The Grid 2: Blueprint for a New Computing Infrastructure

Cloud can be defined as a new computing paradigm that provides scalable, on-demand, and virtualized resources for users. In this style of computing, users can access a shared pool of computing resources which are provisioned with minimal management efforts of users. Yet there are some obstacles and concerns about the use of clouds. Guaranteeing quality of service U+0028 QoS U+0029 by service providers can be regarded as one of the main concerns for companies tending to use it. Service provisioning in clouds is based on service level agreements representing a contract negotiated between users and providers. According to this contract, if a provider cannot satisfy its agreed application requirements, it should pay penalties as compensation. In this paper, we intend to carry out a comprehensive survey on the models proposed in literature with respect to the implementation principles to address the QoS guarantee issue.

Toward cloud computing QoS architecture: analysis of cloud systems and cloud services

https://www.infosys.tuwien.ac.at/Staff/ivona/papers/AutonomicSLADetection.pdf

Towards autonomic detection of SLA violations in Cloud infrastructures

Content delivery networks (CDNs) have gained immense popularity over the years. Replica server placement is a key design issue in CDNs. It entails placing replica servers at meticulous locations, such that cost is minimized and quality of service of end-users is satisfied. Many replica server placement models have been proposed in the literature of traditional CDN. As the CDN architecture is evolving through the adoption of emerging paradigms, such as, cloud computing and network functions virtualization, new algorithms are being proposed. In this paper, we present a comprehensive survey of replica server placement algorithms in traditional and emerging paradigm-based CDNs. We categorize the algorithms and provide a summary of their characteristics. Besides, we identify requirements for an efficient replica server placement algorithm and perform a comparison in the light of the requirements. Finally, we discuss potential avenues for further research in replica server placement in CDNs.

A Survey on Replica Server Placement Algorithms for Content Delivery Networks

Cloud computing is the result of the convergence of several concepts, ranging from virtualization, distributed application design, Grid computing, and enterprise IT management. Efficient management of Cloud computing infrastructures faces with the contradicting goals like unlimited scalability, provision of Service Level Agreements (SLAs), extensive use of virtualization, energy efficiency and minimization of the administration overhead by humans. Thus, autonomic computing seems to be one of the promising paradigms for the implementation of the management infrastructures for Clouds. However, currently available autonomic systems do not consider the characteristics of Clouds, e.g., virtualization layer, and thus are not easily applicable to Cloud infrastructures. In this paper we discuss first steps towards revealing the current MAPE (Monitoring, Analysis, Planning, Execution) loops for the application to Cloud infrastructures. We present novel techniques for the adequate monitoring of Clouds, discuss the approach for the knowledge management and present our solutions for facilitating SLA generation and management.

Revealing the MAPE loop for the autonomic management of Cloud infrastructures

In dynamic and autonomic grid environment, monitoring of heterogonous resources is critical for performance analysis & tuning, job scheduling, fault detection & diagnosis and so on. Existing researches are always limited at either inter-operation or introducing too much intrusive overhead. GridEye is a novel service-oriented monitoring system with a flexible, scalable architecture. An open, extendable information schema is adopted to standardize data contents and Web service interfaces are employed to provide inter-operative ability for different grid system. Furthermore, an improved forecasting algorithm is provided for precise performance prediction on the basic of traditional MA (k) and ExS(alpha) models. Experiments proved that GridEye introduces very little overhead while providing good capabilities. It is also indicated that the algorithm can promote the precision of prediction

GridEye: A Service-oriented Grid Monitoring System with Improved Forecasting Algorithm

The volume of datasets in scientific computing domain is increasing explosively and data is becoming the center of scientific computing. Data Grid is an emerging technology to provide uniform access and management of the large scale distributed scientific datasets. In this paper, the GridDaen system, a new Data Grid middleware, which provides uniform APIs and GUI to access and manage resources, is presented in detail. GridDaen utilizes a three-level naming scheme that shields users from low-level resource discovery and provide global uniform view for users. Coordinated DRB servers and multiple-layer distributed metadata servers are adopted in GridDaen to provide uniform secure access and management of heterogeneous distributed resources across multiple administrative domains. Role-based multi-level access control policy is used in the system and caching and replication mechanisms are utilized to improve the performance of the system. The virtual dataset functions are also supported in GridDaen. GridDaen can achieve good scalability, reliability and can be flexibly deployed and configured according to the application demands.

GridDaen: A Data Grid Engine

Data Grid is an emerging technology to provide uniform access and management of the large scale distributed scientific datasets. To enhance the accessing performance, replica is an ideal solution for the Data Grid. But in the wide-area network environment, to maintain the consistency of those replicas is not a simple task because of the resource’s autonomy and the network’s instability. In this paper, a new asynchronous model is proposed, which could avoid the inconsistency in spite of the possible network congestion and system failure. This model couldbe more suitable for the resource autonomy characteristic, putting fewer burdens on storage resources, and it is also easier to implement while providing more scalability for the grid system. And then a detailed implementation, use case and some further research plans are described.

An asynchronous replica consistency model in data grid

Spatial applications will gain high complexity as the volume of spatial data increases rapidly A suitable data processing and computing infrastructure for spatial applications needs to be established Over the past decade, grid has become a powerful computing environment for data intensive and computing intensive applications Integrating grid computing with spatial data processing technology, the authors designed a spatial data processing grid (called SDPG) to address the related problems Requirements of spatial applications are examined and the architecture of SDPG is described in this paper Key technologies for implementing SDPG are discussed with emphasis

SDPG: spatial data processing grid

Quality of service is one of the most important factors for successful grid applications. However, individual QoS constraint (IQC) and QoS-awared replica placement have not yet been well addressed in the existing data grid. Existing QoS-awared replica placement algorithms neither can support multiple QoS attributes, nor have good scalability. In this paper, a three-phrase QoS-awared replica placement algorithm based on matrix, namely TP-GABMAC, is presented to solve these problems. Furthermore, a replica ring mechanism is introduced to maintain replica consistency and manage update conflicting. Experiments and analysis demonstrate that the proposed algorithms are not only stable and scalable, but also work well under different network topologies, access patterns and workloads.

QoS-awared replica placement techniques in data grid applications

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