the OLSR protocol. As nodes and neighbors in the network moves around with respect to time and relative location, OLSR protocol is able to form new neighbors and elect Multipoint Relay in real time.

Different from mobile ad hoc networks (MANETs) and vehicular ad hoc networks (VANETs), a flying ad hoc network (FANET) is a very low-density network where node topology changes rapidly and irregularly. These characteristics, the density, mobility, and speed of flight nodes, affect the performance of FANET. Furthermore, application scenarios and environmental settings could affect the performance of FANETs. In this paper, we analyzed the representative FANET protocols, AODV, DSDV, and OLSR, according to mobility models, SRWP, MP, RDPZ, EGM, and DPR, under the multi-UAV-based reconnaissance scenario. We evaluated them in terms of the number of nodes, network connectivity, mobility model’s reconnaissance rate, speed of nodes, and ground control station (GCS) location. As a result, we found that AODV showed the highest PDR performance (81%) with SRWP in multiple UAV-based reconnaissance scenarios. As for a mobility model under the consideration of reconnaissance rate, SRWP was excellent at 76%, and RDPZ and EGM mobility models were reasonable at 62% and 60%, respectively. We also made several interesting observations such as how when the number of nodes increases, the connectivity of the network increases, but the performance of the routing protocol decreases, and how the GCS location affects the PDR performance of the combination of routing protocols and mobility models.

A smart meter is an electronic device that accurately tracks your energy consumption and transmits that data to your energy provider so that you can be billed. The smart meters allow the central system and the meter to communicate in both directions. This two-way communication feature distinguishes the advanced metering infrastructure (AMI) in this case from automatic meter reading (AMR). This paper employs a hybrid system based on the Zigbee protocol, the Zigbee used to send messages between the smart meter and the utility company. To successfully complete tasks in this scenario, a cooperative communication system utilizing TDMA is used. The outcomes of Zigbee performance are measured using well-known metrics, also known as performance metrics. Many performance indicators have been chosen for performance evaluation: throughput, average end-to-end delivery ratio, and (PDR). The following conclusions were reached: End-to-end latency was 5.01 milliseconds, throughput was 42.63 kbps, and PDR was 97.19 percent. The network simulator successfully reads and wirelessly transmits voltage or power consumption using the Zigbee protocol and a cooperative communication system.

Internet of Things (IoT) is a new technology with multiple smart connected sensors capable of processing, storing, and computing. IIoT is used in industrial applications such as infrastructure, medical, logistics, and energy efficiency in smart grids. The network lifetime will be extended when sensor node energy usage is effectively controlled. This paper proposed a Multi-Layer Threshold Cluster-based Energy Efficient Low Power and Lossy Networks (MTCEE-LLN) protocol for IIoT devices to decrease the network data traffic, sensor node energy consumption and also extends the network lifetime. The proposed scheme works in three phases: 1) network creation, 2) intra clustering, 3) inter-cluster routing. The MTCEE-LLN forms equal-sized cluster in each transmission and elects the Cluster Head (CH). It maintains the Destination Oriented Directed Acyclic Graph (DODAG) to performs data transmission from the downward layer to the DODAGroot. Further, it aggregates the data packets in the cluster node to increases the network lifetime by reducing the number of redundant data packet transmissions. The proposed routing protocol has been evaluated based on different performance parameters such as Packet Loss Rate (PLR), Energy Consumption (EC), Control Packet Rate (CPR), and Node Failure Ratio. The simulated result proves its effectiveness compared to other traditional routing protocols.

We study the DAO induction attack, a new attack against IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL), the standard routing protocol for the Internet of Things (IoT). In the DAO induction attack, a compromised node in the network periodically transmits a special control message. Each of these crafted control messages induces many nodes in the network to transmit in response. We show that transmitting these unnecessary messages can significantly increase the power consumption of nodes, hence reduce the lifetime of battery-operated IoT devices. In addition, we show that the attack severely impacts end-to-end latency and packet delivery ratio, two important network performance metrics. For instance, in a network with 50 nodes, our simulation results show that the attack increases the average end-to-end latency and packet loss ratio by 410% and 260%, respectively. To counter the attack, we propose a lightweight solution. We show that our solution imposes no overhead when the network is in its normal operation (i.e., it is not under attack) and can quickly detect the attack even when the network experiences high packet loss rates.

