Selectors: High-Level Resource Schedulers

Resource sharing problems can be described in three basically independent modular components. ? The constraints the resource places upon sharing because of physcal limitations and consistency requirements. ? The desired ordering of resource requests to achieve efficiency-either efficiency of resource utilization or efficiency of processes making the requests. ? Modifications to the ordering to prevent starvation of processes waiting for requests which might otherwise never receive service. A high-level nonprocedural language to specify these components of resource sharing problems is described. General deadlock and starvation properties of selectors are proven. Solutions to several classic resource sharing problems are shown to illustrate the expressiveness of this language. Proof techniques for this high-level language are introduced to show how to prove particular selectors are or are not deadlock and starvation free.     

支持服务优先级的多阶段服务模型研究*

多阶段服务模型是一种支持高并发、高吞吐的事件驱动服务应用架构,为使其更好地适应当前Internet上大部分应用提供区分等级服务的现状,提出了一种为该模型增加对带优先级请求支持的方法;定义了动态优先级,改进了随机早期检测算法以控制不同优先级事件的入队,并通过优先级动态提升防止低优先级事件被“饿死”。实验结果表明,改进后的模型在保持系统良好性能的基础上,满足了不同优先级请求的实时性和吞吐率需求。     

Admission control for media on demand services

Admission control software is used to make accept or deny decisions about incoming service requests to avoid overload. Existing media streaming software includes only limited support for admission control by allowing for predefined static rules. Such rules limit for example the number of requests that are allowed to enter the system during a certain time or define thresholds concerning the utilization level of a single resource such as network bandwidth. In media streaming applications, however, the bottleneck resource (CPU, Disk I/O, network bandwidth, etc.) might change over time depending on the current demand for different types of audio or video files. This paper proposes a model for adaptive admission control in the presence of multiple scarce resources. Opportunity costs for a service request are determined at the moment of an incoming request and compared to the revenue of a request in order to make an accept/deny decision. Opportunity costs are based on resource utilization, service resource requirements, expected future demand for services, and the revenue per accepted service. The model allows rejection of service requests early to reserve capacity required to perform future service requests with higher revenues. We describe a number of experiments to illustrate the benefits of adaptive admission control models over static admission control rules.     

Performance analysis of cloud computing services considering resources sharing among virtual machines

Cloud computing is a novel paradigm for the provision of service on demand. Through the use of virtualization, physical resources are converted into “resources pool” which provides service on demand. Due to the complexity and diversity of user requests of the cloud computing system, its performance is difficult to model and analyze. Although there are some researches on cloud service performance, very few of them addressed the issues of resources sharing among VMs and its impact on service performance. This paper presents a model for performance analysis of cloud services. The model considers the resources sharing among VMs. In addition, various types of failures, such as VMs failures, physical servers failures and network failures are also considered. The service requests are also relaxed compared with prior research. A service request is divided into many subtasks and each subtask consists of a series of data processing and transmission. The average service time of service requests is obtained. And a numerical example is presented.     

基于模糊模型的非线性通用模型控制

通用模型控制是一种有效的非线性控制方法,但该方法的应用条件是过程一阶微分模型必须要有显式解.为了克服这一局限性,提出一种基于模糊模型的通用模型控制策略,将非线性过程模型应用逆系统的方法在控制算法中直接嵌入过程模型,从而保证了通用模型控制策略的可实现性.该控制器参数物理意义明显,整定方便,仿真结果表明了该控制策略的有效性和鲁棒性.     

Control-theoretic Analysis of Admission Control Mechanisms for Web Server Systems

Web sites are exposed to high rates of incoming requests. The servers may become overloaded during temporary traffic peaks when more requests arrive than the server is designed for. An admission control mechanism rejects some requests whenever the arriving traffic is too high and thereby maintains an acceptable load in the system. This paper presents how admission control mechanisms can be designed with a combination of queueing theory and control theory. In this paper we model an Apache web server as a GI/G/1-system and then design a PI-controller, commonly used in automatic control, for the server. The controller has been implemented as a module inside the Apache source code. Measurements from the laboratory setup show how robust the implemented controller is, and how it corresponds to the results from the theoretical analysis.     

基于综合安全保护质量的安全服务协商模型

在基于分布式服务的系统体系中，上层应用系统需要确定下层安全服务能够按照要求提供安全服务功能，根据不断变化的实际需要和当前系统状态自适应地调整服务者和服务要求，并同时保障系统的安全性。本文探讨了在应用系统和安全服务之间对安全保护质量进行协商的协议模型，目标是使应用系统所要求达到的安全水平能获得安全服务的支支持，并能得到下层安全服务的有效遵守，使系统的整体安全水平得到保障。     

A HIERARCHICAL MODEL OF INFORMATION FLOW IN COMPLEX SYSTEMS

A model of the information flow in hierarchical information processing organizations is presented. The purpose of the model is to capture the essential information activities that occur as system performs its tasks. An information processing organization transforms (input) requests into (output) responses through a set of procedures or processing rules. The hierarchical model describes transformations as changes in the information state vector of various entities in the organization. The information state vector is a dynamic quantity similar in concept to the state of a system. The paper discusses in detail how the structure of the hierarchical model allows how to deduce the optimal reorganization of procedures. In particular, there is a very strong structural linkage between the model and the problem of optimal control of dynamic systems. This linkage is demonstrated in the paper by use of dynamic programming to solve the reorganization problem using this model.     

