Market Oriented and Service Oriented Architecture of Cloud Storage
Ashwani Kumar, Arjun Singh and Sunita Sirohi GIMT, Kanipla, Kurukshetra
e-mail: [email protected], [email protected]
Abstract
This paper identifies various computing paradigms promising to deliver the vision of computing utilities; defines Cloud computing and provides the architecture for creating market-Oriented and Service market-Oriented Architecture of cloud Storage by leveraging technologies such as VMs; provides thoughts on market-based resource management strategies that encompass both customer-driven service management and Cloud computing describes a broad movement toward the use of wide area networks (WANs), such as the Internet, to enable interaction between information technology (IT) service providers of many types and consumers. Service providers are expanding their offerings to include the entire traditional IT stack, ranging from foundational hardware and platforms to application components, soft ware services, and whole soft ware applications.; presents some representative Cloud platforms especially those developed in industries along with our current work towards realising market-oriented resource allocation of Clouds
I. INTRODUCTION
With the advancement of the modern human society, basic essential services are commonly provided such that everyone can easily obtain access to them. Today, utility services, such as water, electricity, gas, and telephony are deemed necessary for fulfilling daily life routines. These utility services are accessed so frequently that they need to be available whenever Consumers are then able to pay service providers based on their usage of these utility services. In 1969, Leonard Klein rock [1], one of the chief scientists of the original Advanced Research Projects Agency Network (ARPANET) project which seeded the Internet, said: “As of now, computer networks are still in their infancy, but as they grow up and become sophisticated, we will probably see the spread of ‘computer utilities’ which present electric and telephone utilities, will service individual homes and offices across the country.”
Software practitioners are facing numerous new challenges toward creating software for millions of consumers to use as a service rather than to run on their individual computers. Computing services need to be highly reliable, scalable, and autonomic to support ubiquitous access, dynamic discovery and compos ability. In particular, consumers can determine the required service level through Quality of Service (QoS) parameters and Service Level Agreements (SLAs). Of all these computing paradigms, the two most promising ones appear to be Grid computing and Cloud computing.
A Grid [2] enables the sharing, selection, and aggregation of a wide variety of geographically distributed resources including supercomputers, storage systems, data sources, and
specialized devices owned by different organizations for solving large-scale resource-intensive problems in science, engineering, and commerce. the latest paradigm to emerge is that of Cloud computing [3] which promises reliable services delivered through next-generation data centers that are built on compute and storage virtualization technologies. Consumers will be able to access applications and data from a “Cloud” anywhere in the world on demand.
The commercial cloud marketplace offers a wide range of cloud services that vary in complexity and value. Figure 1 organizes this marketplace into a general set of service categories layered in a notional stack, with foundational offerings toward the bottom and more complex offerings toward the top.
II. DEFINITION AND TRENDS
Figure1. Cloud Computing Represented as a Stack of Service Offering Categories
A number of computing researchers and practitioners have attempted to define Clouds in various ways [4]. Based on our observation of the essence of what Clouds are promising to be, we propose the following definition:
Cloud Clients
Presentation Layer Example Browsers, Mobile
Devices
Cloud Application
Software as a Service Example Google Docs or
Calendar
Cloud Services
Components as a Service Example SOA via Web
Service standards
Cloud Platform
Platform as a service Example Web Server, App Server
Cloud Storage
Storage as a service Example formally utility
computing
Cloud infrastructure
Distributed Multi-site Physical Infrasture
"A Cloud is a type of parallel and distributed system consisting of a collection of interconnected
and virtualised computers that are dynamically provisioned and presented as one or more unified computing resources based on service-level agreements established through negotiation between the service provider and consumers.” 2.1 WEB SEARCH TRENDS
The popularity of different paradigms varies with time. The Web search popularity, as measured by the Google search trends during the last 12 months, for terms “cluster computing”, “Grid computing”, and “Cloud computing” is shown in Figure 2. From the Google trends, it can be observed that cluster computing was a popular term during 1990s, from early 2000 Grid computing become popular, and recently Cloud computing started gaining popularity.
