An Algebraic QoS-Based Resource Allocation Model for Competitive Multimedia Applications

A new class of multimedia applications require new mechanisms to consider various Quality of Services with respect to resource constraints so that they could support reliable services and utilize available resources optimally. In this paper we present a new analytical and generic resource management model that is QoS-based. The approach for resource allocation and relevant algorithms is based on a mathematically proved model that manages resource and QoS allocation intelligently so that the total system utility of is maximized. We use the constructs of application benefit functions and resource demand functions to represent the system configuration and to solve the resource allocation problems. Extensive surveys on the related work including systematic and analytical approaches are also presented.     

数据中心的资源分配技术

针对数据中心的资源分配问题,论文讨论了数据中心虚拟化技术及资源分配的核心要求：数据中心性能保证、资源的动态分配、资源分配的公平性及收益最大化,分别针对这些方面讨论了几种资源分配算法,最后进行总结并对未来的研究发展趋势提出观点.     

考虑热效应的资源数量分配算法

芯片上局部的高温对集成电路有很多负面影响.目前已有的行为级综合算法只是在资源绑定阶段降低峰值温度,忽视了资源数量分配阶段对峰值温度的影响.为此,提出一种资源数量分配算法,根据前一个综合结果的功耗密度以及经热分析得到的温度反馈调整各种资源的使用量,使不同种类资源间的功耗密度接近平均分布,从而达到降低峰值温度的效果.实验结果表明,该算法在增加2.0%面积的情况下能平均降低峰值温度9.4℃.     

网络资源市场分配机制的分析

为了能提供一定的QoS（quality of service）,网络必须为有QoS要求的应用分配相应的资源。目前,网络资源的分配主要是基于集中式的,本文运用微观经济学的研究方法,分析了集中分配机制的一些弊端,并引入了市场分配机制。市场分配机制通过价格杠杆来分配稀缺的网络资源,达到帕累托最优,其效率优于集中分配机制,并且其具有分布式的特点,便于在网络中实施。     

Optimal Resource Allocation in Overlay Multicast

Although initially proposed as the deployable alternative to IP multicast, the overlay network actually revolutionizes the way network applications can be built. In this paper, we study the rate allocation problem in overlay-based multirate multicast, which can be understood as a utility-based resource allocation problem. Each receiver is associated with a utility defined as a function of its streaming rate. Our goal is to maximize the aggregate utility of all receivers, subject to network capacity constraint and data constraint. The latter constraint is unique in overlay multicast, mainly due to the dual role of end hosts as both receivers and senders. We use a price-based approach to address this problem. Two types of prices, network price and data price, are generated with regard to the two constraints of the problem. A distributed algorithm is proposed, where each receiver adjusts its flow rate according to the associated network price and data price. The algorithm is proved to converge to the optimal point, where the aggregate utility of all receivers is maximized. We implement our algorithm using an end-host-based protocol. Our protocol purely relies on the coordination of end hosts to accomplish tasks originally assigned to network routers, which makes it directly deployable to the existing network infrastructure.     

Resource Allocation in Bounded Degree Trees

We study the bandwidth allocation problem (bap) in bounded degree trees. In this problem we are given a tree and a set of connection requests. Each request consists of a path in the tree, a bandwidth requirement, and a weight. Our goal is to find a maximum weight subset S of requests such that, for every edge e, the total bandwidth of requests in S whose path contains e is at most 1. We also consider the storage allocation problem (sap), in which it is also required that every request in the solution is given the same contiguous portion of the resource in every edge in its path. We present a deterministic approximation algorithm for bap in bounded degree trees with ratio . Our algorithm is based on a novel application of the local ratio technique in which the available bandwidth is divided into narrow strips and requests with very small bandwidths are allocated in these strips. We also present a randomized (2+ε)-approximation algorithm for bap in bounded degree trees. The best previously known ratio for bap in general trees is 5. We present a reduction from sap to bap that works for instances where the tree is a line and the bandwidths are very small. It follows that there exists a deterministic 2.582-approximation algorithm and a randomized (2+ε)-approximation algorithm for sap in the line. The best previously known ratio for this problem is 7. A preliminary version of this paper was presented at the 14th Annual European Symposium on Algorithms (ESA), 2006.     

