Future Generation Computer Systems 28 (2012) 85–93

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Future Generation Computer Systems

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

Virtual machine provisioning through satellite communications in federatedCloud environmentsAntonio Celesti ∗, Maria Fazio, Massimo Villari, Antonio PuliafitoDepartment of Mathematics, Faculty of Engineering, University of Messina, Contrada di Dio, S. Agata, 98166, Messina, Italy

a r t i c l e i n f o

Article history:Received 17 February 2011Received in revised form11 May 2011Accepted 28 May 2011Available online 12 June 2011

Keywords:Cloud computingFederationSatellite communicationsService deliveryDistributed Cloud service

a b s t r a c t

Cloud federation offers plenty of new services and business opportunities. However, many advancedservices cannot be implemented in the real Cloud market due to several issues that have not beenovercome yet. One of these concerns is the transfer of huge amount of data among federated Clouds. Thispaper aims to overcome such a limitation proposing an approach based on satellite communications. Bycomparing performance in data delivery on the Internet and satellite systems, it is evident that satellitetechnologies are enough ripe to be competitive against systems with a wired infrastructure. Thus, wepropose tomake use of satellite transmission to implement fast delivery of huge amount of data. Throughthe discussion of a use case, where a WEB TV company offers a streaming service, we show how topractically apply the proposed strategy in a real scenario, specifying the involvement of Cloud providers,Cloud users, satellite companies and end-user clients.

© 2011 Elsevier B.V. All rights reserved.

1. Introduction

Cloud computing offers new business opportunities for bothservice providers and their clients (e.g. organizations, enterprises,and end users), by means of an architecture for deliveringInfrastructure as a Service (IaaS), Platform as a Service (PaaS) andSoftware as a Service (SaaS). A Cloud encloses the IaaS, PaaS, and/orSaaS inside its own virtualization infrastructure, in order to carryout an abstraction from its underlying physical assets. Typically,the virtualization of a service implies the aggregation of severalproprietary processes collected in a virtual environment, calledVirtual Machine (VM) [1].

Often, Clouds are also spread over distributed virtualizationinfrastructure covering larger geographical areas (for example, letus think about RESERVOIR (an European project facing the CloudComputing IaaS topic [2]), Amazon [3], and Azure [4]). In addition,the perspective of Cloud federation [5,6], where Cloud providersuse virtualization infrastructures of other federated Clouds, openstoward new scenarios in which more and more types of newservices can be supplied. In fact, Clouds exploiting distributedvirtualization infrastructures are able to provide new types of‘‘Distributed IaaS, PaaS, and SaaS’’.

However, the potential growth of Cloud environments interms of the extension of the covered geographical area, business

∗ Corresponding author.E-mail addresses: acelesti@unime.it (A. Celesti), mfazio@unime.it (M. Fazio),

mvillari@unime.it (M. Villari), apuliafito@unime.it (A. Puliafito).

0167-739X/$ – see front matter© 2011 Elsevier B.V. All rights reserved.doi:10.1016/j.future.2011.05.021

opportunities, and types of services can be delayed by the limitsof the communication infrastructure, which is provided by theInternet. Therefore, in Cloud infrastructures distributed over aWide Area Network (WAN), the provisioning and deployment ofservices raise several issues due to the latency of the Internet. Forexample, provisioning implies the displacement of several VMscomposing a distributed Cloud service, from the Cloud that receivethe service allocation request to the other federated Clouds, wherethe service must be deployed.

Since we believe in Cloud computing as the future serviceprovisioning model, we propose a new strategy to improvethe quality of service provisioning, based on the employmentof satellite technologies for long range and fast data delivery.Satellite systems are becoming very popular for high-speed datatransmission [7]. As confirmed by the effort devoted from manybusiness companies to propose ADSL Broadband Services andtheir investments to launch new satellites into orbit. In ourstrategy, satellite links can be used to implement fast delivery ofhuge amount of data, by using opportunistic burst transmission,such as SMS transmission in cellular networks. In fact, satellitesystems are the best way for broadcasting media content, withoutadditional costs for cabling and regardless geographical positionof transmitters and receivers. In comparison with wired networks,satellite systems allow to performmulti-casting in a very easyway,providing a high improvement in throughput while reducing theeffective load on nodes in the network.

In this paper, we analyze the potentiality of federated Cloudarchitectures [2] focusing on distributed Cloud services andunderlying which new market perspective they can open. We

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discuss the limits of the provisioning of distributed Cloudservices using the Internet, proposing an alternative and moreefficient Cloud service provisioning strategy based on satellitecommunications. In order, to highlight the advantages of such anew scenario, we consider the use case of a WEB TV company,which uses a distributed IaaS in a Cloud federation exploiting thesatellite service.

The paper is organized as follows. Section 2 provides anoverview regarding the delivery of VMs in federated Cloud envi-ronments. In Section 3, we introduce the new idea of distributedCloud services available in federated Cloud environments high-lighting the limits of the delivery due to the Internet infrastructure.Then, we focus on the use case of a WEB TV company perform-ing live streaming, which uses a distributed IaaS. In Section 4, wegive a brief overview of the modern satellite systems and presentsa comparison between performances of satellite and wired linksin terms of coverage and data rate. Then, in Section 5, we discussa new approach to deliver services in federated Clouds based onsatellite communications. In Section 6, we show how satellite sys-tems are useful with reference to the use case of a WEB TV com-pany. Conclusion and highlights to future works are presented inSection 7.

