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[PVS] FGCS Special Issue on Model-driven Provisioning of ApplicationServices in Hybrid Computing Environments [Deadline extended to Feb 15, 2012]

Special Issue on

Model-driven Provisioning of Application Services in Hybrid Computing Environments


Future Generation Computing System

Editor-in-Chief: Peter Sloot


*** Call for Papers ***


This special issue solicits papers that advance the fundamental understanding, technologies, and concepts related to provisioning resources (CPU, storage, and network) and applications over hybrid cloud computing systems. The research advancement is in this area is important because such large, heterogeneous, uncertain and evolving cloud systems are becoming increasingly common, yet current provisioning methods do not scale well and nor do they perform well under highly unpredictable conditions. If these problems are resolved, then cloud-hosted applications will operate more efficiently, with reduced financial and environmental costs, reduced under-utilisation of resources, and better performance at times of unpredictable workload.


Today, Small and Medium Business Enterprises (SMEs) and governments face accelerated business change, more intense domestic and global competition and increased IT demands. They try to meet new demands through rapid implementation of innovative and inclusive business models while at the same time lowering IT barriers to innovation and change. These demands call for a more dynamic computing model that supports rapid innovation for services and their delivery. Cloud computing, which can be an important component of such a model, is a recent advance wherein IT-related functionalities (e.g., CPU, applications, storage, etc.) are provided as a virtualized service to consumers under a usage-based payment model. In a Cloud computing model, consumers (SMEs, governments, universities) can leverage virtualized services probably on the fly based on fluctuating requirements and, in doing so, they avoid worry about infrastructure details such as where these resources are hosted or how they are managed. The new computing environment, buoyed by recent advances in the above areas, has resulted in hybrid computing environments comprised of virtualized services usage-based payment models, and networked devices. The benefit of such an environment is efficiency and flexibility, through creation of a more dynamic computing enterprise, where the supported functionalities are no longer fixed or locked to the underlying infrastructure. This offers tremendous automation opportunities in a variety of computing domains including, but not limited to, e-Government, e-Research, web hosting, and e-Business.


Provisioning means “high-level management of computing, network, and storage resources to allow them to effectively provide and deliver application services to end-users”. The diversity and flexibility of the IT functionalities (dynamically shrinking and growing computing systems) offered by the evolving hybrid environments, combined with the magnitudes and uncertainties of its components (workload, CPU, storage end-users, etc.), pose difficult problems in effective provisioning and delivery of application services. Computing systems managing hybrid environments must deal with the highly transient behaviors of end-users (arrival pattern, profile), virtualized services (CPU utilization, CPU availability, dataset size, I/O and other QoS issues) and networks (bandwidth, disconnections), all of which can be difficult to predict. The problem is further complicated by ever-increasing scale, performance, energy saving and security requirements. To counter these challenges, there is need to develop analytical models for each component that operate as parts of hybrid computing environments. These models will be important because they allow adaptive system management by establishing useful relationships between high-level performance targets (specified by operators) and low-level control parameters and observables that system components can control or monitor. Consequently, there is need to develop models for predicting behaviour and performance of different types of applications services and resources to adaptively transform service requests. Broad range of analytical models and statistical curve-fitting techniques such as multi-class queuing models and linear regression time series can be applied for this purpose. These models will drive and possibly transform the input to a service provisioner, which will improve the efficiency of the system. Such improvements will better ensure the achievement of performance targets (response time, throughput, fairness) and security concerns (confidentiality, integrity and availability), while reducing costs due to improved utilization of resources. It will be a major advancement in the field to develop a robust and scalable system monitoring infrastructure to collect real-time data and re-adjust these models dynamically with a minimum of data and training time. We believe that these models and techniques are critical for the design of stochastic provisioning algorithms across large hybrid environments where resource availability is uncertain.



  Areas of interest for this special issue include the following:

-      Application behavior prediction models

-      Dynamic learning technique for new application behavior adaptation

-      Queuing theory based resource performance model solvers

-      Application auto-scaling models

-      Stochastic fault-tolerance and reliability models

-      Decentralized networking models for scalable application health monitoring and model training

-      Energy-efficiency models for provisioning and migration of applications

-      Industrial and experimental infrastructure enabling hybrid environments

-      Innovative Scientific, Business, and Internet Service Applications

-      Security, privacy and trust in hybrid environment



Submission due date: January 15, 2012 - Deadline extended to Feb 15, 2012

Notification of acceptance: March 15, 2012

Submission of final manuscript: May 15, 2012

Publication date: 1st/2nd Quarter, 2012 (Tentative)


Submission & Major Guidelines

The special issue invites original research papers that make significant contributions to the state-of-the-art in “model-driven provisioning of application services in hybrid computing environments”.  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, Cloud, and Autonomic 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. Rajiv Ranjan – Corresponding Guest Editor

Research Scientist, CSIRO ICT Center

Computer Science and Information Technology Building (108)

North Road, Australian National University, Acton, ACT, Australia

Email: rajiv.ranjan@csiro.au


Prof. Rajkumar Buyya

CEO, Manjrasoft Pty Ltd, Melbourne, Australia

Director, Cloud Computing and Distributed Systems Laboratory

Department of computer science and software engineering

The University of Melbourne, Australia

Email: raj@csse.unimelb.edu.au


Dr. Surya Nepal

Principal Research Scientist, CSIRO ICT Center

Cnr Viemiera and Pembroke Roads

Marsfield, NSW 2122

Email: Surya.Nepal@csiro.au