Applying ontology-based blog to detect information system post-development change requests conflicts

Post-development change requests are user requirements for information systems changes after development. Conflicts might occur as contradictive or inconsistent relationships between requests and existing system design. Detecting conflicts in post-developmenet change requests is an important task during requests management processes. To address this topic, this article proposes an ontology-based blog for automatically discovering conflicts in the extended use-case models of requests from users. This study proposed an information system maintenance process. The proposed approach applies ontologies to represent domain knowledge. A set of rules are used to detect conflicts. This study developed a prototype and invited two companies to evaluate it. Usage feedback opinions about ontology-based blog from two companies indicated the usefulness. The ontology-based blog is a relatively new approach which bridge requirements blogs with a formal and machine interpretable representational model. The automatic conflicts detection capability of the ontology-based blog can reduce the labor cost in requirements analysis phase.     

The Analysis and Performance of Multi-Rate Service in Distributed Video-on-Demand Systems

In this paper, we develop an end-to-end analysis of a distributed Video-on-Demand (VoD) system that includes an integrated model of the server and the network subsystems with analysis of its impact on client operations. The VoD system provides service to a heterogeneous client base at multiple playback rates. A class-based service model is developed where an incoming video request can specify a playback rate at which the data is consumed on the client. Using an analytical model, admission control conditions at the server and the network are derived for multi-rate service. We also develop client buffer requirements in presence of network delay bounds and delay jitter bounds using the same integrated framework of server and network subsystems. Results from an extensive simulation show that request handling policies based on limited redirection of blocked requests to other resources perform better than load sharing policies. The results also show that downgrading the service for blocked requests to a lower bitrate improves VoD system performance considerably. Combining the downgrade option with restrictions on access to high bitrate request classes is a powerful tool for manipulating an incoming request mix into a workload that the VoD system can handle.     

Early failure prediction in feature request management systems: an extended study

Online feature request management systems are popular tools for gathering stakeholders?? change requests during system evolution. Deciding which feature requests require attention and how much upfront analysis to perform on them is an important problem in this context: too little upfront analysis may result in inadequate functionalities being developed, costly changes, and wasted development effort; too much upfront analysis is a waste of time and resources. Early predictions about which feature requests are most likely to fail due to insufficient or inadequate upfront analysis could facilitate such decisions. Our objective is to study whether it is possible to make such predictions automatically from the characteristics of the online discussions on feature requests. This paper presents a study of feature request failures in seven large projects, an automated tool-implemented framework for constructing failure prediction models, and a comparison of the performance of the different prediction techniques for these projects. The comparison relies on a cost-benefit model for assessing the value of additional upfront analysis. In this model, the value of additional upfront analysis depends on its probability of success in preventing failures and on the relative cost of the failures it prevents compared to its own cost. We show that for reasonable estimations of these two parameters, automated prediction models provide more value than a set of baselines for many failure types and projects. This suggests automated failure prediction during requirements elicitation to be a promising approach for guiding requirements engineering efforts in online settings.     

REACTIVE TUNING OF TARGET ESTIMATE ACCURACY IN MULTISENSOR DATA FUSION

Dealing with conflicting and target-specific requirements is an important issue in multisensor and multitarget tracking. This paper aims to allocate sensing resources among various targets in reaction to individual information requests. The proposed approach is to introduce agents for every relevant target responsible for its tracking. Such agents are expected to bargain with each other for a division of resources. A bilateral negotiation model is established for resource allocation in two-target tracking. The applications of agent negotiation to target covariance tuning are illustrated together with simulation results presented. Moreover, we suggest a way of organizing simultaneous one-to-one negotiations, making our negotiation model still applicable in scenarios of tracking more than two targets.     

On the performance of real-time multi-item request scheduling in data broadcast environments

On-demand broadcast is an effective wireless data dissemination technique to enhance system scalability and capability to handle dynamic data access patterns. Previous studies on time-critical on-demand data broadcast were conducted under the assumption that each client requests only one data item at a time. With the rapid growth of time-critical information dissemination services in emerging applications, there is an increasing need for systems to support efficient processing of real-time multi-item requests. Little work, however, has been done. In this paper, we study the behavior of six representative single-item request based scheduling algorithms in time-critical multi-item request environments. The results show that the performance of all algorithms deteriorates when dealing with multi-item requests. We observe that data popularity, which is an effective factor to save bandwidth and improve performance in scheduling single-item requests, becomes a hindrance to performance in multi-item request environments. Most multi-item requests scheduled by these algorithms suffer from a starvation problem, which is the root of performance deterioration. Based on our analysis, a novel algorithm that considers both request popularity and request timing requirement is proposed. The performance results of our simulation study show that the proposed algorithm is superior to other classical algorithms under a variety of circumstances.     