Figure 2: Google search trends for the last 12 months. III. MARKET-ORIENTED CLOUD ARCHITECTURE As consumers will require specific QoS to be maintained by their providers in order to meet their objectives and sustain their operations. Cloud providers will need to consider and meet different QoS parameters of each individual consumer as negotiated in specific SLAs, Cloud providers can no longer continue to deploy traditional system-centric resource management architecture that do not provide incentives for them to share their resources and still regard all service requests to be of equal importance. Instead, market-oriented resource management [5] is necessary to regulate the supply and demand of Cloud resources at market equilibrium, provide feedback in terms of economic incentives for both Cloud consumers and providers, and promote QoS-based resource allocation mechanisms that differentiate service requests based on their utility.
Figure 3 shows the high-level architecture for supporting market-oriented resource allocation in Data Centres and Clouds. There are basically four main entities involved: Users/Brokers: Users or brokers acting on their behalf
submit service requests from anywhere in the world to the Data Centre and Cloud to be processed.
SLA Resource Allocator: The SLA Resource Allocator acts as the interface between the Data Centre/Cloud service provider external users/brokers.
Figure 3: High-level market-oriented cloud architecture.
VMs: Multiple VMs can be started and stopped dynamically on a single physical machine to meet accepted service requests, hence providing maximum flexibility to configure various partitions of resources on the same physical machine to different specific requirements of service requests. In addition, multiple VMs can concurrently run applications based on different operating system environments on a single physical machine since every VM is completely isolated from one another on the same physical machine.
Physical Machines: The Data Centre comprises multiple computing servers that provide resources to meet service demands.
3.1 Comparing Cloud Computing and SOA:
Cloud computing and SOA have important overlapping concerns and common considerations, as shown in Figure 4. The most important overlap occurs near the top of the cloud computing stack, in the area of Cloud Services, which are network accessible application components and soft ware services, such as contemporary Web Services. (See the notional cloud stack in Figure 1.)
Both cloud computing and SOA share concepts of service orientation.[6] Services of many types are available on a common network for use by consumers. Cloud computing focuses on turning aspects of the IT computing stack into commodities[7] , that can be purchased incrementally from the cloud based providers and can be considered a type of outsourcing in many cases. For example, large-scale online storage can be procured and automatically allocated in terabyte units from the cloud. Similarly, a platform to operate web-based applications can be rented from redundant data centres in the cloud. However, cloud computing is currently a broader term than SOA and covers the entire stack from hardware through the presentation layer soft ware systems. SOA, though not restricted conceptually to soft ware, is oft en implemented in practice as components or soft ware services,
as exemplified by the Web Service standards used in many implementations. These components can be tied together and executed on many platforms across the network to provide a business function.
3.2 Can SOA Be Skipped for Cloud Computing?
SOA and cloud computing are complementary activities and both will play important roles in IT planning for senior leadership teams for years to come. Cloud computing and SOA can be pursued independently, or concurrently, where cloud computing platform and storage service offerings can provide a value-added underpinning for SOA efforts. John Foley describes cloud computing as “on-demand access to virtualized IT resources that are housed outside of your own data centre, shared by others, simple to use, paid for via subscription, and accessed over the Web.”[8]
IV. STANDARDIZING CLOUD COMPUTING
INTERFACES
In a programmable interface to the IaaS infrastructure means that you can write client software that uses this interface to manage your use of the Cloud. Many cloud providers have licensed their proprietary APIs freely allowing anyone to implement a similar cloud infrastructure. Despite the accessibility of open APIs, cloud community members have been slow to uniformly adopt any proprietary interface controlled by a single company. The Open Source community has attempted responses, but this has done little to stem the tide of API proliferation. In fact, Open Source projects have increased the tally of interfaces to navigate in a torrent of proprietary APIs.
