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 efficient QoS routing algorithm for multi-constrained path selection

An efficient QoS routing algorithm was proposed for multiple constrained path selection. Making use of efficient pruning policy, the algorithm reduces greatly the size of search space and the computing time. Although the proposed algorithm has exponential time complexity in the worst case, it can get the running results quickly in practical application. When the scale of network increases, the algorithm can efficiently control the size of search space by constraint conditions and prior queue. The results of simulation show that successful request ratio ( r ) of efficient algorithm for multi-constrained optimal path (EAMCOP) is better than that of heuristic algorithm for multi-constrained optimal path (H-MCOP), but average computing time ( t ) of EAMCOP is far less than that of H-MCOP. And it can be seen that the computing time of EAMCOP is only one fourth of that of H-MCOP in Advanced Research Projects Agency Network (ARPANet) topology.

A novel and effective multi-constrained QoS routing scheme in WMNs

Multi-constrained quality of service(QoS)routing aims at finding an optimal path that satisfies a set of QoS parameters,as an NP complete problem,which is also a big challenge for wireless mesh networks(WMNs).Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this problem.However,existing solutions,most of which suffered either from excessive computational complexities or from low performance,were proposed only for wired networks and cannot be used directly in wireless mesh networks.In this paper,we propose a novel routing scheme based on mean field annealing(MFA-RS)to solve this problem.MFA-RS first uses a function of two QoS parameters,wireless link’s delay and transmission success rate as the cost function,and then seeks to find a feasible path by MFA.Because MFA-RS uses a set of deterministic equations to replace the stochastic process in simulated annealing(SA)and uses saddle point approximation in the calculation of the stationary probability distribution at equilibrium,the convergence time is much less than the routing scheme based on SA(SA-RS).Simulation results demonstrate that MFA-RS is an effective algorithm and is very fit for WMNs.

Improved QoS-Secure Routing in MANET Using Real-Time Regional ME Feature Approximation

Mobile Ad-hoc Network(MANET)routing problems are thoroughly studied several approaches are identified in support of MANET.Improve the Quality of Service(QoS)performance of MANET is achieving higher performance.To reduce this drawback,this paper proposes a new secure routing algorithm based on real-time partial ME(Mobility,energy)approximation.The routing method RRME(Real-time Regional Mobility Energy)divides the whole network into several parts,and each node’s various characteristics like mobility and energy are randomly selected neighbors accordingly.It is done in the path discovery phase,estimated to identify and remove malicious nodes.In addition,Trusted Forwarding Factor(TFF)calculates the various nodes based on historical records and other characteristics of multiple nodes.Similarly,the calculated QoS Support Factor(QoSSF)calculating by the Data Forwarding Support(DFS),Throughput Support(TS),and Lifetime Maximization Support(LMS)to any given path.One route was found to implement the path of maximizing MANET QoS based on QoSSF value.Hence the proposed technique produces the QoS based on real-time regional ME feature approximation.The proposed simulation implementation is done by the Network Simulator version 2(NS2)tool to produce better performance than other methods.It achieved a throughput performance had 98.5%and a routing performance had 98.2%.

基于遗传-蚁群优化算法的QoS组播路由算法设计

为了提高网络路由性能,提出并设计了一种基于遗传-蚁群优化算法的服务质量(quality of service,QoS)组播路由算法。首先,设计了自适应变频采集策略用于采集网络与节点信息,以此获得网络和节点的状态,为后续路由优化提供数据支持;其次,计算路径代价,将路径代价最小作为优化目标,建立QoS组播路由优化模型,并设置相关约束条件;最后,结合遗传算法和蚁群算法提出一种遗传-蚁群优化算法求解上述模型,输出最优路径,完成路由优化。实验结果表明,所提算法可有效降低路径长度与路径代价,提高搜索效率与路由请求成功率,优化后的路由时延抖动较小。

基于SDN的空间信息网络自适应QoS路由算法的设计与实现

为了满足用户对网络服务质量的要求,本文提出一种基于SDN的空间信息网络自适应QoS路由算法。该算法采用SDN控制器对网络进行全局控制和管理,通过收集网络拓扑信息和质量参数,动态调整路由策略,实现网络的自适应QoS路由。实验结果表明,该算法能够有效提高网络服务质量,优化网络性能。

Research on Neural Network Based QoS Routing

In this paper, the requirements of routing due to the multimedia applications are briefly discussed. In order to solve the QoS constrained routing effectively and efficiently, the scheme of routing based on Hopfield neural network is proposed after the analysis of related work. Then the QoS routing algorithm for unicast based on Hopfield NN is described and the result of emulation is given. At last, multicast QoS routing considerations based on Hopfield NN are proposed.

