Routing Table Research Articles

On the aggregation of FIBs at ICN routers using routing strategy

Utilizing in-network caching is essential for the current communication network. In the last decade, ICN (Information-Centric Networking) has been under the spotlight as a network that mainly focuses on transmitted and received data rather than on hosts that transmit and receive data. In ICNs, to appropriately forward request packets, a router maintains a routing table called FIB (Forwarding Information Base). However, it is unsuitable for us to assume that FIB can store entries of all contents within a network. This is mainly because the FIB memory is not large enough to store the prefix of all contents. Thus, for realizing global-scale ICNs, it is crucial to develop an effective technique to reduce the size of FIB. In this paper, to tackle the reduction in the FIB size with the aggregation, we propose a routing strategy called constrained shortest-path tree (CSPT) routing. The fundamental idea of our CSPT routing is to combine shortest-paths on the network and that on a shortest-path tree of the network, which is intended to enhance the effect of FIB aggregation. Furthermore, we extensively investigate the relationship, i.e., trade-off, between the FIB aggregation and the communication performance of ICN using CSPT routing. Consequently, we reveal that our CSPT routing can dramatically reduce the number of FIB entries while suppressing the increase in the number of hops required to deliver request packets.

Utilizing a Routing Table of Proactive MANET Routing Protocol to Monitor a Group of People Mobility

Utilizing a Routing Table of Proactive MANET Routing Protocol to Monitor a Group of People Mobility

A energy efficiency optimization routing processing method for Linear Wireless Sensor Networks

Linear wireless Sensor networks (LWSNs) are extensively utilized to monitor linear infrastructure such as railways, bridges, mines, and borders. In the large-scale deployment of sensor networks, extending network life and improving network energy balance remains a significant challenge. The existing routing protocols adopt the path planning method based on the routing information database, which can effectively transmit data packets. However, the methods consume additional energy when establishing and maintaining routing tables, significantly reducing the nodes’ lifespan and leading to unstable data transmission quality. This paper proposes a dynamic random multipath routing method (DRMRM) for LWSNs. The technique combines the node depth and residual energy models to select the optimal next-hop relay node without relying on the transmission routing table. At the same time, we designed a data loss retransmission mechanism and a data loop retreat mechanism to prevent data packets from reaching a dead end. The experimental results demonstrate that our routing method is superior to existing energy consumption balance and network lifespan protocols.

MaP: Increasing node capacity of programmable cloud gateways

Virtual routing table lookup is a crucial operation in multi-tenant cloud gateways, the essential devices to enable the elastic management of Virtual Private Clouds (VPCs). However, software-based cloud gateways face performance bottlenecks when handling ever-increasing traffic. To address this challenge, a recent trend involves accelerating virtual routing table lookups using programmable switches, with Sailfish being the state-of-the-art solution. Nonetheless, Sailfish’s table scale on a single programmable switch is limited by the ASIC memory sizes. We introduce a novel scheme, named MaP (Merge and Partition), to significantly increase the memory efficiency on a single Tofino 1.0 programmable switch. MaP exploits the similarities in routing table entries across various VPCs for table compression and leverages the hardware architecture of programmable chips to minimize the memory occupancy. Performance evaluations using real-world virtual routing tables demonstrate that our approach reduces the memory cost from 25% to 47.7% compared to Sailfish, without negatively impacting the throughput and latency. With MaP, a single programmable switch can manage a massive table containing over 2 million entries for nearly 1 million VPCs, while only occupying 59.0% of memory and 63.0% of stages.

