Green Cloud Computing

Transcription

1 International Journal of Information and Computation Tehnology. ISSN Volume 4, Number 4 (2014), pp International Researh Publiations House irphouse.om /ijit.htm Green Cloud Computing Sindhu S. Pandya Laxmi Vidyapeeth, Sarigam, B-401, Krishna Park, Daulat Nagar, Chala, Vapi, Gujarat, India. Abstrat Green omputing is defined as the study and pratie of designing, manufaturing, using, and disposing of omputers, servers, and assoiated subsystems-suh as monitors, printers, storage devies, and networking and ommuniations systems-effiiently and effetively with minimal or no impat on the environment. The goal of green omputing is to redue the use of hazardous materials, maximize energy effiieny during the produt's lifetime, and promote the reylability of outdated produts and fatory waste. Green omputing an be ahieved by either Produt Longevity Resoure alloation or Virtualization or Power management. Power is the bottlenek of improving the system performane. Power onsumption is ausing serious problems beause of exessive heat. As iruit speed inreases, power onsumption grows. Data enters working with Cloud omputing model have many appliations that require on-demand resoure provisioning and alloation in response to time-varying workloads that are statially alloated based on peak load harateristis, in order to maintain isolation and provide performane guarantees without paying muh attention to energy onsumption. Cloud servie providers need to adopt measures to ensure that their profit margin is not dramatially redued due to high energy osts. There is also inreasing pressure from governments worldwide to redue arbon footprints, whih have a signifiant impat on limate hange. As energy osts are inreasing, while availability dwindles, there is a need to shift fous from optimizing data enter resoure management for pure performane alone to optimizing for energy effiieny while maintaining high servie level performane. In this researh paper I will fous on these poliies whih enable us to ut down data entre

2 4322 Sinndhu S. Pan ndya energy osts, thuss leading too a strong, ompetitive loud om mputing industryy. End userss will also benefit b from m the dereaased energy bills. Keywords: Cloudd Servie Providers, P Power onnsumption, Energy effiienny. 1. Introduttion Thee depletion of o fossil eneergy has beome one of o the majorr hallengess for mankin nd to susttain the ivvilization. Inn addition, overindulg gent energy onsumptiion auses over emiission of greeen-house gas, g whih, aording to o expert onnsensus, is a root ausee for the urrent gllobal warm ming. It is,, therefore,, vital for mankind to seek green g tehhnologies, i.e., tehnologies that an redue energy onnsumption. As Internett has penetrated into our daily liives, loud omputing has h emergedd as a new kkind of utiility thatt gets deliveered throughh wired or wireless neetworks. The inreasingg availabilitty of highh-speed Intternet and orporate IP onnetio ons is enabbling the ddelivery of new netw work-based servies booth to orpoorate and in ndividual ennd users geenerially aalled looud omputiing serviees. The loud omputing vider, servie moddel involvess the provission, by a seervie prov of large l pools of high peerformane omputing g resoures and high-apaity sto orage devies that arre shared among a end users as reequired. Too be suesssful, the loud servvie model also requirees a high-sppeed network to providde onnetiion between n the end user and thhe servie prrovider s inffrastruture. Cloud om mputing poteentially offeers an overaall finaniall benefit, inn that end users u maanaged pooll of storage and ompuuting resourres, rather than sharre a large, entrally ownning and managing m thheir own systems. s Clloud servie providerss invest in n the neeessary infraastruture annd managem ment system ms, and in return r reeivve a time-b based or usage-based u fee from ennd users. Ennergy onsu umption andd arbon em mission by Cloud C infrastrutures has beomee a key enviironmental onern. Clouud Computiing 1

