Packet Routing Research Articles

An Intelligent Routing Frame Work for High Traffic Networks using Deep Learning

The advent of internet usage and technological advancements has resulted in the exponential growth of network traffic, further aggravating this problem by presenting significant challenges in multiple aspects, from managing a network to routing. Traditional routing cannot handle these very high-traffic networks, which causes bottlenecks and network congestion. In this paper, we present a deep learning-based intelligent routing model to solve the above problem. In this context, a deep learning algorithm is applied to analyze the network traffic patterns and predict the routing of data packets assembled at other stations on the fly on the fly. It even dynamically modifies routing decisions, considering network topology, link capacity, and traffic load. It could be continuous training of the deep learning model with fresh data or online updates to a pre-trained model so that shifts in network conditions can be continuously accounted for. We also allow the deep learning model to have some form of memory and use it to learn from its past decisions. Additionally, the framework will come equipped with a network monitoring system to gather and filter data to discover potential network problems and proactively take routing decision changes.

Mitigation of Risks Associated with Distrustful Routers in OSPF Networks—An Enhanced Method

Packet routing in computer networks provides complex challenges in environments with distrustful routers due to security vulnerabilities or potential malicious behaviors. The literature offers solutions to the problem designed for different types of networks. This paper introduces a novel method to mitigate risks associated with distrustful routers by constructing secure and efficient routing paths in Open Shortest Path First (OSPF) networks. Networks in which routing is carried out based on OSPF protocols are currently the most widespread, hence ensuring the security of data transmission in such networks is urgently needed. In turn, distrustful routers can degrade the overall security and performance of the network, creating vulnerabilities that can be used for malicious purposes. The proposed method is based on the Dijkstra algorithm which is enhanced to identify and mitigate the risk connected with potential distrustful network nodes. Analysis of the proposed method shows its ability to build efficient routes exclusively through trusted routers if such paths exist. As a criterion for effectiveness, a metric such as the channel weight is used. The proposed method is validated using applications across networks of varying topologies and sizes, including large-scale networks. For networks containing post-distrustful routers to which there is no path without distrustful nodes, the proposed method is able to build the shortest paths that are marked as not secure but have a minimum number of distrustful nodes on their path. In scenarios with multiple compromised routers with different locations in the network, the proposed method significantly increases network resilience.

A Descriptive Study on Interconnection Networks for Parallel Computing and Algorithm Models in Parallel Computing

In parallel computing, Interconnection networks are very crucial for efficient communication among all processors within a similar system. Parallel computing has become a crucial topic in the concern of computer science and also it is revealed to be critical when researching in high performance. The evolution of computer architectures towards an improved number of nodes, where parallelism could be the approach to option for speeding up an algorithm within the last few decades. Efficient data transfer between processors is an essential component in any large scale parallel computation. Motivated by the growing interest in parallel computers, a significant amount of theoretical research has been devoted to the area of interconnection networks for parallel computers, most of it to the packet routing (or store-and-forward) model of communication. We survey some of the major developments in this field, and discuss several new alternative models of communication, In many large scale applications, communication time dominates the execution time of the whole parallel computation. Thus, the performance of a large scale parallel computer is highly correlated with the efficiency of its network and communication algorithm. The combination of processing units build a model of computation (circuits) has gained an essential place in the area of high performance computing (HPC) due to its configuration and considerable processing supremacy that is parallel, series, etc. The aim of the Presenting this paper is study on the idea of parallel computing and its programming models and also explore some theoretical and technical concepts which can be often needed to understand the Interconnection network. In particular, we show how this technology is new in assisting the field of computational physics, especially when the issue is data parallel. In the real-life example of parallel computing, there are two queues to get a ticket of anything; if two cashiers are giving tickets to 2 persons simultaneously, it helps to save time as well as reduce complexity

W-GPSR Routing Based on Mobility Prediction for Vehicular Ad-Hoc Network (VANET)