2. Related works and background

Over the years, there has been an ever increasing request ofservices provisioned through the Internet. The client/server modelwas the first adopted way for the delivery of multimedia contents.But with the growth of both network complexity and number ofclients, this model has demonstrated several weaknesses. Thusin the 90s, with Napster, OpenNAP and IRC serving channelsappeared the first peer-to-peer (P2P) file sharing systems, whereeach peer was able to supply and consume resources in contrastwith the traditional client/server model. At the same time, inorder to both reduce the exchanged traffic of P2P networks andenhance the Quality of Service (QoS), the NEXUS InternationalBroadcasting Association developed the first Content DeliveryNetwork (CDN). A CDN is a system of computers containingcopies of data (e.g., media files, softwares, documents, etc.),placed in several sites in a network in order to maximize thebandwidth utilization. A CDN using protocols just like InternetContent Adaptation Protocol (ICAP) and Open Pluggable EdgeServices (OPES) can use several algorithms (e.g., Global ServerLoad Balancing, DNS-based request routing, Dynamic metafilegeneration, HTML rewriting, and anycasting) in order to enhancethe network throughput. Examples of free and commercial CDNsinclude Coral Content Distribution Network, FreeCast, PeerCast,Akamai, Bitgravity and CacheFly. Nowadays Cloud computingbrings new scenarios of content delivery especially in federatedenvironments. Considering Cloud federation, new terms such asInterCloud [8] or Cross-Cloud [9] are becoming very debated in thescientific community. As discussed in [5], Cloud federation bringsmany business advantages for the enhancement of providers’profit. In fact it has been proposed as a new paradigm allowingproviders to avoid the limitation of owning only a restrictedamount of resources. In [10], highlighting the limits of several opensource Cloud platforms, a three-phase model is proposed for theestablishment of a federation among different Cloud architectures,where Clouds are able to use the virtualization infrastructure ofother federated Clouds in order to increase their computationaland storage capabilities. Cloud federation raises several issues andone of these is represented by the delivery of large amount ofdata over a WAN. However, on this topic, there have not beenmany available related works yet. Regarding the provisioning anddelivery of VMs among federated Clouds, a relocatable storageaccessmechanismcapable of rapidly relocatingVMs,with a limited

impact on I/O performance of the migrant VMs, is presented in[11,12]. Instead amodel able to reduce the cost of theVMmigrationby means of a disk image composition technique is presentedin [13]. In particular, the authors demonstrate how their approachis valid for scenarios composed of hundreds of federated Clouds.As discussed in Section 3.1, we think that in a federated Cloudenvironment, with a high level of flexibility, approaches based onP2P, CDNs, or relocatable access storage over the Internet are notsuitable. Therefore, in our opinion we need alternatives and morepowerful approaches for the composition, delivery and upgrade ofCloud services.

3. Distributed Cloud service provisioning in federated Cloudenvironments

Cloud providers rely their computational capabilities on theconcept of ‘‘virtualization’’. Virtualization technologies aim tohide the underlying infrastructure by introducing a logical layerbetween the physical infrastructure itself and the computationalprocesses. Through Virtualization Machine Monitors (e.g., [14],KVM [15], VMware [16]), commonly known as ‘‘hypervisors’’,each Cloud is able to control and emulate several processingenvironments (i.e. VMs), each running its own ‘‘guest’’ software,typically an operating system. Commonly, a Cloud uses itsown virtualization infrastructure (i.e., a set of servers runninghypervisors) to instantiate and aggregate one or more VMsand, thus, deliver to its clients IaaS, PaaS, and/or SaaS. Fig. 1depicts an example of IaaS composed of 5 VMs hosted withina Cloud virtualization infrastructure composed of 16 servers. Inour opinion, according to the size of the Clouds’ virtualizationinfrastructure we can distinguish between small, medium, andlarge Clouds. Small and medium Clouds are held by small andmedium size companies, instead large Clouds are held by large sizecompanies (e.g., Amazon Europe or RESERVOIR). The latter are ableto provide new types of Cloud services named ‘‘Distributed IaaS,PaaS, and SaaS’’ (generalizing ‘‘D*aaS’’). With D*aaS, we indicate‘‘a distributed Cloud service composed of a set of VMs spread overa wide geographical area, orchestrated in order to achieve a targetpurpose, and which is provided on demand to a client to meethis business needs’’. Also to give an opportunity to both smalland medium Clouds to offer D*aaS, a federation of Clouds canbe constituted. In a federation, small and medium Clouds canenlarge their virtualization capabilities using the virtualizationinfrastructures of other federated Clouds (small, medium, or large)for a given business purpose, becoming as competitive as largeClouds. This business model permits on one hand to elasticallyincrease the virtualization capabilities of Clouds and, on theother hand to enable Clouds to rent their computational andstorage capabilities when their virtualization infrastructures arepartially or totally unused. A Cloud might choose to establish afederation relationship with other Clouds for many reasons. Forexample: (1) it needs extra resources because the capabilities ofits virtualization infrastructure are run out; (2) it needs to havesome resources placed in a given geographical location; (3) itwantsto save money reducing the electricity consumption allocatingservices in other Clouds and so on. Fig. 2 depicts an exampleof Cloud federation where Cloud D provides a DIaaS to a client,which uses the VMs hosted in other federated. Federated Cloudscover wide geographical areas, so allowing D*aaS for massivedistribution.

The deployment of VMs inside the federation can be performedin two possible ways, which are as follows.

• One-timedeployment: it is characterized by an a priory arrange-ment of resources. If the allocation of VMs does not match realneeds of service users, resources can remain underused or eventotally unused.

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Fig. 1. Example of IaaS provided to a client.

• Real-time deployment: it works without an a priori arrange-ment of resources, since the VMs are allocated on demandwhenever the service requires much more capabilities.

To improve the quality of Cloud services, mirror sites are man-aged according to resource availability, load balancing policies,commercial agreements and geographical location of end users.

In the rest of the paper, we will focus on a Cloud federationscenario because we think it might represent a new profitablebusiness model for enterprises.

