QoS based multicast routing algorithms for real time applications

In recent years, there has been a lot of interest in providing real-time multimedia services like digital audio and video over packet-switched networks such as Internet and ATM. These services require certain quality of service (QoS) from the network. The routing algorithm should take QoS factor for an application into account while selecting the most suitable route for the application. In this paper, we introduce a new routing metric and use it with two different heuristics to compute the multicast tree for guaranteed QoS applications that need firm end-to-end delay bound. We then compare the performance of our algorithms with the other proposed QoS-based routing algorithms. Simulations were run over a number of random networks to measure the performance of different algorithms. We studied routing algorithms along with resource reservation and admission control to measure the call throughput over a number of random networks. Simulation results show that our algorithms give a much better performance in terms of call throughput over other proposed schemes.     

Complexity and design of QoS routing algorithms in wireless mesh networks

Quality of service (QoS) provisioning in wireless mesh networks (WMNs) is an open issue to support emerging multimedia services. In this paper, we study the problem of QoS provisioning in terms of end-to-end bandwidth allocation in WMNs. It is challenging due to interferences in the networks. We consider widely used interference models and show that except a few special cases, the problem of finding a feasible path is NP-complete under the models. We propose a k-shortest path based algorithmic framework to solve this problem. We also consider the problem of optimizing network performance by on-line dynamic routing, and adapt commonly used conventional QoS routing metrics to be used in WMNs. We find the optimal solutions for these problems through formulating them as optimization models. A model is developed to check the existence of a feasible path and another to find the optimal path for a demand; moreover, an on-line optimal QoS routing algorithm is developed. Comparing the algorithms implemented by the proposed framework with the optimization models shows that our solution can find existing feasible paths with high probability, efficiently optimizes path lengths, and has a comparable performance to the optimal QoS routing algorithm. Furthermore, our results show that contrary to wireline networks, minimizing resource consumption should be preferred over load distribution even in lightly loaded WMNs.     

一种业务驱动的多媒体传感器网络路由算法

针对多媒体传感器网络承载业务(视频图像业务、音频业务以及数据业务)的差异性和不同业务对QoS的差异性,基于蚁群算法和混沌理论,抽象业务驱动的QoS路由模型,提出了一种业务驱动的路由算法SDR(Service-Driver Routing)。依据各类业务对QoS的差异性选择相应路由策略,达到充分利用网络资源、提高网络承载业务性能的目标。采用NS2对该算法进行实验仿真,实验结果表明,与其他路由算法相比,该算法可提供区分业务的QoS保障。     

Design and performance analysis of an inductive QoS routing algorithm

Routing mechanism is key to the success of large-scale, distributed communication and heterogeneous networks. Consequently, computing constrained shortest paths is fundamental to some important network functions such as QoS routing and traffic engineering. The problem of QoS routing with multiple additive constraints is known to be NP-complete but researchers have been designing heuristics and approximation algorithms for multi-constrained paths algorithms to propose pseudo-polynomial time algorithms. This paper introduces a polynomial time approximation quality of service (QoS) routing algorithm and constructs dynamic state-dependent routing policies. The proposed algorithm uses an inductive approach based on trial/error paradigm combined with swarm adaptive approaches to optimize lexicographically various QoS criteria. The originality of our approach is based on the fact that our system is capable to take into account the dynamics of the network where no model of the network dynamics is assumed initially. Our approach samples, estimates, and builds the model of pertinent aspects of the environment which is very important in heterogeneous networks. The algorithm uses a model that combines both a stochastic planned pre-navigation for the exploration phase and a deterministic approach for the backward phase. Multiple paths are searched in parallel to find the K best qualified ones. To improve the overall network performance, a load adaptive balancing policy is defined and depends on a dynamic traffic path probability distribution function. We conducted a performance analysis of the proposed QoS routing algorithm using OPNET based on a platform simulated network. The obtained results demonstrate substantial performance improvements as well as the benefits of learning approaches over networks with dynamically changing traffic.     

