Special Issue on Federated Resource Management in Grid and Cloud Computing Systems Future Generation Computer Systems Editor-in-Chief: Peter Sloot

*** Call for Papers *** Grids and Distributed Computing Systems have evolved to enable coordinated access to geographically and topologically distributed resources, and in order to solve challenging problems in the domains of e-Research, e-Science, and e-Business. Different resource types that are shared in a Grid environment include computational clusters, supercomputers, storage devices, scientific instruments, and tiny sensor devices. With the rapid advent of networking and Grid technologies, scientists and engineers have been able to build systems that can manage complex applications involving large data sets and dynamic dependencies. More recently, a new trend has been observed with regards to management and delivery of software services through the next generation data centers and enterprise Clouds. An enterprise Cloud is a type of computing infrastructure that consists of a collection of interconnected computing nodes, virtual machines, and software services that are dynamically provisioned among the competing applications based on their availability, performance, capability, and Quality of Service (QoS) requirements. This new way of architecting data centers and enterprise Cloud is referred to as Cloud computing, which focuses on delivery of reliable, secure, fault-tolerant, sustainable, and scalable services; platforms; and infrastructures to the end-users. All these systems have the same goals: providing the illusion of unlimited computing, storage and hiding the complexity of large-scale distributed computing from users. Emerging

federated

Grid

and

Cloud

computing

infrastructures

are

large,

heterogeneous, and dynamic by nature, which account to unique challenges that have not been previously addressed in the literature. Past efforts in Grid resource management,

especially scheduling and resource allocation are based on static and centralized approaches. Existing Grid scheduling approaches show inability to adapt with changing resource and network conditions. For example, the workflow scheduling algorithms that use meta-heuristics, such as genetic algorithm, make the scheduling plan for the entire workflow in advance and the tasks are executed according to that. Thus, these approaches severely suffer if the resource availability (failure, dynamic leave/join) and network condition change (link failure, congestion). Further, these approaches do not consider the notions of trustworthiness and reliability of resources that are fundamental to ensuring guaranteed service delivery by the Grid and Cloud resources. Next, most of the scheduling studies in Grid resource management literature are conducted around centralized or semi-centralized network models for resource information aggregation. Studies have shown that existing centralized models for information services do not scale well as system grows. Considering the sheer dynamism of federated Grid and Cloud computing environment, there is a need to develop scalable methods for resource discovery and dynamic scheduling that can adapt to changing resource and network conditions. Various Grid domains and Clouds can be pooled together to form a federated infrastructure of resource pools (nodes, services, virtual machines, storage). In a federated computing model: (i) system can grow or shrink based on demand and operating environment (power failure, heat dissipation, natural disasters); (ii) the peak-load handling capacity of every computing domain is enhanced without having the need to maintain or administer any additional hardware or software infrastructure; and (iii) the ability of computing domain as regards to reliable service delivery is augmented due to availability of multiple redundant resource pools that can efficiently tackle disaster conditions and ensure continuity of crucial business and scientific applications. Emerging Grid and Cloud computing applications such as web hosting, social networking, e-Research, and e-Business and the underlying federated hardware infrastructures are inherently large, with heterogeneous resource types that may exhibit temporal resource conditions (availability, load, power efficiency, and heating of the servers). The unique challenges in efficiently managing the federated Grid and Cloud computing infrastructures that span across the multiple service boundaries include: •

Large scale – composed of distributed components (services, nodes, applications, users, virtual machines) that combine together to from a massive problem solving environment. In recent years, Grid domains and Data Centers consisting of hundreds of thousands of computing nodes and storage units are common; hence federating them together leads to a massive scale environment;

Autonomous and distributed - every service domain makes its resource allocation



decision independently and each one is separated by service boundaries; Self-Interested - each service domain has distinct stake holdings with different aims



and utility functions; Dynamic – the participants can leave or join the system at will; resources exhibit



temporal conditions; Heterogeneous - each service domain is expected to be configured with a range of



hardware, software, and virtual machines types; that make the utility oriented resource

allocation

and

load-balancing

(virtual

machine

migration)

across

administrative boundary difficult problems.

Topics Areas of interest for this special issue include the following: -

Architectural models for federation of Clouds and Grids

-

Utility-oriented scheduling and allocation in federated environments

-

Fault-tolerant and reliable application scheduling in federated environments

-

Scalable organization (such as peer-to-peer) of resources, data, and services in large scale federations

-

Decentralized resource discovery and monitoring algorithms

-

Scalable trust, reputation, and security protocols

-

Coordinated interaction of users, middleware services, and resources

-

Energy efficient (Power aware) scheduling and migration of applications in federated Clouds

-

Industrial and experimental infrastructure for federated Grid and Cloud systems

-

Innovative Scientific, Business, and Internet Service Applications

Schedule Submission due date: May 15, 2009 Notification of acceptance: July 15, 2009 Submission of final manuscript: Sept 30, 2009 Publication date: 1st/2nd Quarter, 2010 (Tentative)

Submission & Major Guidelines The special issue invites original research papers that make significant contributions to the state-of-the-art in the areas of federated resource management of Grid and Cloud computing systems. The papers must not have been previously published or submitted for journal or conference publications. However, the papers that have been previously published with reputed conferences could be considered for publication in the special issue if they are substantially revised from their earlier versions with at least 30% new contents or results that comply with the copyright regulations, if any. Every submitted paper will receive at least three reviews. The editorial review committee will include well known experts in the area of Grid and Cloud computing. Selection and Evaluation Criteria: -

Significance to the readership of the journal

-

Relevance to the special issue

-

Originality of idea, technical contribution, and significance of the presented results

-

Quality, clarity, and readability of the written text

-

Quality of references and related work

-

Quality of research hypothesis, assertions, and conclusion

Guest Editors Dr. Rajkumar Buyya Associate Professor and Reader Grid Computing and Distributed Systems Laboratory Department of computer science and software engineering The University of Melbourne, Australia Email: [email protected] Dr. Rajiv Ranjan Research Fellow – Global Grids Grid Computing and Distributed Systems Laboratory Department of computer science and software engineering The University of Melbourne, Australia Email: [email protected]

Call for Papers

Call for Papers ***. Grids and ... This new way of architecting data ... administer any additional hardware or software infrastructure; and (iii) the ability of.

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