Intelligent Service Function Chain Mapping Framework for Cloud-and-Edge-Collaborative IoT

With the rapid development of Internet of thing (IoT) technology, it has become a challenge to deal with the increasing number and diverse requirements of IoT services. By combining burgeoning network function virtualization ( NFV) technology with cloud computing and mobile edge computing ( MEC), an NFV-enabled cloud-and-edge-collaborative IoT (CECIoT) architecture can efficiently provide flexible service for IoT traffic in the form of a service function chain (SFC) by jointly utilizing edge and cloud resources. In this promising architecture, a difficult issue is how to balance the consumption of resource and energy in SFC mapping. To overcome this challenge, an intelligent energy-and-resource-balanced SFC mapping scheme is designed in this paper. It takes the comprehensive deployment consumption as the optimization goal, and applies a deep Q-learning(DQL)-based SFC mapping (DQLBM) algorithm as well as an energy-based topology adjustment (EBTA) strategy to make efficient use of the limited network resources, while satisfying the delay requirement of users. Simulation results show that the proposed scheme can decrease service delay, as well as energy and resource consumption.     

Service chain mapping algorithm based on reinforcement learning

A service chain resource scheduling architecture of multi-agent based on artificial intelligence technology was proposed.Meanwhile,a service chain mapping algorithm based on reinforcement learning was designed.Through the Q-learning mechanism,the location of each virtual network element in the service chain was determined according to the system status and the reward and punishment feedback after the deployment.The experimental results show that compared with the classical algorithms,the algorithm effectively reduces the average transmission delay of the service and improves the load balance of the system.     

Service function chain deployment algorithm based on optimal weighted graph matching

Service function chain can support flexible network service requirement by linking virtual network functions.Aiming at the problem of service function chain deployment in a resource-constrained network,an algorithm for service function chain deployment based on optimal weighted graph matching was proposed.The service function chains was composed into graphs of functional topography,and the optimal matching results between graphs of functional topology and physical topology was obtained using eigendecomposition approach,and furtherly the matching results by hill-climbing method was optimized.Simulation results show that,the proposed algorithm can reduce the required bandwidth to deploy service function chains,balance the load of nodes and bandwidth of links,and support more service requests.What is more,the algorithm has a lower computation complexity and higher time efficience.     

一种集中调控的分布式服务路径选择算法

在可重构网络多态路由模型中,通常存在多条满足业务需求的服务路径。针对最优服务路径选择问题,该文设计了一种集中调控的分布式服务路径选择算法,各节点根据服务请求中的第1个元能力和目的节点生成路由表,控制器实时监控网络,调控代价过高路径并平衡网络的带宽和负载。性能分析和仿真结果表明,分布式路由表能够生成有效的服务路径,表项规模、收敛时间与元能力个数成正比,在30%的集中调控比例下,路径代价和负载均衡度性能良好,与其他算法相比,对服务请求的响应时延降低约50%。     

移动Ad Hoc网络中的负载均衡路由算法

移动Ad Hoe网络(MANET)中的路由算法应尽量使网络负载均衡,不均衡不仅导致正在通信的路由由于过度拥塞而引起数据包延时过大、吞吐量下降,而且会使拥塞节点的能量提前耗尽,从而加剧网络拓扑结构的变化及节点之间的不公平性。本文对目前提出的一些负载均衡路由算法进行了简要比较和分析,在此基础上,指出了目前负载均衡路由算法中存在的一些问题,并提出了一个实现负载均衡路由算法的一般模型。基于该模型,文中提出了一种简单的负载均衡路由算法。仿真结果表明,负载均衡路由算法比未考虑负载均衡的路由算法具有更高的数据包投递率和更低的数据包传输延时。     

MPLS流量工程中的约束路由技术

传统的IP路由协议采用最短路径算法(SPF),极易造成网络的拥塞.流量工程是目前网络中实现负载均衡和提高网络性能的一个重要技术.文中简要介绍了MPLS流量工程,重点分析了MPLS流量工程中所使用的路由协议约束路由,给出了约束的计算方法以及路由度量选择的准则.     

