截止时间约束下独立网格任务的协同调度模型

针对网格环境中任务实时性难于保证的问题,提出一种截止时间保证度的计算方法,用于量化分析资源协同调度对任务实时约束的影响,并设计和实现了一个可扩展的协同调度模型,允许系统动态选择截止时间保证度最优的协同调度方案.实验结果显示,截止时间保证度指标可以较为准确地量化调度决策对任务实时约束的满足程度,从而为实时网格任务调度决策...     

一种支持公平交易的网格计算经济模型

针对网格计算中的资源管理，提出了一种具有公平交易属性的计算经济模型。通过价格监管、公平调度、信誉度和运行监测等方法对日用品市场模型进行控制和约束，从而使得网格资源的市场交易变得稳定、有序且高效。仿真实验结果表明，和传统经济模型比较，模型在任务完成时间、系统吞吐量和稳定性等方面都有所提高。     

军用网格环境下基于优先权的Min-Min任务调度算法

军用网格环境下的资源调度与一般网格环境下的资源调度相比较，一个明显的特点就是必须考虑一些特别任务的优先级。在给出网格独立任务调度模型基础上，提出了一种基于优先权的Min—Min资源调度算法，该算法首先调度优先级高的任务，其余任务则采用Min—Min算法调度。经过分析，该算法的时间复杂度是O（n^2m），与Min—Min相比，该算法的Makespan可能略大，但可以满足军用网格环境下特殊任务优先执行的需求。     

基于生存性和Makespan的多目标网格任务调度算法研究

在动态、复杂的网格系统中,资源的失效非常频繁,网格资源的失效会导致在该节点上执行的计算任务无法正常完成,从而影响网格计算的服务质量和效率。针对这个问题,提出了任务生存性(survivability)的概念,将任务生存性与Makespan结合起来,给出了一个可调节的局部目标函数,实现了基于生存性和Makespan的Min-min启发式调度算法(SM-Min-min)。实验证明该算法能够有效地平衡Makespan和任务生存性目标,并可以通过调节目标函数中的偏好参数满足不同的需求,因此更适合开放复杂的计算网格环境。     

多功能相控阵雷达实时任务调度研究

针对多功能相控阵雷达资源调度问题,建立了合理的雷达任务模型并提出一种新的调度算法.在雷达任务模型中将每一类驻留请求合并为一种任务,这样可以为调度处理提供最大的灵活性,同时基于此任务模型分析了调度器的时间负载.所提出的调度算法综合考虑了任务的工作方式优先级和截止期两个参数,可以较好地适应不同的负载情况.给出了算法的具体实现步骤,并以截止期错失率作为评估指标进行了仿真验证.仿真结果表明,本文所提出的调度算法能够有效降低任务的截止期错失率,对调度性能有明显的改善.     

基于双重自适应策略的旋转相控阵雷达任务调度方法研究北大核心CSCD

针对旋转相控阵雷达任务调度过程中资源利用不充分问题和调度算法优化需求,提出基于双重自适应策略的任务调度算法(TSM-DAS)。首先,通过探究旋转相控阵雷达扫描特性,将雷达任务分为两类;然后,针对不同类型任务的调度时间差异,提出任务调度的双重自适应策略;最后,结合任务时间窗、优先级和贪心算法,给出基于双重自适应策略的任务调度算法,并通过仿真实验对TSM-DAS进行验证。实验结果表明,相比其他同类算法,TSM-DAS能够有效提升雷达资源利用率,降低任务截止期错失率,从整体上提升旋转相控阵雷达的任务调度效能。     

计算网格环境下以QoS为指导的启发式任务调度

实现用户的服务质量QoS是网格的一个重要特征．网格环境下以服务质量为指导的任务调度是一个非常复杂且具有挑战性的问题，特别是在用户的任务具有多种QoS需求的情况下。利用效用函数对用户的多种QoS进行建模．提出了一个同时兼顾任务完成时间和用户服务质量的目标函数。在此基础上提出了一种计算网格环境下针对一组具有QoS需求的相互独立的计算任务的启发式调度算法。模拟实验结果显示，该算法能较好的满足不同用户的需求并提升系统资源的利用率。     

数字阵列雷达波束驻留调度间隔分析算法

针对数字阵列雷达波束驻留调度问题,研究了基于调度间隔分析的调度算法。该算法综合分析了1个调度间隔内申请执行的波束驻留任务,且调度过程中进行了脉冲交错。调度准则充分考虑了任务的工作方式优先级和截止期,并以任务丢失率、实现价值率、系统时间利用率作为评估指标。仿真结果表明修正截止期准则主要强调任务的紧迫性,修正工作方式优先级主要强调任务的重要性,而截止期—工作方式优先级和工作方式—截止期调度准则可以在二者间更好地折中,在总体性能上要优于其他调度准则。     