3.1. Issues in provisioning of distributed Cloud services

The major problem of such a futuristic perspective is repre-sented by the movement of huge amount of data over the Inter-net. In fact, the delivery of both ‘‘one-time’’ and ‘‘real-time’’ DIaaSraises different issues due to the cost of the transmission over theInternet of VMs for the deployment of them in different federatedClouds. This statement is motivated by the fact that each VM mayhave a size of hundreds of gigabytes. An example of such a case

is given by the Cloud use case of RESERVOIR: the eBusiness casestudy [2]. The IT company SAP, one of the world leaders in col-laborative business software, has evidenced the necessity to de-ploy all their business application stack in several VMs. The resultswere the creation of VMs of roughly 120 GBs each. The delivery ofsuch VMs, especially for ‘‘real-time’’ services, implies simultane-ous transfers of VMs within different virtualization infrastructuresplaced in different geographical locations, and this is a very hardtask over traditional Internet links due to their latency. Moreover,thinking about a dynamic scenario including hundreds of federatedClouds where VMs are allocated or migrated from a Cloud to an-other, it is needed to face the costs due to bandwidth consumptionand the workload due to transmissions among Clouds.

Moreover, considering both ‘‘one-time’’ and ‘‘real-time’’ DIaaS,further issues can be also caused by upgrading tasks on the VMsmaking up the DIaaS. For such reasons we think that it is neededto adopt an alternative approach for the provisioning of D*aaS(s)in federated Cloud computing environments.

3.2. The WEB TV use case

In order to better clarify the concept of distributed Cloudservice (D*aaS), we deal with the use case of a WEB TV companybroadcasting live sport events, which wants to offer its streamingservice in perspective of a big football match. For simplicity, weassume that the market of the WEB TV company is Europe. Aclient–server approach is out of place, as the server can become abottleneck for the service itself. Thus the WEB TV company needsto have a copy of its servers in several European cities in order toserve the local audiencewith goodQoS during thematch. The usualapproach tomanagemirroring of servers in Internet is to use eithera P2P or a CDN system,which replicate the service and improve thescalability of the system. However, mirroring means allocation ofresources with high costs of deployment, since it uses best-effortInternet links. Moreover, in order to accommodate possible peaksof workload, mirroring represents a ‘‘one-time’’ service whichimplies an a priori reservation of resources. The biggest drawbackof CDNs is that resources can be reserved for a long time eventhough they remain underused or even totally unused. The delivery

Fig. 2. Example of distributed IaaS provided to a client in a federated Cloud environment.

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of mirroring services as Cloud-based DIaaS allows to overcome allthese limits. For example, if the WEB TV requires the mirroringDIaaS temporarily (just for the sunday evening football match) andsuddenly (when it realizes that it cannot satisfy all the requests ofits clients) it is not possible to utilize neither a peer-to-peer (P2P)nor a CDN approach for the VMs’ delivery due to the cost in datatransmission. In fact, as it is not possible for an apriori provisioning,the VMs should be transmitted simultaneously in a very shorttime in different geographical locations and this is not possibleconsidering the latency of the current Internet infrastructure.

In our use case, the WEB TV company, acting as Cloud client,sends to a Cloud provider a DIaaS request instantiation, uploadingor remotely composing a template of the VM representing its webserver. The required DIaaS consists of VMs, acting as servers of theWEB TV and hosted in the Cloud sites. Several copies of the sameVM (acting as proxies) are hosted in federated Clouds.

Basically, the WEB TV company can require from the Cloudprovider two types of DIaaS: ‘‘one-time’’ or ‘‘real-time’’. In thefirst case, if the WEB TV company expects a possible peaks ofrequests, it can use the DIaaS to create new mirrors of its serverin different geographical locations or where the peaks of requestsare expected. In the second case, when a peak of request for thestream occurs, the Cloud instantaneously adapts the DIaaS of theWEB TV client, by creating one or more mirrors in the interestedgeographical locations.

When a client accesses to theWEB TV site, according to both theinstantaneous workload of the server and information regardingthe geographical location of the client, the DIaaS performs a sort ofproxy service, redirecting theWEB TV’s client request to themirrorcloser to him.

4. Satellite system for Cloud service provisioning

In this section, we provide a brief overview on satellitetechnologies and analyze their possible impact in federated Cloudenvironments, with particular reference to D*aaS provisioning.

4.1. Overview of satellite systems

Satellites are radio repeaters located at different altitudesout of the Earth atmosphere. Among the basic types of satellitesystems, there is the geostationary (GEO) one (geosynchronousorbit [17]), which is commonly used for monitoring severe localevents (e.g., storms and tropical cyclones), for video contentdistribution, and for high-speed data transmission. Each GEOsatellite is stationary over one spot above the equator. Theirposition can be approximated to a circle with a ray of 42168 km(from the Earth center), coplanar with the Earth equatorial circle(6378 km from the Earth center), distant 35786 km from the Earthground level. GEO satellites are in synchronized motion with theEarth angular velocity; that is, the relative angular velocity of thesatellite respect to the Earth rotation is equal to zero.

The principal advantage of this type of satellite is that atEarth’s ground level, directional antenna can be aimed and thenleft in position without further adjustment. Also, because highlydirectional antennas can be used, interference from surface-basedsources, and from other satellites, is minimized.

According to the specific features of wireless communications,satellite transmissions are broadcast. It means that all the placesunder the satellite footprint receive the signal it sends. So atransmission over a satellite link implements a multi-castingservice. GEO satellite transmitters have an area of coverage, Fig. 3highlights an example of a satellite footprint. The spot in thepicture is an example of a geostationary satellite (named H1)belonging to ASTRA (European satellite provider), positioned withan angle of 19.2° East respect to Earth Terrestrial Meridian 0°

Fig. 3. Example of satellite footprint covering the Europe: ASTRA 1 H (source:Lyngsat [18]).

Table 1HotBird: number of satellite transponders operating in Ku band, during the past20 years.