Optimal deployment of cloudlets based on cost and latency in Internet of Things networks

With the development of the Internet of Things (IoT), a large amount of data is generated on the network edge. Given the limited computing power of mobile devices (MDs) and access to computing resources from remote clouds, which leads to high latency to MDs, edge computing provides a way to reduce service latency by building a miniature cloud (Cloudlet). MDs transfer tasks they generate to nearby cloudlets for lower latency. Although a lot of research has been done in the field of edge computing, little attention has been paid to how to deploy cloudlets in the network. In this paper, we study the cloudlet deployment on a large number of wireless access points (APs) in an IoT network to optimize both deployment cost and network latency. When the cloudlets has been deployed in the network, we propose a fault-tolerant cloudlet deployment scheme. When the original cloudlets in the network fail, the software-defined network technology is used to start the fault-tolerant cloudlets in time to ensure the stability of the network latency. To address the above problems, we propose a binary-based differential evolution cuckoo search (BDECS) algorithm, which selects the permanent cloudlet deployment location among a large number of APs on the network. Extensive simulations reveal that the proposed algorithm has better performance in minimizing cost and latency compared with other deploymegt algorithms. Moreover, the convergence speed of the BDECS algorithm is also superior to other algorithms.

     

基于流量预测的物联网卫星节点动态缓存分配路由策略

针对低轨物联网卫星系统的路由问题,提出了基于流量预测的物联网卫星节点动态缓存分配路由策略。首先,分析低轨卫星覆盖区域内业务分布的时空特性,提出了端到端流量预测方法。然后,根据流量预测结果,提出了动态缓存分配路由策略。卫星节点通过对星间链路的流量负载进行周期性监测,动态分配与邻居节点间各条星间链路的缓存资源,分为初始化和系统运行2个阶段。同时,提出了节点拥塞时的业务分流及数据分组转发策略,通过比较排队时延和转发时延的大小,决定数据分组是否需要进行重路由。仿真结果表明,所提路由策略有效地降低了分组丢失率及平均端到端时延,改善了业务在全网的分布情况。     

Performance analysis of path rerouting algorithms for handoffcontrol in mobile ATM networks

This paper studies the effects of user mobility and handoff path rerouting on the traffic distributions in a mobile network environment. In mobile ATM networks, extra traffic load may be added to network links due to user mobility and handoff path rerouting. This requires higher network link capacity and possible topology reengineering in order to support the same quality of service (QoS) for mobile services. To capture the dynamic variations in mobile ATM networks, we propose to use a flow model. The model represents the mobile-generated traffic as a set of stochastic flows over a set of origin-destination (OD) pairs. The user mobility is defined by transfer probabilities of the flows and the handoff path rerouting algorithm is modeled by a transformation between the routing functions for traffic flows. The analysis shows that user mobility may cause temporal variations as well as smoothing effects on the network traffic. Using the flow network model, typical handoff path rerouting algorithms are evaluated through both analytical and experimental approaches. The evaluation methodology can be used for either redesigning the network topology for a given path rerouting algorithm or selecting a path rerouting algorithm for a given network topology under a specific mobile service scenario     

基于最长有效功能序列的服务功能链部署算法

服务功能链的服务性能取决于功能的部署位置和数据传输路径的选择。针对资源有限的网络中的服务功能链部署问题,该文设计了一种基于最长有效功能序列(LEFS)的服务功能链部署算法,以功能复用和带宽需求联合优化为目标,在控制路径长度的同时根据LEFS逐步搜索中继节点,直至满足服务请求。仿真结果表明,该算法能够均衡网络资源,同时优化网络的功能部署率和带宽利用率,与其他算法相比,网络资源利用率降低了10%,可以支持更多的服务请求,且算法计算复杂度低,可以实现对服务请求的快速响应。     

