三网融合下的动态带宽分配方案研究

以三网融合的接八技术EPON为基础,分析三网融合后不同等级用户、不同等级业务的竞争关系,研完了已有的经典动态带宽分配方案,并根据ONU端不同用户的SLA（服务等级协议）划分,及ONU内部不同优先级业务的划分,设计了支持用户SLA的EPON系统,最后给出一种新的带宽分配算法STFD-DBA,并在理论上分析了该算法的可行性...     

一种WDM-PON系统中基于SLA的动态带宽算法

文章提出了一种基于业务等级协议(SLA)的动态带宽分配算法,该算法根据SLA为光网络单元(ONU)分配带宽权重和相应的优先权,确保了ONU的带宽分配和服务质量,改善了网络的性能,满足了网络业务的QoS要求.最后,通过仿真证明了这种算法的正确性.     

云计算中基于QoS的调配优化算法

研究和设计云计算环境下一种优化的基于QoS约束的调配算法,并验证其正确性。在QoS需求下采用具有服务等级协议(SLA)参数的约束条件,对任务划分优先级,形成优先级队列。SLA服务参数采用二进制权值的方法进行标记,避免了作业分级重叠的情况。在对该任务分配计算资源时,采用资源等级队列的方法,分配合理的工作节点。通过对几种算法的比较实验,验证优化算法运转的鲁棒性和正确性。     

云计算服务等级协议（SLA）研究

以云计算服务等级协议SLA为研究对象,从云计算SLA的概念、需求以及云计算SLA所涉及到的参数等几个方面,对云计算服务等级协议SLA进行了研究和阐述。重点对目前常见的几种云计算服务所涉及的关键服务质量参数进行了分类阐述。     

云服务中SLA体系的建立

SLA（服务等级协议）将服务规范化、可度量化,是运营商给用户的服务承诺。对云来说,SLA尤为重要,它关系到用户对运营商的信任度。文章着重描述云数据中心服务中SLA体系的建立方法,包括如何设计和度量SLA指标,如何实施并优化LSLA体系等,希望SLA体系建立完成后能帮助云服务进一步走向成熟。     

云计算环境下的服务等级协议管理

文章对云计算环境下的SLA(服务等级协议)作了详细的描述,并从云计算基础设施提供商的角度对其重要性作了分析。简述了SLA如何从一个基础设施可用性的问题演进成为云计算环境下复杂的应用SLO(服务等级目标)相关的问题。文章为云计算基础设施服务提供商提供了一些必要的方法来评估客户应用SLA对基础设施的相关要求,同时给出了完整的框架和步骤来实现这些SLA保障。     

SLA在5G 2B中面临的挑战与应对策略

针对SLA（服务等级协议）在5G 2B（商业对商业）中面临的挑战,从技术、工程、商务维度开展分析,提出通过对2B需求进行原子化归类,并与网络特性、建设方案、维护手段进行一一匹配,形成映射数据库的应对方法。从而实现对网络建设和维护成本能力的快速测算,形成满足SLA条件下的商业报价,为促成5G 2B领域的商业合作提供有效保障。同时,简要介绍利用数字化软件工具促进SLA在5G 2B项目中广泛使用的方法。     

基于业务等级的波长分配算法

本文主要研究在WDM全光通信网中,将业务等级约定(SLA)和路由波长分配(RWA)问题结合在一起考虑,根据实际网络情况,确保高等级业务得到更好的服务。本文从不同的角度考虑,提出了两种算法,并对其进行了仿真比较和分析。     

IP网络的SLA(服务等级协议)探讨

自从中国加入WTO以来,国内电信市场全球化步伐日益加快,电信行业的竞争也逐步从简单的价格战转向提高服务品质和客户满意度。因此。如何规范服务品质、提高服务质量,已经成为国内电信企业面临的最新挑战。正是在新的市场竞争趋势和市场需求的双重压力下,SLA（服务等级协议）模式引起了广泛关注。介绍了电信领域SLA产生的背景和SLA管理的概念、内容,探讨了IP网络的SLA基本参数,并结合实际情况,探讨了电信运营商IP网络SLA实施中存在的困难。     

面向典型工业应用场景的5G SLA指标研究

重点研究机器视觉、视频回传分析、AGV（自动导引运输车）控制、AR（增强现实）、PLC（可编程逻辑控制器）柔性控制、远程控制、机器人巡检这7大类典型工业应用场景，构建面向典型工业应用场景的5G网络SLA（服务等级协议）指标。在此基础上，开展3大类别场景的SLA指标分析，归纳总结具有相似业务功能特性的应用场景对5G网络的共性需求，并对未来5G+工业场景的发展建设过程中将会遇到的问题提出思考和建议。     

