Mapping service-level agreements in distributed applications

In previous column, we discussed how to build distributed systems from quality-of-service (QoS)-aware software components. We also described a design by which individual components can engage in QoS negotiation and perform admission control so that new incoming requests don't violate committed QoS requirements. But what happens in a distributed application made up of several QoS-aware components and if the application has a global service-level agreement (SLA) for maximum end-to-end execution time. The problem we discuss in this paper is how to determine which SLAs should be negotiated at the component level so that the global SLA is satisfied at the minimum possible cost.     

The WSLA Framework: Specifying and Monitoring Service Level Agreements for Web Services

We describe a novel framework for specifying and monitoring Service Level Agreements (SLA) for Web Services. SLA monitoring and enforcement become increasingly important in a Web Service environment where enterprise applications and services rely on services that may be subscribed dynamically and on-demand. For economic and practical reasons, we want an automated provisioning process for both the service itself as well as the SLA managment system that measures and monitors the QoS parameters, checks the agreed-upon service levels, and reports violations to the authorized parties involved in the SLA management process. Our approach to these issues is presented in this paper. The Web Service Level Agreement (WSLA) framework is targeted at defining and monitoring SLAs for Web Services. Although WSLA has been designed for a Web Services environment, it is applicable as well to any inter-domain management scenario, such as business process and service management, or the management of networks, systems and applications in general. The WSLA framework consists of a flexible and extensible language based on XML Schema and a runtime architecture comprising several SLA monitoring services, which may be outsourced to third parties to ensure a maximum of objectivity. WSLA enables service customers and providers to unambiguously define a wide variety of SLAs, specify the SLA parameters and the way they are measured, and relate them to managed resource instrumentations. Upon receipt of an SLA specification, the WSLA monitoring services are automatically configured to enforce the SLA. An implementation of the WSLA framework, termed SLA Compliance Monitor, is publicly available as part of the IBM Web Services Toolkit.     

Fault-tolerant Service Level Agreement lifecycle management in clouds using actor system

Automated Service Level Agreements (SLAs) have been proposed for cloud services as contracts used to record the rights and obligations of service providers and their customers. Automation refers to the electronic formalized representation of SLAs and the management of their lifecycle by autonomous agents. Most recently, SLA automated management is becoming increasingly of importance. In previous work, we have elaborated a utility architecture that optimizes resource deployment according to business policies, as well as a mechanism for optimization in SLA negotiation. We take all that a step further with the application of actor systems as an appropriate theoretical model for fine-grained, yet simplified and practical, monitoring of massive sets of SLAs. We show that this is a realistic approach for the automated management of the complete SLA lifecycle, including negotiation and provisioning, but focus on monitoring as the driver of contemporary scalability requirements. Our proposed work separates the agreement’s fault-tolerance concerns and strategies into multiple autonomous layers that can be hierarchically combined into an intuitive, parallelized, effective and efficient management structure.     

An interoperable and self-adaptive approach for SLA-based service virtualization in heterogeneous Cloud environments

Cloud computing is a newly emerged computing infrastructure that builds on the latest achievements of diverse research areas, such as Grid computing, Service-oriented computing, business process management and virtualization. An important characteristic of Cloud-based services is the provision of non-functional guarantees in the form of Service Level Agreements (SLAs), such as guarantees on execution time or price. However, due to system malfunctions, changing workload conditions, hard- and software failures, established SLAs can be violated. In order to avoid costly SLA violations, flexible and adaptive SLA attainment strategies are needed. In this paper we present a self-manageable architecture for SLA-based service virtualization that provides a way to ease interoperable service executions in a diverse, heterogeneous, distributed and virtualized world of services. We demonstrate in this paper that the combination of negotiation, brokering and deployment using SLA-aware extensions and autonomic computing principles are required for achieving reliable and efficient service operation in distributed environments.     

