Future Generation Computer Systems 28 (2012) 1003–1004

Contents lists available at SciVerse ScienceDirect

Future Generation Computer Systems

journal homepage: www.elsevier.com/locate/fgcs

Editorial

Special Section: QoS in Grid and Cloud

This special section follows a session theme presented at theInternational Conference on Computer Supported CooperativeWork in Design held in Shanghai in 2010. The conference wasattended by about 150 delegates. During the event therewasmuchinterest in the area of Quality of Service in distributed computing,particularly when services are delivered across the Internet.The guest editors thought that it would be very interesting todraw together relevant papers from the international researchcommunity. Hence the decision to apply for a special sectionentitled ‘‘QoS in Grid and Cloud’’ in the prestigious FutureGeneration Computer Systems journal and to launch an open callto researchers for contributions to it. The open call attracted fortysubmissions from which thirteen excellent papers were selectedfollowing a rigorous refereeing process.

And so we now have our special section containing thirteenpapers, covering both Grid and Cloud, all with a QoS unifyingtheme. Within this context, four sub-themes have emerged fromthe selected papers: firstly the sub-theme of the development ofsystems which exploit autonomy or adaptivity in that changes inthe run-time environment can be detected and effectively handled,resulting in better QoS; secondly the sub-theme of managingservice discovery and composition in a manner that satisfiesor improves QoS; thirdly the sub-theme of the developmentof improved scheduling and congestion handling techniques toimprove performance; and finally the sub-theme of empowermentof users, thus furnishing users with better understanding andcontrol over the QoS they request.

The sub-theme of adaptivity and autonomy includes six papers.The paper by Sánchez et al. describes an autonomic subsystemintended to provide self-management features aimed at efficientlyreducing the I/O problem in a Grid computing environment,thereby enhancing the QoS. The system takes into account thatdata produced in an I/O system is not usually immediatelyrequired. Therefore, performance improvements are related notonly to current but also to any future I/O access. However, theexact time of the next I/O operations is unknown. Thus, theapproach proposes a long-term prediction designed to forecast thefuture workload of Grid components. This enables the autonomicsubsystem to determine the optimal data placement to improveboth current and future I/O operations. Next we have the paperby Emeakaroha et al. where work on autonomic detection ofService Level Agreement (SLA) violations in Cloud infrastructuresis presented. SLA violations are detected through sophisticatedresource monitoring which maps host up and down time touser defined SLAs and matches this with service level objectives.The paper by Dong et al. proposes an effective data aggregationbased adaptive long-term CPU load prediction mechanism for thecomputational Grid. The authors state that existing prediction

0167-739X/$ – see front matter© 2012 Published by Elsevier B.V.doi:10.1016/j.future.2012.03.014

algorithms usually fail to achieve good prediction accuracy in long-term prediction. Thus the authors claim the proposed algorithmis able to provide more useful information for task scheduling.The fourth paper in this sub-theme is authored by Lee, Leu andChen who present Popular File Replicate First (PFRF), an adaptivedata replication algorithm based on star-topology data grids.Data replication algorithms are used in data grids to replicatefrequently accessed data to appropriate sites. The PFRF periodicallycalculates file access popularity to track users’ access behaviourand replicates the files accordingly on the star topology. The nextpaper addresses the network, an integral part of computationaland data grids. This work authored by Tomás et al. focuseson an implementation of an autonomic network-aware, meta-scheduling architecture that is capable of adapting its behaviourto the current status of the environment, so that jobs can beefficiently mapped to computing resources. The final paper inthis sub-theme is authored by Paton, de Aragão and Fernandeswho introduce utility-driven adaptive query workload execution.Adaptive query processing (AQP) changes theway inwhich a queryis evaluated while the query is running. The authors describe howutility functions can be used to coordinate adaptations and theyshow how local and global objectives can be supported througha common framework such that overall query response times canbeminimised and the number of queriesmeeting quality of servicerequirements can be maximised.

The sub-theme of managing service discovery and compositionfor QoS contains three papers in this special section. The firstpaper is by Liu et al. who describe a QoS-aware execution planselection approach for service composition. The QoS-aware ServiceComposition (QSC) problem is to find an execution plan of theservice composition process which can ensure that the qualityof service meets given user requirements. In this paper theproblem ismodelled as an extended flexible constraint satisfactionframework. The second paper in this sub-theme is provided byKumar, Iqbal and Chilamkurti who address capacity and load-aware service discovery in peer-to-peer grids. The dynamic natureof peer-to-peer grids makes it infeasible for a participating peerto decide the optimal selection of services. This paper addressesthis issue by formulating the problem of service discovery andselection as a linear programming (LP) problem, together withthe constraints and proposed algorithms. The final paper of thissub-theme is by Liu et al. who describe a service deploymentmanagement system for optimization in Clouds. This systemprovides a facility to optimise service deployment by recognisingand exploiting families of compatible services.

The third sub-theme is on the development of improvedscheduling and congestion handling techniques. In this sub-themewe have two papers. You and Zhao describe a new dynamicrequests scheduling approach in multi-core systems. Their work

1004 Editorial / Future Generation Computer Systems 28 (2012) 1003–1004

is based on the concept of Weighted-Fair-Queuing (WFQ) andit exploits the performance of multi-core CPUs. The secondpaper of this sub-theme is authored by Munir et al. The paperaddresses data movement and bandwidth reservation. It describesa system of combining explicit admission control and congestioncontrol for predictable data transfers in grids. The approachadopts opportunistic sharing of the capacity by flows which haveheterogeneous bandwidth and delay requirements.

The final sub-theme of empowerment of users is covered bytwo papers. Albodour, James and Yaacob firstly present a modelfor high-level QoS within a business context. Various levels ofQoS and associated user requirements specification are supportedin the proposed system thus providing a more tailored overallservice which suits the diverse needs of the business landscape.The final paper of this sub-theme and indeed of the special sectionis provided by Farsandaj and Ding who address the matter ofhelping users to specify QoS requirements accurately. The authorshave developed a system which allows users to browse QoS datathrough the service repository so that they can find out actualQoS value distributions and thus include reasonable numbers intheir QoS queries. The authors apply the scatter/gather model to

QoS browsing. By discovering the typical QoS provided by services,users will have a better idea of the levels of service to expect andrequest. Service providers should also benefit from the browsingas they will discover more about user preferences.

The guest editors would like to thank the authors for amost interesting set of papers. We hope that our fellow Gridand Cloud researchers and developers enjoy reading them andthat further good ideas and implementations emerge from thiscommunication!

Guest EditorsAnne James

Distributed Systems and Modelling Research Group,Coventry University,

Coventry, UKE-mail address: a.james@coventry.ac.uk.

Weiming ShenNational Research Council of Canada,

London, Ontario, CanadaE-mail address:weiming.shen@nrc.gc.ca.