脏纸编码的多用户MIMO-OFDM系统中基于纳什公平的资源分配算法

MIMO-OFDM技术是实现大容量无线数据传输的一项关键技术。多用户系统中,在最大化系统资源利用率的同时保证用户间资源分配的公平性是系统设计的一个重要问题。该文首先分析了MIMO系统中最大化吞吐量的一种实现方式脏纸编码(DPC),然后基于纳什公平性准则提出了一种用于DPC的多用户MIMO-OFDM系统中的自适应资源分配算法。仿真结果表明,该算法在损失较小系统吞吐量的前提下,很好地保证了用户间资源分配的公平性。     

面向用户体验的多小区混合非正交多址接入网络资源分配方法

该文研究了多小区混合非正交多址接入(MC-hybrid NOMA)网络的资源分配.为满足异构用户的服务体验,以最大化全网综合平均意见评分(MOS)累加和为目标,考虑基站选择、信道接入和功率资源分配的联合优化问题,该文提出一种用户、基站和信道3方的2阶段转移匹配算法,并根据用户MOS进行子信道功率优化.仿真结果表明所提多...     

效用max—min公平准则及其在ABR业务中的应用

本文提出一种新的基于效用函数的max-min(UMM）公平准则,它实现的是用户效用之间的公平分配。在ABR业务下,本文提出UMM公平性的另外两个等价定义,考察了用户的最小需求和最大需求。为了求解UMM公平分配,文中给出集中式的UMM公平分配算法及其数学证明。文章从保证分配效率的角度出发赋予峰值信元位率PCR以新的含义。UMM公平性不仅是对以往ABR业务中max-min公平性的概括,还具有很好的推广前景,特别适用于多应用类型的网络资源分配。     

Adaptive Fair Subcarrier/Rate Allocation in Multirate OFDMA Networks: Radio Link Level Queuing Performance Analysis

This paper presents a semi-analytical methodology for radio link level performance analysis in a multirate "orthogonal frequency-division multiple-access" (OFDMA) network with adaptive fair rate allocation. Multirate transmission is assumed to be achieved through adaptive modulation, and fair rate allocation is based on the principle of generalized processor sharing to allocate the subcarriers adaptively among the users. The fair rate allocation problem is formulated as an optimization problem with the objective of maximizing system throughput while maintaining fairness (in terms of transmission rate) among the users. The "optimal" fair rate allocation is obtained by using the "Hungarian method." A heuristic-based approach, namely the "iterative approach," that is more implementation friendly is also presented. The throughput performance of the iterative fair rate allocation is observed to be as good as that of optimal fair rate allocation and is better than that of the static subcarrier allocation scheme. Also, the iterative fair allocation provides better fairness compared to that for each of the optimal and the static subcarrier allocation schemes. To this end, a queuing model is formulated to analyze radio link level performance measures such as packet dropping probability and packet transmission delay under the above rate allocation schemes. In this formulation, packet arrivals are modeled by the discrete Markov modulated Poisson process, which is flexible to model different types of traffic arrival patterns. The proposed framework for radio link level performance analysis of multirate OFDMA networks is validated by extensive simulations. Also, examples on the application of the proposed model for connection admission control and quality-of-service provisioning are illustrated     

基于共享资源量的动态多资源公平分配策略

针对云计算共享系统中多资源分配问题,提出一种基于共享资源量的动态多资源公平分配策略。该策略根据不同用户资源需求和共享资源量建立一个线性规划模型,同时证明该模型满足公平分配的4个重要属性：动态帕累托最优、激励共享、动态无嫉妒性和防止策略性操作,而且给出一种改进的动态多资源公平分配算法来提高算法运行效率。实验结果表明,所提动态多资源公平分配策略能够在满足任务资源需求的同时,尽可能保证公平分配下最大化占优资源份额,并且改进的分配算法能够有效地提高资源的分配效率。     

Application-Oriented Flow Control: Fundamentals, Algorithms and Fairness

This paper is concerned with flow control and resource allocation problems in computer networks in which real-time applications may have hard quality of service (QoS) requirements. Recent optimal flow control approaches are unable to deal with these problems since QoS utility functions generally do not satisfy the strict concavity condition in real-time applications. For elastic traffic, we show that bandwidth allocations using the existing optimal flow control strategy can be quite unfair. If we consider different QoS requirements among network users, it may be undesirable to allocate bandwidth simply according to the traditional max-min fairness or proportional fairness. Instead, a network should have the ability to allocate bandwidth resources to various users, addressing their real utility requirements. For these reasons, this paper proposes a new distributed flow control algorithm for multiservice networks, where the application's utility is only assumed to be continuously increasing over the available bandwidth. In this, we show that the algorithm converges, and that at convergence, the utility achieved by each application is well balanced in a proportionally (or max-min) fair manner     