What is needed instead is a vendor neutral, standard API for cloud computing that all vendors can implement with minimal risk and assured stability. This will allow customers to move their application stacks from one cloud vendor to another, avoiding lock-in and reducing costs.
4.1 Introducing OCCI
The Open Grid Forum™ has created a working group to standardize such an interface. The Open Cloud Computing Interface (OCCI) is a free, open, community consensus driven API, targeting cloud infrastructure services. The API shields IT data centers and cloud partners from the disparities existing between the line up of proprietary and open cloud APIs. 4.2 The OCCI Reference Architecture
The OCCI has adopted a "Resource Oriented Architecture (ROA)" to represent key components comprising cloud infrastructure services. Each resource (identified by a canonical URI) can have multiple representations that may or may not be hypertext (e.g. HTML). The OCCI working group is planning mappings of the API
Figure 4: The OCCI API
to several formats. Atom/Pub, JSON and Plain Text are planned for the initial release of the standard. A single URI entry point defines an OCCI interface. Interfaces expose "nouns" which have "attributes" and on which "verbs" can be performed. Figure 4 shows how the components of an OCCI URI align to IaaS Resources:
V. STORAGE FOR CLOUD COMPUTING
For cloud computing boot images, cloud storage is almost always offered via traditional block and file interfaces such as iSCSI or NFS. These are then mounted by the virtual machine and attached to a guest for use by cloud computing. Additional drives and file systems can be similarly provisioned. Of course cloud computing applications can use the data object interface as well, once they are running.
VI. WHAT MAKES CLOUD STORAGE DIFFERENT? The difference between the purchase of a dedicated appliance and that of cloud storage is not the functional interface, but merely the fact that the storage is delivered on demand. The customer pays for either what they actually use or in other cases, what they have allocated for use. In the case of block storage, a LUN or virtual volume is the granularity of allocation. For file protocols, a file system is the unit of granularity. In either case, the actual storage space can be thin provisioned and billed for based on actual usage. Data services such as compression and reduplication can be used to further reduce the actual space consumed.
The management of this storage is typically done out of band of these standard Data Storage interfaces, either through an API, or more commonly, though an administrative browser based user interface. This interface may be used to invoke other data services as well, such as snapshot and cloning. 6.1 Introducing CDMI
The Storage Networking Industry Association™ has created a technical work group to address the need for a cloud storage standard. The new Cloud Data Management Interface (CDMI) is meant to enable interoperable cloud storage and data management. In CDMI, the underlying storage space exposed by the above interfaces is abstracted using the notion of a container. A container is not only a useful abstraction for storage space, but also serves as a grouping of the data stored in it, and a point of control for applying data services in the aggregate.
CDMI Containers are accessible not only via CDMI as a data path, but other protocols as well. This is especially useful for using CDMI as the storage interface for a cloud computing environment as shown in Figure 8 below:
Figure 6: CDMI and OCCI in an integrated cloud computing environment
The exported CDMI containers can be used by the Virtual Machines in the Cloud Computing environment as virtual disks on each guest as shown. With the internal knowledge of the network and the Virtual Machine, the cloud infrastructure management application can attach exported CDMI containers to the Virtual Machines.
VII. GLOBAL CLOUD EXCHANGE AND MARKETS Enterprises currently employ Cloud services in order to improve the scalability of their services and to deal with bursts in resource demands. However, at present, service providers have inflexible pricing, generally limited to flat rates or tariffs based on usage thresholds, and consumers are restricted to offerings from a single provider at a time. Also, many providers have proprietary interfaces to their services thus restricting the ability of consumers to swap one provider for another.
The idea of utility markets for computing resources has been around for a long time. Recently, many research projects such as SHARP [9], Tycoon [10], Bellagio [11], and Shirako [12] have come up with market structures for trading in resource allocations. These have particularly focused on trading in VM based resource slices on networked infrastructures such as Planet Lab. As mentioned before, the Grid bus project has created a resource broker that is able to negotiate with resource providers. Thus, the technology for enabling utility markets is already present and ready to be deployed.
