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International Journal of Computer Science Engineering and Information Technology Research (IJCSEITR) ISSN 2249-6831 Vol. 3, Issue 4, Oct 2013, 13-18 © TJPRC Pvt. Ltd.

CLOUD COMPUTING ARCHITECTURE TO AID TELEMEDICINE NEHA BISHNOI & ANUPMA SEHRAWAT Department of Computer Science, Amity University, Gurgaon, Haryana, India

ABSTRACT A cloud is a utility based computing model that provides a service and allows virtualized resources to be easily and efficiently scale on demand. Cloud computing is such a technique which can be used for start up and small businesses that lack infrastructure. It can also be used to provide storage facility to an individual. In this paper we will discuss efficient cloud computing architecture that is based on distributed data centers which will support application in the hospital network in order to reduce latency.

KEYWORDS: Cloud Computing, Distributed Data Centers, Latency INTRODUCTION Internet is a dynamic and rapidly evolving mechanism that it seems impossible for traditional human information system such as libraries, prints media to keep pace. Today’s scenario, cloud computing services are very much necessary for web users to access computing resources over internet. Cloud computing refers to both the applications delivered as the services over internet and hardware and software in data centers that provide services. Cloud computing is that customers only use what they need, and pay for what they actually use. Resources as a service are available over Cloud at any time and from any location via the Internet [1]. Among the popular Cloud service providers are: Amazon [5], Google [6], Microsoft [7] etc.

BACKGROUND Cloud computing is largely a combination of existing technologies that have been around since the early 90’s. These technologies include: Grid Computing: In this technology we have distributed computers where the resources of many heterogeneous computers on a network work on a same task at same time. This is the best technology for large work because of its parallel processing. Utility Computing: In this technology a service provider makes computing resources available to the customer, as required, and charges them on the basis of pay-per-use. Virtualization: In this technology various hardware and software resources are viewed and managed as a pool, which provides improved utilization of resources. This helps in achieving centralized management, optimized resources, and efficient use of the available computing capacity. Service Oriented Architecture (SOA): In this technique each service provides a specific function. A deployed SOA- based architecture provides a set of services that can be used in multiple business domains.


Neha Bishnoi & Anupma Sehrawat

CLOUD COMPUTING: ESSENTIAL CHARACTERISTICS Table 1 Name Rapid Elasticity Measured Service

   

Broad Network Access

   

Resource pooling

 

On-Demand Self Service

  

Features Can add or remove resources as required To the customer, cloud seems to be endless Customer are charged on pay-per-use basis To maintain transparency, usage of resources is monitored and reported Services can be accessed via any thin client No need of any particular platform to access a service Allows to access the services from anywhere, anytime Allows multiple customers to access the resources at the same time Provides location independence Based on multitenancy, resources are assigned and reassigned according to the demand Allows customers to get services whenever required Customers can select services of their choice from the service catalogue Self-service interface must be user-friendly

CLOUD SERVICES: AN EXAMPLE Here is an example of the type of the requirements of the customers and the services provided by the cloud. In this the first customer is a single user who wants to have some secure storage from cloud, so that he can access his data from anywhere at any time without any trouble. For this type of requirement cloud service providers provides IaaS (Infrastructure-as-a-service). The second one is an organization, which is new and doesn’t want to increase its expenditure for buying Storage, platforms, operating systems, etc. For this type of requirement Cloud service providers makes you enable for using their applications, infrastructure, platforms etc. This type of service is known as SaaS (Software-as-aservice). The third customer is a single user and just wants to use Excel application, so that he can prepare his spreadsheets. For this type of requirements Cloud service providers allow you to use only an application. This is also known as SaaS. The last one in the example is again an organization, which needs various platforms for their application. Here cloud service providers allow the organization to use various platforms. This is known as PaaS (Platform-as-a-Service).

Figure 1: An Example of Services Provided by a Cloud


Cloud Computing Architecture to Aid Telemedicine

BENEFITS OF USING CLOUD Table 2 Benefit Flexible Scaling Reduced IT cost Business agility support High Availability Less Energy Consumption

Description A cloud can be easily upgraded and degraded based on the demand. Customers can save money by hiring the services instead of purchasing. Customers can reduce the time required for the deployment of new applications and services. A cloud can ensure application availability to the customer according to the priority and policies. A cloud enables the customers to reduce power and space consumption.