Resource Allocation in Multi-channel Multi-user Relay System with Fairness Constraints

In this paper, we derive optimal joint power allocation, subchannel pairing and scheduling strategies in multiple orthogonal channels multiple users wireless networks in the presence of a single regenerative relay node. Two models with users’ data rate request (fairness) constraint in different time domains are considered. The first one is called deterministic model in which each user’s data rate request has to be satisfied in each time slot t (named short term fairness constraint) and the second one is called stochastic model in which users have average data rate request (named long term fairness). In these two models the optimization problems of maximizing system capacity with total transmit power constraint and fairness constraint are formulated. The Lagrangian dual method is used to derive the optimal solution for deterministic model and in the stochastic model stochastic approximation and dual method are employed to find out the optimal algorithm. Both algorithms have polynomial times complexity, which is reduced significantly compared with the Exhaustive Search Method (ESM). Since Lagrangian dual method is utilized in both schemes, the dual gap is also analyzed. Furthermore, through the analysis and simulation, we see that the optimal resource allocation algorithm in stochastic model has better performance than that in the deterministic model for its ability to exploit temporal diversity.     

Fairness and Load Balancing in Wireless LANs Using Association Control

The traffic load of wireless LANs is often unevenly distributed among the access points (APs), which results in unfair bandwidth allocation among users. We argue that the load imbalance and consequent unfair bandwidth allocation can be greatly reduced by intelligent association control. In this paper, we present an efficient solution to determine the user-AP associations for max-min fair bandwidth allocation. We show the strong correlation between fairness and load balancing, which enables us to use load balancing techniques for obtaining optimal max-min fair bandwidth allocation. As this problem is NP-hard, we devise algorithms that achieve constant-factor approximation. In our algorithms, we first compute a fractional association solution, in which users can be associated with multiple APs simultaneously. This solution guarantees the fairest bandwidth allocation in terms of max-min fairness. Then, by utilizing a rounding method, we obtain the integral solution from the fractional solution. We also consider time fairness and present a polynomial-time algorithm for optimal integral solution. We further extend our schemes for the on-line case where users may join and leave dynamically. Our simulations demonstrate that the proposed algorithms achieve close to optimal load balancing (i.e., max-min fairness) and they outperform commonly used heuristics.     

QoS‐Guaranteed Multiuser Scheduling in MIMO Broadcast Channels

This paper proposes a new multiuser scheduling algorithm that can simultaneously support a variety of different quality‐of‐service (QoS) user groups while satisfying fairness among users in the same QoS group in MIMO broadcast channels. Toward this goal, the proposed algorithm consists of two parts: a QoS‐aware fair (QF) scheduling within a QoS group and an antenna trade‐off scheme between different QoS groups. The proposed QF scheduling algorithm finds a user set from a certain QoS group which can satisfy the fairness among users in terms of throughput or delay. The antenna trade‐off scheme can minimize the QoS violations of a higher priority user group by trading off the number of transmit antennas allocated to different QoS groups. Numerical results demonstrate that the proposed QF scheduling method satisfies different types of fairness among users and can adjust the degree of fairness among them. The antenna trade‐off scheme combined with QF scheduling can improve the probability of QoS‐guaranteed transmission when supporting different QoS groups.     

Fair and efficient opportunistic interference alignment algorithm based on round-robin scheduling

Opportunistic interference alignment (OIA) algorithm was proposed for the practical implementation of interference alignment (IA).A fair and efficient OIA algorithm was presented for the unfairness in resource allocation and high dependence of tremendous users in the existing OIA algorithms.Firstly,the users with the best channel was selected in the primary cell based on round-robin scheduling after the coordinate cluster was determined.Then,the interference from the primary users was eliminated by skillfully designing the useful signal spaces in the subordinate cells.Furthermore,the users with the minimum interference leakage was selected in the subordinate cells.Finally,the fairness performance was theoretically analyzed.Simulation results show that both the sum-rate and fairness of the proposed algorithm are significantly higher than that of the conventional algorithm with less interference leakage.Besides,the users can achieve a quick access.