In recent years, Vehicular Ad-Hoc Networks (VANETs) innovation has been regarded as a significant research area. This is owing to the increasing popularity of vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communications in the area of Intelligent Transportation System (ITS) to improve traffic management, safety, CO2 emission mitigation, and other applications. A variety of routing protocols for VANETs are being recently developed. More specifically, geographic-based routing algorithms such as Greedy Perimeter Stateless Routing (GPSR) have provoked the most interest in VANETs due to their compatibility with a regularly changing network structure and the highly unsteady nature of automobile nodes. This paper proposes an efficient weight based mobility method in VANET to improve the mechanism of the GPSR protocol through optimizing the greedy forwarding strategy; which is so called O-Greedy Mode. Therefore, the key goal is to achieve the optimal data forwarding paths. The next hop is determined by estimating the neighbors' mobility based on each neighbor's Greedy Link Weight Factor (GLWF). The Weighted GPSR (W-GPSR) based on Mobility Prediction is then evaluated using OMNeT++ simulator with Inet, Veins and SUMO traffic simulator. The results demonstrate the efficiency of W-GPSR in contrast with the traditional existing protocols for essential metrics of Packet Delivery Ratio (PDR), throughput, End-to-End Delay (E2ED), Normalized Routing Load (NRL) and Packet Loss Ratio (PLR).

An upgraded IoT based Mobile Ad- hoc Network enactment founded on optimized Signal Strength Based Routing algorithm

It is a wireless network with mobile nodes that function independently and communicate with one another with radio waves. When a node gets a packet, they evaluate all of the possible routes before selecting the optimal one. In this way, the capabilities of routing are incorporated into each node of the network. Researchers used ant colonies to find the best path between two sites. The Simple Ant Routing Protocol has improved with the assistant of Internet of Things (IoT). Energy Aware Simple Ant Routing Algorithm (EASARA), a new protocol, considers each node's energy usage. The change improved routing overhead and packet delivery ratio. It also improved communication. EASARA performed better with more hosts. Traffic congestion statistics followed. One parameter estimated host power reserve and connection congestion. Energy-congestion conscious protocol is basic routing algorithm is ECSARA (Energy-congestion based Simple Ant Routing Algorithm). The protocol improves with more hosts. It sends packets faster. Hence, transmission data transfer increased. Energy savings extended the route's lifespan. Signal strength predicted connection failures. This metric chooses a new route. Signal-to-Anchor-Receiver-Attendance based Simple Ant Routing Algorithm is SS-SARA. All host monitors detected strong signals. Communication uses substitute pathways when signal strength goes below a threshold. The protocol improved packet delivery and throughput on congested networks, according to experiments.

An Optimized Transmission Mechanism for Mitigating Jamming Attacks in Multi-Hop Wireless Networks

Aim: To address the vulnerability of Multi-Hop Wireless Network Systems (MHWNs) to jamming attacks and propose an effective solution to maintain communication integrity and Quality of Service (QoS). Background: In MHWNs, the open-access nature makes them susceptible to jamming attacks, which disrupt communication by interfering with authenticated nodes in the wireless medium. Existing methods primarily focus on tracking and countering jammers but lack effectiveness in preventing communication disruptions. Objective: The objective of this study is to introduce a novel algorithm, Optimized Transmission Mechanism (OTM), to mitigate the impact of jamming attacks on MHWNs. OTM aims to optimize node handover and packet routing to bypass jammed areas, ensuring uninterrupted packet transmission and preserving QoS. Methods: The proposed OTM algorithm determines the optimal transmission route based on radio transmitter location and connection quality. It prioritizes routes with the highest connection quality to maintain QoS even in jammed conditions. Additionally, it incorporates mechanisms for packet redirection away from jammed areas to ensure successful transmission. Results: Evaluation of the Extended Optimized Transmission Mechanism (EOTM) demonstrates significant improvements in packet delivery performance compared to existing algorithms. The enhanced algorithm effectively mitigates the impact of jamming attacks, ensuring reliable communication and preserving QoS in MHWNs. Conclusion: The proposed OTM algorithm presents a promising approach to counter-jamming attacks in MHWNs by dynamically routing packets to avoid jammed areas and maintain communication integrity. The results highlight the effectiveness of EOTM in improving packet delivery performance and ensuring uninterrupted communication in the face of jamming threats.

