Cluster ComputDOI 10.1007/s10586-014-0352-5

Introduction to cloud computing: platforms and solutions

Jesus Carretero · Javier Garcia Blas

© Springer Science+Business Media New York 2014

Abstract This special issue of the cluster computing jour-nal will feature articles that discuss tools and applications forcloud computing. Specifically, it aims at delivering the state-of-the-art research on current cloud computing tools topics,and at promoting the cloud applications discipline by bring-ing to the attention of the community novel problems thatmust be investigated.

Keywords Cloud computing · Platforms · Special issue

1 Introduction

Cloud Computing is a recent trend in information technol-ogy and scientific computing that moves computing and dataresources to large data centers. Following NIST [20], Cloudcomputing is a model for enabling ubiquitous, convenient,on-demand network access to a shared pool of configurablecomputing resources (e.g., networks, servers, storage, appli-cations, and services) that can be rapidly provisioned andreleased with minimal management effort or service providerinteraction. Although the idea of cloud computing has beenaround for quite some time, cloud computing is characterizedas a computing environment where computing needs by oneparty can be accessed via Internet from external servers thatdo not belong to the user’s company but to the cloud owner orto a cloud federation, allowing the user to get resources elasti-cally as they change. Thus, cloud computing moves comput-

J. Carretero (B) · J. G. BlasComputer Science and Engineering Department,University Carlos III of Madrid, Madrid, Spaine-mail: jesus.carretero@uc3m.es

J. G. Blase-mail: fjblas@arcos.inf.uc3m.es

ing and data away from small personal or company systemsto large data centers, whose services are provided in a pay-per-use model.

Technologically, cloud computing joins several differ-ent computing technologies coming from virtualization, gridcomputing, peer-to-peer computing, autonomic computing,web services, ubiquitous computing, service oriented archi-tecture, etc. [2]. However, driving forces for cloud computingare not only technological. First motivation was an inside-out solution to allow the resource providers to fully exploitthe under-utilized resources in computing and data centers.However, the companies discovered great advantages in thistechnology, and a outside-in pressure was created to get util-ity computing and a IT services available anytime world-wide form any device. The possibility of outsourcing cheapservices is a major advantage of cloud computing, as thecustomers do not have to purchase or maintain their owninfrastructure, getting services ranging from software to stor-age or security, while they don’t have to suffer technologyobsolescence ot their own installations.

Cloud Computing opens new perspectives in inter-net-working technologies, raising new issues in the architec-ture, design, and implementation of existing networks anddata centers. The relevant research has just recently gainedmomentum and the space of potential ideas and solu-tions is still far from being widely explored, existing novelchallenges [19,32] that must be investigated. In this briefoverview, we show some of them and provide the readerwith references for extending her information.

2 Cloud computing solutions

Cloud computing solutions usually rely on applications thatare built on top of services [20,25]. Services are offered

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through the network using standard mechanisms, as web ser-vices, by providers disconnected from the users, which buildsapplications as needed by compiling mash-ups of services,that can include heterogeneous platforms with well definedbehavior. Nowadays, enabling cloud-based services [24], itis not as transparent as it should be. Several programmingmodels have been proposed based on service composition,work-flows, and map-reduce paradigms.

Cloud service providers can be roughly classified intothree categories: software as a service (SaaS), platform asa service (PaaS), and infrastructure as a service (IaaS).

SaaS aims to provide application developers services(or even complete applications), which run on the cloudinfrastructure of the provider. Applications are accessiblethrough standard Web services, to build programmed appli-cations, or by using web browsers, to build applications. Theuser is not aware of the underlying infrastructures, neither cancontrol it. The provisions are controlled through service levelagreements (SLA). Google apps are a typical exponent ofSaaS. In this paradigm, cloud service hosting, service mobil-ity, and service migration are key aspects of the provider, butthey are also transparent to the user [10,12].

PaaS, where users can deploy complete applications onthe cloud infrastructure, without controlling it [29]. Insteadof supplying services, the providers supply libraries and toolsin order to deploy the application itself. Applications are exe-cuted on the virtual platform in a transparent manner, similarto the Google Apps Engine and Morph Labs. The platformlayer provides value-added services from both a technicaland a business perspective, for example Salesforce and xRMenables the whole application life cycle for the development,deployment, and management of tailored business applica-tions.

IaaS, where computing resources, data-storing, and net-working are explicitly offered as services through virtual-ized machines using the providers infrastructure [16]. In thiscase, users are completely aware of the virtual infrastruc-ture and they must manage it. The provider’s computingresources are pooled to serve multiple consumers usinga multi-tenant model, with different physical and virtualresources dynamically, assigned and reassigned according toconsumer demand. Typical examples are Amazons Dynamoand Googles Bigtable, but lower level IaaS are also offered,as GoogleFS and OpenFlow. When dealing with IaaS, it iscrucial that the provider may have cloud infrastructure man-agement facilities for visualization, automation, and diagno-sis of the whole system state.

