End-to-End QoS Support for a Medical Grid Service Infrastructure

Quality of Service support is an important prerequisite for the adoption of Grid technologies for medical applications. The GEMSS Grid infrastructure addressed this issue by offering end-to-end QoS in the form of explicit timeliness guarantees for compute-intensive medical simulation services. Within GEMSS, parallel applications installed on clusters or other HPC hardware may be exposed as QoS-aware Grid services for which clients may dynamically negotiate QoS constraints with respect to response time and price using Service Level Agreements. The GEMSS infrastructure and middleware is based on standard Web services technology and relies on a reservation based approach to QoS coupled with application specific performance models. In this paper we present an overview of the GEMSS infrastructure, describe the available QoS and security mechanisms, and demonstrate the effectiveness of our methods with a Grid-enabled medical imaging service.     

Enhancing Availability of Grid Computational Services to Ubiquitous Computing Applications

The Grid is an integrated infrastructure that can play the dual roles of a coordinated resource consumer as well as a donator in distributed computing environments. The enormous growth in the use of mobile and embedded devices in ubiquitous computing environment and their interaction with human beings produces a huge amount of data that need to be processed efficiently anytime anywhere. However, such devices often have limited resources in terms of CPU, storage, battery power, and communication bandwidth. Thus, there is a need to transfer ubiquitous computing application services to more powerful computational resources. In this paper, we investigate the use of the Grid as a candidate for provisioning computational services to applications in ubiquitous computing environments. In particular, we present a competitive model that describes the possible interaction between the competing resources in the Grid Infrastructure as service providers and ubiquitous applications as subscribers. The competition takes place in terms of quality of service (QoS) and cost offered by different Grid Service Providers (GSPs). We also investigate the job allocation of different GSPs by exploiting the noncooperativeness among the strategies. We present the equilibrium behavior of our model facing global competition under stochastic demand and estimate guaranteed QoS assurance level by efficiently satisfying the requirement of ubiquitous application. We have also performed extensive experiments over Distributed Parallel Computing Cluster (DPCC) and studied overall job execution performance of different GSPs under a wide range of QoS parameters using different strategies. Our model and performance evaluation results can serve as a valuable reference for designing appropriate strategies in a practical grid environment.     

HECTOR: Enabling Microarray Experiments over the Hellenic Grid Infrastructure

Biologists, medical experts, biochemical engineers and researchers working on DNA microarray experiments are increasingly turning on Grid computing with the scope of leveraging the Grid’s computing power, immense storage resources, and quality of service to the expedient processing of a wide range of datasets. In this paper we present a combined experience of grid application experts and bioinformatics scientists in deploying a pilot service enabling computationally efficient processing and analysis of data stemming from microarray experiments. This pilot service is accessible over the Hellenic portion of the EGEE grid and has been demonstrated in the scope of several public events. We highlight the process of grid application enablement, grid deployment challenges, as well as lessons learnt from a bi-annual effort to port and deploy a MATLAB DNA microarray application on a production grid. In addition to describing the parallelization of the application, we also emphasize on the development of a distributed federated database for storing and post-processing the results of the microarray experiments. Overall we believe that our experience could be proven valuable not only to microarray data scientists but also to other Grid users that intend to Grid-enable and deploy their applications.     

Introduce: An Open Source Toolkit for Rapid Development of Strongly Typed Grid Services

Service-oriented architectures and applications have gained wide acceptance in the Grid computing community. A number of tools and middleware systems have been developed to support application development using Grid Services architectures. Most of these efforts, however, have focused on low-level support for management and execution of Grid services, management of Grid-enabled resources, and deployment and execution of applications that make use of Grid services. Simple-to-use service development tools, which would allow a Grid service developer to leverage Grid technologies without needing to know low-level details, are becoming increasingly important for wider application of the Grid. In this paper, we describe an open-source, extensible toolkit, called Introduce, that supports easy development and deployment of Web Services Resource Framework (WSRF) compliant services. Introduce is designed to reduce the service development and deployment effort by hiding low level details of the Globus Toolkit and to enable the implementation of strongly typed services. In strongly typed services, a service produces and consumes data types that are well-defined and published in the Grid. This enables data-level syntactic interoperability so that clients and services can access and consume data elements programmatically and correctly. We expect that enabling strongly typed Grid services while lowering the difficulty of entry to the Grid via toolkits like Introduce will have a major impact to the success of the Grid and its wider adoption as a viable technology of choice in the commercial sector as well as in academic, medical, and government research.     