SI-INSPIRED ENERGY AWARE QoS ROUTING TREE FOR WSN

A heuristic theoretical optimal routing algorithm （TORA） is presented to achieve the data-gathering structure of location-aided quality of service （QoS） in wireless sensor networks （WSNs）. The construction of TORA is based on a kind of swarm intelligence （SI） mechanism, i. e. , ant colony optimization. Firstly, the ener- gy-efficient weight is designed based on flow distribution to divide WSNs into different functional regions, so the routing selection can self-adapt asymmetric power configurations with lower latency. Then, the designs of the novel heuristic factor and the pheromone updating rule can endow ant-like agents with the ability of detecting the local networks energy status and approaching the theoretical optimal tree, thus improving the adaptability and en- ergy-efficiency in route building. Simulation results show that compared with some classic routing algorithms, TORA can further minimize the total communication energy cost and enhance the QoS performance with low-de- lay effect under the data-gathering condition.

On-demand QoS routing protocol based on energy and bandwidth requirement in Ad Hoc networks

Along with the emergence of real-time multi-media,interactive service,real-time voice and other services calling for high quality of service,there should be a good network to support those services.Most present route algo- rithms with computational complexity hardly consider the restriction of node energy,so it degrades the whole capabil- ity of network.Bandwidth guarantee is one of the most crucial factors in real-time application,and this paper brings forward a distributed on-demand QoS routing protocol based on energy and bandwidth requirement.This QoS routing protocol makes use of bandwidth calculation algorithm and analyzes its route mechanism.The simulation results veri- fy its validity.The QoS routing protocol improves the packet delivery fraction and average end-to-end delay,prolongs the network lifetime,enhances the network performance and satisfies the route requirement for ad hoc networks.

云雾网络中低延迟QoS路由模型的研究

文章提出一种适用于云雾计算环境的低延迟QoS路由模型,以应对云雾网络中的数据传输延迟问题,并保证服务的可靠性与效率。在深入分析云雾网络特性基础上,构建了包含关键QoS参数的网络切片评估模型,并据此设计出能够动态调整路由策略的算法,有效适应网络状态变化。仿真实验显示,处理1000MB数据时,该模型较传统云计算网络减少了11.95秒的延迟时间,仅需18.47秒,显著提升了网络吞吐量与操作速度,同时降低了丢包率,对提升网络性能和用户体验至关重要。

QoS multicast routing algorithm based on GA

The multicast routing problem with multiple QoS constraints in networks with uncertain parameters is discussed, and a network model that is suitable to research such QoS multicast routing problem is described. The QMRGA, a multicast routing policy for Internet, mobile network or other highperformance networks is mainly presented, which is based on the genetic algorithm(GA), and can provide QoSsensitive paths in a scalable and flexible way in the network environment with uncertain parameters. The QMRGA can also optimize the network resources such as bandwidth and delay, and can converge to the optimal or nearoptimal solution within few iterations, even for the network environment with uncertain parameters. The incremental rate of computational cost can be close to a polynomial and is less than exponential rate. The performance measures of the QMRGA are evaluated by using simulations. The results show that QMRGA provides an available approach to QoS multicast routing in network environment with uncertain parameters.

Multiple constraints-based QoS multicast routing: model and algorithms

Constraint-based multicast routing, which aims at identifying a path that satisfies a set of quality of service (QoS) constraints, has became a very important research issue in the areas of networks and distributed systems. In general, multi-constrained path selection with or without optimization is a NP-complete problem that can not be exactly solved in polynomial time. Hence, accurate constraints-based routing algorithms with a fast running time are scarce, perhaps even non-existent. The expected impact of such a constrained-based routing algorithm has resulted in the proposal of numerous heuristics and a few exact QoS algorithms. This paper aims to give a thorough, concise and fair evaluation of the most important multiple constraint-based QoS multicast routing algorithms known today, and it provides a descriptive overview and simulation results of these multi-constrained routing algorithms.

Anycast service model and its QoS routing algorithm

In the Internet, a group of replicated servers is commonly used in order to improve the scalability of network service. Anycast service is a new network service that can improve network load distribution and simplify certain applications. In this paper, the authors described a simple anycast service model in the Internet without significant affecting the routing and protocol processing infrastructure that was already in place, and proposed an anycast QoS routing algorithm for this model. The algorithm used randomized method to balance network load and improve its performance. Several new techniques are proposed in the algorithm, first, theminimum hops for each node are used in the algorithm, which are used as metric for computing the probability of possible out links. The metric is pre computed for each node in the network, which can simplify the network complexity and provide the routing process with useful information. Second, randomness is used at the link level and depends dynamically on the routing configuration. This provides great flexibility for the routing process, prevents the routing process from overusing certain fixed routing paths, and adequately balances the delay of the routing path. the authors assess the quality of QoS algorithm in terms of the acceptance ratio on anycast QoS requests, and the simulation results on a variety of network topologies and on various parameters show that the algorithm has good performances and can balance network load effectively.

Ant Colony Algorithm for Solving QoS Routing Problem

Based on the state transition rule, the local updating rule and the global updating rule of ant colony algorithm, we propose an improved ant colony algorithm of the least\|cost quality of service (QoS) unicast routing. The algorithm is used for solving the routing problem with delay, delay jitter, bandwidth, and packet loss\|constrained. In the simulation, about 52.33% ants find the successful QoS routing , and converge to the best. It is proved that the algorithm is efficient and effective.

