Multi-Path Routing and Resource Allocation in Active Network

An algorithm of traffic distribution called active multi-path routing (AMR)in active network is proposed. AMR adopts multi-path routing and applies nonlinear optimizeapproximate method to distribute network traffic among multiple paths. It is combined to bandwidthresource allocation and the congestion restraint mechanism to avoid congestion happening and worsen.So network performance can be improved greatly. The frame of AMR includes adaptive trafficallocation model, the conception of supply bandwidth and its' allocation model, the principle ofcongestion restraint and its' model, and the implement of AMR based on multi-agents system in activenetwork. Through simulations, AMR has distinct effects on network performance. The results show AMRisa valid traffic regulation algorithm.

Improved Multi-Path Routing for QoS on MANET

A Mobile Ad hoc NETwork(MANET)is a self-configuring network that is not reliant on infrastructure.This paper introduces a new multipath routing method based on the Multi-Hop Routing(MHR)technique.MHR is the consecutive selection of suitable relay nodes to send information across nodes that are not within direct range of each other.Failing to ensure good MHR leads to several negative consequences,ultimately causing unsuccessful data transmission in a MANET.This research work consists of three portions.The first to attempt to propose an efficient MHR protocol is the design of Priority Based Dynamic Routing(PBDR)to adapt to the dynamic MANET environment by reducing Node Link Failures(NLF)in the network.This is achieved by dynamically considering a node’s mobility parameters like relative velocity and link duration,which enable the next-hop selection.This method works more efficiently than the traditional protocols.Then the second stage is the Improved Multi-Path Dynamic Routing(IMPDR).The enhancement is mainly focused on further improving the Quality of Service(QoS)in MANETs by introducing a QoS timer at every node to help in the QoS routing of MANETs.Since QoS is the most vital metric that assesses a protocol,its dynamic estimation has improved network performance considerably.This method uses distance,linkability,trust,and QoS as the four parameters for the next-hop selection.IMPDR is compared against traditional routing protocols.The Network Simulator-2(NS2)is used to conduct a simulation analysis of the protocols under consideration.The proposed tests are assessed for the Packet Delivery Ratio(PDR),Packet Loss Rate(PLR),End-to-End Delay(EED),and Network Throughput(NT).

SOPA:Source Routing Based Packet-Level Multi-Path Routing in Data Center Networks

Many ＂rich - connected＂ topologies with multiple parallel paths between smwers have been proposed for data center networks recently to provide high bisection bandwidth, but it re mains challenging to fully utilize the high network capacity by appropriate multi- path routing algorithms. As flow-level path splitting may lead to trafl＇ic imbalance between paths due to flow- size difference, packet-level path splitting attracts more attention lately, which spreads packets from flows into multiple available paths and significantly improves link utilizations. However, it may cause packet reordering, confusing the TCP congestion control algorithm and lowering the throughput of flows. In this paper, we design a novel packetlevel multi-path routing scheme called SOPA, which leverag- es OpenFlow to perform packet-level path splitting in a round- robin fashion, and hence significantly mitigates the packet reordering problem and improves the network throughput. Moreover, SOPA leverages the topological feature of data center networks to encode a very small number of switches along the path into the packet header, resulting in very light overhead. Compared with random packet spraying （RPS）, Hedera and equal-cost multi-path routing （ECMP）, our simulations demonstrate that SOPA achieves 29.87%, 50.41% and 77.74% higher network throughput respectively under permutation workload, and reduces average data transfer completion time by 53.65%, 343.31% and 348.25% respectively under production workload.

MRBCH: A Multi-Path Routing Protocol Based on Credible Cluster Heads for Wireless Sensor Networks

Wireless sensor networks are widely used for its flexibility, but they also suffer from problems like limited capacity, large node number and vulnerability to security threats. In this paper, we propose a multi-path routing protocol based on the credible cluster heads. The protocol chooses nodes with more energy remained as cluster heads at the cluster head choosing phase, and then authenticates them by the neighbor cluster heads. Using trust mechanisms it creates the credit value, and based on the credit value the multi-path cluster head routing can finally be found. The credit value is created and exchanged among the cluster heads only. Theoretical analysis combined with simulation results demonstrate that this protocol can save the resource, prolong the lifetime, and ensure the security and performance of the network.