CMAF: Context and Mobility-Aware Forwarding Model for V-NDN

Content dissemination in Vehicular Ad hoc Networks (VANET) is a challenging topic due to the high mobility of nodes, resulting in the difficulty of keeping routing tables updated. State-of-the-art proposals overcome this problem by avoiding the management of routing tables but resort to the so-called table of neighbors (NT) from which a next-hop is selected. However, NTs also require updating. For this purpose, some solutions resort to broadcasting beacons. We propose a Context- and Mobility-Aware Forwarding (CMAF) strategy that resorts to a Short-Term Mobility Prediction—STMP—algorithm, for keeping the NT updated. CMAF is based in Named Data Networking (NDN) and works in two modes, Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I). V2V CMAF leverages the overheard packets to extract mobility information used to manage NT and feed the STMP algorithm. V2I CMAF also uses a controlled and less frequent beaconing, initially from the Road-Side Units (RSUs), for a further refinement of the predictions from STMP. Results from extensive simulations show that CMAF presents superior performance when compared to the state of the art. In both modes, V2V and V2I (with one beacon broadcast every 10 s) present 5–10% higher Interest Satisfaction Ratio (ISR) than those of CCLF for the same overhead, at a cost of 1 s of increased Interest Satisfaction Delay (ISD). Moreover, the number of retransmissions of CMAF is also comparatively low for relatively the same number of hops. Compared to VNDN and Multicast, CMAF presents fewer retransmissions and 10% to 45% higher ISR with an increased overhead of about 20%.

Secure Routing and Reliable Packets Transmission In MANET Using Fast Recursive Transfer Algorithm

Mobile Ad-hoc Network (MANET) autonomous operation can be multi-hop it is the infrastructure-less wireless network. Security is one of the biggest challenges in Mobile Adhoc Network. The MANETs security there are considerations must be so that the routing protocol in order to protect the secure data transmission. In the routing and security that is an important aspect for in a MANETs, existing method routing protocol, however, is not enough to security requirements. The proposed method using Fast Recursive Transmission Algorithm (FRTA) used designed to maximize the data security, routing optimization, minimizing the impact of malicious attack using Collision Detection Avoid Algorithm (CDAA) activity over the MANET and select the best path. Table-driven routing protocols, also known as proactive routing protocols, mandate that every node on the network keep up-to-date routing data. To maintain consistent routing information for network nodes, these protocols propagate frequent updates to the routing table throughout the network, necessitating changes to the network topology. There's a lot of overhead from these upgrades. The suggested FRTA algorithm lowers node data loss rates and increases network energy efficiency. Table-driven routing protocols, also known as proactive routing protocols, mandate that every node on the network keep up-to-date routing data. To maintain consistent routing information for network nodes, these protocols propagate frequent updates to the routing table throughout the network, necessitating changes to the network topology. There's a lot of overhead from these upgrades. The suggested FRTA algorithm lowers node data loss rates and increases network energy efficiency. The proposed method shows high performance than other existing evaluations of the most advanced security and routing energy, end-to-end delay, packet transfer rate, packet loss

Routing protocols for B2B e-commerce logistics in cyber-physical internet (CPI)

Currently, the boom in B2B e-commerce logistics and the fragmentation of logistics networks have put tremendous pressure on the efficient and economical routing of packages. The idea of the cyber-physical internet (CPI) in logistics is to establish a new paradigm for sending and receiving goods, similar to how sending and receiving instant messages over the internet might be a solution. This work focuses on the routing process in B2B e-commerce logistics driven by the CPI. A framework of B2B e-commerce logistics in CPI networks is proposed to integrate logistics networks with components such as CPI routers, routing tables, and autonomous logistics systems (ALSs). Routing protocols within and among ALSs are proposed for making routing decisions based on information in routing tables for efficient and economical routing. Finally, two B2B e-commerce logistics scenarios are utilized to simulate the routing protocols in CPI networks to prove their feasibility, and their sensitivity is analysed. This work may support the improvement of B2B e-commerce logistics networks and intelligent logistics in Industry 4.0.

Galor: Global view assisted localized fine-grained routing for LEO satellite networks

Low Earth Orbit (LEO) satellite networks have been expected to provide global coverage for Internet services with immediacy requirements. The dynamics of an LEO satellite network topology induce the challenges of achieving efficient content retrieval. This article takes an initial step toward achieving efficient content retrieval in LEO satellite networks from the routing perspective. We start with investigating the topology characteristics of LEO satellite networks in terms of the deterministic neighbor relation and the intermittent inter-satellite links. We then propose a Global view Assisted Localized fine-grained Routing (GALOR), which is an information-centric routing mechanism customized to LEO satellite networks. Specifically, GALOR disseminates the link state within a predefined range instead of the entire constellation, incurring less convergence time and control overhead. Therefore, GALOR can calculate the routing table (to guide interest forwarding) based on the local link state and the global neighbor relations. Moreover, GALOR improves the forwarding method of the information-centric routing by reconstructing a failed Pending Interest Table (PIT) entries in response to occasional link failures. Our packet-level experiments show that GALOR outperforms state-of-the-art mechanisms (up to 103.4%) in terms of average packet delivery ratio in content-sharing.