The major reason to abstract more and more current cloudsis to avoid the users the cumbersome policy managementrelated to system in cloud computing [27]. IaaS paradigmoffer interfaces too close to the infrastructure. However, mostusers demand functionalities that automate the managementof their services as a whole unit, so that services and capabil-

ity can be elastically and automatically provisioned so thatthey seem to be unlimited ant any time. The prevalent mod-els are pay per use or based on subscription. In the first case,resource usage is carefully measured at the appropriate leveland reported to the users.

Currently, all major vendors are providing many kind ofservices and the predominant model is pay-per-use [31].Process, practice, and mechanisms are now well established[15]. For example, there are well-known cloud schedulingalgorithms, platform and application, migration services, etc.[17]. However, there are still pending aspects to be solved incloud computing, being security, privacy, and confidentialityin clouds [22,33].

3 Cloud computing platforms

Clouds computing platforms are, in most cases, organized byresource providers in a cluster-like structure in order to facili-tate virtualization technologies. Usually, cloud platforms areprovided through medium or large scale data and comput-ing centers where all the systems have virtualization facili-ties installed [30] based on hypervisors such as Xen, Azure,and ESX. Virtualization is the heart of a cloud computingplatform, as the services are provided by using standardizedor tailored virtual machines to the different cloud computingsolutions presented in the previous section. The possibility ofproviding elastic computing and storage transparently to theupper layers [7] motivates researchers and companies, as theycan have low cost resources adapted to their requirements torun varying size experiments or to allow the company growwith the clients demand. However, harnessing virtualizationis not an straightforward work. Along several years, hypervi-sors have been optimized to avoid performance looses. Novelmiddle wares have been included to easily deploy both virtualmachines and applications, and new tools have been devel-oped to cope with the cloud increasing complexity [3,23].

One of the major attractions of cloud is the unlimited datastorage facilities it provides for the users. Currently, there aremany services such as Amazon Simple Storage Service (S3),simple database (SD), Google FS, etc, which offer a file sys-tems and databases virtualization layer [8]. Cloud Database-as-a-Service (DaaS) allows to host databases in the cloudenvironment and provides database features such as data def-inition, storage and retrieval, on a subscription basis over theInternet [11]. To provide elastic services and a tremendousstorage capacity, most providers have large data centers geo-graphically distributed (Google, as an example, has morethan one million systems). Thus, the data center architec-ture becomes extremely important and it must be solved ina holistic way, as compute environment is now multi-tenantand operating compute, storage and network independentlydoes not meet this paradigm [1]. Thus, cloud data centers

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must provide secure multi-tenancy, efficient virtual machineand data mobility, infrastructure scalability, including band-width and latency, and a unified service management. All thisfeatures must also take into account energy management andpower consumption optimizations [5,28], as energy is, andwill remain to be, one of the major costs of the service. Thus,a strong research and industrial effort is being deployed toachieve green data centers [14].

Cloud computing is also very attractive because, some-how, it allows to transfer the risk from the private installa-tions or smaller SaaS providers, to the larger cloud serviceproviders, who theoretically are better equipped to mitigatethe risks by providing fault-tolerance in clouds [6]. A goodexample is Amazon S3 storage service, which is being usedby many large enterprises for archiving all their historic datato avoid loosing it and because of its unlimited scalability.Map-reduce paradigm can be also used to improve resilienceby replicating services and processes through inexpensivenodes, paying only when the users need it.

From the point of view of their organization, cloud plat-forms can be public, community, private, and hybrid [20].Private clouds are deployed by a single organization for itsown service. It may be owned, managed, and operated bythe organization, a third party, or some combination of them.and it may exist on or off premises. Private clouds can beimplemented in the company premises or it could be out-sourced to a third party to have exclusive service. A com-munity cloud is aimed to share the cloud infrastructure by aspecific community of users that share a mission or concern.The service could be managed by a member of the commu-nity or outsourced to a third party. Public clouds are opento the use by the general public, that use them as a pay-per-use basis. The cloud infrastructure is owned, managed,and operated by a external organization, that may be a com-pany or a government organization, that hosts the infrastruc-ture in its premises. Finally, hybrid clouds are a compositionof two or more distinct and independent cloud infrastruc-tures that are bound together to enable data and applicationportability.

Given the scale and mobility required nowadays, hybridcloud platforms are becoming more and more complex[13,26]. Cloud federations [9] are starting to be commonto provide ultra-large scale systems, specially in scientificcomputing facilities. Interconnection facilities between twoor more independent clouds are provided for the purpose ofload balancing traffic, accommodating spikes in demand, orsaving energy. Cloud federation offers two substantial bene-fits to cloud providers. First by optimizing the usage of idle orunderutilized resources. Second, by expanding their scale toaccommodate spikes in demand or to provide larger scaleservices without further installations. However, providinginter-cloud operations (e.g., cloud bursting for load balanc-ing between clouds) [4], all aspect of cloud operation must

be shared and transparent to the users. However, there arestill many challenges to be solved to have complete inter-operability among clouds, such as cloud management archi-tecture, cloud auditing, cloud security, or cloud applicationdeployment. To overcome those challenges Distributed Man-agement Task Force (DMTF) and International Standardiza-tion Organization (ISO) are working to define open cloudstandards at several levels, as the Open Virtualization For-mat (OVF) and Open Cloud Computing Interface (OCCI) tofavor interoperability and to be cloud provider independent.The former effort are complemented with the multi-cloudsystems approach [21] that aims to facilitate the modeling,deployment, and configuration of complex applications inmultiple infrastructure clouds.