However, significant challenges persist in the universal application of such markets. Enterprises currently employ conservative IT strategies and are unwilling to shift from the traditional controlled environments. Cloud computing uptake has only recently begun and many systems are in the proof-of concept stage. Regulatory pressures also mean that enterprises have to be careful about where their data gets processed, and therefore, are not able to employ Cloud services from an open market. This could be mitigated through SLAs that specify strict constraints on the location of the resources. However, another open issue is how the participants in such a market can obtain restitution in case an SLA is violated. This motivates the need for a legal framework for agreements in such markets, a research issue that is out of scope of themes pursued in this paper.
VIII. SUMMARY AND CONCLUSION
Cloud computing is a new and promising paradigm delivering IT services as computing utilities. As Clouds are designed to provide services to external users, providers need to be compensated for sharing their resources and capabilities. In this paper, we have proposed architecture for market-oriented allocation of resources within Clouds. We have discussed some representative platforms for Cloud computing covering the state-of-the-art. We have also presented a vision for the creation of global Cloud exchange for trading services. SOA and cloud computing are complementary activities, and both will play important roles in IT planning for senior leadership teams for years to come. Cloud computing and SOA can be pursued independently, or concurrently, where cloud computing platform and storage service offerings can provide a value-added underpinning for SOA efforts.
REFERENCES
[1] L. Kleinrock. A vision for the Internet. ST Journalof Research, 2(1):4-5, Nov. 2005.
[2] I. Foster and C. Kesselman (eds). The Grid: Blueprint for a Future Computing Infrastructure. Morgan Kaufmann, San Francisco, USA, 1999.
[3] A. Weiss. Computing in the Clouds. netWorker, 11(4):16-25, Dec. 2007.
[4] Twenty Experts Define Cloud Computing, http://cloudcomputing.sysconcom/read/612375_p.htm [18 July 2008].
[5] R. Buyya, D. Abramson, and S. Venugopal. The Grid Economy. Proceedings of the IEEE, 93(3):698-714, IEEE Press, USA, March 2005.
[6] Kevin Jackson, “Cloud Computing Related Technologies and their Use in the Public Sector to
Support Net-centric Operation”
http://kevinljackson.blogspot.com/2008/09/6-layers-of-cloud-computing-tack.html
[7] Bernard Lunn, “Th e New Stack: SaaS, Cloud
Computing, Core Technology”
http://www.readwriteweb.com/archives/new_technolo gy_stack.php
[8] John Foley, “A Defi nition of Cloud Computing,” http://www.informationweek.com/ cloud-computing/blog archives/2008/09/a_defi nition_of.html
[9] Y. Fu, J. Chase, B. Chun, S. Schwab, and A. Vahdat SHARP: an architecture for secure resource peering. ACM SIGOPS Operating Systems Review, 37(5):133– 148, Dec. 2003.
[10] K. Lai, L. Rasmusson, E. Adar, L. Zhang, and B. A. Huberman. Tycoon: An implementation of a distributed, market-based resource allocation system. Multiagent and Grid Systems, 1(3):169–182, 2005. [11] A. AuYoung, B. Chun, A. Snoeren, and A. Vahdat.
Resource allocation in federated distributed computing infrastructures. In Proceedings of the 1st Workshop on Operating System and Architectural Support for the Ondemand IT Infrastructure (OASIS 2004), Boston, USA, Oct. 2004.
[12] D. E. Irwin, J. S. Chase, L. E. Grit, A. R. Yumerefendi, D. Becker, and K. Yocum. Sharing networked resources with brokered leases. In Proceedings of the 2006 USENIX Annual Technical Conference (USENIX 2006), Boston, USA, June 2006.