Equal Preference Multi-Path Routing for L2 Hierarchical Networks

The layer 2 network technology is extending beyond its traditional local area implementation and finding wider acceptance in provider’s metropolitan area networks and large-scale cloud data center networks. This is mainly due to its plug-and-play capability and native mobility support. Many efforts have been put to increase the bisection bandwidth in a layer 2 network, which has been constrained by the spanning tree protocol that a layer 2 network uses for preventing looping. The recent trend is to incorporate layer 3’s routing approach into a layer 2 network so that multiple paths can be used for forwarding traffic between any source-destination (S-D) node pair. ECMP (equal cost multipath) is one such example. However, ECMP may still be limited in generating multiple paths due to its shortest path (lowest cost) requirement. In this paper, we consider a non-shortest-path routing approach, called EPMP (Equal Preference Multi-Path) that can generate more paths than ECMP. The EPMP is based on the ordered semi-group algebra. In the EPMP routing, paths that differ in traditionally-defined costs, such as hops, bandwidth, etc., can be made equally preferred and thus become candidate paths. We found that, in comparison with ECMP, EPMP routing not only generates more paths, provides higher bisection bandwidth, but also allows bottleneck links in a hierarchical network to be identified when different traffic patterns are applied. EPMP is also versatile in that it can use various ways of path preference calculations to control the number and the length of paths, making it flexible (like policy-based routing) but also objective (like shortest path first routing) in calculating preferred paths.

A multi-path routing algorithm of LEO satellite networks based on an improved ant colony system

Geography rectangle is used to reduce signaling overhead of the LEO satellite networks.Moreover,a multi-path routing algorithm based on an improved ant colony system(MPRA-AC) is proposed.Matrix indicating the importance of the link between satellites is introduced into MPRA-AC in order to find the optimal path more quickly.Simulation results show that MPRA-AC reduces the number of iterations to achieve a satisfactory solution.At the same time,the packet delivery ratio of LEO satellite networks when running MPRA-AC and DSR-LSN(dynamic source routing algorithm for LEO satellite networks) is compared.The packet delivery ratio is about 7.9%lower when running DSR-LSN.Moreover,because of the mechanism of active load balancing of MPRA-AC,simulation results show that MPRA-AC outperforms DSR-LSN in link utilization when data packets are transmitted in the networks.

Novel multi-path routing scheme for UWB Ad hoc network

The routing protocols play an important role for ad hoc networks performance.As some problems with DSR,SMR,and AMR protocols were analyzed,a new routing protocol suitable for UWB Ad hoc networks was proposed in this paper.The new routing protocol utilize an act of orientation of UWB and tries to get sufficient route information and decrease the network load caused by route discovery at the same time.Simulation results show that the routing load of the new protocol is lower and throughput is higher than that of DSR.While the node’s mobility increases,these advantages become more obvious.

Research of multi-path routing based on network coding in space information networks

A multi-path routing algorithm based on network coding is proposed for combating long propagation delay and high bit error rate of space information networks. On the basis of traditional multi-path routing, the algorithm uses a random linear network coding strategy to code data pack- ets. Code number is determined by the next hop link status and the number of current received packets sent by the upstream node together. The algorithm improves retransmission and cache mechanisms through using redundancy caused by network coding. Meanwhile, the algorithm also adopts the flow distribution strategy based on time delay to balance network load. Simulation results show that the proposed routing algorithm can effectively improve packet delivery rate, reduce packet delay, and enhance network performance.