基于移动Agent的无线多媒体传感器网络QoS路由算法

无线多媒体传感器网络(WMSNs)的主要特点包括资源有限、时延敏感和数据冗余性高。此外,音视频数据流传输所需的带宽是多媒体传感器节点所能承受的最大传输带宽的几倍。上述因素使得WMSNs的QoS 路由成为一个亟待解决的关键技术问题。鉴于此,首先通过基于等差数列的非均匀分簇算法对网络区域进行划分,然后在此网络拓扑上,提出一种基于移动Agent的WMSNs的QoS路由算法(MAQR)。MAQR由路由发现和数据传输两个阶段组成。在路由发现阶段,采用移动代理技术完成多路径路由发现。在数据传输阶段,采用多优先级多路径传输模型把数据流进行分类,并利用流量预测算法实现网络的负载均衡。最后,在NS-2平台上实现了MAQR,通过与同类算法进行仿真比较,发现MAQR较之同类算法能够明显地提高音视频传输的服务质量。此外,MAQR算法比同类算法的能耗更低。     

A new approach to dynamic bandwidth allocation in Quality of Service networks: Performance and bounds

Efficient dynamic resource provisioning algorithms are necessary to the development and automation of Quality of Service (QoS) networks. The main goal of these algorithms is to offer services that satisfy the QoS requirements of individual users while guaranteeing at the same time an efficient utilization of network resources.In this paper we introduce a new service model that provides per-flow bandwidth guarantees, where users subscribe for a guaranteed rate; moreover, the network periodically individuates unused bandwidth and proposes short-term contracts where extra-bandwidth is allocated and guaranteed exclusively to users who can exploit it to transmit at a rate higher than their subscribed rate.To implement this service model we propose a dynamic provisioning architecture for intra-domain Quality of Service networks. We develop a set of dynamic on-line bandwidth allocation algorithms that take explicitly into account traffic statistics and users’ utility functions to increase users’ benefit and network revenue.Further, we propose a mathematical formulation of the extra-bandwidth allocation problem that maximizes network revenue. The solution of this model allows to obtain an upper bound on the performance achievable by any on-line bandwidth allocation algorithm.We demonstrate through simulation in realistic network scenarios that the proposed dynamic allocation algorithms are superior to static provisioning in providing resource allocation both in terms of total accepted load and network revenue, and they approach, in several network scenarios, the ideal performance provided by the mathematical model.     

一种基于DPSO的无线传感器网络QoS路由算法

针对无线传感器网络中不同业务对服务质量(QoS)的不同需求,提出一种基于离散粒子群优化(DPSO)的无线传感器网络QoS路由(DPSO-QR)算法。算法将路由建立过程抽象为多目标优化过程,以节点间通信的传播损耗、时延、带宽、丢包率为优化目标,利用DPSO算法实现多目标优化,为拥有不同QoS需求的网络业务提供满足其特有需求的优化路由。仿真实验表明:与SAR,EQR算法相比,DPSO-QR算法降低了网络平均端到端时延,减小了丢包率,延长了网络寿命。     

基于软件定义的WSNs非均匀分簇QoS路由算法

针对传统无线传感器网络非均匀分簇QoS路由中节点资源受限,无法动态管理等问题,提出一种基于软件定义的无线传感器网络非均匀分簇QoS路由算法(SDNUCQS)。控制器考虑节点能量、节点间距离和QoS指标,采用熵权法竞选出高质量簇头,并对网络进行非均匀分簇。利用交叉分类法将所要传输的数据通过时延和丢失率分成不同类型。在簇间路由中,控制器以链路QoS指标和节点负载度为参数,采用集中式方式分别计算QoS数据和普通数据传输的最佳路径。仿真实验结果表明,SDNUCQS算法能显著降低网络时延和丢失率,与LEACH、EEUC、CRIPSO和tPSOEB算法比较,能降低簇头能耗且延长了网络生命周期。     

基于SDN分级分域架构的QoS约束路由算法

传统分布式的网络架构制约路由算法的创新,软件定义网络的出现为路由算法的优化提供了新思路。已有研究中,启发式算法广泛应用于服务质量路由,但由于计算复杂度高而无法在大型网络中应用。而其他算法均存在不同程度的问题,要么复杂度较高,要么算法性能较差,如最短路径算法。基于 SDN 分级分域架构,提出了 LC-LD 路由算法,综合时延条件和代价度量约束并在计算复杂度和算法性能之间保持平衡。仿真分析表明,LC-LD路由算法在有较低的计算复杂度的同时还有较高的服务质量路由选路性能。