Light Weight Concurrent Scheduling of Mobile Sink routing protocol towards Minimization of Propagation Delay against Spatial and Temporal Uncertainties of Cluster based Wireless Sensor Network

Wireless Sensor Network highly exposed to certain security attacks due to various uncertainties of the network which lead to node compromise. Hence considerable attention has been made by researcher during scheduling of the mobile sink to data collection of sensed information from the sensor nodes. Many secure data aggregation mechanism has been proposed to withstand the network against these kind of attack. Despite of many advantageous, those architectures will lead to several limitations such as large propagation delay and high energy consumption and spatial and temporal uncertainties. In order to mitigate those challenges, Light Weight Concurrent Scheduling of Mobile Sink routing protocol towards Minimization of Propagation Delay against Spatial and Temporal Uncertainties of Wireless Sensor Network is designed. It should be capable achieving energy efficiency and collision avoidance due to uncertainty in transmission and reception. Proposed model eliminates the packet collision and poor channel utilization challenges. Initially, node is partitioned and cluster head is selected based on the highest energy density of the node in the particular location. Employing Full duplex channel easily examines the spatial and temporal characteristic of the node through utilization cache information of routing table. It further helps to build the light weight scheme with behavioral strategies of the nodes for secure propagation of the sensed data to the mobile sink. Light weight scheme deployed in mobile sinks estimate the node trustworthiness and simultaneously collects the secure aggregated data packets of the sensor node through cluster head against dynamic time slots concurrently .Comparing with traditional secure routing architecture, simulation results demonstrates that proposed architecture can reduce the propagation delay against various uncertainties and maximizes the life time of the network on increasing the networking performances with respect to packet delivery ratio, throughput and propagation delay. Finally proposed model obtains the cooperative communication of sensor node information to the base station through mobile sink on heterogeneous wireless sensor network environment. DOI: https://doi.org/10.52783/pst.387

Minimizing the Number of Distrustful Nodes on the Path of IP Packet Transmission

One of the important directions for improving modern Wide Area Networks is efficient and secure packet routing. Efficient routing is often based on using the shortest paths, while ensuring security involves preventing the possibility of packet interception. The work is devoted to improving the security of data transmission in IP networks. A new approach is proposed to minimize the number of distrustful nodes on the path of IP packet transmission. By a distrustful node, we mean a node that works correctly in terms of hardware and software and fully implements its data transport functions, but from the point of view of its organizational subordination, we are not sure that the node will not violate security rules to prevent unauthorized access and interception of data. A distrustful node can be either a transit or an end node. To implement this approach, we modified Dijkstra’s shortest path tree construction algorithm. The modified algorithm ensures that we obtain a path that will pass only through trustful nodes, if such a path exists. If there is no such path, the path will have the minimum possible number of distrustful intermediate nodes. The number of intermediate nodes in the path was used as a metric to obtain the shortest path trees. Routing tables of routers, built on the basis of trees obtained using a modified algorithm, provide increased security of data transmission, minimizing the use of distrustful nodes.

Load Balancing Algorithm of API Gateway Based on Microservice Architecture for a Smart City

Abstract As the entrance of the computer systems, the API gateway is an indispensable part of the microservice architecture. To realize the load balancing of API gateway, this paper studies the load balancing algorithm of the API gateway based on the microservice architecture. In doing this, we analyze the microservice architecture level from the data layer, the basic layer, and other levels, take the container cloud as the carrier of the microservice architecture, combine it with the client and API gateway, and design the API gateway based on the microservice architecture. We then judge whether the microservice identifier in the request source of the API gateway client is included in the API gateway routing table and determine the service cluster to which the microservice belongs according to the microservice identifier. After retrieving the qualified backend microservice container list according to the service cluster information, it adopts a load balancing algorithm based on dynamic weight, takes central processing unit (CPU) utilization and memory utilization as parameters to evaluate the resource load of microservers, uses an extreme gradient lifting model to predict CPU utilization and memory utilization, calculates the weight of microservers based on the prediction results, selects the microserver with the highest weight value to make API gateway service requests, and initiates API gateway service calls to specific backend microservice containers, thereby completing the load balancing of the API gateway. The experimental results show that the average load balancing degree of the algorithm is about 95 %, the average network resource utilization rate is as high as 89 %, and the algorithm execution time is short.