4 Special issue contents

This special issue contains three papers selected from a setof invited papers extracted from the papers presented in The10th IEEE International Symposium on Parallel and Dis-tributed Processing with Applications (ISPA 2012), held inMadrid, Spain, July 10–13, 2012 [18]. ISPA 2012 accepted32 papers out of 98 full paper submissions covering bothfoundational and practical issues in parallel and distributedprogramming and systems. The objective of ISPA 2012 wasto provide a forum for scientists and engineers in academiaand industry to exchange and discuss their experiences, newideas, research results, and applications about all aspects ofparallel and distributed computing and net working.This con-ference featured session presentations, workshops, tutorialsand keynote speeches. ISPA 2012 was sponsored by IEEETechnical Committee on Scalable Computing (TCSC) andIEEE Computer Society.

This special issue of the Cluster Computing Journalpresents the latest research and technology related to cloudcomputing, a recent trend in information technology that pro-vides computing and storage services remotely to the usersrelying on large computing centers. The articles that discusstools and applications for cloud computing. For this specialissue, we invited 12 selected papers from ISPA 2012 confer-ence to submit extended versions to Cluster Computing Jour-nal. All of them accepted and made paper submission to thejournal. All paper were peer to peer reviewed following thereview procedures on the Cluster Computing Journal. Fromthem only three were accepted after two rounds of reviews.

The papers selected addresses five cloud challenges men-tioned in the previous sections: reusable and portable appli-cations development, map-reduce energy aware scheduling,and workflow scheduling. A small introduction to the papersis shown below.

In Developing a model driven approach for engineer-ing applications based on mOSAIC: towards sharing elastic

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components in the cloud, the authors investigate the possi-bilities to introduce a Model Driven Architecture (MDA) forthe cloud computing domain, which would support composi-tion, customization, flexibility, maintenance and reusabilityof cloud application components in the particular case ofscientific and engineering applications.

To the paper MapReduce framework energy adaptationvia temperature awareness, the authors explore the possibil-ity of scheduling in a power-efficient manner without theneed for expensive power monitors on every node. Theydeveloped a MapReduce framework to evaluate the cur-rent status of each node and dynamically react to estimatedpower usage to shift power consumption work toward moreenergy efficient nodes which are currently consuming lesspower.

The paper HSGA: a hybrid heuristic algorithm for work-flow scheduling in cloud systems proposes a hybrid heuris-tic method (HSGA) to find a suitable scheduling for work-flow graph, based on genetic algorithm in order to obtain theresponse quickly moreover optimizes makespan, load bal-ancing on resources and speedup ratio.

In Trust-driven and QoS demand clustering analysis basedcloud workflow scheduling strategies the authors introduce atrust mechanism into cloud workflow scheduling process andpropose a novel trust-based customizable cloud workflowscheduling model. Trust mechanism ensures the executionsuccess rate of critical tasks and the introduction of two-level based scheduling mode reduces the problem scale ofworkflow scheduling.

Finally, the authors of Virtualizing high-end GPGPUs onARM clusters for the next generation of high performancecloud computing propose of a possible next generation ofcomputing clouds, characterized by a highly heterogeneousparallelism, a lower electric power demanding, less heat pro-ducing, and more environmental friendliness.

Acknowledgments We would like to thank all the authors, reviewersand editors involved in the elaboration of this special issue, includingalso the reviewers that were involved in the ISPA 2012 conference,where short versions of the papers were previously selected. We areespecially grateful to the editor in chief of the Cluster Computing Jour-nal, Prof. Salim Hariri, for approving this special issue and for his helpalong the process of its preparation.

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Jesus Carretero is full pro-fessor of Computer Architectureand Technology at the Universi-dad Carlos III de Madrid (Spain),where he is responsible for thatknowledge area since 2000. Heis also Director of the Masterin Administration and Manage-ment of Computer Systems, thathe founded in 2004. He serves asa Technology Advisor in severalcompanies. His major researchis in parallel and distributed sys-tems, real time systems and com-puting systems architecture. He

is Senior Member of IEEE. He has participated in many conferenceorganization committees, and in the last three years he has been GeneralChair of HPCC 2011 and MUE 2012, and Program Chair of EuroMPI2013 and ISPA 2012.

Javier Garcia Blas has beena teaching assistant of the Uni-versity Carlos III of Madridsince 2005. He has cooper-ated in several projects withresearchers from various highperformance research institu-tions including HLRS (funded byHPC-Europe program) DKRZ,and Argonne National Labora-tory. He is currently involvedin various projects on topicsincluding parallel I/O and paral-lel architectures. He received theMS degree in Computer Science

in 2007 at the University Carlos III of Madrid. He also received a PhDin Computer Science from University Carlos III in 2010.

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