An optimization-based adaptive resource management framework for economic Grids: A switching mechanism

The application of Grid computing has been broadening day by day. An increasing number of users has led to the requirement of a job scheduling process, which can benefit them through optimizing their utility functions. On the other hand, resource providers are exploring strategies suitable for economically efficient resource allocation so that they can maximize their profit through satisfying more users. In such a scenario, economic-based resource management strategies (economic models) have been found to be compelling to satisfy both communities. However, existing research has identified that different economic models are suitable for different scenarios in Grid computing. The Grid application and resource models are typically very dynamic, making it challenging for a particular model for delivering stable performance all the time. In this work, our focus is to develop an adaptive resource management architecture capable of dealing with multiple models based on the models’ domains of strengths (DOS). Our preliminary results show promising outcomes if we consider multiple models rather than relying on a single model throughout the life cycle of a Grid.     

Brokering of risk‐aware service level agreements in grids

Service level agreements (SLAs) are facilitators for widening the commercial uptake of Grid technology. They provide explicit statements of expectation and obligation between service consumers and providers. However, without the ability to assess the probability that an SLA might fail, commercial uptake will be restricted, since neither party will be willing to agree. Therefore, risk assessment mechanisms are critical to increase confidence in Grid technology usage within the commercial sector. This paper presents an SLA brokering mechanism with risk assessment support, which evaluates the probability of SLA failure. WS‐Agreement and risk metrics are used to facilitate SLA creation between service consumers and providers within a typical Grid resource usage scenario. An evaluation is conducted to examine risk models, the performance of the broker's implementation as well as a comparison of its capabilities against similar SLA‐based solutions from the literature. Copyright © 2011 John Wiley & Sons, Ltd.     

Trouble Management for Multimedia Services in Multi-Provider Environments

As telecommunications and computers evolve, multimedia services are being increasingly deployed over a variety of organizational and technology domains. Customer requirements and the competitive market mean that the delivery of multimedia services at a guaranteed level of quality can play a significant role in differentiating between service providers. In order to meet such quality of service requirements, service providers need to be supported by trouble management capabilities suitable for today's heterogeneous environment. This paper presents an integrated network and service trouble management system that has been designed for such an environment within the framework of the European ACTS project FlowThru. The FlowThru Service Quality Assurance System has been developed using TINA and TMN concepts and TeleManagement Forum business processes in order to support service providers with the necessary infrastructure, models and mechanisms for automated end-to-end trouble management in a multi-domain environment.     

Adaptive service scheduling for workflow applications in Service-Oriented Grid

When the workflow application is executed in Service-Oriented Grid (SOG), performance issues such as service scheduling should be considered, to achieve high and stable performance in execution. However, most of the prior works on workflow management neither study the performance issues nor provide evaluation methodologies on the performance of Grid Services. Therefore, it is infeasible to apply for the service scheduling problem in SOG. In this paper, we propose and model evaluation metrics for the Grid Service performance. The metrics are extracted based on common properties of Grid Services and are used to quantify and evaluate the performance of an individual Grid Service. With these metrics, we develop a service scheduling scheme with a list scheduling heuristic, to choose proper and optimal Grid Services for tasks in workflow applications. It ensures high performance in the execution of the workflow applications. In addition, we propose a low-overhead rescheduling method, referred to as Adaptive List Scheduling for Service (ALSS), to adapt to the dynamic nature of a grid environment. ALSS provides stable performance for workflow applications, even in abnormal circumstances. Finally, we design an experimental environment with actual traces and perform simulations to quantify the benefits of our approach. Throughout the experiments, we demonstrate that ALSS outperforms conventional scheduling methods. Our scheme produces a scheduling performance that is superior to AHEFT by 50.2%, SLACK by 50.8%, HEFT by 68.3%, MaxMin by 72.0%, MinMin by 71.0%, and Myopic by 69.8%.     

Enhancing grid security by fine-grained behavioral control and negotiation-based authorization

Nowadays, Grid has become a leading technology in distributed computing. Grid poses a seamless sharing of heterogeneous computational resources belonging to different domains and conducts efficient collaborations between Grid users. The core Grid functionality defines computational services which allocate computational resources and execute applications submitted by Grid users. The vast models of collaborations and openness of Grid system require a secure, scalable, flexible and expressive authorization model to protect these computational services and Grid resources. Most of the existing authorization models for Grid have granularity to manage access to service invocations while behavioral monitoring of applications executed by these services remains a responsibility of a resource provider. The resource provider executes an application under a local account, and acknowledges all permissions granted to this account to the application. Such approach poses serious security threats to breach system functionality since applications submitted by users could be malicious. We propose a flexible and expressive policy-driven credential-based authorization system to protect Grid computational services against a malicious behavior of applications submitted for the execution. We split an authorization process into two levels: a coarse-grained level that manages access to a computational service; and a fine-grained level that monitors the behavior of applications executed by the computational service. Our framework guarantees that users authorized on a coarse-grained level behave as expected on the fine-grained level. Credentials obtained on the coarse-grained level reflect on fine-grained access decisions. The framework defines trust negotiations on coarse-grained level to overcome scalability problem, and preserves privacy of credentials and security policies of, both, Grid users and providers. Our authorization system was implemented to control access to the Globus Computational GRAM service. A comprehensive performance evaluation shows the practical scope of the proposed system.