Risk in Two-Stage Optimal Resource Allocation

Two integral two-stage multi-period optimal resource allocations with expectation and quantile criteria are compared. Effective algorithms for solving the problem in our formulation are designed for the case of independent components of the random demand vector.     

风格资源调度的探讨

本文从多个方面就网格资源调度进行讨论,阐述了如何在动态、异构的虚拟组织间实现协同的资源共享以及协同地解决某一问题.     

具有用户体验保障的资源优化分配算法

在研究智能电视用户体验质量(Quality of Experience,QoE)量化的基础上,提出一种具有用户体验保障的资源分配模型,并针对该模型提出两种资源分配算法:RA_BAT算法和RA_GHEU算法.实验结果表明,基于回溯法的RA_BAT能够求得问题的最优解,可作为算法比较的参照系,而启发式算法RA_GHEU可在极短的运行时间内求出接近于最优的解,适合用于智能电视资源分配的实时处理.     

农田资源优化分配的计算机仿真

对于既定面积的农田资源,为使所产作物较能针对市场需求,并使种植经济效益最大化,需合理分配不同作物的种植面积.通过分析不同作物的种植成本,存贮成本,结合作物的收成与销售价格,获得各作物的种植经济效益对于种植面积的非线性关系,建立相应的计算机仿真数学模型.为了有效预测来年的作物收成和销售价格,简化假定来年的种植计划不影响来年的销售价格,根据往年的统计数据得到有关的预测数据.对资源分配问题用遗传算法进行优化求解,得到使净收益最大化的种植田亩分配方案结果.分析结论表明,最大经济效益对应的种植面积分配方案有一定的选择范围,更合理的种植面积分配方案必须面向市场需求.     

无线MIMO系统的上行资源分配算法研究

在存在同信道干扰的无线MIMO系统中,为具有多种QoS需求的调度业务分配资源是一个具有挑战性的问题.提出一种实用的、基于SDMA的贪婪资源分配(SGRA)算法.在高效的干扰管理基础上,SGRA算法可以执行两阶段启发式计算和搜索.在第1阶段,包括上行调度和子信道分配的贪婪资源分配首先在时域-频域二维进行;在第2阶段,资源分配被扩展到时域-频域-空域三维进行.SGRA的算法复杂度低,适用于实际无线通信系统.仿真结果表明,与同类算法相比,SGRA算法可以提高系统吞吐量,更好地保证实时业务的时延和最小数据速率需求,同时兼顾系统公平性.     

基于NC-OFDM系统的快速资源分配算法

非连续正交频分复用（Non-continuous orthogonal frequency division multiplexing,NC-OFDM）技术是认知无线电（Cognitive radio,CR）的一项应用。在NC-OFDM通信系统中,认知用户感知无线环境中授权频段的频谱空洞（Spectrum hole）并加以利用,以减少频谱的浪费。为保证授权用户的通信质量,认知用户需要在授权用户接入通信时立即退出,这使NC-OFDM通信系统对实时性要求较高,适用于OFDM通信系统的传统资源分配算法无法满足实时性要求。基于NC-OFDM系统的频谱特点,提出两种快速资源分配算法。所提出的算法首先依据误比特率与增益噪声比计算功率门限,采用一次判断选出认知用户使用的子信道,降低解空间维数;接着直接计算注水常量,进行初始资源分配;最后基于二分思想对已排序的子信道（方法1）或未排序的子信道（方法2）进行剩余资源的分配。理论分析与仿真结果表明,提出的快速资源分配算法与最优算法的资源分配结果相同（方法1）或相近（方法2）,复杂度更低,资源分配的速度更快。     