Minimized and nearly deterministic end-to-end latency facilitates real-time data acquisition and actuator control. In addition, defined latency is an integral part of quality oriented service in order to get closer to the reliability of wired networks and at the same time take advantage of wireless networking. This paper introduces a QoS routing protocol capable of balancing power consumption between wireless sensor and actuator nodes while minimizing end-to-end latency. We introduce a TDMA scheme in the routed wireless network to enable defined latency and in addition it improves the energy efficiency by avoiding collisions which eliminates time and energy consuming retries. Our novel routing method allows latency and round-trip times to be calculated in advance. We implemented a demonstrator and show experimental results of a wireless sensor network with our proposed routing scheme.

Blockchain based cryptocurrencies have received great attention but long confirmation times of transactions hinder its adoption for micro-payments. Payment network is one of the solutions proposed to address the scalability issue. It transforms the problem into a routing problem by leveraging Hash Time Locked Contracts (HTLC). Payment networks possess unique characteristics to be considered when routing protocol is designed. Channels must stay balanced to have a sustainable network. In this paper, we present a payment network design that aims to keep the channels balanced by using a common weight policy across the network. We additionally utilize multi-point connection for unbalanced payment scenarios. The results show that we can keep the channels in the network more equally balanced compared to minimal fee approach and multiple connections from customers to stores increases the success ratio.

6G cellular networks bring about proactive communications with predictive decision making by incorporating artificial intelligence (AI) and machine learning (ML) in vehicular networks, towards envision of the Internet of Vehicles (IoV). Currently, vehicular communications suffer from unreliable communication links due to multi-hop ad-hoc communications and high mobility environment. The available literature falls short in providing a reliable routing scheme that proactively and accurately estimates or predicts connectivity duration between two vehicles. In this study, we highlight the need for communication route compatibility (connectivity duration) as a route selection parameter along with trustworthiness. We propose an ML and analytical compatibility-based ad-hoc routing protocol that allows a vehicle to estimate or predict the compatibility time of all candidate routes, to choose the best route. We evaluated one analytical and five ML classification techniques on our OpenStreemMap (OSM) and SUMO mobility trace generated dataset (Seoul and Berlin). Our exhaustive simulation demonstrated that our proposed scheme (six variations) dismisses all short-lived routes and achieves 2˜3 times higher packet delivery ratio in comparison to existing hop count-based routing (AOMDV and TCSR). The proposed scheme disregards paths having few intermediate nodes for long-lasting paths with the expenses of a few extra hops. We also present a comprehensive comparative study to evaluate ML techniques based on well-known metrics such as accuracy, time, misclassification, F1-score, etc.

Many organizations nowadays have multiple sites at different geographic locations. Typically, transmitting massive data among these sites relies on the interconnection service offered by ISPs. Segment Routing over IPv6 (SRv6) is a new simple and flexible source routing solution which could be leveraged to enhance interconnection services. Compared to traditional technologies, e.g., physical leased lines and MPLS-VPN, SRv6 can easily enable quick-launched interconnection services and significantly benefit from traffic engineering with SRv6-TE. To parse the SRv6 packet headers, however, hardware support and upgrade are needed for the conventional routers of ISP. In this paper, we study the problem of SRv6 incremental deployment to provide a more balanced interconnection service from a traffic engineering view. We formally formulate the problem as an SRID problem with integer programming. After transforming the SRID problem into a graph model, we propose two greedy methods considering short-term and long-term impacts with reinforcement learning, namely GSI and GLI. The experiment results using a public dataset demonstrate that both GSI and GLI can significantly reduce the maximum link utilization, where GLI achieves a saving of 59.1% against the default method.

