will need to provide QoEand SLA-based charging as well. If there is an SLA violation, a credit to the user will have to be initiated.

20.5.1.5  Interprovider Charging

There will be many cases where the revenue collected by the cloud vendor needs to be shared with partners and other providers who are part of the value-chain. This demands an inter-provider charging agreement that will rate and calculate the charges payable to or receivable from the partner provider like the SaaS, PaaS, or the IaaS. This will be driven by the following considerations:

1.Bill & keep – this is a special type of billing agreements between the providers where the provider keeps [14] all the money they collect from the subscriber. Nobody shares any revenue with any other provider.

2.Usage of resource is measured, rated, and billed at the point of interconnection (POI). Rates will be determined by service combined with spatial, temporal, and instance attributes.

20.6  Taxation in the Cloud

It is easy to formulate a taxation policy for tangible movable or immovable assets; it is also possible to formulate a taxation policy when these assets cross the border of a state. Tax is levied at the point of consumption of the service; therefore, conventional taxation principles will not be able to support the complex needs of taxation in a virtual cloud environment. Cloud computing is predicated on a concept of borderless global services. Governments, for one reason or another, do not like this idea – at a basic level, governments need borders.

The taxation in the cloud will be the responsibility of the cloud vendor who will have a local tax registration and be governed by the local tax regulations. Taxation in the cloud can be managed with similar taxation model as mobile network operators or mobile virtual network operator (MVNO). A mobile subscriber can consume the service of the home service provider while at the home network; the subscriber can use the service of a foreign network being present at the home network. The subscriber can also be roaming in a foreign country with different taxation policies and consume services of the foreign network or the home network. Similarly, in the cloud, the end-user could be in one country and the cloud vendor could be in another country offering services from providers that originate in other countries.

Over a period of time, we believe that there will be clearing houses that will manage the interstate and intercountry taxations of the consumables. This might lead to a situation where there are dangers of double taxation. If tax is based on the location of the registered office of a cloud computing company, then there is always an option to the virtual offices to be located in a lower tax or tax-free export zone.

References

1.Security Guidance for Critical Areas of Focus in Cloud Computing (2009, April) Prepared by the Cloud security alliance

2.Talukder AK, Chaitnya M (2008) Architecting secure software systems. CRC Press, Boca Raton, FL

3.Lee S, Cooper LF (2009, August) IT managers discover the high cost of ignoring data center efficiency problems. BizTechReports.Com. Cited in an IBM WebEx presentation entitled: dynamic infrastructure in action: reducing costs while increasing value. http://researchlibrary. theserverside.net/detail/RES/1254491035_498.html

4.Weisman J (2008) GigaOM network: the 10 laws of Cloudonomics. BusinessWeek Online. http://www.businessweek.com/technology/content/sep2008/tc2008095_942690.htm. Originally posted 6 September 2008

5.Matzke P (2008, November) Cloud computing: from vision to reality. http://download.sczm.t- systems.de/t-ystems.de/en/StaticPage/55/02/30/550230_10_Presentation_Cloud- Computing-ps.pdf. Original presentation given 25 November 2008

6.Google (2009). Efficient computing: data center efficiency measurements. http://www.google. com/corporate/green/datacenters/measuring.html. Accessed September 2009

7.The Bhikshu (Mendicant) from The Dhammapada, A Collection of Verses. http://www. sacred-texts.com/bud/sbe10/sbe1027.htm

8.Gaggioli A, Bassi M, Delle Fave A (2003) Quality of experience in virtual environments. In: Riva G, Davide F, IJsselsteijn WA (eds) Being there: concepts, effects and measurement of user presence in synthetic environments. Los Press, Amsterdam, p 121

9.ITU-T Recommendation G.1000, Communications quality of service: A framework and definitions

10. ITU-T E.600, Terms and definitions of Traffic Engineering, 1993 11. RFC3644, Policy Quality of Service (QoS) Information Model

12. Oodan A et al (2002) Telecommunications quality of service management: from legacy to emerging services. Institution of Electrical Engineers

13. Armbrust M et al (2009, Feb 10) Above the clouds: a Berkeley view of cloud computing. UC Berkeley Reliable Adaptive Distributed Systems Laboratory. http://radlab.cs.berkeley.edu/

14. Berger U (2004) Bill-and-Keep vs. cost-based access pricing revisited. http://ideas.repec. org/p/wpa/wuwpio/0408002.html

