Ramin Yahyapour

Service Level Agreements for Cloud Computing

Service Level Agreements for Cloud Computing provides a unique combination of business-driven application scenarios and advanced research in the area of service-level agreements for Clouds and service-oriented infrastructures. Current state-of-the-art research findings are presented in this book, as well as business-ready solutions applicable to Cloud infrastructures or ERP (Enterprise Resource Planning) environments. Service Level Agreements for Cloud Computing contributes to the various levels of service-level management from the infrastructure over the software to the business layer, including horizontal aspects like service monitoring. This book provides readers with essential information on how to deploy and manage Cloud infrastructures. Case studies are presented at the end of most chapters. Service Level Agreements for Cloud Computing is designed as a reference book for high-end practitioners working in cloud computing, distributed systems and IT services. Advanced-level students focused on computer science will also find this book valuable as a secondary text book or reference.

Multiple Workflow Scheduling Strategies with User Run Time Estimates on a Grid

In this paper, we present an experimental study of deterministic non-preemptive multiple workflow scheduling strategies on a Grid. We distinguish twenty five strategies depending on the type and amount of information they require. We analyze scheduling strategies that consist of two and four stages: labeling, adaptive allocation, prioritization, and parallel machine scheduling. We apply these strategies in the context of executing the Cybershake, Epigenomics, Genome, Inspiral, LIGO, Montage, and SIPHT workflows applications. In order to provide performance comparison, we performed a joint analysis considering three metrics. A case study is given and corresponding results indicate that well known DAG scheduling algorithms designed for single DAG and single machine settings are not well suited for Grid scheduling scenarios, where user run time estimates are available. We show that the proposed new strategies outperform other strategies in terms of approximation factor, mean critical path waiting time, and critical path slowdown. The robustness of these strategies is also discussed.

Attributes for communication between Grid scheduling instances

Typically, Grid resources are subject to individual access and usage policies because they are provided by different owners. These policies are usually enforced by local management systems that maintain control of the resources. However, few Grid users are willing to deal with those management systems directly in order to coordinate the resource allocation for their jobs. This leads to a Grid scheduling architecture with several layers. In such an architecture, a higher-level Grid scheduling layer and the lower-level layer of local scheduling systems must efficiently cooperate in order to make the best use of Grid resources. In this chapter we describe attributes characterizing those features of local management systems that can be exploited by a Grid scheduler.

A Proposal for a Generic Grid Scheduling Architecture

In the past years, many Grids have been deployed and became commodity systems in production environments. While several Grid scheduling systems have already been implemented, they still provide only “ad hoc” and domain-specific solutions to the problem of scheduling resources in a Grid. However, no common and generic Grid scheduling system has emerged yet. In this work we identify generic features of three common Grid scheduling scenarios, and we introduce a single entity called scheduling instance that can be used as a building block for the scheduling solutions presented. We identify the behaviour that a scheduling instance must exhibit in order to be composed with other instances, and we describe its interactions with other Grid services. This work can be used as a foundation for designing common Grid scheduling infrastructures.

Performance Evaluation of a Scalable Software-Defined Networking Deployment

Since the introduction of software-defined networking (SDN), scalability has been a major concern. There are different approaches to address this issue, and most of them can be addressed without losing the benefits of SDN. SDN provides a level of flexibility that can accommodate network programming and management at scale. In this work we present the recent approaches, which are proposed to address scalability issue of SDN deployment. We particularly select a hierarchical approach for our performance evaluation study. A mathematical framework based on network calculus is presented and the performance of the selected scalable SDN deployment in terms of upper bound of event processing and buffer sizing of the root SDN controller is reported.

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 agreements fault-tolerance concerns and strategies into multiple autonomous layers that can be hierarchically combined into an intuitive, parallelized, effective and efficient management structure. We elaborate a utility architecture that optimizes resource deployment.We provide a mechanism for optimized SLA negotiation.Using Actor system as basis, the entire SLA management can be efficiently parallelized.We separate the agreements fault-tolerance strategies into multiple autonomous layers.A realistic approach for the automated management of the complete SLA lifecycle.

Resource Management for Future Generation Grids

This paper discusses the requirements for and functionalities of resource management systems for future generation Grids. To this end it is also necessary to review the actual scope of future Grids. Here we examine differences and similarities of current Grid systems and distinguish several Grid scenarios to highlight the different understandings of the term Grid which exist today. While we expect that a generic Grid infrastructure cannot suite all application scenarios, it would certainly be beneficial to many of them to share such an infrastructure. Instead of identifying a minimal subset of necessary Grid middleware functionalities, we postulate that Grids need a resource management system both well-designed and rich in features to be usable for a large variety of applications. This includes for example extended functionalities for information and negotiation services which can be used by automatic scheduling and brokering solutions.

Iterative big data clustering algorithms: a review

Enterprises today are dealing with the massive size of data, which have been explosively increasing. The key requirements to address this challenge are to extract, analyze, and process data in a timely manner. Clustering is an essential data mining tool that plays an important role for analyzing big data. However, large‐scale data clustering has become a challenging task because of the large amount of information that emerges from technological progress in many areas, including finance and business informatics. Accordingly, researchers have dealt with parallel clustering algorithms using parallel programming models to address this issue. MapReduce is one of the most famous frameworks, and it has attracted great attention because of its flexibility, ease of programming, and fault tolerance. However, the framework has evident performance limitations, especially for iterative programs. This study will first review the proposed iterative frameworks that extended MapReduce to support iterative algorithms. We summarize these techniques, discuss their uniqueness and limitations, and explain how they address the challenging issues of iterative programs. We also perform an in‐depth review to understand the problems and the solving techniques for parallel clustering algorithms. Hence, we believe that no well‐rounded review provides a significant comparison among parallel clustering algorithms using MapReduce. This work aims to serve as a stepping stone for researchers who are studying big data clustering algorithms. Copyright

The NRW-Metacomputer - building blocks for a worldwide computational grid

Presents the results of the NRW-Metacomputing Taskforce, which has been working on the development of a (German) country-wide metacomputer since 1996. The resulting installation is among the very few that are already operational, have full support for heterogeneous resources, contain a decent security model and feature an advanced scheduling subsystem for the metacomputing environment. The NRW-Metacomputer has been implemented using a modular software architecture. Hence, its concepts and components can be re-used by others without the need to obtain the metacomputing software as a whole. Furthermore, the NRW-Metacomputer already provides well-defined interfaces for linking the system with other metacomputing environments to form a truly global computational grid. Distinctive features of this system are its highly scalable and fault-tolerant software architecture, its advanced resource planning mechanisms, as well as an integration into a DCE (Distributed Computing Environment)/DFS (Distributed File System) environment.

Improving Workflow Execution through SLA-based Advance Reservation

In SOA-based Grid environments service provider and service consumer usually do not know each other. In order to establish a business relation they must inter alia (i) create a trust relationship, and (ii) set up mechanisms to create reliable, verifiable, and, at least in a commercial environment, also audible agreements with respect to the services requested, delivered and consumed. In this paper we will only briefly address (i) but concentrate on solutions for (ii) based on Service Level Agreements (SLAs). Therefore we will give an overview on the state-of-the-art of SLA usage in Grids, highlight possible obstacles for the deployment of SLAs, and present a detailed example of a service improving the execution of workflows through the use of WS-Agreement to negotiate advance reservation of resources to execute workflow components.