On the Placement of Infrastructure Overlay Nodes

Overlay routing has emerged as a promising approach to improving performance and reliability of Internet paths. To fully realize the potential of overlay routing under the constraints of deployment costs in terms of hardware, network connectivity and human effort, it is critical to carefully place infrastructure overlay nodes to balance the tradeoff between performance and resource constraints. In this paper, we investigate approaches to perform intelligent placement of overlay nodes to facilitate (i) resilient routing and (ii) TCP performance improvement. We formulate objective functions to capture application behavior: reliability and TCP performance, and develop several placement algorithms, which offer a wide range of tradeoffs in complexity and required knowledge of the client-server location and traffic load. Using simulations on synthetic and real Internet topologies, and PlanetLab experiments, we demonstrate the effectiveness of the placement algorithms and objective functions developed, respectively. We conclude that a hybrid approach combining greedy and random approaches provides the best tradeoff between computational efficiency and accuracy. We also uncover the fundamental challenge in simultaneously optimizing for reliability and TCP performance, and propose a simple unified algorithm to achieve both.      

Load balance in hierarchical routing network

In this article, the problem of load balance in hierarchical routing network is studied. Since conventional shortest path first (SPF) algorithm over aggregated topology in hierarchical routing network may result in worse routing performance, a traffic sharing path selection algorithm and a variable weight scheme are put forward for hierarchical routing network, which can equilibrate the utilities of link resources and reduce the blocking probability of connections with the improvement on survivability. Simulations are conducted to evaluate proposed variable weight and traffics balance (VWTB) algorithm, which combines traffic sharing and variable weight. From the simulation results, it can be found that the proposed VWTB algorithm can balance the traffics and equilibrate the utilities of link resources significantly.     

三层动态网络联合优化选路算法

 IP/MPLS over WDM被认为是下一代互联网络的最理想解决方案,但是在目前以及以后的很长一段时间内,网络结构仍然是IP/MPLS over SDH over WDM这样三层网络共存的情况。为了能够有效降低三层动态网络中的业务阻塞率,本文提出了三层动态网络联合优化选路算法。该算法分为两种模式,在模式1中,上层网络中被阻塞的业务可以开放的利用下层网络的空闲资源;在模式2中,将三层网络整合成为一个网络,在这个综合网络中为每一个业务进行选路。为了能够实时的传输每一个到达的动态业务,在这两种模式中采用蚁群策略为动态业务进行选路,提出了一个新的前向蚂蚁路径选择概率模型以及路径质量评判参数,使得所选的路径能兼顾链路利用率和路径跳数。仿真实验表明,同其他算法相比,本文提出的算法可以有效地降低三层动态网络的阻塞率。     

基于改进灰狼优化算法的服务功能链映射算法

随着工业互联网、车联网、元宇宙等新型互联网应用的兴起，网络的低时延、可靠性、安全性、确定性等方面的需求正面临严峻挑战。采用网络功能虚拟化技术在虚拟网络部署过程中，存在服务功能链映射效率低与部署资源开销大等问题，联合考虑节点激活成本、实例化开销，以最小化平均部署网络成本为优化目标建立了整数线性规划模型，提出基于改进灰狼优化算法的服务功能链映射（improved grey wolf optimization based service function chain mapping，IMGWO-SFCM）算法。该算法在标准灰狼优化算法基础上添加了基于无环K最短路径（K shortest path，KSP）问题算法的映射方案搜索、映射方案编码以及基于反向学习与非线性收敛改进三大策略，较好地平衡了其全局搜索及局部搜索能力，实现服务功能链映射方案的快速确定。仿真结果显示，该算法在保证更高的服务功能链请求接受率下，相较于对比算法降低了11.86%的平均部署网络成本。     