Market‐based grid resource co‐allocation and reservation for applications with hard deadlines

Grid computing technology enables the creation of large‐scale IT infrastructures that are shared across organizational boundaries. In such shared infrastructures, conflicts between user requirements are common and originate from the selfish actions that users perform when formulating their service requests. The introduction of economic principles in grid resource management offers a promising way of dealing with these conflicts. We develop and analyze both a centralized and a decentralized algorithm for economic grid resource management in the context of compute bound applications with deadline‐based quality of service requirements and non‐migratable workloads. Through the use of reservations, we co‐allocate resources across multiple providers in order to ensure that applications finish within their deadline. An evaluation of both algorithms is presented and their performance in terms of realized user value is compared with an existing market‐based resource management algorithm. We establish that our algorithms, which operate under a more realistic workload model, can closely approximate the performance of this algorithm. We also quantify the effect of allowing local workload preemption and different scheduling heuristics on the realized user value. Copyright © 2009 John Wiley & Sons, Ltd.     

Building Automated Data Driven Systems for IT Service Management

Enterprises and service providers are increasingly challenged with improving the quality of service delivery while containing the cost. However, it is often difficult to effectively manage the complex relationships among dynamic customer workloads, strict service level requirements, and efficient service management processes. In this paper, we present our progress on building autonomic systems for IT service management through a collection of automated data driven methodologies. This includes the design of feedback controllers for workload management, the use of simulation-optimization methodology for workforce management, and the development of machine learning models for event management. We demonstrate the applicability of the presented approaches using examples and data from a large IT service delivery environment.     

Service level agreement based adaptive Grid superscheduling

Grid computing brings heterogeneity and decentralization to the world of science and technology. It leverages every bit of idle computing resources and provides a straightforward middleware for integrating cross-domain scientific devices and legacy systems. In a super big Grid, job scheduling is challenging specifically when it needs to have access to vast amount of resources. The process of mapping jobs onto Grid resources requires significant consideration in terms of Grid architecture design, consumer demands and provider revenues. In this paper, we simultaneously utilize the legacy architecture of superscheduling, forwarding strategy, service level, success rate, and service pricing strategies and finally propose a service level agreement based on adaptive superscheduling (SAS) algorithm. SAS algorithm presents unified connectivity via efficient diffusion of jobs through the Grid infrastructure that is fueled from the previous scheduling events across the Grid. Moreover, by enforcing the service level agreement terms from a rich set of ask and bid prices, system performance, and load statistics, SAS successfully boosts revenue and utilization statistics. We perform an extensive experimental analysis for different Grid scales. Based on our experimental result, the SAS algorithm maximizes revenue while guarantees quality of service. More specifically, the quality of service is achieved through a high ratio of completed jobs and remarkable utilization of resources.     

Algorithms for Web service selection with static and dynamic requirements

A main feature of Service Oriented Architectures is the capability to support the development of new applications through the composition of existing Web services that are offered by different service providers. The runtime selection of which providers may better satisfy the end-user requirements in terms of quality of service remains an open issue in the context of Web services. The selection of the service providers has to satisfy requirements of different nature: requirements may refer to static qualities of the service providers, which do not change over time or change slowly compared to the service invocation time (for example related to provider reputation), and to dynamic qualities, which may change on a per-invocation basis (typically related to performance, such as the response time). The main contribution of this paper is to propose a family of novel runtime algorithms that select service providers on the basis of requirements involving both static and dynamic qualities, as in a typical Web scenario. We implement the proposed algorithms in a prototype and compare them with the solutions commonly used in service selection, which consider all the service provider qualities as static for the scope of the selection process. Our experiments show that a static management of quality requirements is viable only in the unrealistic case where workload remains stable over time, but it leads to very poor performance in variable environments. On the other hand, the combined management of static and dynamic quality requirements allows us to achieve better user-perceived performance over a wide range of scenarios, with the response time of the proposed algorithms that is reduced up to a 50 % with respect to that of static algorithms.     