Toward path reliability by using adaptive multi-path routing mechanism for multimedia service in mobile Ad-hoc network

Traditional multi-path routing mechanisms aim to establish complete node or link disjoint paths. However, under some circumstances if multiple paths cannot be established based on the current network topology, the traditional multi-path routing mechanism will degenerate into single path routing mechanism, thus the advantages of multi-path routing cannot be exhibited. To enhance the end-to-end path reliability, an adaptive multi-path routing mechanism with path segment is proposed, in which multi-path can be established at part of the end-to-end path. In this way the reliability of the path can be enhanced. This path segment mechanism can divide the end-to-end path into several short segments, and a parallel forwarding mechanism is proposed for guaranteeing the quality of service of multimedia services over the wireless network. Simulations show that the network performance metrics such as the packet delivery ratio, the end-to-end delay and the number of route discoveries are all improved by using the adaptive multi-path routing mechanism.

Multi-path routing based on load-balance for cognitive packet networks

Quality of service （QoS） routing algorithms have been hardly discussed in the scientific community, most previous work on QoS routing concentrates on the performance of the single route. Cognitive packet network （CPN） has been designed for providing QoS routing. In this paper, to balance the loads among networks, we present a multi-path routing algorithm based on load-balance （MPRLB）, which is carried out in two steps. The algorithm with low computational complexity is firstly applied to establish multi path routing for each source and destination node pairs （SD-pair） nodes in the network. Then, we propose the hopfield neural network algorithm, which is applied to improve the efficiency of the flow deviation method for fast flow allocation among the links of the network based on load balance. Extensive simulation results demonstrate that the proposed scheme significantly improves the performance compared with the existing scheme that ignores load balancing.

The quickly switching routing algorithm based on multi-path in mobile Ad Hoc networks

This paper proposes a new on-demand multi-alternate-path algorithm, called quickly switching routing algorithm(QSRA). It switches failure routing to an alternate path as quickly as the network can. Like a nervure shape, algorithm QSRA shapes disjoint-alternate-path structure, but is not limited to. It also contains another structure that every primary node has several links to alternate paths. This structure has two advantages, the first one is that primary nodes can select one alternate path immediately when primary routing is failure without going back to source node to re-discover a new routing or choose an alternate path; the second is that it guarantees primary nodes can select another alternate path as quickly as possible once one of alternate paths fails. Strongpoint of algorithm QSRA is reducing frequency of routing re-discovering. Besides, the structure occupies fewer resources than other routing algorithms due to its distributed structure. Simulation shows that QSRA has higher packets received ratio and lower control packet overhead and lower end-to-end delay.

Study of network survivability based on multi-path routing mechanism

As an important secure routing mechanism, multi-path routing is one of the major ways to improve network efficiency and to guarantee the network security, which ensures the reliability of data transmission by using backup paths when the primary one is unavailable due to local node or link failures. Most current studies on multi-path routing mechanism are based on experiments or simulations. The resulta are usually specific application scenarios oriented heuristic algorithms, lacking universal significance. In this paper, a theoretic analysis is performed on the relationship between the multi-path routing policy, the network efficiency and its survivability. Starting with point-to-point communication network, an impactoriented analysis is made on the network interference under multi-path routing mechanism. Based on the analysis, the upper-limit of network performance under interference impact is also discussed.

Robust multi-path routing for dynamic topology in wireless sensor networks

Wirreless sensor networks are being widely researched and are expected to be used in several scenarios. On the leading edge of treads, on-demand, high-reliability, and low-latency routing protocol is desirable for indoor environment applications. This article proposes a routing scheme called robust multi-path routing that establishes and uses multiple node-disjoint routes. Providing multiple routes helps to reduce the route recovery process and control the message overhead. The performance comparison of this protocol with dynamic source routing （DSR） by OPNET simulations shows that this protocol is able to achieve a remarkable improvement in the packet delivery ratio and average end-to-end delay.