VIRTUALIZATION TECHNOLOGY Virtualization is the first step towards building a cloud infrastructure which enables a smooth transition from Classical Data Center (CDC) to Virtual Data Center (VDC). This enables multiple operating systems to run concurrently on single or clustered physical machines. And also encapsulates an operating system and an application into a Portable Virtual Machine (VM). VM is a logical entity that looks and behaves like a physical machine. Virtualization layer resides between the hardware and the VM and it is also called as hypervisor. An operating system that runs within a VM is called a guest operating system. Each VM is independent and can run its own applications. A VM uses a virtual hardware. Each guest OS sees the hardware devices as if they were physical and owned by them. A logical resource pool is created from a physical machine which is then allocated to the VM’s according to their demands. We clone data from physical machine’s disk to VM’s disk. Then we change IP address and computer name of the VM. Then install the required device drivers to the VM.

PROPOSED CLOUD ARCHITECTURE Due to the world wide hype, Cloud computing clients continue to multiply. More number of users as compared to the service providers has increased the problem of latency. If a cloud service provider is far away from the client, then data need to travel a lot through several mediums and equipments in the network, resulting in a time delay in getting the services. In order to reduce this latency problem we propose a model based on distributed data centers. To make the concept clearer, we have taken an example of hospital network in India.

Figure 2: Proposed Cloud Architecture


Neha Bishnoi & Anupma Sehrawat

In figure 2, we try to discuss how cloud computing can be used to fill in the gap of providing quality healthcare to those whose disease can be easily diagnose with known symptoms and can be provided with suitable medicine as per their needs. In the proposed architecture data-centers work in master-slave model. Each hospital in the country has its own cloud and keeps all the records such as patient record, treatment history, prescription, schedules, appointments, doctor’s information, etc on the cloud. All the hospitals in one city will lie in the same zone i.e. nearest data-centers form a computing zone and users can create their instances of request in multiple zones. In the above diagram, we have created master data-center at Delhi and other data-centers are regional located in various cities of India. Here master data-center is located in premises of the administrator of cloud provider. Billing of users depending on pay-as-per-use is done here. Slave data-center are geographically scattered in order to serve user’s requests in minimum physical distance. As soon as user initiates a request, it directly reaches at master data-center or it is directed via third party. Master data-center creates user instance at appropriate slave data-center considering minimum latency. Before hosting needs of the users, each time master data-center scans SLAs. After receiving a request for creating an instance, master data-center will look for resources in the user’s local data-center. If desired resources are available there, then user gets his required instance, and run the application to access the required information with minimum latency. If resources are not available in the user’s local data-center, then master data-center searches other data-centers of same zone. If resources are not available even in same zone and user request is for multiple zone, then master data-center will look for resources in other zones, else request will be denied.

ALGORITHM BASED ON PROPOSED ARCHITECTURE In algorithm we denote master data-center as MDC and slave data-center as SDC. The steps involved in algorithm are as follows: 

Algorithm starts with location of user as i and j

Firstly user requests for an instance to MDC

MDC checks for resources in local data-center

If resources are available, an instance is created as Uij where i and j is location of the user

Else MDC looks for resources in other data-centers of the same zone and accordingly creates an instance

Else MDC looks for resources in other zones if user has requested for multiple zone search

Else MDC denies the request and user is supposed to make a fresh request

Algorithm ends


Quick response to request by users.

Reduces Latency.

Data-centers can be created using existing infrastructure

Commodity hardware can be used to form data-centers


Cloud Computing Architecture to Aid Telemedicine


CONCLUSIONS As a kind of emerging business computational model, Cloud Computing distribute computational task on the resource pool which consists of massive computers, accordingly, the application systems can gain the computational strengths, the storage space and software services according to its demand. Cloud Computing is not actually the revolutionary recent development, but is the result of continuous evolution of data management technology. In this paper, we have proposed architecture for hospital network which is based on distributed data-centers. This architecture help the users to access the information about any hospital from anywhere in the world. This architecture can also be used by doctors in rural sectors, with fewer facilities as they can refer to the information of the cloud for treatment of their patients. They use of existing infrastructure makes this architecture cost effective.


Rolim, C.O.; Koch, F.L.; Westphall, C.B.; Werner, J.; Fracalossi, A. Salvador, G.S. A Cloud Computing Solution for Patient's Data Collection in Health Care Institutions in Second International Conference on eHealth, Telemedicine, and Social Medicine, 2010. ETELEMED '10, pp.95-99, 10-16 Feb. 2010.


Kugean, C.; Krishnan, S. M.; Chutatape, O.; Swaminathan, S.; Srinivasan,N.; Wang, P. Design of a mobile telemedicine system with wireless LAN in Asia-Pacific Conference on Circuits and Systems, 2002. APCCAS '02, vol.1, pp. 313- 316 , 2002.


Richard Wootton, John Craig, VictorPatterson Introduction to Telemedici, in Royal Society Of Medicine Press Ltd.,2011.


Alamri, A. Cloud-Based E-Health Multimedia Framework for Heterogeneous Network in International Conference onMultimedia and Expo Workshops (ICMEW) ,IEEE , pp.447-452, 9-13 July 2012.