Unmanned aerial vehicle (UAV) multi-hop communication networks are foreseen to be widely employed in both military and civilian scenarios. However, in ultra-dense scenarios with swarm UAVs, nodes are highly dynamic mobile, ultra-dense deployment and non-centralized distribution. These characteristics make the centralized resource management policy not apply. Meanwhile, existing routing protocols can't meet the performance challenges of high dynamic, topology and link frequency changes of ultra-dense scenarios with swarm UAVs. To solve the above challenges of resource management and routing protocol, a cross-layer optimization method is presented with a novel mean field game (MFG) in this paper. It is based on the cross-layer design method of the MFG theory and jointly considers the power resources in the physical layer, frequency resources in the medium access control (MAC) layer, and routing resources in the network layer. By dividing into subproblems, the original problem is solved. Meanwhile, the optimal data transmission path can be selected through the management and allocation of frequency resources and power resources. A crosslayer resource management dynamic source routing (CLRMDSR) protocol is designed based on that which adds link quality measurement. The simulation results show that the presented CLRM-DSR with the proposed resource management scheme can improve the data packet transmission rate, reduce end-toend delay, and lower routing overhead for the multi-hop swarm UAV communication network.

A mobile ad hoc network is a complicated distributed system organized by mobile terminals or wireless nodes through wireless connections. The mobile ad hoc network is suitable for those who lack basic communication equipment or do not have technical communication equipment, and the price is relatively high and impractical. It is agreed that the node can move and maintain the connection when connecting or leaving at any time. Wireless ad hoc network routing technology occupies an important position in wireless networks. First, wireless communication depends on wireless routing. At present, it is necessary to select an appropriate route for transmission on wireless communication. Therefore, routing of wireless ad hoc networks is the most important technology in wireless networks. Because the network is a free combination of mobile users, and the bandwidth of the wireless connection network is relatively limited. Network topology Since each node in the network can join or move freely, it is very important to find a link for forwarding data in a dynamic network. This article analyzes the common problems of hop count in MANET networks and compares the backbone of MANET. The wireless ad hoc network composed of DLA-GF algorithm and ant colony algorithm proposes an effective method to detect the routing in the wireless ad hoc network. Combined with route detection, the node sends multiple copies of the hop count packet to increase node communication Degree. The algorithm can effectively overcome the problem of ambiguity in the number of hops in wireless ad hoc networks, and achieve the effect of saving network energy and reducing power consumption.

In the era of IoT, the energy consumption of sensor nodes in WSN is one of the main challenges. It is crucial to reduce energy consumption due to the limited battery life of the sensor nodes. Recently, Zone-based Energy-Aware data coLlection (ZEAL) routing protocol is proposed to improve energy consumption and data delivery. In this paper, an enhancement to ZEAL is proposed to improve WSN performance in terms of energy consumption and data delivery. Enhanced ZEAL (E-ZEAL) applies the K-means clustering algorithm to find the optimal path for the mobile-sink node. As well, it provides better selections for sub-sink nodes. The experiments are performed using the ns-3 simulator. The performance of E-ZEAL is compared to ZEAL. E-ZEAL reduces the number of hops and distance by more than 50%, Leading to speed up the data-collection phase by more than 30% with complete delivery of data. Moreover, E-ZEAL improves the lifetime of the network by 30%.

Flying ad hoc networks (FANETs) have emanated over the last few years for numerous civil and military applications. Owing to underlying attributes such as a dynamic topology, node mobility in three-dimensional (3D) space, and the limited energy of unmanned aerial vehicles (UAVs), a routing protocol for FANETs is challenging to design. Exiting topology-based routing is unsuitable for highly dynamic FANETs. Location-based routing protocols can be preferred for FANETs owing to their scalability, but are based on one-hop neighbor information and do not contemplate the reachability of further appropriate nodes for forwarding. Owing to the rapid mobility of UAVs, the topology frequently changes; thus, some route entries in the routing table can become invalid and the next-hop nodes may be unavailable before a timeout. That is, the routing decision based on one-hop neighbors cannot assure a successful delivery. In this study, we propose a novel Q-learning-based topology-aware routing (QTAR) protocol for FANETs to provide reliable combinations between the source and destination. The proposed QTAR improves the routing decision by considering two-hop neighbor nodes, extending the local view of the network topology. With the Q-learning technique, QTAR adaptively adjusts the routing decision according to the network condition. Our simulation results reveal that QTAR outstrips the existing routing protocols in respect of various performance metrics under distinct scenarios.