MTCR-CR Routing Strategy for Connection-Oriented Routing over Satellite Networks

The high-speed movement of satellites makes it not feasible to directly apply the mature routing scheme on the ground to the satellite network.DT-DVTR in the snapshot-based connectionoriented routing strategy is one of the representative solutions,but it still has room for improvement in terms of routing stability.In this paper,we propose an improved scheme for connection-oriented routing strategy named the Minimal Topology Change Routing based on Collaborative Rules(MTCR-CR).The MTCR-CR uses continuous time static topology snapshots based on satellite status to search for intersatellite link(ISL)construction solutions that meet the minimum number of topology changes to avoid route oscillations.The simulation results in Beidou-3 show that compared with DT-DVTR,MTCR-CR reduces the number of routing changes by about 92%,the number of path changes caused by routing changes is about38%,and the rerouting time is reduced by approximately 47%.At the same time,in order to show our algorithm more comprehensively,the same experimental index test was also carried out on the Globalstar satellite constellation.

CoopAI-Route: DRL Empowered Multi-Agent Cooperative System for Efficient QoS-Aware Routing for Network Slicing in Multi-Domain SDN

The emergence of beyond 5G networks has the potential for seamless and intelligent connectivity on a global scale.Network slicing is crucial in delivering services for different,demanding vertical applications in this context.Next-generation applications have time-sensitive requirements and depend on the most efficient routing path to ensure packets reach their intended destinations.However,the existing IP(Internet Protocol)over a multi-domain network faces challenges in enforcing network slicing due to minimal collaboration and information sharing among network operators.Conventional inter-domain routing methods,like Border Gateway Protocol(BGP),cannot make routing decisions based on performance,which frequently results in traffic flowing across congested paths that are never optimal.To address these issues,we propose CoopAI-Route,a multi-agent cooperative deep reinforcement learning(DRL)system utilizing hierarchical software-defined networks(SDN).This framework enforces network slicing in multi-domain networks and cooperative communication with various administrators to find performance-based routes in intra-and inter-domain.CoopAI-Route employs the Distributed Global Topology(DGT)algorithm to define inter-domain Quality of Service(QoS)paths.CoopAI-Route uses a DRL agent with a message-passing multi-agent Twin-Delayed Deep Deterministic Policy Gradient method to ensure optimal end-to-end routes adapted to the specific requirements of network slicing applications.Our evaluation demonstrates CoopAI-Route’s commendable performance in scalability,link failure handling,and adaptability to evolving topologies compared to state-of-the-art methods.

Enhancing Network Design through Statistical Evaluation of MANET Routing Protocols

This paper contributes a sophisticated statistical method for the assessment of performance in routing protocols salient Mobile Ad Hoc Network(MANET)routing protocols:Destination Sequenced Distance Vector(DSDV),Ad hoc On-Demand Distance Vector(AODV),Dynamic Source Routing(DSR),and Zone Routing Protocol(ZRP).In this paper,the evaluation will be carried out using complete sets of statistical tests such as Kruskal-Wallis,Mann-Whitney,and Friedman.It articulates a systematic evaluation of how the performance of the previous protocols varies with the number of nodes and the mobility patterns.The study is premised upon the Quality of Service(QoS)metrics of throughput,packet delivery ratio,and end-to-end delay to gain an adequate understanding of the operational efficiency of each protocol under different network scenarios.The findings explained significant differences in the performance of different routing protocols;as a result,decisions for the selection and optimization of routing protocols can be taken effectively according to different network requirements.This paper is a step forward in the general understanding of the routing dynamics of MANETs and contributes significantly to the strategic deployment of robust and efficient network infrastructures.

Dynamic Routing of Multiple QoS-Required Flows in Cloud-Edge Autonomous Multi-Domain Data Center Networks