A NEW APPROACH TO WIRELESS CHARGING AND ON-DEMAND DATA GATHERING (SSWCODDG) FOR RWSN

These days, WSNs (wireless sensor networks) are all about collecting data and reducing energy use. Mobile sinks and chargers can visit Cluster Heads (CHs) to gather data and recharge their batteries, respectively. A mobile VAN (MV) combines a mobile charger and sinks to improve the energy efficiency of a WSN. Determining the CHs’ guest instructions for wireless data collecting and charging is difficult. In response to these problems, the authors of this study present SSWCODDG (Santosh Soni Wireless Charging and on Demand Data Gathering), a new approach to wirelessly charging and data collection for rechargeable wireless sensor networks. Utilizing mobile VAN, the proposed algorithm gathers data from CHs and charges them according to their choices and needs. Here, Mobile VAN maintains a routing table and, in response to requests, visits CHs. To divide the network into clusters, the proposed method employs the LEACH clustering algorithm. One full cycle is executed by the LEACH (Low Energy Adaptive Clustering Hierarchy) algorithm. To back up its claims, this study compares the recently created SSWCODDG algorithm to the SPSS and M2C algorithms that came before it. In addition, SSWCODDG outperforms SPSS (Single path scheduling scheme) and M2C (Mobile to Cluster) for a range of sensor node densities by 38.62 and 25.78 percentage points, respectively.

Evaluate OSPF and EIGRP Based on Route Table Size and Dropped Traffic using Different Topologies (Star, Loop)

The study compares between OSPF and EIGRP based on the route table size and dropped traffic, using two different Topologies (Star, Loop) with each of them, using Opnet simulator. The results indicate that, regardless of the network's form, EIGRP has a larger route table size than OSPF. The location of the routers affects the size of the route table. The core router’s route tale size ordering differs from distribution routers and from access routers. Even though they were using different topologies, the dropped traffic in EIGRP was greater than that of OSPF.

Detection of black hole attacks in vehicle-to-vehicle communications using ad hoc networks and on demand protocols

PurposeThe potential of vehicle ad hoc networks (VANETs) to improve driver and passenger safety and security has made them a hot topic in the field of intelligent transportation systems (ITSs). VANETs have different characteristics and system architectures from mobile ad hoc networks (MANETs), with a primary focus on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. But protecting VANETs from malicious assaults is crucial because they can undermine network security and safety.Design/methodology/approachThe black hole attack is a well-known danger to VANETs. It occurs when a hostile node introduces phony routing tables into the network, potentially damaging it and interfering with communication. A safe ad hoc on-demand distance vector (AODV) routing protocol has been created in response to this issue. By adding cryptographic features for source and target node verification to the route request (RREQ) and route reply (RREP) packets, this protocol improves upon the original AODV routing system.FindingsThrough the use of cryptographic-based encryption and decryption techniques, the suggested method fortifies the VANET connection. In addition, other network metrics are taken into account to assess the effectiveness of the secure AODV routing protocol under black hole attacks, including packet loss, end-to-end latency, packet delivery ratio (PDR) and routing request overhead. Results from simulations using an NS-2.33 simulator show how well the suggested fix works to enhance system performance and lessen the effects of black hole assaults on VANETs.Originality/valueAll things considered, the safe AODV routing protocol provides a strong method for improving security and dependability in VANET systems, protecting against malevolent attacks and guaranteeing smooth communication between cars and infrastructure.