1990 1996 2002 200826 32 40 64

(GreenwichMeridian: GM), able to cover a great area in the Europe.

The usage of the radio spectrum is strictly regulated by interna-tional laws and, today, the available frequency bands are:

• P band (0.2–1 GHz)• C band (4–8 GHz)• Ku band(10–18 GHz)• Ka band (18–31 GHz).

Each band can be partitioned in several radio channels (calledtransponders), characterized by different frequency carriers. Thecapability to send a high amount of digital data is related to boththe number of transponders on board of a satellite and the databit-rate of each transponder. It explainswhy several companies areenforcing to increase the number of transponders for their satellitesystems. As example, we show in Table 1 the increase throughthe last years of transponders of HotBird1, the European satelliteconstellation of Eutelsat [19], positioned at an angle of 13° Eastwith respect to GM.

Currently, satellite providers have the core business in videocontent delivery SD-mpeg2 (Standard Definition) and HD-mpeg4(High Definition), but they see a slow shifting of their businessesalso toward the Internet. An example is given by the direct Internetaccess with satellite links in bidirectional (upload/download)communication (see [20]). However, its massive deployment hasrepresented a big challenge yet. In fact, end users need to burdenpart of the costs; this can occur all the time the end user hasdifficulty to gain the Internet access as in the rural areas, wherea wired infrastructure cannot guarantee the coverage [21]. Forthese particular scenarios, wireless technologies can be applied toprovide network access. In particular, the WiMax technology hasbeen designed to this purpose. Also, Cellular radio technology is apromising answer to overcome this problem, at the beginningwithUMTS, then with HSDPA, and recently with LTE. However, suchwireless technologies imply additional costs due to the installationof access points and hot-spots. In contrast, satellite systemsguarantee high-bit-rate transmission and ubiquitous coveragewithout any cost or effort [22,23].

1 In 1990, transmissions of transponders were analogic.

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Fig. 4. Measurement of the throughput over the Internet.

Another interesting solution has been enforced by Cisco, thatis Internet Routing In Space (IRIS) [24]. Through IRIS, Cisco istransforming space-based communications by allowing satellitesto become part of the converged IP network and enabling NextGeneration Global Services. Furthermore, thanks to IRIS, Ciscowill extend the information transport power of the Internet intospace, integrating satellite systems and ground infrastructure forcommercial and government users who need anytime, anywhereIP-based data, video, voice and mobile communications.

4.2. Wired vs. satellite communications

To prove the efficiency of satellite communications over theInternet, we have carried out a set of experiments in order tomeasure performance of data delivery services on Internet. In thispaper, we refer to geostationary satellites with limited coveragearea, such as ASTRA 1 in Fig. 3. To compare satellite capabilitieswith the Internet ones, we have limited our analysis to a portion ofthe Internet, which involves just sites inside the European area.

In our experiments, we have selected 30 servers around theEurope, mirrors of the Debian linux distribution. From each ofthem, we have downloaded the ISO image of Debian for DVD, afile of 4.4 GB, by using both the HTTP and the FTP protocols. Wehave observed the throughput for the file download over a week.Then, we have calculated the throughput on average to provide ameasurement of the speed in contents delivery on the Internet.In Fig. 4, we show the results on the daily throughput, in orderto know how the performance of the network changes during aday. In particular, we provide the maximum, minimum and meanthroughput measured in intervals of three hours. As expected, themean throughput changes a lot at different times, due to the highload of servers and communication links in theworking hours. Thiseffect is confirmed by the degradation of themaximum throughputevaluated in the period [9–12]. From the experiments, we notethat, in the best case, a client can benefit at most of 11 Mbps ofcommunication throughput to access a server in the Internet.

To analyze satellite system performance, we have been refer-ring to the trend of the downloading bit-rate estimated by [18,19]since the past 15 years to the next 20, shown in Fig. 5.

The Y axis is expressed in Mbps in logarithmic scale, whilethe X axis reports years interval with a constant gap of 5 years.The curve is related to the digital satellite transmission which hasbeen occurring in Europe since 1995/1997. The figure shows ascurrently the system is able to deliver up to 100 Mbps for eachtransponder. As reported in ‘‘King of Sat’’ satellite web portal [25],the main European satellite HD-TV distributors (i.e., SKY Italy,SKY UK, Premier DE etc.) can deliver through each transponder4–10 HD-TV flows (digital channels) that roughly range from 20 to10 Mbps. In the near feature the estimation is to deliver roughly10 Gbps [24], up to 120 Gbps in 2015 [20,26]. For a long termestimation, satellite links should deliver 5 Tera-bps (Tbps) [27].

Fig. 5. Digital data delivery of a satellite link (transponder) in downloading mode;currently in Ku band, and for the near future in Ka band.

Even if results in Fig. 5 represent just an estimation of futurebandwidth and cannot give guarantees on the real next data rateof satellite transponders, they allow to highlight how satellitecommunications are becoming an outstanding technology forhigh-speed communications. In particular, comparing the resultsshown in Figs. 4 and 5, we draw the surprising conclusion, thatsatellite technologies are enough ripe to be competitive againstsystems with wired infrastructure. Current satellite throughputsare much higher than the throughput estimated for data deliveryin the Internet and the gap between wired and satellite capacitiesis expected to increase in the next future.

All the considerations we have discussed with reference tothe European scenario can be extended to any other geographicalarea around the world. Also, three satellites in geostationary orbitseparated by 120° cover most of the entire earth, excluding onlythe areas near the north and south poles. Considering as referencethe speed of light about 300 000 km/s, the delay in sending a signalfrom a point on the equator to a satellite at 35786 km from theEarth ground level and 35786 km back is (2× 35 786)/300 000 =

0.24 s. So, we can provide worldwide satellite coverage seamlesslyat least through three-hop connections increasing the delay in datadelivery of about 1 min.