Chapter 21

Towards Application-Specific Service Level

Agreements: Experiments in Clouds and Grids

Bin Li, Lee Gillam, and John O’Loughlin

Abstract  Service Level Agreements (SLAs) become increasingly important in clouds, grids and utilities. SLAs that provide bilaterally beneficial terms are likely to attract more consumers and clarify expectations of both consumers and providers. This chapter extends our existing work in SLAs through evaluating application-specific costs within a commercial cloud, a private Eucalyptus cloud and a grid-based system. We assess the total runtime, as well as the wait time due to scheduling or the booting time of a virtual instance. With relatively short processes, this start-up overhead becomes insignificant. In undertaking these experiments, we have provided some justification for a recent hypothesis relating to a preference for job completion time over raw compute performance [4].

21.1  Introduction

Cloud computing [14, 17], and its recent forefathers of grid systems [1, 2, 3, 6] and utility computing [5, 14], have led to a number of organisations reappraising their IT infrastructures. Organisations with existing IT infrastructures are increasingly questioning the ownership model of computing, with cost management [7] being a key concern. Clouds, grids and utilities have also become the basis for, or a core part of, other businesses, and are typified by the strong emergence of Software as a Service (SaaS). The move towards SaaS, essentially Internet-based software applications, is reported by producers and consumers alike to be both strategically and financially beneficial. Removing the need for physically locating, powering and cooling, certain kinds of core and bespoke infrastructure – with regular maintenance schedules and

B. Li (*)

Department of Computing, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, Surrey, United Kingdom, GU2 7XH

e-mail: B.Li@surrey.ac.uk

Systems and Applications, Computer Communications and Networks,

DOI 10.1007/978-1-84996-241-4_21, © Springer-Verlag London Limited 2010

concomitant staffing – presents a different cost model for IT. Though email is typically­ given as a prime example of a widely used SaaS, software such as Google Apps, SalesForce, Zoho, g.ho.st and MobileMe can support a variety of uses. Such software may be offered for free up to certain limits, beyond which differential costs will be applied to specific levels of support or quantities of storage; models for such costs will vary by provider, requiring the consumer to ascertain the best value for money offering. Popular SaaS offerings with relatively fixed characteristics, such as email, readily scale to the number of users and user demands, implying that utilisation can be maximised and the resulting cost-efficiencies can be passed on to consumers.

While SaaS may offer solutions for generic software needs, specific computational activities that rely on mechanisms of distributed computing for complex calculations, Web Services for remote access, P2P networks for file sharing and distribution, and so on, present different challenges. Cloud computing has grown to encompass wider infrastructural issues for businesses, offering organisations and individuals the opportunity to use different forms of commoditised computer systems, with various associated costs for processor hours and storage in managed facilities. Such facilities can be used by organisations internally, or as part of the external-facing business activity, or as part of an overall customer offering in which the offering may encompass the costs of processor hours and storage. Although accessing such systems has long been technically possible, the costs have typically been rather less transparent and efficiently maximising use of the infrastructure has been of less economic importance. Traditionally, peak requirements tended to dictate the size of a system; now it is possible to run 1,000 servers for a short period without having to own them, and the costs of doing so should not far exceed that of using a server for 1,000 hours. The IT infrastructure can grow and shrink as needed, with costs directly proportionate. Businesses are exploring solutions within this space that might help with cutting costs; however, the range of choices is substantial.

Cloud systems may not be to everybody’s tastes for a variety of reasons: lack of bandwidth makes such systems either difficult or impossible to use; organisations may prefer the existence of tangible assets; legislative/regulatory issues may be too great; and concern may exist over vendor dependency or so-called lock-in. Alongside such issues, we would also include the importance of having wellspecified bilateral Service Level Agreements (SLAs) that provide generally understandable clauses for assurances of availability, reliability and liability. In previous work [10–13], we have explored the construction of SLAs such that a price comparison service – as exists for other products. Commercial Cloud systems enable us to capture price–performance information relating to specific applications with relatively well-known demands on systems, and to be able to determine how such a comparison service may be formulated. Such a comparison service will necessarily depend on both the performance requirements of the user and the current availability of the system, as well as the price willing to be paid by the consumer. A variety of factors are involved in determining the best value: a supercomputer may be able to undertake specific kinds of analysis at a much faster rate than a commercial cloud system [15] once the required work has been ­appropriately initiated.