Quantum networks with coherent routing of information through multiple nodes

Large-scale communication networks, such as the Internet, rely on routing packets of data through multiple intermediate nodes to transmit information from a sender to a receiver. In this paper, we develop a model of a quantum communication network that routes information simultaneously along multiple paths passing through intermediate stations. We demonstrate that a quantum routing approach can in principle extend the distance over which information can be transmitted reliably. Surprisingly, the benefit of quantum routing also applies to the transmission of classical information: even if the transmitted data is purely classical, delocalising it on multiple routes can enhance the achievable transmission distance. Our findings highlight the potential of a future quantum internet not only for achieving secure quantum communication and distributed quantum computing but also for extending the range of classical data transmission.

Method of designing a cyber-resilient information and communication network

The proposed method for designing a cyber-resilient information and communication network (ICN) is based on solving an optimization problem related to the mutually coordinated calculation of various control variables responsible for choosing the network topology; the order of connecting access networks to ICN core routers; determining the characteristics of the equipment used in terms of its performance and security level; determining the order of routing packet flows. The method assumes that the locations of the probable placement of network routers are known in advance. Due to the synthesized mathematical model, the method provides not a sequential but a simultaneous solution to the primary design tasks, which significantly affects the level of efficiency of the final solutions. The mathematical model on which the developed design method is based is mostly linear. Only the conditions for preventing the overloading of communication links (router interfaces) are non-linear. The cyber resilience of design solutions is ensured by the fact that in the objective function to be minimized, the weighting coefficients, along with cost and quality of service indicators, should also consider network (information) security indicators – the compromise probability or information security risks of network equipment. This will make it possible to synthesize a network with specified or predicted cyber resilience indicators. Prospects for further research in this area are related to the introduction of a mathematical model and a method for designing conditions for ensuring guaranteed quality of service, which will allow only the requirements for the level of cyber resilience to be taken into account at the level of the optimality criterion. On the other hand, an attempt to move to a linear version of the conditions for preventing communication link overload is a certain direction of model improvement, which will somewhat reduce the computational complexity of calculations related to the determination of a large number of control variables.

FRR: A Fast Routing Recovery mechanism minimizing network formation time in smart grids

In recent years, Internet of Things (IoT) technologies have been applied to the most diverse types of applications, highlighting their use in Smart Grids (SGs), such as smart metering, demand response, fault detection and renewable energy integration, as well as in Smart Cities, such as smart lighting, smart parking and environmental monitoring. A technology that has been widely used in these contexts is the Wireless Smart Ubiquitous Networks Field Area Network (Wi-SUN FAN) standard, which defines the implementation and behavior of interoperable networks based on open standards such as IEEE 802.15.4 and the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL). The adopted standards allow Wi-SUN FAN networks to take advantage of features such as security, frequency hopping, multi-hop packet routing, and IPv6 addressing, ensuring a wide coverage area and immunity against electromagnetic interference. Despite all the advantages, a shortcoming of Wi-SUN FAN networks is the long network formation time. In this article, we propose a mechanism called Fast Routing Recovery (FRR), which aims to accelerate the reconnection process in networks that use the RPL protocol by memorizing information about the nodes’ preferred parents. We evaluate the FRR mechanism by simulations and experiments. The results indicate that FRR can reduce the network formation time by up to 50% in certain network scenarios.

Research on AUV Multi-Node Networking Communication Based on Underwater Electric Field CSMA/CA Channel.

To address the issues of high attenuation, weak reception signal, and channel blockage in the current electric field communication of underwater robots, research on autonomous underwater vehicle (AUV) multi-node networking communication based on underwater electric field Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) channel was conducted. This article, first through simulation, finds that the Optimized Link State Routing (OLSR) protocol has a smaller routing packet delay time and higher reliability compared to the Ad Hoc On-Demand Distance Vector (AODV) protocol on underwater electric field CSMA/CA channels. Then, a 2FSK underwater electric field communication system was established, and dynamic communication experiments were carried out between two AUV nodes. The experimental results showed that within a range of 0 to 3.5 m, this system can achieve underwater dynamic electric field communication with a bit error rate of 0 to 0.628%. Finally, to avoid channel blockage during underwater AUV multi-node communication, this article proposes a dynamic backoff method for AUV multi-node communication based on CSMA/CA. This system can achieve dynamic multi-node communication of underwater electric fields with an error rate ranging from 0 to 0.96%. The research results have engineering application prospects for underwater cluster operations.