In summary, satellite communications can bring advantages inhigh-speed data transmission for at least two reasons: (1) satellitelinks guarantees high throughput and (2) the satellite coverageallows a communication service anywhere and everywhere. Thedeployment of satellite links in Internet may highly increase thequality of communication services, avoiding bottlenecks in theroutes for the data delivery. All these considerations justify therecent effort of many companies in providing Internet servicesthrough satellite communications, such as Cisco [24].

5. Enhancement of Cloud service provisioning through satellitetechnologies

From the point of view of providers of Cloud computingservices, increasing performance in data transmission may bevery strategic. As explained in Section 3.1, the displacement ofVMs in federated datacenters can suffer from bottlenecks in thecommunication infrastructure. Often, VMs are characterized by asignificant size in terms of GBs. In particular, let us consider thecase of SAP in the RESERVOIR project, which has shown the needsto deploy VMs of 120 GBs. It is reasonable that a lot of IT operatorsshould fall in a similar situation. In fact, considering an optimisticdata rate of 11 Mbps through the Internet, according to the results

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in Fig. 4, the delivery of 120 GBs takes (120 ∗ 8 ∗ 210)/11 =

89.367 s ∼= 24h. Additionally, a strong limitation arises if data haveto be deployed over several datacenters. For example, if SAPwishesto adopt a replication policy to increase fault tolerance or to reducethe failures’ probability deploying applications in 20 differentdatacenters spread around Europe, it needs a file transfer roughlyof 240 TBs among the datacenters. In this scenario, an efficientsolution is offered by satellite operators, which can provide theirinfrastructure and services to increase the delivery speed. Byconsidering a realistic data rate for satellite communications of1 Gbps against the estimation of future bandwidth in Fig. 5, thedelivery of 120 GBs takes (120 ∗ 8)/1 = 960 s ∼= 17 min. Also,due to the broadcast nature of wireless communications, this timeis independent from the number of datacenters involved in thedeployment of data. This example shows the valuable benefit inthe employment of satellite communications in Cloud systems.

According to the above example,we assumeanewbusiness sce-nario where different entities need to mutually provide efficient,distributed and on-demand services. These entities are as follows.

• Satellite operators (e.g., Eutelsat, ASTRA, etc.), which offera plethora of different business opportunities direct to newservices for Internet.

• Cloud providers (e.g., Amazon, Google, etc.), which invest insatellite technologies in order to improve the quality of theirdistributed services.

• Cloud clients (e.g., SAP, Oracle, CNN, Telecom, etc.), IT compa-nies that lean on Cloud providers to design new business ser-vices to meet requirements of private clients.

• End-user clients (private clients or business companies), whichmake use of services offered by Cloud clients (that are ITcompanies), but are unaware on advanced technologies behindthe services themselves.

A Cloud provider comes to an agreement with a satelliteoperator to make use of satellite links on demand. Terms of thisagreement will be discussed in the next paragraph. Also, theCloud provider fulfill requests of Cloud clients according to severalSLA. Different SLA can include on-time data delivery, real-timedata delivery, or both, according to the allocation of resourcesdiscussed in Section 3. For example, if a Cloud client needs todeploy a VM of 1 GB to provide a new service to end-user clients, itcontacts the Cloud provider. The deployment of the VM throughsatellite links with 1 Gbps of bandwidth allows the delivery ofthe VM in just 8 s against about 12 min if wired links are used.The Cloud client can ask for a one-time service, if it is ableto plan the necessary amount of resources it needs inside theCloud environment. It implies that the Cloud provider will reserveresources to the Cloud client regardless of the client application.If the Cloud client asks for a real-time service, the allocation ofresources in the Cloud infrastructure depends on the evolutionof the application of the Cloud user. Resource can be efficientlymanaged to providemirroring, increase fault tolerance or to reducethe failures’ probability of the application itself. Considering theabove example on the deployment of a VM of 1 GB, 8 s is anacceptable delay for the reorganization of resources over a largefederated Cloud infrastructure in comparison with the benefit thatresources are not wasted if they are not necessary.

5.1. New satellite policies for Cloud providers

The incoming satellite technology in Cloud environmentsimplies the necessity to define new Business models for satelliteproviders, in order to fix costs for the proposed services. Satelliteoperators should introduce new charge models, based on bursttransmissions. To better understand our idea, we can considertelecom operators. They provide the SMS service besides the

voice, to offer an asynchronous transmission of bursts of data.From the point of view of telecom operators, costs to deliverSMSs are negligible, since resources are engaged for short periodsof time according to the operator needs. VMs deployment oversatellite links in Clouds shouldwork like SMS in telecomnetworks:asynchronous transfers of bursts of data. Costs for such a servicefor satellite operators should be very low, but nowadays satelliteoperators do not offer such a service. We believe that the proposedCloud scenario might be seen as a suggestion for new businessmodels aimed at satellite operators, who are trying to differentiatetheir revenues. From this point of view, the new satelliteagreements will be far away from typical ADSL/HDSL agreementsand differences between uplink or downlink communications losemeaning, like for SMS against Internet access through cellulardevices.

Another very important point that have to be addressed to usesatellite communications in the Cloud is data security and privacy.Due to the broadcast nature of satellite links, every antenna ina geographical area covered by a satellite spot signal is ableto receive and store data. However, satellite technologies anddata provisioning in Cloud computing are mature enough face upsecurity problems. In our proposal, we can consider three differentsolutions that strongly ensure data privacy of customers, that areas follows.