3 Green Cloud Computing Cloud Computing Deployment Models Cloud omputing is a paradigm of offering on-demand servies to end-users. The Cloud deployments are lassified into three types: Publi Cloud, Private Cloud and Hybrid Cloud. 2.1 Publi Cloud A publi loud is hosted on the internet and designed to be used by any user with an internet onnetion to provide servies. The famous publi louds are Amazon Web Servies (AWS), Google AppEngine, and Mirosoft Azure. In this deployment, Cloud servies are made available to the publi in a pay-as-you-go-manner. A publi loud an offer any of the three kinds of servies: IaaS, PaaS and SaaS. For example, Amazon EC2 is a publi loud providing infrastruture as a servie, Google AppEngine is a publi Cloud providing an appliation development platform as a servie, and Salesfore.om is a publi loud providing Software as a Servie. The main harateristis of publi louds are its multitenany, quality of servie and seurity. 2.2 Private Cloud A Private loud is hosted within an enterprise, behind its firewall, and intended only to be used by that enterprise by investing and managing its own loud infrastruture, but gains benefits from pooling a smaller number of entrally maintained highperformane omputing and storage resoures instead of deploying large number of lower performane systems. The private loud servies offer greater ontrol over the infrastruture, improving seurity and servies resiliene beause its aess is restrited to one or few organizations. 2.3 Hybrid Cloud Hybrid Clouds is the deployment whih emerged due to diffusion of both publi and private louds advantages. In this model, organizations outsoure non-ritial information proessing to the publi loud, while keeping ritial servies and data in their ontrol. Three loud omputing servies are onsidered, inluding storage as a servie, proessing as a servie, and software as a servie. Storage as a servie allows users to store data in the loud. Proessing as a servie gives users the ability to outsoure seleted omputationally intensive tasks to the loud. Software as a servie ombines these two servies and allows users to outsoure all their omputing to the loud and use only a very-low-proessing-power terminal at home. 3. Cloud Servie Models 3.1 Software as a Servie Consumer software is purhased with a fixed upfront payment for a liense and a opy of the software on appropriate media. This software liense typially only permits the user to install the software on one omputer. When a major update is applied to the

4 434 Sindhu S. Pandya software and a new version is released, users are required to make a further payment to use the new version of the software. Users an ontinue to use an older version, but one a new version of software has been released, support for older versions is often signifiantly redued and updates are infrequent. Software developers are trying to provide Software as a Servie, lients are harged a monthly or yearly fee for aess to the latest version of software. The software is hosted in the loud and all omputation is performed in the loud. The lient s PC is only used to transmit ommands and reeive results. Typially, users are free to use any omputer onneted to the Internet. One example of software as a servie is Google Dos. In this senario, data storage and proessing is always performed in the loud and we are thus able to signifiantly redue the funtionality, and onsequently, the power onsumption, of the lient s PC. 3.2 Storage as a Servie In storage as a servie, users an outsoure their data storage requirements to the loud. All proessing is performed on the user s PC, whih may have only a solid state drive, and the user s primary data storage is in the loud. Files stored in the loud an be aessed from any omputer with an Internet onnetion at any time. For modifying any file it must first be downloaded, edited using the user s PC and then the modified file uploaded bak to the loud. One example of storage as a servie is the Amazon Simple Storage Servie. 3.3 Proessing as a Servie Proessing as a servie provides users with the resoures of a powerful server for speifi large omputational tasks whih are uploaded to the loud, proessed in the loud, and the results are returned to the user. The proessing servie an be aessed from any omputer onneted to the Internet. One example of proessing as a servie is the Amazon Elasti Compute Cloud servie. 4. Features of Clouds Enabling Green Computing Cloud Infrastruture has beome a key environmental onern keeping in view of energy onsumption and arbon emission. The key driver tehnology for energy effiient Clouds is Virtualization, proess of presenting a logial grouping or subset of omputing resoures so that they an be aessed in ways that give benefits over the original onfiguration. The following are the four key fators that have enabled the Cloud Computing to lower energy usage and arbon emissions from ICT. In this way, organizations an redue arbon emissions by at least 30% per user by moving their appliations to the loud. 4.1 Dynami Provisioning In traditional settings, IT ompanies end up deploying far more infrastruture than needed. It is very diffiult to predit the demand at a time and to guarantee availability