Provable Security for the Onion Routing and Mix Network Packet Format Sphinx

Onion routing and mix networks are fundamental concepts to provide users with anonymous access to the Internet. Various corresponding solutions rely on the Sphinx packet format. However, flaws in Sphinx's underlying proof strategy were found recently. It is thus currently unclear which guarantees Sphinx actually provides, and, even worse, there is no suitable proof strategy available. In this paper, we restore the security foundation for all these works by building an analytical framework for Sphinx. We discover that the previously-used Decisional Diffie-Hellman (DDH) assumption is insufficient for a security proof and show that the Gap Diffie-Hellman (GDH) assumption is required instead. We apply it to prove that a slightly adapted version of the Sphinx packet format is secure under the GDH assumption. We are thus, to the best of our knowledge, the first to provide a detailed, in-depth security proof for Sphinx that holds. Our adaptations to Sphinx are necessary, as we demonstrate with an attack on sender privacy that would otherwise be possible in Sphinx's adversary model.

Multi-objective-derived efficient energy saving in multipath routing for mobile ad hoc networks with the modified aquila–firefly heuristic strategy

Mobile ad hoc networks (MANETs) suffer from a major problem with the energy drainage of network nodes, as the mobile nodes rely on batteries and do not have a permanent power supply. Therefore, a new multipath routing technique, using a novel hybrid heuristic algorithm, is designed to solve the diverse metrics of a multi-objective function, including energy consumption, distance, routing overhead ratio, throughput, end-to-end delay and packet delivery ratio. This approach implements a new hybrid algorithm termed the modified aquila–firefly heuristic strategy (MA-FHS), which integrates the aquila optimizer and the firefly algorithm. This derived fitness function is applied to achieve optimal paths in multipath routing with minimization of the multi-objective function. The simulation demonstrates that the developed routing protocols outperformed traditional protocols under several network constraints.

Neuro‐fuzzy‐based cluster formation scheme for energy‐efficient data routing in IOT‐enabled WSN

SummaryInternet of things–enabled wireless sensor networks face challenges like inflexibility, poor scalability, suboptimal cluster head selection, and energy inefficiencies. This is due to the faster data transmission rates between cluster nodes during data packet routing. This creates unnecessary energy consumption burdens for those actively transmitting nodes. Conceptually, an effective cluster formation phase supports better data routing mechanisms, while sustaining the energy efficiency of individual nodes. This paper proposes a Neuro‐Fuzzy based Cluster Formation (NFCF) scheme to facilitate adaptive and energy‐efficient cluster topologies. NFCF utilizes fuzzy logic and neural networks to identify optimal super nodes for flexible cluster formations. This approach enables configurable cluster sizes along with inclusion/exclusion criteria for member nodes based on energy thresholds. Parameters evaluated for node selection include the degree of super node, expected energy per cluster, energy variance, and residual energy. Nodes not meeting the thresholds are excluded. The neural network updates fuzzy rules to guide optimal clustering decisions based on anticipated energy dynamics under different conditions. The performance of the proposed NFCF scheme is evaluated based on objective function changes related to data transmission, individual node energy variation, energy variance before and after transmissions, and averaged end‐to‐end delay across transmission cycles. Results are compared against genetic fuzzy clustering, fuzzy energy‐aware clustering, fuzzy‐based distributed clustering, fuzzy logic‐based multi‐hop clustering, and fuzzy weighted k‐means clustering.