An ACO Look-Ahead Approach to QOS Enabled FaultTolerant Routing in MANETs

MANET routing is critical and routing decision should be made sooner before the node leaves the network.Fast decisions always compensate network performance.In addition,most MANET routing protocols assume a friendly and cooperative environment,and hence are vulnerable to various attacks.Trust and Reputation would serve as a major solution to these problems.Learning the network characteristics and choosing right routing decisions at right times would be a significant solution.In this work,we have done an extensive survey of fault tolerant protocols and ant colony algorithms applied to routing in MANETs.We propose a QoS constrained fault tolerant ant lookahead routing algorithm which attempts to identify valid route and look-ahead route pairs which might help in choosing the alternate path in case of valid route failure.The results prove that the proposed algorithm takes better routing decisions with 20-30 percent improvement compared with existing ant colony algorithms.

Multicast routing algorithm of multiple QoS based on widest-bandwidth

A multicast routing algorithm of multiple QoS constraints based on widest-bandwidth （MRQW） which takes available bandwidth as the prime metric, considering the constraints of the surplus energy of the node, delay and delay jitter, is presented. The process of routing based on MRQW is provided for as well. Correctness proof and the complexity analysis of the MRQW are also given in the paper. Simulation results show that the MRQW has a good performance in creating multicast trees. It not only satisfys multiple QoS constraints but also makes multicast links have larger available bandwidth

A DISTRIBUTED QOS ROUTING BASED ON ANT ALGORITHM FOR LEO SATELLITE NETWORK

Low Earth Orbit (LEO) satellites provide short round-trip delays and are becoming in- creasingly important. One of the challenges in LEO satellite networks is the development of specialized and efficient routing algorithms. To satisfy the QoS requirements of multimedia applications, satellite routing protocols should consider handovers and minimize their effect on the active connections. A distributed QoS routing scheme based on heuristic ant algorithm is proposed for satisfying delay bound and avoiding link congestion. Simulation results show that the call blocking probabilities of this al- gorithm are less than that of Shortest Path First (SPF) with different delay bound.

Distributed QoS multicast routing protocol in ad hoc networks

Quality of service （QoS） routing and multicasting protocols in ad hoc networks are face with the challenge of delivering data to destinations through multihop routes in the presence of node movements and topology changes. The multicast routing problem with multiple QoS constraints is discussed, which may deal with the delay, bandwidth and cost metrics, and describes a network model for researching the ad hoc networks QoS multicast routing problem. It presents a distributed QoS multicast routing protocol （DQMRP）. The proof of correctness and complenty analysis of the DQMRP are also given. Simulation results show that the multicast tree optimized by DQMRP is better than other protocols and is fitter for the network situations with frequently changed status and the realtime multimedia application. It is an available approach to multicast routing decision with multiple QoS constraints.

QoS Routing Algorithm with Multi-Dimensions for Overlay Networks

Overlay networks have emerged as a useful approach to providing a general framework for new applications and services that are to be implemented without significantly changing the IP-layer network infrastructure.Overlay routing has been used as an alternative to the default best effort Internet routing for the absence of end-to-end Quality of Service(QoS). While the former has recently been investigated, the conflict of QoS restraints and resource optimization remains unsolved. Recent studies have shown that overlay paths can give better latency, loss rate and TCP throughput. In this paper, a multi-dimensional QoS objective model based on the analysis of multiple QoS constraints has been presented, and a routing algorithm to optimise the overlay resource of its nodes and links is then proposed.In fact, the algorithm obtained multiple QoS values using probability theory to achieve the routing according to the multi-dimensional QoS objective vector of the QoS objective model. Simulation results reveals that the algorithm works better than other existing algorithms in balancing the network resources, and applications with stringent QoS requirements could be run.

Design of QoS Aware Routing Protocol for IoT Assisted Clustered WSN

In current days,the domain of Internet of Things(IoT)and Wireless Sensor Networks(WSN)are combined for enhancing the sensor related data transmission in the forthcoming networking applications.Clustering and routing techniques are treated as the effective methods highly used to attain reduced energy consumption and lengthen the lifetime of the WSN assisted IoT networks.In this view,this paper presents an Ensemble of Metaheuristic Optimization based QoS aware Clustering with Multihop Routing(EMOQoSCMR)Protocol for IoT assisted WSN.The proposed EMO-QoSCMR protocol aims to achieve QoS parameters such as energy,throughput,delay,and lifetime.The proposed model involves two stage processes namely clustering and routing.Firstly,the EMO-QoSCMR protocol involves crossentropy rain optimization algorithm based clustering(CEROAC)technique to select an optimal set of cluster heads(CHs)and construct clusters.Besides,oppositional chaos game optimization based routing(OCGOR)technique is employed for the optimal set of routes in the IoT assisted WSN.The proposed model derives a fitness function based on the parameters involved in the IoT nodes such as residual energy,distance to sink node,etc.The proposed EMOQoSCMR technique has resulted to an enhanced NAN of 64 nodes whereas the LEACH,PSO-ECHS,E-OEERP,and iCSHS methods have resulted in a lesser NAN of 2,10,42,and 51 rounds.The performance of the presented protocol has been evaluated interms of energy efficiency and network lifetime.