A Service Level Agreement Language for Dynamic Electronic Services

This paper proposes a novel language for Service Level Agreements (SLAs) for dynamic and spontaneous electronic services. In a cross-organizational setting, it is important for customers of a service to obtain, monitor and enforce quality of service (QoS) guarantees by service providers, usually expressed in the form of SLAs. Since the supervision and management of SLAs and the provisioning of corresponding systems should be automated for economic reasons, we need a formal language to define an SLA. If, moreover, providers and customers want to sign custom-made SLAs, the SLA language, correspondingly, must provide a large degree of flexibility.The SLA language described in this paper aims at providing the needed flexibility by means of an XML-based representation and a runtime system for SLAs. Using this language, parties to an SLA can describe how parameters are measured and computed from raw metrics, the guarantees they want with respect to those parameters and the involvement of third parties to, e.g., independently verify SLA compliance.     

SLA based resource allocation policies in autonomic environments

Nowadays, large service centers provide computational capacity to many customers by sharing a pool of IT resources. The service providers and their customers negotiate utility based Service Level Agreement (SLA) to determine the costs and penalties on the base of the achieved performance level. The system is often based on a multi-tier architecture to serve requests and autonomic techniques have been implemented to manage varying workload conditions. The service provider would like to maximize the SLA revenues, while minimizing its operating costs. The system we consider is based on a centralized network dispatcher which controls the allocation of applications to servers, the request volumes at various servers and the scheduling policy at each server. The dispatcher can also decide to turn ON or OFF servers depending on the system load. This paper designs a resource allocation scheduler for such multi-tier autonomic environments so as to maximize the profits associated with multiple class SLAs. The overall problem is NP-hard. We develop heuristic solutions by implementing a local-search algorithm. Experimental results are presented to demonstrate the benefits of our approach.     

数据驱动的船载外测数据实时处理软件架构设计与实现

针对航天测控任务的多样性和复杂性不断增加,特别是数据采样频率的变化调整,原有的时间驱动处理模式已经逐渐不能满足需求,基于时间驱动的软件架构开发的外测软件日益复杂,维护难度不断增加等问题,提出了一种数据驱动的船载外测数据实时处理软件架构,在银河麒麟操作系统下,基于该架构实现了外测数据实时处理软件,该软件包含多个由数据驱动的功能组件,各组件之间使用服务总线来实现数据交互与集成。实验表明,基于该架构实现的外测数据实时处理软件很好地解决了时延过大和时序交替的问题,能够满足当前航天任务需求。     

Utilizing unreliable public resources for higher profit and better SLA compliance in computing utilities

Computing utilities are emerging as an important part of the infrastructure for outsourcing computer services. Fundamental to outsourcing is the notion of quality of service, which is defined by service level agreements (SLAs) between the computing utilities and clients. One of the major objectives of computing utilities is to maximize their net profit while maintaining customer loyalty. To achieve this objective, the computing utilities should meet or exceed their SLA constraints most of the time. Defining the SLAs conservatively might be one way of easily achieving these goals. However, by tuning the SLA parameters conservatively the computing utility might under utilize its resources with a resultant loss of revenue. Therefore, we can see two main issues with SLA management: designing SLAs competitively so that expected revenue for the computing utility is maximized and maintaining the operating conditions such that SLAs are satisfied with very high probability. In this paper, we show that inducting unreliable public resources into a computing utility enables more competitive SLAs while maintaining higher levels of run time compliances as well as maximizing profit. Our scheduling algorithms assume that idle cycles from public resources are available in plenty, therefore, the performance gains do not incur any additional financial cost. However, there is communication overhead when public resources from a wide area network is included. This overhead is kept to the minimum by enabling the scheduler work without any monitoring on the public resources.     

