Model Of Multipath Routing Research Articles

QIBMRMN: Design of a Q-Learning based Iterative sleep-scheduling & hybrid Bioinspired Multipath Routing model for Multimedia Networks

QIBMRMN: Design of a Q-Learning based Iterative sleep-scheduling & hybrid Bioinspired Multipath Routing model for Multimedia Networks

A Sub-flow Adaptive Multipath Routing Algorithm for Data Centre Network

In response to the fast and intensive traffic changes and the presence of redundant links in the network topology in data centre networks, multipath routing has become the dominant approach. Existing multipath routing algorithms are still inadequate in terms of adapting to dynamic changes in the network state quickly and the cooperation of path selection and sub-flow assignment. Therefore, this paper proposes a sub-flow adaptive multipath routing algorithm for data centre networks (SAMP). The deep deterministic policy gradient (DDPG) algorithm is introduced. DDPG combines deep learning (DL) and reinforcement learning (RL) to implement different network state changes quickly, especially in the process of topology, to achieve dynamic migration of the optimised decisions that have been learned. An adaptive multipath routing model for subflows is established to accomplish collaborative scheduling of path selection and subflow assignment based on the real-time state of the network. The experimental results show that the algorithm can be well adapted to the data centre network, and when compared with several traditional methods, it reduces the latency by an average of 31.3%, improves the task transmission success rate by an average of 14.9%, and increases the throughput by 37.1%.

Reliable Fault Tolerant-Based Multipath Routing Model for Industrial Wireless Control Systems

Communication in industrial wireless networks necessitates reliability and precision. Besides, the existence of interference or traffic in the network must not affect the estimated network properties. Therefore, data packets have to be sent within a certain time frame and over a reliable connection. However, the working scenarios and the characteristics of the network itself make it vulnerable to node or link faults, which impact the transmission reliability and overall performance. This article aims to introduce a developed multipath routing model, which leads to cost-effective planning, low latency and high reliability of industrial wireless mesh networks, such as the WirelessHART networks. The multipath routing model has three primary paths, and each path has a backup node. The backup node stores the data transmitted by the parent node to grant communication continuity when primary nodes fail. The multipath routing model is developed based on optimal network planning and deployment algorithm. Simulations were conducted on a WirelessHART simulator using Network Simulator (NS2). The performance of the developed model is compared with the state-of-the-art. The obtained results reveal a significant reduction in the average network latency, low power consumption, better improvement in expected network lifetime, and enhanced packet delivery ratio which improve network reliability.

Providing cyber resilience in software-defined networks by secure routing means

This paper is devoted to solving the technical task of providing cyber resilience utilizing secure routing means in Software-Defined Networks (SDN). The work analyzes the SDN architecture and its main components, the concept of cyber resilience and its means, as well as security issues in SDN. Particular attention is paid to the use of secure routing in software-defined networks. Numerical research of the model of secure multipath routing of fragmented confidential messages in the SDN data plane was conducted. The calculation of the message compromise probability for different values of links compromise probabilities was performed. The obtained results showed that the model of secure multipath routing of fragmented confidential messages with redundancy provides a better balancing of message parts by routes. Results of the numerical study proved the adequacy of the selected secure multipath routing model.

GCLR: GNN-Based Cross Layer Optimization for Multipath TCP by Routing

Multipath TCP has attracted increasing attention as a promising technology for 5G networks. To fully utilize network interfaces on multi-homed terminals and the whole network resources, MPTCP is proposed as an extension of TCP to transfer packets concurrently over multiple paths. Cross layer optimization techniques have been applied for MPTCP such as routing and path management. However, existing multipath routing algorithms and network modeling techniques are facing the challenges of subflow asymmetry due to network heterogeneity, thus cannot handle routing optimization problems comprehensively. To address these problems, in this paper, firstly, a novel Graph Neural Network (GNN) based multipath routing model is proposed to explore the complications among links, paths, subflows and the MPTCP connection on various topologies. Leveraging the GNN model, expected throughput can be predicted with given network topology and multipath routes, which can further be the guidance for optimzing the multipath routing. Then, GCLR, a GNN based cross layer optimization system for MPTCP by routing, is proposed with the help of SDN (Software Defined Networking). According to simulation results, our off-line learned GNN model can predict the expected throughput of specific MPTCP connections with very low error. Besides, it's validated that the model has high generalization ability in terms of connection arbitrary and topology arbitrary, it can maintain MSE (mean squared error) at a low level when the situations are not seen during training, which is sufficient for throughput prediction in multipath routing decisions. Finally, the online routing optimization system is realized using SDN, experimental results show that our proposed routing optimization system can achieve significant throughput enhancement compared with traditional multipath routing algorithms.