The 6th generation mobile networks(6G)network is a kind of multi-network interconnection and multi-scenario coexistence network,where multiple network domains break the original fixed boundaries to form connections and convergence.In this paper,with the optimization objective of maximizing network utility while ensuring flows performance-centric weighted fairness,this paper designs a reinforcement learning-based cloud-edge autonomous multi-domain data center network architecture that achieves single-domain autonomy and multi-domain collaboration.Due to the conflict between the utility of different flows,the bandwidth fairness allocation problem for various types of flows is formulated by considering different defined reward functions.Regarding the tradeoff between fairness and utility,this paper deals with the corresponding reward functions for the cases where the flows undergo abrupt changes and smooth changes in the flows.In addition,to accommodate the Quality of Service(QoS)requirements for multiple types of flows,this paper proposes a multi-domain autonomous routing algorithm called LSTM+MADDPG.Introducing a Long Short-Term Memory(LSTM)layer in the actor and critic networks,more information about temporal continuity is added,further enhancing the adaptive ability changes in the dynamic network environment.The LSTM+MADDPG algorithm is compared with the latest reinforcement learning algorithm by conducting experiments on real network topology and traffic traces,and the experimental results show that LSTM+MADDPG improves the delay convergence speed by 14.6%and delays the start moment of packet loss by 18.2%compared with other algorithms.

An Energy-Efficient Routing Algorithm for UAV Formation Based on Time-Aggregated Graph

The limited energy and high mobility of unmanned aerial vehicles(UAVs)lead to drastic topology changes in UAV formation.The existing routing protocols necessitate a large number of messages for route discovery and maintenance,greatly increasing network delay and control overhead.A energyefficient routing method based on the discrete timeaggregated graph(TAG)theory is proposed since UAV formation is a defined time-varying network.The network is characterized using the TAG,which utilizes the prior knowledge in UAV formation.An energyefficient routing algorithm is designed based on TAG,considering the link delay,relative mobility,and residual energy of UAVs.The routing path is determined with global network information before requesting communication.Simulation results demonstrate that the routing method can improve the end-to-end delay,packet delivery ratio,routing control overhead,and residual energy.Consequently,introducing timevarying graphs to design routing algorithms is more effective for UAV formation.

QoS Routing Optimization Based on Deep Reinforcement Learning in SDN

To enhance the efficiency and expediency of issuing e-licenses within the power sector, we must confront thechallenge of managing the surging demand for data traffic. Within this realm, the network imposes stringentQuality of Service (QoS) requirements, revealing the inadequacies of traditional routing allocation mechanismsin accommodating such extensive data flows. In response to the imperative of handling a substantial influx of datarequests promptly and alleviating the constraints of existing technologies and network congestion, we present anarchitecture forQoS routing optimizationwith in SoftwareDefinedNetwork (SDN), leveraging deep reinforcementlearning. This innovative approach entails the separation of SDN control and transmission functionalities, centralizingcontrol over data forwardingwhile integrating deep reinforcement learning for informed routing decisions. Byfactoring in considerations such as delay, bandwidth, jitter rate, and packet loss rate, we design a reward function toguide theDeepDeterministic PolicyGradient (DDPG) algorithmin learning the optimal routing strategy to furnishsuperior QoS provision. In our empirical investigations, we juxtapose the performance of Deep ReinforcementLearning (DRL) against that of Shortest Path (SP) algorithms in terms of data packet transmission delay. Theexperimental simulation results show that our proposed algorithm has significant efficacy in reducing networkdelay and improving the overall transmission efficiency, which is superior to the traditional methods.

An SDN-Based Algorithm for Caching,Routing,and Load Balancing in ICN

One of the challenges of Informationcentric Networking(ICN)is finding the optimal location for caching content and processing users’requests.In this paper,we address this challenge by leveraging Software-defined Networking(SDN)for efficient ICN management.To achieve this,we formulate the problem as a mixed-integer nonlinear programming(MINLP)model,incorporating caching,routing,and load balancing decisions.We explore two distinct scenarios to tackle the problem.Firstly,we solve the problem in an offline mode using the GAMS environment,assuming a stable network state to demonstrate the superior performance of the cacheenabled network compared to non-cache networks.Subsequently,we investigate the problem in an online mode where the network state dynamically changes over time.Given the computational complexity associated with MINLP,we propose the software-defined caching,routing,and load balancing(SDCRL)algorithm as an efficient and scalable solution.Our evaluation demonstrates that the SDCRL algorithm significantly reduces computational time while maintaining results that closely resemble those achieved by GAMS.