Distributed MA‐IDDPG‐OLSR based stable routing protocol for unmanned aerial vehicle ad‐hoc network

AbstractIn unmanned aerial vehicle ad‐hoc network (UANET), the node speed of unmanned aerial vehicles (UAVs) may reach up to 400 km/h. The fast or slow movement of UAV nodes leads to different speeds of topology change of the nodes. Traditional optimized link state routing (OLSR) protocol cannot adaptively adjust the routing update period when the network topology changes, which may lead to the nodes calculating incorrect routing tables. This increases the average end‐to‐end delay and packet loss rate for packet transmission. To enhance the adaptability of OLSR routing protocol to network topology changes, this paper proposes a multi‐agent independent deep deterministic policy gradient‐OLSR (MA‐IDDPG‐OLSR) routing protocol based on distributed multi‐agent reinforcement learning. The protocol deploys DDPG algorithm on each UAV node, and each UAV node adaptively adjusts the Hello and TC message sending intervals, according to the one‐hop neighbouring nodes as well as its own state. Simulation results show that the proposed protocol is able to improve the throughput and reduce the packet loss rate as compared to traditional AODV, GRP, OLSR, and distributed multiple‐agent independent proximal policy optimization‐OLSR (MA‐IPPO‐OLSR), distributed multiple‐agent independent twin delayed deep deterministic policy gradient‐OLSR (MA‐ITD3‐OLSR) routing protocols. Since MA‐IDDPG‐OLSR relies only on local information, there is a minor performance degradation in MA‐IDDPG‐OLSR compared to centralized single‐agent DQN‐OLSR routing protocol. But it is more suitable to a completely distributed UAV network without a centralized node.

Adaptive HELLO protocol for vehicular networks

In vehicular networks, the update of car Firmware Over The Air (FOTA) is becoming a challenging issue and it mainly relies on topology discovery of neighbouring nodes. Topology discovery in mobile wireless networks is usually done by using HELLO messages. Due to mobility, topology changes occur frequently and must be quickly discovered to avoid routing failures. Since the optimal HELLO frequency depends on parameters that are subject to changes (e.g., speed of nodes, density of nodes), it must be dynamically adjusted to obtain the best trade-off between the network load and the freshness of routing tables. Existing solutions assume random mobility, constant node density and average speed, which do not hold in vehicular networks because vehicles follow specific trajectory patterns (the roads) and density and speed evolve as a function of time (rush hour vs non-rush hour) and area (urban, rural, highway). In this paper, we first draw the specific features of a vehicular network at different times and spaces by analysing real datasets and then propose a dynamic neighbour discovery protocol, Vehicular Adaptive Neighbour discovery Protocol (VANP). VANP is a fully-distributed protocol that sends beacons at an optimal frequency without knowing it a priori. The objective is to reduce the frequency at which HELLO messages are sent to save bandwidth and energy while still preserving the quality of the neighbour discovery. Through extensive simulations run on real datasets, we show that the optimal HELLO frequency can be reached by maintaining a constant optimal turnover, independent from the speed of the nodes and by aiming at this turnover, nodes automatically use the optimal HELLO frequency. Results show that VANP allows the discovery of relevant neighbours by missing at most two neighbours over all scenarios and reducing the number of HELLO messages up to twice, hence saving bandwidth and energy.

Deep reinforcement learning enhanced skeleton based pipe routing for high-throughput transmission in flying ad-hoc networks

Artificial Intelligence (AI) is a huge step towards the emergence of powerful and smart decision-makers which can optimally tune the network parameters. In this work, a novel idea of an intelligent pipe (iPipe) routing scheme for a network of unmanned aerial vehicles (UAVs) is presented by considering the availability of a centralized entity with enough computational resources. The proposed scheme deploys artificial intelligence to optimally decide on the direction of the routing pipe (i.e. the medial axis), based on the current network information and the prediction of the immediate future. To address the potential influx of input data, the application of Deep Reinforcement Learning (DRL) is proposed to enhance the throughput performance and adapt more effectively to network dynamics. The scheme benefits from the concept of flying ad hoc network (FANET) to provide nodes with geometric coordinates in order to facilitate the data forwarding mechanism. Compared to the conventional AI-based routing strategies, the proposed scheme does not require making decisions for the routing table of all the nodes. Instead, it only finds the trend as a set of geometric indices which will be included in the packet headers. However, the pipe nodes still act in a distributed manner. They build their routing tables according to the trend suggested by the controller and adjust the transmission probability of each link based on the local feedback. This reduces the complexity of the centralized solution. The simulation results show that the proposed iPipe method can outperform the other state-of-the-art SSR routing scheme, which is a distributed but low-cost pipe routing.