高性能调度技术中应用程序调度模型设计--地理空间信息网格调度技术的研究

地理空间信息网格调度技术，要比传统的高性能计算中的调度技术复杂，原因是如果将全部网格资源作为一个应用程序的调度和执行目标，必将导致通信延迟、成本昂贵、执行低效等。为此，综合考虑应用程序特性、机器特性等，研究设计了地理空间信息网格高性能调度技术中的应用程序调度模型，包括地理空间信息网格应用程序分析；资源特性分析；应用程序分解；性能预测；资源调度；机器选择；任务映射；任务调度；任务调度器和调度器管理模块。以实现为不同的应用程序匹配不同的计算资源，提高计算资源的利用率和应用程序的执行效率。     

基于QoS的网格工作流的选择调度算法

开放网格服务架构（OGSA）和计算经济模型的提出,使得动态的、不同QoS的服务支持下的资源调度成为一个复杂且具有挑战性的问题。文中提出了基于QoS的网格工作流的选择调度算法,该算法采用动态资源选择策略适应网格计算环境下的动态性和自治性。在满足用户对服务质量要求的基础上,平衡了工作流中服务实例的花费、处理时间和可用性之间的关系。试验证明该调度算法符合计算网格的复杂环境,能够更好地满足不同用户的实际需要。     

A game theoretic framework for bandwidth allocation and pricing inbroadband networks

In this paper, we present a game theoretic framework for bandwidth allocation for elastic services in high-speed networks. The framework is based on the idea of the Nash bargaining solution from cooperative game theory, which not only provides the rate settings of users that are Pareto optimal from the point of view of the whole system, but are also consistent with the fairness axioms of game theory. We first consider the centralized problem and then show that this procedure can be decentralized so that greedy optimization by users yields the system optimal bandwidth allocations. We propose a distributed algorithm for implementing the optimal and fair bandwidth allocation and provide conditions for its convergence. The paper concludes with the pricing of elastic connections based on users' bandwidth requirements and users' budget. We show that the above bargaining framework can be used to characterize a rate allocation and a pricing policy which takes into account users' budget in a fair way and such that the total network revenue is maximized     

Coding schemes for multislot messages in multichannel ALOHA withdeadlines

Slotted multichannel ALOHA is the access scheme of choice for short messages and for reserving channels for longer ones in many satellite-based networks. This paper proposes schemes for increasing the capacity (maximum attainable throughput) of multichannel slotted ALOHA subject to meeting a user-specified deadline with a (high) required probability, thereby jointly capturing the users' requirements and the system owner's desires. The focus is on short yet multislot messages. A key idea is to achieve a low probability of missing the deadline by permitting a large maximum resource expenditure per message, while holding the mean expenditure low in order to minimize "pollution." For a K-slot message, redundant single-slot fragments are constructed using block erasure-correcting codes, such that any K fragments suffice for message reception. With multiround coding, an optimized number of fragments are transmitted in each round until K are received or the deadline is reached. Even with very strict constraints, capacities that approach the 1/e limit are attained. The coding-reservation scheme raises capacity above 1/e by allowing the hub, upon receipt of any message fragment(s), to grant contention-free slots for the remaining required fragments. Both schemes are also adapted for use with single-transmitter stations at a small performance penalty in most cases. Finally, because capacity is maximized by minimizing the mean per-message transmission resources, the transmission scheme is also energy-efficient     

Mechanism-based resource allocation for multimedia transmission over spectrum agile wireless networks

We propose to add a new dimension to existing wireless multimedia systems by enabling autonomous stations to dynamically compete for communication resources through adjustment of their internal strategies and sharing their private information. We focus on emerging spectrum agile wireless networks, where developing an efficient strategy for managing available communication resources is of high importance. The proposed dynamic resource management approach for wireless multimedia changes the passive way stations are currently adapting their joint source-channel coding strategies according to available wireless resources. Each wireless station can play the resource management game by adapting its multimedia transmission strategy depending on the experienced channel conditions and user requirements. The resource allocation game is coordinated by a network moderator, which deploys mechanism-based resource management to determine the amount of transmission time to be allocated to various users on different frequency bands such that certain global system metrics are optimized. Subsequently, the moderator charges the various users based on the amount of resources it has allocated to them, in order to discourage them from being dishonest about their resource requirements. We investigate and quantify both the users' and the system performance when different cross-layer strategies, and hence users' levels of smartness, are deployed by wireless stations. Our simulations show that mechanism-based resource management outperforms conventional techniques such as air-fair time and equal time resource allocation in terms of the obtained system utility. They also provide insights that can guide the design of emerging spectrum agile network protocols and applications     

ForCES网络中的资源调度算法和经济模型(英文)

Resource scheduling algorithm for ForCES(Forwarding and Control Element Separation) networks need to meet the flexibility,programmability and scalability of node resources.DBC(Deadline Budget Constrain) algorithm relies on users select cost or time priority,then scheduling to meet the requirements of users.However,this priority strategy of users is relatively simple,and cannot adapt to dynamic change of resources,it is inevitable to reduce the QoS.In order to improve QoS,we refer to the economic model and resource scheduling model of cloud computing,use SAL(Service Level Agreement) as pricing strategy,on the basis of DBC algorithm,propose an DABP(Deadline And Budget Priority based on DBC) algorithm for ForCES networks,DABP combines both budget and time priority to scheduling.In simulation and test,we compare the task finish time and cost of DABP algorithm with DP(Deadline Priority) algorithm and BP(Budget Priority) algorithm,the analysis results show that DABP algorithm make the task complete with less cost within deadline,benifical to load balancing of ForCES networks.     