Development of the tensor model of multipath qоe-routing in an infocommunication network with providing the required quality rating

This work has solved a relevant task to ensure the required level of quality of experience in an infocommunication network, which implied the development of a mathematical model of the multipath QoE-routing while maintaining the required quality rating. In this case, quality rating calculation requires the introduction to the mathematical model of routing of additional conditions for obtaining the indicators of an end-to-end delay and a packet loss probability. To this end, it is advisable to use the tensor formalization of these conditions when implementing a multipath routing strategy. Such a technique for expanding the mathematical models (introduction of additional analytical conditions) is more flexible and would full account for the complexity of relationship between network parameters within QoE. Given this, the quality of experience of speech transmission is not defined by the absolute values of delays and loss probabilities, but rather by their relationship. The result of studying the proposed model is the calculated quantitative indicator for a quality rating, which, compared to recommended indicators according to existing recommendations, makes it possible to evaluate the execution of the predefined level of QoE. In other words, given the preset intensity of traffic in a network, we calculated indicators for the average end-to-end delay and a packet loss probability, which make it possible to assess the quality of experience in terms of a quality rating and indicate the efficiency of the proposed solution. And, on the contrary, owing to the developed model of QoE-routing, it has become possible to control the probability of losses and the average end-to-end packet delay in an infocommunication network in order to ensure meeting the specified QoE-requirements. In addition, a comparative analysis was performed of a flow model of multipath routing based on using the IGRP metric, which made it possible to assess the effectiveness of the proposed solution and demonstrated better performance in terms of a quality rating by 12 to 25 % depending on the source data.

Multiconstrained Multipath Routing for Wireless Sensor Networks in the Fuzzy Random Environment

Fuzziness and randomness exist simultaneously in the routing constraints of wireless sensor networks.However,the existing routing algorithms only consider randomness,which can not describe the routing constraints precisely.This paper adopts fuzzy stochastic process and fuzzy random programming to model fuzziness,randomness and time-varying property of the delay and reliability of wireless links,and proposes a fuzzy random multiconstrained multipath routing model to reflect real characteristics of wireless links.A novel routing algorithm for wireless sensor networks is presented,which considers fuzziness,randomness and time-varying property and has polynomial complexity.Simulation results show that the proposed algorithm can meet different needs of practical applications for quality of service by flexibly adjusting the strength of the routing constraints.

Network coding based reliable disjoint and braided multipath routing for sensor networks

This paper presents network coding based reliable disjoint and braided multipath routing (NC-RMR ) for sensor networks, which forms multipath by hop-by-hop method and only maintains local path information of each node without establishing end-to-end paths. Neighbors of each local node are divided into groups according to their hops to sink nodes to improve the network load balancing. For further performance improvement of NC-RMR with disjoint multipath model, local nodes select their own backup nodes in neighbor nodes to form additional logical paths, which implement a braided multipath model. Security advantages of NC-RMR with multipath and network coding mechanisms are analyzed. Analytical and simulation results prove that braided multipath routing model has better performance over disjoint model, and NC-RMR protocol can reduce the required number of transmission paths, ensure load balance of sensor network system, reduce the energy consumption of nodes.

Algorithms for multicast connection under multi-path routing model

Given a source node and a set of destination nodes in a network, multicast routing problem is usually treated as Steiner tree problem. Unlike this well-known tree based routing model, multicast routing under multi-path model is to find a set of paths rooted at the source node such that in each path at most a fixed number of destination nodes can be designated to receive the data and every destination node must be designated in a path to receive the data. The cost of routing is the total costs of paths found. In this paper we study how to construct a multicast routing of minimal cost under multi-path model. We propose two approximation algorithms for this NP-complete problem with guaranteed performance ratios.