An ad hoc network is a network made of movable nodes built on the fly and constructed dynamically when there is no longer an infrastructure or pre-built network on the scene. The nodes can also perform both end-to-end terminals and shape MANET roles, meaning they contribute to each route's configurations. The data must travel through several intermediate nodes during the route while routing a given flow from a source to a destination. The data should be larger than needed for just a single application use. The intermediate nodes forward data to the intended destination, taking into account the locations to which it must be sent to arrive correctly. The routing protocol in an Ad hoc network (human-made network) uses nodes to look at different device locations and procedures for any data path they choose before deciding on the route and ways in which they exchange data are viable. Anomaly, since the existing trust among the various nodes and dynamic topology, leaves the routing protocols susceptible to Denial of service attacks like a black hole, wormhole, Denial of service, and being non-integrated into a central infrastructure present a condition which MANETs are subject to such as Conventional networks typically work by injecting some control packets and tracking the target's movement once the user is already on the wireless. Still, in a MANET, the attacker acts before the mark has moved into the wireless medium. Maliciously exploiting various routing information has the potential to drive the system into a situation of more significant disorder, which will eventually lead to widespread network failure. This existing AODV attack, called the Blackhole attack, might have worked by purposefully withholding important routing information from end-users who could have benefitted from it, which is just what the adversary does in this task. In this scenario, the data packets are never delivered, and the system suffers a total data loss. The variety of detection and protection techniques employed against the blackhole attacker significantly lower the number of suspects. Therefore, this paper advocate for OSPFV [for wireless LANs] protocol integration with built-in security, where Threshold evaluation and cryptographic verification are employed. In this paper, two protocols: the blackhole attack and the proposed AODV-BS protocols, are simulated on different MANET models, and the two other network metrics are used: Network Packet Delivery Ratio and the normalized Out of Routing Overhead Utilization and Network Delay are calculated, and then their performance is studied to discover the result.

In underwater acoustic wireless sensor networks (UAWSNs), the conventional routing protocols continuously transmit data packets containing the same information when a source node detects an event of interest. This approach, however, leads to high energy consumption, high interference and challenges the stability of the network due to heavy data load on the nodes close to water surface. To overcome these challenges, this article proposes two routing protocols for UAWSNs. They are, SRRPV: stability-aware routing with restricted packets transmission and void-avoidance and LS-ACRPV: link and stability-aware adaptive cooperative routing with restricted packets transmission and void-avoidance. In SRRPV, a source node detects the event of interest, generates and routes packets. Subsequent packets routing is performed only when a change in intensity of the event is detected. Due to restricted packets transmission, three-hop connected paths with suitable neighbors are chosen to overcome the existence of a void (non-availability of a suitable forwarder) and, therefore, control packets loss. Moreover, the defined packet holding time ensures that nodes with the highest available energy transfer the most packets by holding the packets for the shortest interval of time. This strategy, in combination with restricted packets transmission, achieves network stability. Since limited number of packets are routed, the LS-ACRPV protocol is designed that adds reliability to the SRRPV protocol by selecting a routing link with the highest probability of successfully delivering packets to the destination or using adaptive cooperative routing to combat severe link conditions. Unlike the conventional protocols, the proposed protocols do not require the geographical position coordinates of nodes, which is challenging in underwater environment as nodes change their positions with sea tides and currents. Extensive simulation results reveal promising performance of the proposed schemes in terms of energy expenditure, delay and network stability at the expense of low packets delivery due to restricted packets transmission.