Dual time-scale distributed capacity allocation and load redirect algorithms for cloud systems

Resource management remains one of the main issues of cloud computing providers because system resources have to be continuously allocated to handle workload fluctuations while guaranteeing Service Level Agreements (SLA) to the end users. In this paper, we propose novel capacity allocation algorithms able to coordinate multiple distributed resource controllers operating in geographically distributed cloud sites. Capacity allocation solutions are integrated with a load redirection mechanism which, when necessary, distributes incoming requests among different sites. The overall goal is to minimize the costs of allocated resources in terms of virtual machines, while guaranteeing SLA constraints expressed as a threshold on the average response time. We propose a distributed solution which integrates workload prediction and distributed non-linear optimization techniques. Experiments show how the proposed solutions improve other heuristics proposed in literature without penalizing SLAs, and our results are close to the global optimum which can be obtained by an oracle with a perfect knowledge about the future offered load.     

Deploying diffserv in backbone networks for tight SLA control

The differentiated services architecture (Diffserv) enables service providers to offer tighter, more comprehensive service-level agreements (SLAs) for IP service performance. One way it does this is by letting designers engineer IP backbone networks to assure that SLA parameters are met on a per-class basis. This review covers best practices for designing, validating, deploying, and operating Diffserv in the network backbone. It also presents new results from router-based testing that demonstrate how, with Diffserv, high-performance backbone routers can achieve tight SLA capabilities.     

Applying Trajectory approach with static priority queuing for improving the use of available AFDX resources

AFDX (Avionics Full Duplex Switched Ethernet) standardized as ARINC 664 is a major upgrade for avionics systems. The mandatory certification implies a worst-case delay analysis of all the flows transmitted on the AFDX network. Up to now, this analysis is done thanks to a tool based on a Network Calculus approach. The more recent Trajectory approach has been proposed for the computation of worst-case response time in distributed systems. It has been shown that the worst-case delay analysis of an AFDX network can be improved using an optimized Trajectory approach. This paper extends this optimized approach with the integration of static priority QoS policies. This extension makes possible to compute the bounds needed for deterministic avionics flows (high priority) when (lower priority) non avionics flows are added. Moreover, the paper provides an analysis of the pessimism of the obtained bounds.     

SLA-Driven Clustering of QoS-Aware Application Servers

In this paper, we discuss the design, implementation, and experimental evaluation of a middleware architecture for enabling service level agreement (SLA)-driven clustering of QoS-aware application servers. Our middleware architecture supports application server technologies with dynamic resource management: application servers can dynamically change the amount of clustered resources assigned to hosted applications on-demand so as to meet application-level quality of service (QoS) requirements. These requirements can include timeliness, availability, and high throughput and are specified in SLAs. A prototype of our architecture has been implemented using the open-source J2EE application server JBoss. The evaluation of this prototype shows that our approach makes possible JBoss' resource usage optimization and allows JBoss to effectively meet the QoS requirements of the applications it hosts, i.e., to honor the SLAs of those applications     

基于生物迁移的网络动态负载平衡的研究

生物系统中的关键机理和重要原理可用于设计一种新颖的生物网络结构及其仿真平台，以满足未来Internet网络的关键需求。本文在此框架下讨论了生物实体的不同迁移方式，并探讨了将其用于网络动态负载平衡问题，给出了一种负载平衡算法。通过对网络中不同任务量在采用和不采用负载平衡策略两种情况下的仿真试验，比较了不同条件下的响应时间，验证了算法的合理性。     

A method for the optimum selection of datacenters in geographically distributed clouds