1. Native satellite security (conditioned access allowed by satel-lite equipments). A conditional access module (CAM) is anelectronic device which equips satellite boxes and is used fordirect-broadcast satellite (DBS) services. It provides the hard-ware facility to view conditional access contents that have beenencrypted using a conditional access system. Also, it accom-plishes a different communication model, that is the Multicast.In the Multicast case, a subset of digital satellite receivers areable to get contents. In our scenario, only receivers of feder-ated Clouds could be able to download the transferred VMs and,hence they need to be equipped by CAMs to gain the access dataover satellite communications.The model we are talking about is equivalent to TV Channelssatellite distribution (i.e., SKY satellite operator may representan example). In that case end users are able to see encryptedmovies, thanks to their contract subscription accomplishedthrough smart cards. Each satellite receiver (often defined SetTop Box) has a CA Module (CAM) where to insert the customersmart card and enabling the TV vision. The communicationamong satellite and STBs occurs in a full security way, usingconsolidated encryption systems. The satellite provider caneasily enable or disable any specific customer even in real-time.In particular, the satellite operator can modify the type of endusers subscription changing their access with a high level ofgranularity.Let us focus on our use case, datacenters having to receivethe VMs through the satellite links are totally unaware of theencryption technology used during the communication. Theyneed a low cost CAM and a smart card. Hereby there is the listof some encryption systems for which CAMs are available in themarket:Logiways, Nagravision, Viaccess, Mediaguard, Irdeto, KeyFly, Veri-matrix, Cryptoworks, Mascom, Diablo CAM, Conax. CAM vendorsare constantly changing and improving their version in orderto prevent any fraudulent access to the medium. Finally, it isimportant to underline that these solutions can leverage theIn House Technology of satellite providers. Their systems are al-ready enabled formanaging this type of secure communication.

2. Cloud-based security (symmetric keys distribution through out-band communication). In thiswork, our concept of Cloud Feder-ation is based on the opportunity to use amiddleware, installedin each Cloud client (i.e., a federated datacenter) able to interact

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Fig. 6. Security solutions necessary for guaranteeing data privacy during VMs delivery in satellite broadcast communications.

each others for providing distributed Cloud features. The mid-dleware is also able to setup secure communication channelsamong parties. All the times a Cloud client has to download newVMs for allowing new services, it needs to receive the symmet-ric keymanaged by the Cloud operator asking new computationcapabilities. It is clear enough that the Internet is the network inwhich Cloud can offer these capabilities. For enforcing the secu-rity in our system, we use Internet connection even as an out-band channel for spreading symmetric keys. These symmetrickeys (i.e., AES, BlowFish, etc.) are used for efficiently encryptingthe VMs. Encrypted VMs can be sent on satellite links avoid-ing any security breach. Only the enabled datacenters have theopportunity to decrypt VMs using keys achieved through theout-band channel.

3. Security with hybrid approach (using the above solutions to-gether). It is a combination of the previous solutions.Whenevera Cloud operator asks for new capabilities, it interacts with thesatellite provider giving it the list of enabled customers (iden-tified by the CAM and smart card). Then it upload encryptedVMs to satellite, which broadcast data in its spot. Only the en-abled receivers can get that data, but only some of them, whohas achieved the decryption key can really execute the VMs. Inthis case, a double level of security is guaranteed. In our pointof view, the Cloud paradigm is opening new concrete marketsin many directions, even in the satellite one.

Fig. 6 shows an example of how both ‘‘native satellite security’’(solution 1) and ‘‘Cloud-based security’’ (solution 2) work. In thecase of native satellite security, Cloud provider A deploys VMs inCloud provider C by means of satellite communication withoutany encryption. In this case, the Cloud provider A simply makesan agreement with satellite operator selecting the ConditionedAccess Module (CAM) to use for the transmission. In the case ofCloud-based security, Cloud A deploys VMs in Cloud provider Bby means of satellite communication using symmetric encryption.All the times the Cloud Provider A needs to deploy VMs throughthe satellite link, it encrypts data before sending them over thesatellite. In this use case, symmetric keys are provided through an‘‘out of band channel’’ over the Internet. Therefore, data will bedecrypted in Cloud provider B using the proper symmetric key.Solution 3, i.e., ‘‘Security with Hybrid Approach’’, can be easilydeducted combining the first two solutions.

6. Satellite DIaaS provisioning

Satellite systems are able to solve many issues of D*aaSprovisioning allowing fast composition, delivery, and upgrade ofVMs. According to our case of study, to implement the proxyservice for the WEB TV’s server, Cloud providers should guaranteea fast placement of VMs holding an updated release of the webserver in the Cloud federation. However, as the Cloud architectureis deployed on the Internet infrastructure, the delivery capacity ofthe Internet limits the performance of service provisioning.

In order to better explain the effect of such a relationship, letus consider the example of the satellite Cloud DIaaS provisioningdepicted in Fig. 7. The WEB TV company is the Cloud client ofthe Cloud federation and wants to serve the audience in severalEuropean countries. In step 1, it asks a DIaaS to the Cloud providerA placed, for example, in Rome, in order to haveWEB TVmirrors inseveral sites in Europe. To satisfy the request, the Cloud providerA establishes agreements with several federated Clouds placed inEurope. The WEB TV company uploads a VM containing its webserver to CloudA and this latter has to replicate it on all themirrors.To speed up this task, in step 2, the Cloud provider A contacts asatellite operator, commits the required satellite resources for aburst transmission and then, in step 3, performs a provisioning ofthe VMs containing the WEB TV server mirrors. In step 4, Cloud Afinalizes the instantiation of the DIaaS adding mirroring and proxymechanisms in the Rome’s site and delivers the distributed Cloudservice to the WEB TV company. Future upgrade of the WEB TVserver from the WEB TV company will be up to date in the mirrorsaccording to steps 1–4 again.

Fig. 8 depicts how the DIaaS works under the assumption thata Swedish end-user client (we call him Sten, for simplicity) of theWEB TVwants towatch a particular event (e.g., the footballmatch).In step 1, Sten starts up the WEB TV viewer (that is the WEB TVclient) and contacts the main WEB TV server hosted in Cloud A.In step 2a, Cloud A accepts the WEB TV client requests. Then, instep 2b, considering the geographical position of the end user andaccording to theworkload of thewhole DIaaS, redirects the requestfrom the Sten’s WEB TV client to the server in the VM placed in thefederated Cloud F (Stockholm). Finally, in step 3, Cloud F providesthe WEB TV service to Sten, who can enjoy the match with a goodquality of service.