缓冲辅助中继网络中的缓冲资源分配方法

随着通信技术和智能终端的发展,移动内容消费出现了明显的增长。人们随时随地享受无线网络带来的多媒体娱乐体验的同时,也给蜂窝网络带来了巨大的压力,尤其是热门视频的重复传输,浪费了网络资源。预存储技术被认为是解决这类问题的有效方法。它是在非高峰时段,将热门视频等预先存储在网络边缘,以缓解高峰时段网络流量的压力。为了给用户提供更好的内容传输效率,预存储技术中基于缓冲辅助的中继网络被提出。由于中继结点缓冲空间有限,当其需要服务多个用户时,有必要对中继结点的缓冲资源进行优化分配。基于此,本文提出了一种中继结点的缓冲资源分配方法。首先,根据中继结点数据到达模型和数据处理模型,以及中继结点能忍受的缓冲区溢出概率,得到中继结点可以贡献出的最大缓冲区比例;接着,根据用户的数据到达模型和数据服务模型,给出用户缓冲区溢出概率与缓冲区比例关系的表达式;然后,建立优化问题,以最小化网络中所有用户缓冲区溢出概率和为目标,给出最优的缓冲区分配方法;最后,仿真结果证实了本文提出的方法比均匀分配法能获得更小的用户缓冲区溢出概率和。     

OFDMA系统中的一种资源分配算法

在OFDMA系统中,通过为每个用户分配不同的子载波可以实现并行数据传输.资源分配是OFDMA系统资源调度中的一个重要研究问题.本文时OFDMA无线网络系统的下行链路,考虑了资源分配的问题.重点研究了功率和子载波在用户之间的分配问题,以往的分配算法通常是非线性的迭代算法,复杂度非常高.本文的资源分配算法降低了运算复杂度,与其它算法相比考虑了信道估计的误差问题,更加符合实际情况.仿真结果表明,该算法获得了较好的分集增益.     

P2P中一种基于信誉的资源分配策略

节点的主动贡献对于P2P系统的成功运行,具有重要的作用。针对P2P中一些节点不愿意贡献资源等问题,提出一种基于信誉的资源分配策略,不同于以往的基于信誉的机制,文章是通过该策略主动选择合适的服务请求提供者,这种资源分配策略的收益是两方面的,首先把更多的资源进行共享,给更多的请求节点,其次最大化满足竞争节点。通过实验分析可知,贡献高的节点,节点的信誉和满意度都较高。     

工作流资源分配中约束规则的建模研究

传统工作流系统在对任务节点进行资源分配时,只进行了组织、角色、人员的分配,而较少对不同任务节点上执行人间的潜在关系进行建模.根据企业的实际应用需求,将这种潜在的约束关系提取出来进行建模,并以规则的形式进行定义.最后采用强有力的推理工具--规则引擎--来完成对定义的规则冲突检测以及规则的实现.     

Design of Semipersistent Resource Allocation in LTE-V Network

Radio network access technology currently used in 4G/5G is Long Term Evolution-Advanced (LTE-A), which was developed by 3rd Generation Partnership Project (3GPP). Device-to-device (D2D) communication is a technology enabling direct communications among wireless devices without forwarding through an evolved Node B (eNB). Moreover, D2D transmission can support vehicles as a vehicle-to-vehicle (V2V) environment. It is possible to avoid accidents via exchanging movement-related information among vehicles and effectively increase driving safety (and efficiency). However, radio resources are limited in radio networks. A vehicle transmits through D2D in Long Term Evolution-Vehicle (LTE-V) mode-3 standard, and an eNB can allocate the same spectrum radio resources for cellular and V2V links simultaneously. When using the same radio resources, the probability of interference may increase. This study designed a semipersistent resource allocation algorithm based on different cycles in an LTE-V network. Moreover, resource allocation under different cycles was analyzed, and a scheme for resource selection is proposed based on cycle size. The proposed Semi Persistent Gain Aware Resource Allocation (SP-GARA) scheme selects resources based on the expected sum rate of the cycle size and analyzes and discusses the results of the total sum rate at different cycles and speeds for an improved performance.     