The optimal selection of a datacenter is one of the most important challenges in the structure of a network for the wide distribution of resources in the environment of a geographically distributed cloud. This is due to the variety of datacenters with different quality-of-service (QoS) attributes. The user’s requests and the conditions of the service-level agreements (SLAs) should be considered in the selection of datacenters. In terms of the frequency of datacenters and the range of QoS attributes, the selection of the optimal datacenter is an NP-hard problem. A method is therefore required that can suggest the best datacenter, based on the user’s request and SLAs. Various attributes are considered in the SLA; in the current research, the focus is on the four important attributes of cost, response time, availability, and reliability. In a geo-distributed cloud environment, the nearest datacenter should be suggested after receiving the user’s request, and according to its conditions, SLA violations can be minimized. In the approach proposed here, datacenters are clustered according to these four important attributes, so that the user can access these quickly based on specific need. In addition, in this method, cost and response time are taken as negative criteria, while accessibility and reliability are taken as positive, and the multi-objective NSGA-II algorithm is used for the selection of the optimal datacenter according to these positive and negative attributes. In this paper, the proposed method, known as NSGAII_Cluster, is implemented with the Random, Greedy and MOPSO algorithms; the extent of SLA violation of each of the above-mentioned attributes are compared using four methods. The simulation results indicate that compared to the Random, Greedy and MOPSO methods, the proposed approach has fewer SLA violations in terms of the cost, response time, availability, and reliability of the selected datacenters.     

网络RAID存储系统边界性能研究

目前针对网络存储系统性能的研究大都集中在定性研究方面,缺乏有效的定量分析方法和模型．在有限容量闭合排队网络理论的基础上,提出了网络RAID存储系统性能的定量分析模型．并提出了一种新的计算有限容量闭合排队网络系统边界性能的分析方法-APBA法,和其他近似分析方法相比,APBA法的计算时间复杂度更低．测试结果表明,通过利用APBA方法,由网络RAID存储系统的性能定量分析模型获得的系统性能值,可以有效反映网络RAID存储系统在轻载区、重载区和过载区的性能边界,以及系统的最大负载量．     

Memory aware load balance strategy on a parallel branch‐and‐bound application

The latest trends in high performance computing systems show an increasing demand on the use of a large scale multicore system in an efficient way so that high compute‐intensive applications can be executed reasonably well. However, the exploitation of the degree of parallelism available at each multicore component can be limited by the poor utilization of the memory hierarchy. Actually, the multicore architecture introduces some distinct features that are already observed in shared memory and distributed environments. One example is that subsets of cores can share different subsets of memory. In order to achieve high performance, it is imperative that a careful allocation scheme of an application is carried out on the available cores, based on a scheduling specification that considers not only processors characteristics but also memory contention. This paper proposes a multicore cluster representation that captures relevant performance characteristics in multicores systems such as the influence of memory hierarchy and contention on application performance. Improved performance was achieved by a branch‐and‐bound application applied to the partitioning sets problem that incorporated a memory aware load balancing strategy based on the proposed multicore cluster representation. An in‐depth analysis on this application execution showed its applicability to modern systems. Copyright © 2014 John Wiley & Sons, Ltd.     

Hierarchical aggregation of Service Level Agreements

IT-based Service Economy requires Service Markets to flourish for the trade of services. A market does not represent a simple buyer-seller relationship, rather it is the culmination point of a complex chain of stake-holders with a hierarchical integration of value along each point in the chain. To enable a Service Economy, Service Markets must be practically realized, which in turn requires an enabling infrastructure to support service value chains and service choreographies resulting from service composition scenarios. In such scenarios, services compose together hierarchically in a producer-consumer manner to form service supply-chains of added value. Service Level Agreements (SLAs) are defined at various levels in this hierarchy to ensure the expected quality of service for different stakeholders. Automation of service composition directly implies the aggregation of their corresponding SLAs.In this paper we elaborate on the requirements of hierarchical aggregation of SLAs corresponding to service choreographies leading to business models such as Business Value Networks. During the hierarchical aggregation of SLAs, certain SLA information pertaining to different stakeholders is meant to be restricted and can be only partially revealed to a subset of their business partners. We introduce the concept of SLA-Views to protect such privacy concerns. We then formalize the notion of SLA Choreography and define an aggregation model based on SLA-Views to enable the automation of hierarchical aggregation of Service Level Agreements. The aggregation model has been designed to comply with the WS-Agreement standard.     