92 A. Celesti et al. / Future Generation Computer Systems 28 (2012) 85–93

Fig. 7. Satellite VM provisioning example.

Fig. 8. Example of DIaaS running.

7. Conclusions and future works

In this paper, we have proposed a new strategy to implementfast delivery of data in federated Cloud environments. This makesuse of satellite systems, which can provide efficient transmissionlinks to carry out opportunistic delivery of huge amount of data.

Analyzing issues in provisioning of distributed Cloud services,it is evident that the major problem is represented by the transferof big amount of data among federated Clouds. In some businessprojects for developing services in federated Clouds, the delivery ofVMs with size more than 10 GBs are necessary. However, latencyover the Internet reduces the applicability of Cloud solutions inreal cases. To overcome these limits, satellite links can offer avalid alternative. There are several improvements brought fromsuch an approach. First, satellites cover a wide geographical areaand, due to the broadcast nature of wireless communications,each transmitter inside the covered area can receive the satellitesignal. Also, current satellite throughputs aremuch higher than the

throughput estimated for data delivery in the Internet and the gapbetween wired and satellite capacities is expected to increase inthe near future.

Through the discussion of a use case, where aWEB TV companyoffers a streaming service, we showed how to practically apply theproposed strategy in a real scenario, specifying the involvementsof Cloud providers, Cloud users, satellite companies and end-userclients.

References

[1] R. Buyya, J. Broberg, A. Goscinski, Cloud Computing: Principles and Paradigms,Wiley Press, New York, USA, 2011.

[2] B. Rochwerger, D. Breitgand, A. Epstein, D. Hadas, I. Loy, K. Nagin, J. Tordsson, C.Ragusa, M. Villari, S. Clayman, E. Levy, A. Maraschini, P. Massonet, H.Munoz, G.Toffetti, Reservoir—when one Cloud is not enough, Computer 44 (2011) 44–51.http://dx.doi.org/http://doi.ieeecomputersociety.org/10.1109/MC.2011.64.

[3] Amazon Elastic Compute Cloud (Amazon EC2). http://aws.amazon.com/ec2/.[4] Azure: Microsoft’s service Cloud platform. http://www.microsoft.com/

windowsazure/.

A. Celesti et al. / Future Generation Computer Systems 28 (2012) 85–93 93

[5] Goiri, J. Guitart, J. Torres, Characterizing Cloud federation for enhancingproviders’ profit, in: Cloud Computing, IEEE International Conference on CloudComputing, 2010, pp. 123–130.

[6] R. Ranjan, R. Buyya, Decentralized overlay for federation of enterpriseclouds, in: Handbook of Research on Scalable Computing Technologies, 2010,pp. 191–217.

[7] K. Kanev, N. Mirenkov, Satellite Cloud computing, in: Advanced InformationNetworking and Applications, WAINA, 2011 IEEE Workshops of InternationalConference on, 2011, pp. 147–152. doi:10.1109/WAINA.2011.61.

[8] SunMicrosystems, Take your business to a higher level—sun Cloud computingtechnology scales your infrastructure to take advantage of new businessopportunities, guide, April 2009.

[9] W. Li, L. Ping, Trust model to enhance security and interoperability of Cloudenvironment, in: Cloud Computing, in: Lecture Notes in Computer Science,vol. 5931, 2009, pp. 69–79.

[10] A. Celesti, F. Tusa,M. Villari, A. Puliafito, How to enhance Cloud architectures toenable cross-federation, in: Cloud Computing, IEEE International Conferenceon Cloud Computing, 2010, pp. 337–345.

[11] T. Hirofuchi, H. Ogawa, H. Nakada, S. Itoh, S. Sekiguchi, A live storagemigrationmechanism over wan for relocatable virtual machine services on clouds,in: The 9th IEEE/ACM International Symposium on Cluster Computing and theGrid, 2009, pp. 460–465.

[12] T. Hirofuchi, H. Ogawa, H. Nakada, S. Itoh, S. Sekiguchi, A live storagemigration mechanism over wan and its performancee evaluation, in: The3rd International Workshop on Virtualizationtechnologies in DistributedComputing, 2009, pp. 67–74.

[13] A. Celesti, F. Tusa, M. Villari, A. Puliafito, Improving virtual machine migrationin federated Cloud environments, in: The Second International Conference onEvolving Internet, Internet 2010, 2010, pp. 61–67.

[14] Xen, The powerful open source industry standard for virtualization.http://xen.org/.

[15] Kernel Based Virtual Machine (KVM). http://www.linux-kvm.org.[16] VMware, the powerful open source industry standard for virtualization.

http://www.vmware.com/.[17] C.-S. Park, C.-G. Kang, Y.-S. Choi, C.-H. Oh, Interference analysis of geostation-

ary satellite networks in the presence of moving non-geostationary satellites,in: Information Technology Convergence and Services, ITCS, 2010 2nd Inter-national Conference on, 2010, pp. 1–5. doi:10.1109/ITCS.2010.5581292.

[18] LyngSat is a registered trademark, owned by Lyngemark Satellite. http://www.lyngsat.com/.

[19] Satellite Operator Eutelsate: HotBird Constellation. http://it.wikipedia.org/wiki/Hot_Bird.

[20] VIASAT is Transforming Satellite Broadband. http://www.viasat.com/broadband-satellite-networks/viasat-1.

[21] J. Xiao, F. Shaodong, L. Wei, Z. Gengxin, Z. Guozhen, Research on cooperativediversity in mobile satellite communication system, in: Education Technologyand Computer Science, ETCS, 2010 Second International Workshop on, vol. 1,2010, pp. 304–307. doi:10.1109/ETCS.2010.455.