Bio-inspired wireless sensor networks - a protocol for an enhanced hybrid energy optimization routing

Recently, there has been a focus on the significance of swarm intelligence-inspired routing algorithms for achieving optimum solutions in biologically inspired wireless sensor networks (WSNs). These protocols depict a network of wireless mobile nodes forming an infrastructure that is agile, dynamic, and independent of a central administrative facility. Among the challenges faced by bio-inspired WSNs, mobility awareness and excessive energy consumption (EC) stand out as significant hurdles, particularly in dynamic models with intermittent connections. This project seeks to tackle these obstacles by deploying the hybrid energy efficiency (HEED) approach to distributed clustering for network system cluster formation, along with fusion routing protocol of particle swarm optimization (PSO) and PIO to select cluster-heads and optimize solutions in bio-inspired WSNs. The success of the suggested approach is assessed using a variety of criteria, such as energy usage, rate of packet delivery, EC, and routing overhead and network lifetime. The methods like ad hoc on-demand distance vector's (AODV) and ant colony optimization (ACO) methods are employed in the testing and validation. In comparison to the reactive AODV routing protocol and ACO, the suggested routing protocol (HPSOPIO) reduces energy usage and increases network lifespan.

Analysis of ANN Routing Method on Integrated IOT with WSN

Internet of Things (IoT) in recent times offers a greater amount of flexible design during the deployment of it in the form of network. The interfacing of IoT with a wireless sensor network (WSN) requires an optimal solution to preserve the consumption of energy while the data has been transmitted via nodes. In this paper, we develop machine learning (ML)-assisted routing to route the data packets of IoT sensors from the real-time environment over WSN. In this study, we use three different planes for optimal routing of packets from the source node to the destination node. The source node is the IoT sensors that involve data collection, and the intermediate nodes are the WSN sensor nodes that route the packets. Optimal routing decisions based on the pre-trained data in an artificial neural network (ANN) stabilize the routing of data packets without congestion. The simulation is conducted to test the efficacy of the ANN routing in the integrated network, and the results show that the ANN-based routing achieves higher energy efficiency and throughput than other models.

A Comprehensive Review on Cluster-Oriented Routing Protocols for Underwater Wireless Sensor Networks

Underwater Wireless Sensor Networks (UWSNs) have emerged for various tasks in marine environments. Routing Protocols (RPs) in UWSNs face challenges such as high propagation delay, Energy Consumption (EC), low bandwidth, and low throughput compared to Terrestrial WSNs (TWSNs). UWSNs operate autonomously without human intervention, and the limited energy of sensor batteries poses a significant challenge. Uneven energy resource utilization reduces network longevity, which is a major issue in UWSNs. To combat these issues, a promising approach involves the design of RPs employing clusters for efficient packet routing from source to destination. This paper systematically reviews recent Cluster-oriented RPs (CRPs) in UWSNs, organizing them chronologically. It assesses their merits, drawbacks, and overall network performance, offering insights into future directions for improvement in this domain

Secured osprey-based energy efficient routing and congestion control in WSN

An adaptive metaheuristic optimization-based QoS-aware, Energy-balancing, Secure Routing Protocol (AQoS-ESRP) is proposed in this article. The network is modelled as a biconcentric hexagon (BiCon-HexA), and the clusters are formed within the BiCon-HexA network. The BiCon-HexA is divided into six sectors to support effective data aggregation, and then clusters are formed within all sectors. The optimal cluster head (CH) selection mechanism is modelled by an Adaptive Hunter-Prey Optimization (AdapH-PO) algorithm considering QoS parameters. Data aggregation is then done securely with an enhanced encryption approach. Here, upgraded elliptic curve cryptography (UEllip-CC) is used to encode data in CH. This UEllip-CC approach provides security improvements in data transmission. Furthermore, in this study, CHs are combined in the multi-hop routing of data packets to reduce the power consumption problems of wireless sensor networks (WSN). To determine the optimal route for data transmission, an energy-balanced multi-path routing algorithm called improved convolutional osprey network (ICON) is presented. Nevertheless, the data transmission nodes can be overloaded in the data routing phase. Here, the congestion problem can be solved by applying an improved version of the Random Early Detection (RED) congestion control model to discard the data packets more noticeably. The simulation of AQoS-ESRP is done with Matlab, and the performance is evaluated using different metrics. When compared to existing systems, the simulation results clearly indicate a significantly higher throughput and delay. Thus, the AQoS ESRP model is employed to maximize the overall data transfer in the WSN.