Formulating and managing viable SLAs in cloud computing from a small to medium service provider's viewpoint: A state-of-the-art review

In today's competitive world, service providers need to be customer-focused and proactive in their marketing strategies to create consumer awareness of their services. Cloud computing provides an open and ubiquitous computing feature in which a large random number of consumers can interact with providers and request services. In such an environment, there is a need for intelligent and efficient methods that increase confidence in the successful achievement of business requirements. One such method is the Service Level Agreement (SLA), which is comprised of service objectives, business terms, service relations, obligations and the possible action to be taken in the case of SLA violation. Most of the emphasis in the literature has, until now, been on the formation of meaningful SLAs by service consumers, through which their requirements will be met. However, in an increasingly competitive market based on the cloud environment, service providers too need a framework that will form a viable SLA, predict possible SLA violations before they occur, and generate early warning alarms that flag a potential lack of resources. This is because when a provider and a consumer commit to an SLA, the service provider is bound to reserve the agreed amount of resources for the entire period of that agreement – whether the consumer uses them or not. It is therefore very important for cloud providers to accurately predict the likely resource usage for a particular consumer and to formulate an appropriate SLA before finalizing an agreement. This problem is more important for a small to medium cloud service provider which has limited resources that must be utilized in the best possible way to generate maximum revenue. A viable SLA in cloud computing is one that intelligently helps the service provider to determine the amount of resources to offer to a requesting consumer, and there are number of studies on SLA management in the literature. The aim of this paper is two-fold. First, it presents a comprehensive overview of existing state-of-the-art SLA management approaches in cloud computing, and their features and shortcomings in creating viable SLAs from the service provider's viewpoint. From a thorough analysis, we observe that the lack of a viable SLA management framework renders a service provider unable to make wise decisions in forming an SLA, which could lead to service violations and violation penalties. To fill this gap, our second contribution is the proposal of the Optimized Personalized Viable SLA (OPV-SLA) framework which assists a service provider to form a viable SLA and start managing SLA violation before an SLA is formed and executed. The framework also assists a service provider to make an optimal decision in service formation and allocate the appropriate amount of marginal resources. We demonstrate the applicability of our framework in forming viable SLAs through experiments. From the evaluative results, we observe that our framework helps a service provider to form viable SLAs and later to manage them to effectively minimize possible service violation and penalties.     

Resource management for bursty streams on multi-tenancy cloud environments

The number of applications that need to process data continuously over long periods of time has increased significantly over recent years. The emerging Internet of Things and Smart Cities scenarios also confirm the requirement for real time, large scale data processing. When data from multiple sources are processed over a shared distributed computing infrastructure, it is necessary to provide some Quality of Service (QoS) guarantees for each data stream, specified in a Service Level Agreement (SLA). SLAs identify the price that a user must pay to achieve the required QoS, and the penalty that the provider will pay the user in case of QoS violation. Assuming maximization of revenue as a Cloud provider’s objective, then it must decide which streams to accept for storage and analysis; and how many resources to allocate for each stream. When the real-time requirements demand a rapid reaction, dynamic resource provisioning policies and mechanisms may not be useful, since the delays and overheads incurred might be too high. Alternatively, idle resources that were initially allocated for other streams could be re-allocated, avoiding subsequent penalties. In this paper, we propose a system architecture for supporting QoS for concurrent data streams to be composed of self-regulating nodes. Each node features an envelope process for regulating and controlling data access and a resource manager to enable resource allocation, and selective SLA violations, while maximizing revenue. Our resource manager, based on a shared token bucket, enables: (i) the re-distribution of unused resources amongst data streams; and (ii) a dynamic re-allocation of resources to streams likely to generate greater profit for the provider. We extend previous work by providing a Petri-net based model of system components, and we evaluate our approach on an OpenNebula-based Cloud infrastructure.