Khalifehsoltani, S.N Gerami, M.R. E-health Challenges, Opportunities and Experiences of Developing Countries, in International Conference on e-Education, e-Business, e- Management, and e-Learning, IC4E '10 IEEE proceeding, , pp.264-268, 22-24 Jan. 2010.


Mishra, S.K.; Gupta, D.; Kaur, J., Telemedicine in India: Initiatives and vision, in 9th International Conference one-Health Networking, Application and Services, 2007, vol., no., pp.81-83, 19-22 June 2007. Sangal


A.K.; Satyamurthy, L.S.; Bhatia, B.S.; Bhaskarnarayana, A.; , Communication satellite based network for telemedicine in India, in 6th International Workshop on Enterprise Networking and Computing in Healthcare Industry, 2004. HEALTHCOM 2004. Proceedings, 0p149- 151, 28-29 June 2004.


Koufi, V.; Malamateniou, F.; Vassilacopoulos, G., Ubiquitous access to cloud emergency medical services,in 10th IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB), 2010 , pp.14, 3-5 Nov. 2010.


Wooten, R.; Klink, R.; Sinek, F.; Yan Bai; Sharma, M., Design and Implementation of a Secure Healthcare Social Cloud System, in 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), 2012, pp.805-810, 13-16 May 2012

10. Mohammed, S.; Servos, D.; Fiaidhi, J.; HCX: A Distributed OSGi Based Web Interaction System for Sharing Health Records in the Cloud, in the proceedings of 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), Toronto, Canada,vol.3, pp.102-107, Sept. 2010.


Neha Bishnoi & Anupma Sehrawat

11. Botts, N.; Thoms, B.; Noamani, A.; Horan, T.A., Cloud Computing Architectures for the Underserved: Public Health Cyberinfrastructures through a Network of HealthATMs, in the proceedings of 43rd Hawaii International Conference on System Sciences (HICSS). Hawaii, USA, pp.1-10, Jan. 2010. 12. Chia-Chi Teng and Mitchell, J.; Walker, C.; Swan, A.; Davila, C.; Howard, D.; Needham, T.; A medical image archive solution in the cloud, in the proceedings of 2010 IEEE International Conference on Software Engineering and Service Sciences (ICSESS), Beijing, China, pp.431-434, July 2010. 13. Chowdhary, S.K.; Yadav, A.; Garg, N.; , Cloud computing: Future prospect for e-health, in 3rd International Conference onElectronics Computer Technology (ICECT),, vol.3, pp.297-299, 8-10 April 2011 14. Kailanto, H.; Hyvarinen, E.; Hyttinen, J., Mobile ECG measurement and analysis system using mobile phone as the base station, in Second International Conference on Pervasive Computing Technologies for Healthcare. PervasiveHealth 2008, pp.12-14, Jan. 30 -Feb. 1 2008. 15. Behl, A., Emerging security challenges in cloud computing:An insight to cloud security challenges and their mitigation, in World Congress on Information and Communication 16. Rajkumar Buyya, Chee Shin Yeo, and Srikumar Venugopal, Market- Oriented Cloud Computing: Vision, Hype, and Reality for Delivering IT Services as Computing Utilities,Proceedings of the 10th IEEE International Conference on High Performance Computing and Communications (HPCC 2008), Dalian, China, Sept. 25-27, 2008. 17. Zhenyu Fang and Changqing Yin, BPM Architecture Design Based on Cloud Computing, in Online Journal on Intelligent Information Management, Vol 2, May 2010, pp 329-333. 18. Norman W. Paton, Marcelo de Aragao, Kevin Lee, Alvaro Fernandes and Rizos Sakellariou, Optimizing Utility in Cloud Computing through Autonomic Workload Execution, retrieved 19. Chetna Dabas and J.P Gupta, A Cloud Computing Architecture Framework for Scalable RFID, Proceeding of the International Multi Conference of Engineers and Computer Scientsts (IMECS 2010,) Hong Kong, Vol 1, March 2010, pp 217-220. 20. Rodrigo N. Calheiros, Rajiv Ranjan, Anton Beloglazov, Cesar A. F. DeRose, and Rajkumar Buyya, CloudSim: A Toolkit for Modeling and Simulation of Cloud Computing Environments and Evaluation of Resource Provisioning Algorithms, Volume 41, Number 1, Pages: 23-50, New York, USA, January, 2011. 21. Virtualization Technology, http :// 22. Vitual Machines through VMware, Sean K Barker, Prashant Shenoy, Empirical Evaluation of Latency-sensitive Application Performance in the Cloud 23. Pandey, Suraj, 2010. Cloud Computing Technology & GIS Application. Asian Symposium on Geographic & Information system From Computer & Engineering View (ASGIS 2010), China.

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