Secure Patient Data Monitoring and Efficient Routing Optimization using a Hyperelliptic Curve Cryptography with Fuzzy-based Priority in WBSN

Aims and Background: Wireless Body Sensor Network (WBSN) technology is one of the major research areas in the medical and entertainment industries. A wireless sensor network (WSN) is a dense sensor network that senses environmental conditions, processes, and outgoing data at the sink node. A WBSN develops patient monitoring systems that provide the flexibility and mobility needed to monitor patient health. In data communications, it is difficult to find flexible optical routing paths, switching capabilities, and packet processing in the composition of optical networks. Information-centric networks (ICNs) are a new network model and are different from information- centric models. The priority of the information-centric model is the communication network. Objectives: In the existing literature, such methods are typically developed using computationally expensive procedures, such as bilinear pairing, elliptic curve operations, etc., which are unsuitable for biomedical devices with limited resources. Using the concept of hyperelliptic curve cryptography (HECC), we propose a new solution: a smart card-based two-factor mutual authentication scheme. In this new scheme, HECC’s finest properties, such as compact parameters and key sizes, are utilized to enhance the real-time performance of an IoT-based TMIS system. Methodology: A fuzzy–based Priority Aware Data Sharing (FPADS) method is introduced to schedule the priority data and monitor the transmission length. The child node adjusts the transmission speed of the cluster head with the help of a fuzzy logic controller (FLC). Results: The proposed model estimated the traffic load of the child node and the priority of the different amounts of data to be transmitted. The principle of scheduling data packets to be developed is based on the precedence of the data with the lowest transmit length in the network. Conclusion: The proposed FPADS performance increases in terms of scheduling time utilisation, traffic distribution, and mean delay. Simulations have been done using NS2, and the outcomes have shown that the proposed methodology is efficient and improves the overall QoS of the system.

Evaluating the Advantages and Disadvantages of Transition Technologies for IPv6 in the Context of IPv4-as-a-Service

The shift towards IPv6 has led to the emergence of various IPv4-as-a-Service (IPv4aaS) transition technologies that allow the provisioning of IPv4 connectivity over IPv6 networks. The six main IPv4aaS mechanisms – 464XLAT, DS-Lite, Lightweight 4over6, MAP-E, MAP-T, and D4across6 – are compared in this study. We assess these protocols’ performance under a range of network situations using detailed simulation modeling in the ns-3 network simulator. With 100 nodes, we simulate an ISP-scale network architecture. We then configure several routing protocols, traffic patterns, connection delays, and implement each protocol according to its request for proposals. Different random seeds are used for each simulation run, and variables like packet sizes, routing protocols, and traffic loads are varied. The key performance parameters that are gathered are protocol overhead, packet loss, delay, and throughput. Important insights into the workings of each mechanism and how they tackle the problems of coexisting IPv4 and IPv6 under various network circumstances are provided by our thorough examination. The findings demonstrate how much better 464XLAT and D4across6 perform in most situations in terms of low latency, high throughput, minimal packet loss, and low overhead. This site may help network operators locate IPv4aaS solutions that meet their requirements and implementation procedures. Networking must alter transition technologies. This study improves comprehension of IPv4aaS protocols via trustworthy simulations.

Federated Learning-Based Security Attack Detection for Multi-Controller Software-Defined Networks

A revolutionary concept of Multi-controller Software-Defined Networking (MC-SDN) is a promising structure for pursuing an evolving complex and expansive large-scale modern network environment. Despite the rich operational flexibility of MC-SDN, it is imperative to protect the network deployment against potential vulnerabilities that lead to misuse and malicious activities on data planes. The security holes in the MC-SDN significantly impact network survivability, and subsequently, the data plane is vulnerable to potential security threats and unintended consequences. Accordingly, this work intends to design a Federated learning-based Security (FedSec) strategy that detects the MC-SDN attack. The FedSec ensures packet routing services among the nodes by maintaining a flow table frequently updated according to the global model knowledge. By executing the FedSec algorithm only on the network-centric nodes selected based on importance measurements, the FedSec reduces the system complexity and enhances attack detection and classification accuracy. Finally, the experimental results illustrate the significance of the proposed FedSec strategy regarding various metrics.