High-performance technique for satellite range scheduling

As the number of daily satellite service requests increases, the satellite range scheduling problem becomes more intractable during the ground station operations management. The NP-complete problem involves scheduling satellite requests to ground station antennas within their time windows so that the profit from the scheduled requests is maximized. This paper analyzes various conflicts between satellite requests and then develops a conflict-resolution technique. The technique first builds an elite initial schedule using a prescheduling strategy and then improves the initial schedule using a rescheduling strategy in a subspace of feasible solutions. The main highlight of the technique is its dual functions of quickly generating a high-quality solution and providing a good bound. As shown in the experimental results from the actual data and more difficult random instances, the proposed technique is significantly better than the best-known heuristic.     

Update transport: a new technique for update synchronization inreplicated database systems

A fully distributed approach to update synchronization is presented where each site completely executes every update. This approach has several features-higher resiliency to different kinds of failures, higher parallelism, improved response to user requests, and low communication overhead. A fully distributed algorithm for concurrency control obtained by rehashing a previously published semidistributed algorithm into the fully distributed model of update execution is presented. A performance model of replicated database systems is presented and used to study the performance of the proposed algorithm and its semidistributed version. The results of the performance study reveal that the proposed approach can substantially improve the performance at the cost of moderate input/output overhead     

Dynamic quota-based admission control with sub-rating in multimedia servers

An admission control algorithm for a multimedia server is responsible for determining if a new request can be accepted without violating the Quality of Service (QoS) requirements of the existing requests in the system. A novel quota-based admission control algorithm with sub-rating for two priority classes of requests is proposed in this study. The server capacity is divided into three partitions based on the quota values: one for each class of requests and one common pool shared by two classes of requests. Reward and penalty are adopted in the proposed system model. High-priority requests are associated with higher values of reward as well as penalty than low-priority ones. Given the characteristics of the system workload, the proposed algorithm finds the best partitions, optimizing the system performance based on the objective function of the total reward minus the total penalty. The sub-rating mechanism will reduce the QoS requirements of several low- priority clients, by cutting out a small fraction of the assigned server capacity, to accept a new high- priority client and to achieve a higher net earning value. A stochastic Petri-Net model is used to find the optimal quota values and two approximation approaches are developed to find sub-optimal settings. The experiment results show that the proposed algorithm performs better than one without sub-rating mechanism, and that the sub-optimal solutions found by the proposed approximation approaches are very close to optimal ones. The approximation approaches enable the algorithm to dynamically adjust the quota values, based on the characteristics of the system workload, to achieve higher system performance.     

Mitigation of DHCP starvation attack

DHCP starvation attack is an attack that targets DHCP servers whereby forged DHCP requests are crafted by an attacker with the intent of exhausting all available IP addresses that can be allocated by the DHCP server. Under this attack, legitimate network users can be denied service. In this paper, we describe the seriousness of the attack and survey and evaluate existing solutions designed to mitigate such an attack. In addition, we propose a novel mitigation solution. Our solution overcomes the limitations of existing solutions in terms of performance, effectiveness, and flexibility. Our solution is based on dynamic fair allocation of IP addresses and is suitable for unshared and shared (wireless) access networks. We study and analyze the proposed mitigation technique through numerical examples and simulations. Furthermore, simulation results show that our proposed solution is far superior in mitigating DHCP starvation attack when compared to other existing techniques such as fixed allocation and DHCP request rate detection.     

Web机群服务质量控制自管理模型

基于服务类别的资源请求和服务等级给出一种资源划分策略，对各类别的服务请求状态进行建模，使用反馈控制理论的方法对各类别资源进行动态调整，与资源调整规则相结合，以适应访问的突发性和保证服务质量要求，实现了Web机群服务质量的自管理。实验表明自管理模型能有效支持区分服务质量和资源效用控制。     

A model of grid service capacity

Computational grids （CGs） are large scale networks of geographically distributed aggregates of resource clusters that may be contributed by distinct organizations for the provision of computing services such as model simulation, compute cycle and data mining. Traditionally, the decision-making strategies underlying the grid management mechanisms rely on the physical view of the grid resource model. This entails the need for complex multi-dimensional search strategies and a considerable level of resource state information exchange between the grid management domains. In this paper we argue that with the adoption of service oriented grid architectures, a logical service-oriented view of the resource model provides a more appropriate level of abstraction to express the grid capacity to handle incoming service requests. In this respect, we propose a quantification model of the aggregated service capacity of the hosting environment that is updated based on the monitored state of the various environmental resources required by the hosted services. A comparative experimental validation of the model shows its performance towards enabling an adequate exploitation of provisioned services.