[22] C. Sacchi, T. Rossi, M. Ruggieri, F. Granelli, Efficient waveform design for high-bit-rate w-band satellite transmissions, IEEE Transactions on Aerospace andElectronic Systems 47 (2) (2011) 974–995. http://dx.doi.org/10.1109/TAES.2011.5751238.

[23] L. Jiong, C. Zhigang, K. Junaid, Tp-satellite: a new transport protocol for satelliteip networks, IEEE Transactions on Aerospace and Electronic Systems 45 (2)(2009) 502–515. http://dx.doi.org/10.1109/TAES.2009.5089537.

[24] J. Johnson, J. Connary, J. Thompson, P. Donner, Internet routing in spaceNMS architecture, in: Aerospace Conference, 2009 IEEE, 2009, pp. 1–11.doi:10.1109/AERO.2009.4839382.

[25] King of SAT, The European Satellite Zapping & Directory. http://it.kingofsat.net/data-13.0E.php.

[26] Hughes HTS named Jupiter coming in 2012. http://www.dslreports.com/forum/r23279756-Hughes-HTS-named-Jupiter-coming-in-2012.

[27] T. Iida, Satellite broadband system: its needs and technology, in: SignalProcessing for Space Communications, 2008. SPSC 2008, 10th InternationalWorkshop on, 2008, pp. 1–6. doi:10.1109/SPSC.2008.4686693.

Antonio Celesti was born in Messina on April 30th 1984.He received the master degree in Computer Science at theFaculty of Mathematical, Physical and Natural Sciences,University of Messina (Italy) in 2008, final score 110/110cum summa laude; the subject of his thesis includedService Oriented Architectures (SOAs) and web services.From April 2009, he is attending his Ph.D. studies in‘‘Advanced Technologies for Information Engineering’’ atthe Faculty of Engineering, University of Messina. FromApril 2009 he is one of themembers of theMultimedia andDistributed Systems Laboratory (MDSLab). His scientific

activity has been focused on studying distributed systems and Cloud computing.His main research interests include virtualization, migration, security, federation,and information retrieval.

Maria Fazio received the degree in Electronic Engineeringin 2002 and the Ph.D. in 2006 from the University ofMessina (Italy). Her scientific activities have been focusedon distributed systems and mobile networks, especiallywith regard to wireless multi-hop networks. She wasan exchange visitor at the Department of ComputerScience of the University of California in Los Angeles in2005, where she has involved in research on VehicularNetworks. She received a post-doc fellowship in 2006and was an Assistant Researcher from 2009 to 2010 atthe University of Messina (Italy). Her current research

activities include Cloud computing, with particular attention on the integration ofdifferent communication technologies, federation and services provisioning.

Massimo Villari received his Ph.D. in 2003 from the Com-puter Science School of Engineering and the Laurea degree(bachelor’s degree + masters) in 1999 in Electronic Engi-neering from the University of Messina, Italy. Since 2006he is an Assistant Professor at the University of Messina.He is actively working as IT Security and Distributed Sys-tems Analyst in Cloud computing, virtualization and Stor-age for the European Projects ‘‘RESERVOIR’’ and ‘‘VISION’’.Previously, he was an academic advisor of STMicroelec-tronics, help an internship in Cisco Systems andworked onthe MPEG4IP and NEMO projects. He investigated issues

related with user mobility and security, in wireless ad hoc and sensor networks. Heis a member of IEEE. Currently, he is strongly involved in EU Future Internet initia-tives, specifically, Cloud Computing and Security in Distributed Systems. His mainresearch interests include virtualization, migration, security, federation, and auto-nomic systems.

Antonio Puliafito is a full professor of computer engi-neering at the University of Messina, Italy. His interestsinclude parallel and distributed systems, networking,wireless and GRID and Cloud computing. During 1994–1995 he spent 12 months as visiting professor at theDepartment of Electrical Engineering of Duke University,North Carolina, USA, where he was involved in researchon advanced analytical modeling techniques. He is the co-ordinator of the Ph.D. course in Advanced Technologies forInformation Engineering currently available at the Univer-sity of Messina and the responsible for the course of study

in computer engineering. He was a referee for the European Community for theprojects of the fourth, fifth and sixth Framework Program and he is currently actingas a referee also in the seventh FP. He has contributed to the development of thesoftware tools WebSPN, MAP and ArgoPerformance, which are being used both atnational and international level. Dr. Puliafito is the co-author (with R. Sahner andKishor S. Trivedi) of the text entitled ‘‘Performance and Reliability Analysis of Com-puter Systems: An Example-Based Approach Using the SHARPE Software Package’’,edited by Kluwer Academic Publishers. He is currently the director of the RFIDLab,a joint research lab with Oracle and Intel on RFID and wireless. He acted as thedirector of the Centre on Information Technologies Development and their Appli-cations (CIA) till 2009. He is currently the vice-president of the Consorzio Cometawhose aim is to enhance and exploit high performance computing. From 2006 to2008 he acted as the technical director of the Project 901, aiming at creating awireless/wired communication infrastructure inside the University of Messina tosupport new value added services (winner of the CISCO innovation award). He isalso the responsible of two big Grid Projects (TriGrid VL, http://www.trigrid.it, andPI2S2, http://www.pi2s2.it) for the University ofMessina, funded by the Sicilian Re-gional Government and by theMinistry of University and Research, respectively. Heis currently amember of the general assembly and of the technical committee of theReservoir project, an IP project funded by the European Commission under the sev-enth FP to explore the deployment and management of IT services across differentadministrative domains, IT platforms and geographies. He is the scientific directorof Inquadro s.r.l., a spin-off company of the University of Messina whosemain busi-ness is RFID and its application both in public and private sectors.