Federation Lifecycle Management Incorporating Coordination of Bio-inspired Self-management Processes

As it has evolved, the Internet has had to support a broadening range of networking technologies, business models and user interaction modes. Researchers and industry practitioners have realised that this trend necessitates a fundamental rethinking of approaches to network and service management. This has spurred significant research efforts towards developing autonomic network management solutions incorporating distributed self-management processes inspired by biological systems. Whilst significant advances have been made, most solutions focus on management of single network domains and the optimisation of specific management or control processes therein. In this paper we argue that a networking infrastructure providing a myriad of loosely coupled services must inherently support federation of network domains and facilitate coordination of the operation of various management processes for mutual benefit. To this end, we outline a framework for federated management that facilitates the coordination of the behaviour of bio-inspired management processes. Using a case study relating to distribution of IPTV content, we describe how Federal Relationship Managers realising our layered model of management federations can communicate to manage service provision across multiple application/storage/network providers. We outline an illustrative example in which storage providers are dynamically added to a federation to accommodate demand spikes, with appropriate content being migrated to those providers servers under control of a bio-inspired replication process.     

Modeling and analysis of the effects of QoS and reliability on pricing, profitability, and risk management in multiperiod grid-computing networks

In this paper we develop a network equilibrium model for optimal pricing and resource allocation in Computational Grid Network. We consider a general network economy model with Grid Resource Providers, Grid Resource Brokers and Grid Users. The proposed framework allows for the modeling and theoretical analysis of Computational Grid Markets that considers a non-cooperative behavior of decision-makers in the same tier of the grid computing network (such as, for example, Grid Resource Providers) as well as cooperative behavior between tiers (between Resource Providers and Grid Brokers). We introduce risk management into the decision making process by analyzing the decision-marker's reliability and quality of service (QoS) requirement. We analyze resource allocation patterns as well as equilibrium price based on demand, supply, and cost structure of the grid computing market network. We specifically answer the following questions with several numerical examples: How do system reliability levels affect the QoS levels of the service providers and brokers under competition? How do system reliability levels affect the profits of resource providers and brokers in a competitive market? How do system reliability levels influence the pricing of the services in a competitive environment? How do users' service request types, QoS requirements, and timing concerns affect users' behaviors, costs and risks in equilibrium? How does the market mechanism allocate resources to satisfy the demands of users? We find that for users who request same services certain timing flexibility can not only reduce the costs but also lower the risks. The results indicated that the value of QoS can be efficiently priced based on the heterogeneous service demands.     

An Adaptive Execution Scheme for Achieving Guaranteed Performance in Computational Grids

Nature of the resource pool in a Grid environment is heterogeneous and dynamic. Availability, load and status of the resources may change at the time of execution of an application. Therefore, in order to maintain the performance guarantee (as has been agreed upon through service level agreements (SLAs) between the client and the resource providers), an application may need to adapt to its run-time environment on the basis of resource availability and application demands. Often it may be required to migrate the application components to a new set of resources during their execution so that performance guarantee can be maintained. Objective of this paper is to present an adaptive execution scheme for achieving guaranteed performance on the basis of the SLAs. The scheme has been implemented based on the notion of performance properties and by deploying a set of autonomous agents within an integrated performance-based resource management framework.     

A PSO-based intelligent service dispatching mechanism for customer expectation management

In the era of experience economy, service providers have to provide customers with high quality service experience in order to attract more customers and achieve higher customer satisfaction. Managing customer expectation is a critical approach for service providers to consider. Although customer expectation has been discussed across different research disciplines, to our knowledge, there is still no systematical and feasible way to apply customer expectation management into real environments. This study attempts to establish an intelligent service dispatching mechanism by using particle swarm optimization for customer expectation management. This mechanism can help service providers design and deliver satisfactory service experience to customers. In order to evaluate the effectiveness and robustness of this mechanism, this study employs micro- and macro-simulation experiments to confer and analyze its performance. The simulation results show service providers can gain benefit and raise customer satisfaction by managing customer expectation during service experience delivery. Meanwhile, customers can also receive memorable experiences and have positive responses to service providers and other customers. Consequently, a high performance ecosystem within service providers and customers can be formed.     

A Market-Oriented Grid Directory Service for Publication and Discovery of Grid Service Providers and their Services

The emergence of Grids as a platform for sharing and aggregation of distributed resources increases the need for mechanisms that allow an efficient management of resources. The Grid economy has been identified as one of the potential solutions as it helps in managing the supply and demand for resources and enables sustained sharing of resources by providing economic incentive for Grid resource providers. An economy based Grid computing environment needs to support an infrastructure that enables the creation of a marketplace for meeting of providers and consumers. This paper presents the Grid Market Directory (GMD) that serves as a registry for publication and discovery of Grid service providers and their services.