计算网格资源分配研究

计算网格是一种新的技术,有很多内容都刚开始研究发展,还不成熟。由于网格资源的异构与时变,网格资源用户的不同需求,使网格资源分配成为一个重要问题。因而,网格资源分配技术也成为一种关键技术。给出了基于代理的网格资源分配策略和资源代理的迭代算法,从而实现了资源的协调分配。     

Adaptive Resource Allocation for Service-Based Systems

Due to its major advantages, service-oriented architecture (SOA) has been adopted in various distributed systems, such as web services, grid computing systems, utility computing systems and cloud computing systems. These systems are referred as service-based systems (SBS). In order to effectively use these systems in various applications, one major challenge which must be addressed is to manage the quality of services (QoS) to satisfy users’ requirements. In SBS, multiple services are often hosted by the same server and compete for the limited system resources of the server, such as CPU-time, memory and network bandwidth. In addition, service compositions, resource status of servers, workflow priorities and QoS requirements are usually dynamically changing in runtime. Hence, it is necessary to have effective techniques to allocate the system resources to each service provided by a server in order to satisfy the QoS requirements of multiple workflows in SBS. In this paper, a resource allocation approach is presented to adaptively allocating the system resources of servers to their services in runtime in order to satisfy one of the most important QoS requirements, the throughput, of multiple workflows in SBS.     

TCP is Competitive with Resource Augmentation

The well-known Transport Control Protocol (TCP) is a crucial component of the TCP/IP architecture on which the Internet is built, and is a de facto standard for reliable communication on the Internet. At the heart of the TCP protocol is its congestion control algorithm. While most practitioners believe that the TCP congestion control algorithm performs very well, a complete analysis of the congestion control algorithm is yet to be done. A lot of effort has, therefore, gone into the evaluation of different performance metrics like throughput and average latency under TCP. In this paper, we approach the problem from a different perspective and use the competitive analysis framework to provide some answers to the question “how good is the TCP/IP congestion control algorithm?” We describe how the TCP congestion control algorithm can be viewed as an online, distributed scheduling algorithm. We observe that existing lower bounds for non-clairvoyant scheduling algorithms imply that no online, distributed, non-clairvoyant algorithm can be competitive with an optimal offline algorithm if both algorithms were given the same resources. Therefore, in order to evaluate TCP using competitive analysis, we must limit the power of the adversary, or equivalently, allow TCP to have extra resources compared to an optimal, offline algorithm for the same problem. In this paper, we show that TCP is competitive to an optimal, offline algorithm provided the former is given more resources. Specifically, we prove first that for networks with a single bottleneck (or point of congestion), TCP is ${\mathcal{O}}(1)The well-known Transport Control Protocol (TCP) is a crucial component of the TCP/IP architecture on which the Internet is built, and is a de facto standard for reliable communication on the Internet. At the heart of the TCP protocol is its congestion control algorithm. While most practitioners believe that the TCP congestion control algorithm performs very well, a complete analysis of the congestion control algorithm is yet to be done. A lot of effort has, therefore, gone into the evaluation of different performance metrics like throughput and average latency under TCP. In this paper, we approach the problem from a different perspective and use the competitive analysis framework to provide some answers to the question “how good is the TCP/IP congestion control algorithm?” We describe how the TCP congestion control algorithm can be viewed as an online, distributed scheduling algorithm. We observe that existing lower bounds for non-clairvoyant scheduling algorithms imply that no online, distributed, non-clairvoyant algorithm can be competitive with an optimal offline algorithm if both algorithms were given the same resources. Therefore, in order to evaluate TCP using competitive analysis, we must limit the power of the adversary, or equivalently, allow TCP to have extra resources compared to an optimal, offline algorithm for the same problem. In this paper, we show that TCP is competitive to an optimal, offline algorithm provided the former is given more resources. Specifically, we prove first that for networks with a single bottleneck (or point of congestion), TCP is O(1){\mathcal{O}}(1)-competitive to an optimal centralized (global) algorithm in minimizing the user-perceived latency or flow time of the sessions, provided we allow TCP O(1){\mathcal{O}}(1) times as much bandwidth and O(1){\mathcal{O}}(1) extra time per session. Second, we show that TCP is fair by proving that the bandwidths allocated to sessions quickly converge to fair sharing of network bandwidth.