5 Green Cloud Computing 435 of servies and to maintain ertain level of servie quality to end users. The virtual mahines in a Cloud infrastruture an be live migrated to another host in ase user appliation requires more resoures. Cloud providers monitor and predit the demand and thus alloate resoures aording to demand. Those appliations that require less number of resoures an be onsolidated on the same server. Thus, dataenters always maintain the ative servers aording to urrent demand, whih results in low energy onsumption than the onservative approah of over-provisioning. 4.2 Multi-tenany Cloud omputing infrastruture redues overall energy usage and assoiated arbon emissions. The SaaS providers serve multiple ompanies on same infrastruture and software. This approah is obviously more energy effiient than multiple opies of software installed on different infrastruture, whih an minimize the need for extra infrastruture. The smaller flutuation in demand results in better predition and results in greater energy savings. 4.3 Server Utilization Using virtualization tehnologies, multiple appliations an be hosted and exeuted on the same server in isolation, thus lead to utilization levels up to 70%. Even though high utilization of servers results in more power onsumption, server running at higher utilization an proess more workload with similar power usage. 4.4 Dataentre Effiieny The power effiieny of dataenters has major impat on the total energy usage of Cloud omputing. By using the most energy effiient tehnologies, Cloud providers an signifiantly improve the Power Usage Effetiveness (PUE) of their dataenters. Cloud omputing allows servies to be moved between multiple dataenter whih are running with better PUE values. This is ahieved by using high speed network, virtualized servies and measurement, and monitoring and aounting of dataenter. 5. Green Cloud Arhiteture In the Green Cloud arhiteture, users submit their Cloud servie requests through a new middleware Green Broker that manages the seletion of the greenest Cloud provider to serve the user s request. A green request an be of three types i.e., software, platform or infrastruture. The Cloud providers an register their servies in the form of green offers to a publi diretory whih is aessed by Green Broker. The green offers onsist of green servies, priing and time when it should be aessed for least arbon emission. Green Broker gets the urrent status of energy parameters for using various Cloud servies from Carbon Emission Diretory. The Carbon Emission Diretory maintains all the data related to energy effiieny of Cloud servie. This data may inlude PUE and ooling effiieny of Cloud dataenter whih is providing the servie, the network ost and arbon emission rate of eletriity, Green Broker alulates the arbon emission of all the Cloud providers who are offering the requested Cloud servie. Then, it selets the set of servies that will result in least arbon emission and buy these servies on behalf users.

6 436 Sindhu S. Pandya The Green Cloud framework is designed to make their servie lean by keeping trak of overall energy usage of serving a user request. It relies on two main omponents, Carbon Emission Diretory and Green Cloud offers. A user an use Cloud to aess any of these three types of servies (SaaS, PaaS, and IaaS), and therefore proess of serving them should also be energy effiient. In other words, from the Cloud provider side, eah Cloud layer needs to be Green onsious. SaaS Level: Sine SaaS providers mainly offer software installed on their own dataenters or resoures from IaaS providers, the SaaS providers need to model and measure energy effiieny of their software design, implementation, and deployment. For serving users, the SaaS provider hooses the dataenters whih are not only energy effiient but also near to users. PaaS level: PaaS providers offer in general the platform servies for appliation development. The platform failitates the development of appliations whih ensures system wide energy effiieny. Platforms itself an be designed to have various ode level optimizations whih an ooperate with underlying omplier in energy effiient exeution of appliations. IaaS level: Providers in this layer plays most ruial role in the suess of whole Green Arhiteture. They use latest tehnologies for IT and ooling systems to have most energy effiient infrastruture. By using virtualization and onsolidation, the energy onsumption is further redued by swithing-off unutilized server. Various energy meters and sensors are installed to alulate the urrent energy effiieny of eah IaaS providers and their sites. This information is advertised regularly by Cloud providers in Carbon Emission Diretory. The Cloud provider designs various green offers and priing shemes for providing inentive to users to use their servies during off-peak or maximum energy-effiieny hours. 6. Conlusion The management of power onsumption in data entres has led to a number of substantial improvements in energy effiieny. Cloud omputing infrastruture is housed in data entres and has benefited signifiantly from these advanes. Tehniques suh as sleep sheduling and virtualization of omputing resoures in loud omputing data entres improve the energy effiieny of loud omputing. Referenes [1] Open Cloud Manifesto [2] P. Mell and T. Grane, Draft NIST Working Definition of Cloud omputing [3] Google Dos. [4] Amazon Web Servies. [5] Salesfore.om [6] Buyya, R., Yeo, C.S. and Venugopal, S Market-oriented Cloud omputing: Vision, hype, and reality for delivering it servies as omputing utilities. Proeedings of the 10th IEEE International Conferene on High Performane Computing and Communiations, Los Alamitos, CA, USA. [7] Greenpeae International Make IT Green international/en/publiations/reports/make-it-green-cloudomputing/ [8] Mell, P. and Grane, T The NIST Definition of Cloud omputing, National Institute of Standards and Tehnology.