VANET (Vehicular Ad-hoc NETwork) is a wireless network technology that uses vehicles as mobile nodes to exchange data without the need for a Central Access (CA) point, which is used for safety problems. In this, the vehicles (node) transmit data about traffic and road conditions. Because of the latest advances in information technologies, it is now important to take the first step toward using software to evaluate this network prior to deployment. By implementing the network in a real-world environment, we can use simulation software to perform a detailed review of it. There are various network simulators, each with its own collection of features that set it apart from the others. We should concentrate on finding the right alternative that yields the best outcomes. NS2 is the most commonly used simulator tools; in this paper, we used NS2 to build the VANET, which allowed communication between nodes using AODV routing protocols. By changing the number of vehicles when applying TCP traffic, we use routing protocols (AODV) for various standard metrics, such as Cumulative Sum of Packet, throughput, jitter, and packet loss. The simulation was carried out using the NS2 simulation tool. Different mobility models would be considered in order to make the network situation more realistic. In this paper, we used Five forms of mobility patterns using 10, 20, 30, 40, and 50 vehicle nodes. On NS2, we drafted a TCL script to verify the affectations of the routing protocols used in the VANET. After successfully run, we conclude that the Cumulative Sum of Packet gets less forwarded to the destination, throughput is high in case of sent Packet, Jitter gets stable at last, and the most important is that there is no loss of any packet from Source to Destination.

The routing protocols are considered to be the backbone of the network communication. Each protocol has its outlined algorithmic program that decides the routing choices for the designated router. The Routing Information Protocol comes under category of Distance Vector Routing Protocol and is related to several dimensions, that define the scope of improvement also, in RIP. In this paper, a detailed analysis of RIP has been done, appended with the implementation in Packet Tracer. This analysis is augmented with the insight into the Interior Border Gateway Protocol and concluded with their comparative analysis.

Considering the high mobility and uneven distribution of vehicles, an efficient routing protocol should avoid that the sent packets are forwarded within road segments with ultra-low density or serious data congestion in vehicular networks. To this end, in this paper, we propose a Traffic aware and Link Quality sensitive Routing Protocol (TLRP) for urban Internet of Vehicles (IoV). First, we design a novel routing metric, i.e., Link Transmission Quality (LTQ), to account for the impact of the number, quality and relative positions of communication links along a routing path on the network performance. Then, to adapt to the dynamic characteristics of IoV, a road weight evaluation scheme is presented to assess each road segment using the real-time traffic and link information quantified by the LTQ. Next, the path with the lowest aggregated weight is selected as the routing candidate. Extensive simulations demonstrate that our proposed protocol achieves significant performance improvements compared to the state-of-the-art protocol MM-GPSR, the typical junction-based scheme E-GyTAR, and the classic connectivity-based routing iCAR, in terms of packet delivery ratio and average transmission delay.

Highly dynamic networks face frequent topological changes. In such a network, traditional routing protocols are inefficient and even impractical, as they need to detect network topology and update locations frequently. To mitigate this problem, this paper puts forward a location-based opportunistic geographic routing (LOGR) protocol, an opportunistic packet transmission mechanism based on geographic locations. In most traditional routing protocols, the forwarding nodes are selected in advance. In the proposed protocol, the sending node does not know which is the next-hop node. Instead, the sending node broadcasts the forwarding rules and the data packet together, utilizing the broadcast nature of wireless transmission. Then, each node receiving the packet will judge whether it has the right to forward the packet, according to the preset rules. Another difference between our protocol and common protocols lies in the priority assignment of opportunistic forwarding. In common protocols, all candidate forwarding nodes are ranked in turn. In our protocol, the absolute priority method is adopted, such that any candidate receiving the packet can derive its own priority from its location information and forwarding rules, and determine the forwarding time, without knowing the information of other candidates. In this way, our protocol eliminates the need for topology detection or location update, and avoids the huge network overhead incurred in pairwise comparison of nodes for priority assignment. Therefore, unlike traditional protocols constrained by network scale and network topology, our protocol can better adapt to the frequent topology change in the highly dynamic network Experimental results show that the LOGR protocol worked effectively on the network containing fast moving nodes, and, in the same environment, the network performed much better under the LOGR protocol than under traditional routing protocols.