Multi-Hop and Mesh for LoRa Networks: Recent Advancements, Issues, and Recommended Applications

A comprehensive review is presented on the latest approaches to solutions focusing on multi-hop and mesh LoRa networks through the evaluation of simulations and real-world experiments, based on papers published between 2015 and 2023. The approaches are systematically classified into four (4) aspects: energy awareness, concurrent access and duty cycle regulations, routing protocols, and security. The first aspect encompasses parameter selection, distance, and clustering. The second aspect focuses on network segregation and time synchronisation. The third aspect covers proactive, reactive, and hybrid routing protocols. The aspect of security includes privacy and Denial-of-Service (DoS). Findings show a consensus that multi-hop networks and adherence to radio duty cycle are able to lower average power consumption. Concurrent access method can improve network performance, but more research is needed due to different conclusions. Reactive protocols have a slight advantage over proactive protocols in terms of node deployment scalability and lower power consumption due to less frequent routing table updates. Hybrid protocols are only beneficial in specific topology deployments. Security is still a major concern for LoRa networks, particularly on attacks such as Man-In-The-Middle (MITM), spoofing, wormholes, flooding, packet replay, and information disclosure. The upcoming trend of implementing machine learning algorithms to multi-hop and mesh LoRa networks opens up a wide range of possibilities, ranging from airspace efficiency, efficient route selection, and improving data throughput. A detailed discussion of the aspects’ issues and recommended industry applications that will benefit from multi-hop and mesh LoRa networks are also provided.

Cross-Layer Energy Efficient (CLEE) Routing Algorithm for Mobile Ad-Hoc Networks

Ad-hoc routing algorithms in Wireless Sensor Networks (WSN) rely on nodes’ position awareness by regularly updating routing data of neighbouring nodes. Meanwhile, the transmission energy usage is not optimised as a result of this repeated updates and routing table deployment. Therefore, it is very critical to consider techniques of optimising or conserving energy in the design of wireless sensor networks (WSNs) in order to prolong the lifetime of the individual nodes. One of these techniques is the Cross-layer design which, is considered as an efficient method for addressing this challenge with WSNs. In this paper, we propose a Cross-Layer Energy Efficient (CLEE) routing algorithm to establish an optimal route from the source node to the destination node by selecting candidate nodes from neighbouring nodes based on the distance between these nodes and the rate of energy consumption by a possible candidate node. Then to select a designated node from the candidate nodes, the algorithm further computes the Signal Strength Quality (SQS) and the Link Lifetime (LL) as well as the Throughput (TH) rate of selected nodes. The proposed algorithm was simulated with a network size of 600 X 600 on Network Simulator 3 (NS3) in order to analyse its performance. An evaluation of the performance of the proposed CLEE protocol with existing similar protocols such as Ad-hoc On-Demand Distance Vector (AODV) and Dynamic Source Routing (DSR) reveals that CLEE outperformes AODV and DSR by conserving about 44% of available energy.

On Maximizing the Probability of Achieving Deadlines in Communication Networks

We consider the problem of meeting deadline constraints in wireless communication networks. Fulfilling deadlines depends heavily on the routing algorithm used. We study this dependence generically for a broad class of routing algorithms. For analyzing the impact of routing decisions on deadline fulfillment, we adopt a stochastic model from operations research to capture the source-to-destination delay distribution and the corresponding probability of successfully delivering data before a given deadline. Based on this model, we propose a decentralized algorithm that operates locally at each node and exchanges information solely with direct neighbors in order to determine the probabilities of achieving deadlines. A modified version of the algorithm also improves routing tables iteratively to progressively increase the deadline achievement probabilities. This modified algorithm is shown to deliver routing tables that maximize the deadline achievement probabilities for all nodes in a given network. We tested the approach by simulation and compared it with routing strategies based on established metrics, specifically the average delay, minimum hop count, and expected transmission count. Our evaluations encompass different channel quality and small-scale fading conditions, as well as various traffic load scenarios. Notably, our solution consistently outperforms the other approaches in all tested scenarios.