Generalized quality-of-service routing with resource allocation

We present a general framework for the problem of quality-of-service (QoS) routing with resource allocation for data networks. The framework represents the QoS parameters as functions rather than static metrics. The formulation incorporates the hardware/software implementation and its relation to the allocated resources into a single framework. The proposed formulation allows intelligent adaptation of QoS parameters and allocated resources during a path search, rather than decoupling the path search process from resource allocation. We present a dynamic programming algorithm that, under certain conditions, finds an optimal path between a source and destination node and computes the amount of resources needed at each node so that the end-to-end QoS requirements are satisfied. We present jitter and data droppage analyzes of various rate-based service disciplines and use the dynamic programming algorithm to solve the problem of QoS routing with resource allocation for networks that employ these service disciplines.     

一种基于用户需求的OFDM系统资源分配算法

提出了一种新的基于OFDM多用户通信系统的资源分配算法。该算法在总功率限制和用户数据率要求下,通过以下两步实现子载波、比特和功率的动态分配：第一步,基于用户的平均信道增益和数据率要求进行资源初分配（每个用户分配多少个子载波、功率）;第二步,对步骤1中的结果进行调整,最终决定每个用户分配到的子载波、功率以及比特载入方式。相比于Hujun Yjn等人提出的另一种基于用户需求的算法,新算法的基站发射功率略有增加,但复杂度大为降低,在实际运用中更有利用价值。     

On the network utility optimal allocation of radio resources in WCDMA systems

We discuss an optimization framework for radio resource allocation in a WCDMA system supporting elastic traffic. In particular, we assume the users' preferences as driven by utility functions depending on the assigned transmission rate, and the network capacity constraints as related to interference and power limitations. In this framework, we perform the constrained instantaneous network utility maximization through a logarithmic barrier method. The obtained results are compared and discussed.     

Cross layer scheduling for real-time traffic in multiuser MIMO-OFDMA systems

A novel cross layer scheduling algorithm is proposed for real-time (RT) traffic in multiuser downlink multiple-input multiple-output orthogonal frequency division multiple access (MIMO-OFDMA) wireless systems. The algorithm dynamically allocates resources in space, time and frequency domain based on channel state information (CSI), users' quality of service (QoS) requirements and queue state information (QSI). To provide higher data rate and spectrum efficiency, adaptive modulation and coding (AMC) is employed. The proposed algorithm can improve cell throughput and increase the number of users that can be supported while guaranteeing users' QoS requirements and fairness among all users. Simulation results indicate that the proposed algorithm can achieve superior performance.     

An Optimized Collaborative Scheduling Algorithm for Prioritized Tasks with Shared Resources in Mobile-Edge and Cloud Computing Systems

Mobile edge computing (MEC) is a promising technology that has the potential to meet the latency requirements of next-generation mobile networks. Since MEC servers have limited resources, an orchestrator utilizes a scheduling algorithm to decide where and when each task should execute so that the quality of service (QoS) of each task is achieved. The scheduling algorithm should use the least possible resources required to meet the service demands. In this paper, we develop a two-level cooperative scheduling algorithm with a centralized orchestrator layer. The first scheduling level is used to schedule tasks locally on MEC servers. In contrast, the second level resides at the orchestrator and assigns tasks to a neighboring base station or the cloud. The tasks serve in accordance with their priority, which is determined by the latency and required throughput. We also present a resource optimization algorithm for determining resource distribution in the system in order to ensure satisfactory service availability at the minimum cost. The resource optimization algorithm contains two variations that can be employed depending on the traffic model. One variant is used when the traffic is uniformly distributed, and the other is used when the traffic load is unbalanced among base stations. Numerical results show that the cooperative model of task scheduling outperforms the non-cooperative model. Furthermore, the results show that the suggested scheduling algorithm performs better than other well-known scheduling algorithms, such as shortest job first scheduling and earliest deadline first scheduling.

     

智能流程应用模式下基于流程语义库的需求获取

为自动生成满足用户需求的个性化流程,在给出智能流程应用模式的基础上,提出一种用户个性化需求获取新方法。对业务流程中活动进行归纳和抽象,定义一种新服务——元服务,并由元服务组成流程语义库,然后基于流程语义库,提出一种用户需求获取算法,帮助用户快速准确地输入需求信息。理论分析和应用表明：算法提高了用户需求获取的准确程度和效率。