Domain load balancing routing for multi-gateway wireless mesh networks

As Wireless Mesh Networks (WMNs) are typically used for Internet access, most traffic is routed through the gateways which connect WMN to the wired network. As a result, the gateways tend to get congested and balancing of the traffic load of gateways is critical. In this paper, we consider applications that require continuous provision of a certain bandwidth to a server located at the wired network. If a path that satisfies the bandwidth request cannot be found, the request will be rejected, so that load imbalance will result underutilization of the network capacity. We present a novel load balancing routing algorithm for maximizing the network utilization (i.e., accommodating service requests as many as possible) for multi-gateway WMNs. In the proposed scheme, a WMN is divided into domains. Each domain is served by one gateway, so that all traffic of a domain is served by the corresponding gateway. Our scheme determines routing to balance the traffic load among domains, and then performs load balancing routing within each domain. Simulation results show that in square grid topologies, our intra-domain routing achieves near optimal performance with about 70% less overhead than the existing schemes. Our inter-domain load balancing scheme outperforms the existing heuristics by up to 25% while achieving about 80% performance of the optimal solution.     

一种基于匹配博弈的服务链协同映射方法

针对软件定义网络(SDN)/网络功能虚拟化(NFV)环境下服务链映射难以兼顾效率与物理资源利用率的问题,该文提出一种基于匹配博弈的服务链协同映射方法。首先,以最大化网络资源效用为目标,建立服务链映射模型MUSCM;然后,分虚拟网络功能(VNF)部署和组链两个部分解决服务链映射问题,VNF部署部分,设计基于多对一匹配博弈理论的算法协同服务链和服务节点双方互相进行选择,有效提升了服务链的映射效率和物理资源的利用率,在此基础上,设计基于分段路由策略的算法实现各VNF实例间的流量牵引以完成VNF组链,有效降低了链路传输时延。实验结果表明,与经典算法相比,该算法在保证映射请求接受率的同时,有效降低了服务链的平均传输延时,提升了系统的物理资源利用率。     

IP网络时延敏感型业务流自适应负载均衡算法

互联网对时延敏感的业务数据流,要求具有较低的端到端时延,但是网络拥塞的发生,将会使服务质量无法保证。基于链路关键度提出了一种新的自适应负载均衡路由算法(LARA,load adaptive routing algorithm),能最大限度地避开拥塞链路从而减少端到端延迟。该算法通过得到一个优化目标函数,并利用凸优化理论将优化目标函数分解为若干个子函数,最终得到一个简单的分布式协议。利用NS2仿真器在基于CERNET2真实的拓扑结构上进行仿真实验,同时与网络中能普遍部署的等开销多路径(ECMP,equal-costmulti-path)算法相比较,通过测试反馈时延、分组丢失率、流量负载,结果表明LARA具有更好的自适应性和健壮性,性能相比更优。     

一种满足带宽和时延约束的选播QoS路由算法

建立一个满足带宽和时延约束的选播通信服务模型，提出相应的选播QoS路由算法。仿真实验结果表明：该算法是有效且切实可行的，它能同时满足带宽和时延的约束条件，较好地平衡网络负载．改善了网络服务质量。     

Joint service function chain deploying and path selection for bandwidth saving and VNF reuse

Service function chain (SFC) is managed as a set of chained virtual network functions (VNFs) in a particular order. The efficiency of a network closely depends on how these VNFs are deployed in the network. In this paper, we study the joint problem of service function chain deploying and path selection for bandwidth saving and VNF reuse. We first describes the problem as a multiobjective and multirestriction problem, and then a heuristic service function chain deployment algorithm based on longest function assignment sequence is proposed. Via simulations, we show that our design can reduce the number of deployed VNFs and link bandwidth requirement jointly and serve more requests than other algorithms.     

Adaptive routing and wavelength assignment algorithm for WDM networks with uniform and non-uniform traffic model

This letter studies routing and wavelength assignment (RWA) problem in wavelength-routed wavelength-division multiplexing networks with both uniform and nonuniform traffic model. Our research shows that the potential traffic load information is a crucial factor for routing algorithm design. Based on our analysis, an adaptive RWA algorithm is proposed. The simulation shows that the proposed algorithm performs much better than other adaptive RWA algorithms.