A Proposed Framework for Ranking and Reservation of Cloud Services Based on Quality of Service

II,III A Proposed Framework for Ranking and Reservation of Cloud Services Based on Quality of Service I Samir.m.zaid, II Hazem.m.elbakry, III Islam.m.abdelhady I Dept. of Geology, Faculty of Sciences, zagazig University, Egypt Dept. of Information Systems, Faculty of Computer and Information Sc., Mansoura Univ., Egypt Abstract Cloud Computing is integrated model of software, hardware, and middleware that has been provided as a service. Cloud computing is becoming progressively more significant. In recent years with the rapid growth of cloud computing more and more organizations and companies started to offer cloud services to consumers on the basis of their functional and non-functional requirement. Currently no software framework can index cloud services based on their needs, because of diversity offers from services of cloud. Hence, in this paper, we propose a framework for ranking and reservation cloud services from clouds based on some features such as quality of services (QoS) attributes, performance and increase the competition between cloud providers. The contribution of this paper over the work presented in [10] is that the number of QoS attributes is increased to achieve more accurate results. I. Introduction In the last years the development of systems based on services of cloud has grown in importance [1].The Cloud computing can be define as management of resources, applications and information as services through the internet under request. Instead of purchasing actual physical devices servers, storage, or any networks equipment[2].in recent years with the rapid growth of cloud computing many organizations and companies started to offer their services to different kinds of consumers like Amazon, HP and IBM [3]. Every user of clouds prefer to use cloud services wants to apply one cloud service for own application has different requirement [4]. There are three types for providing services they are software, platform and infrastructure, Service means an act of help or assistance to the user, every service serves a different purpose and offers different products for individual people and businesses in every place in the world in first software as a service all customers can access to all services these services are located on the cloud and software is managed and owned via providers Software as a Service and customers can access to these services over the public internet. In second model platform as a service enables all customers to organize their own software and application in the cloud. In third model infrastructure as a Service Provides a set of virtualized computing resources (storage capacity, network bandwidth, processing power, memory) in the clouds [5]. Cloud computing is new technology that allows people to use their applications from any place in the world and from any computers without any installation [6].Cloud computing allows more than efficacious computing via processing, bandwidth, memory and centralization storage, in cloud computing environment every user wants to use cloud services has its own requirements. Therefore the users of cloud can choose the most appropriate service that can fulfills their requirements, in the general the aims from ranking services of cloud are assistant users to estimate, compare and choose from different services that services can satisfy their requirements from clouds,the ranking mechanism help users and customers to select the service providers that will provide the best performance and satisfy their requirements from quality of service attributes,selecting services provider based on our quality of service attributes are very important to success our business. II. Related work The aim from cloud computing is to distribute a network of virtual services so that consumers might be arrive to them from anyplace in the world on payment at competitive costs depending on their quality of service (QoS) requirements [9].Because of increased number of requests from services of cloud the services provider can t deliver the requested services at the right time so the author proposed novel framework for ranking and advanced reservation by using quality of service (QoS) attributes, implementation all those attributes aren t used but the characteristics are explained [7]. The authors proposed a quality of service ranking prediction framework for services of Cloud via taking past service usage experiences of consumers, framework that used to avoid expensive real-world service invocations and time-consuming [8]. The authors proposed a framework to measure the quality and prioritize services of cloud, this framework increase the competition between Cloud providers and makes significant impact, this technique is used only for quantifiable quality of service (QoS) attributes and it is not suitable for non-quantifiable quality of service attributes [9]. The aim is to satisfy the user s quality of service requirements via selecting the better infrastructure as a service service. Together, the combined services can offer the better service of cloud to the users via our selection system. III. Proposed Framework That framework includes diversity clouds and services processing unit. The services processing unit in that framework includes these units: provision unit, ranking unit and reservation unit. A. Provision Unit Provision unit be central among consumers of clouds and providers of services through: 1- Presenting all requests from users to providers of services. 2- Aggregating all requests and offers. 3- Responsible about generating a unique id for all requests and offers. 4- After that will providing mapping for all submitted offers and request. 5- Presenting all offers to the ranking unit. 6- Aggregating all ranked offers and presenting it to users. 7- Aggregating resources choice by users and presenting it to reservation unit. www.ijarcst.com 195

ISSN : 2347-8446 (Online) Fig. 1: Cloud Framework [10]. B. Ranking Unit When there are multiple service providers and we want to choice from them, there will be confusion which service they can use and what is the basis for their choice. To avert this scenario ranking mechanism is included. In that unit we will provide ranking for services of clouds via forming hierarchical structure of the quality of service attributes. That attributes are calculated and categorized as first, second and third. Then the relative weights for all attributes are assigned randomly. After that we will calculate ranking vector and ranking matrix for each attributes. In the final the second level ranking vector are aggregated to calculate the ranking matrix of first level attributes and the first level ranking vector aggregated to get the last ranking Matrix. C. Reservation Unit Reservation unit in that framework is responsible about generating a unique reservation id for every reservation request. After that it will get the resources selected by the user, reservation time and period of the cloud selected. With all that details the reservation unit will check the availability. If the requested resources are available for the requested time the reservation unit will close the reserved resources for the reserved period. IV. Hirarachical Structure of Qos Attributes for Ranking That attributes provide the classification of QoS attributes wanted via the customers for choosing the appropriate service providers they are [9][15]. 4.1. Reliability This type of attributes responsible about keeps operating over time without any fail. 4.2. Scalability Scalability is an ability of infrastructure as a service to function well without degradation of other quality of service attributes and Scalability is an ability to scale to any size you want and to be available wherever you want the service. 4.3. Agility The agility is represents important feature of clouds, with agility the organization and companies can extend and will change without any disbursement. 4.4. When we going to clouds the first question the organization will think about it before the organization decide to use clouds is that whether the cost efficacious or not. So, cost is certainly active attributes for IT. 4.5. Assurance All organization prefers and looks to increase their business and provide best services to their customers. So, resiliency, accuracy, and service constancy will be very important for customers before use Cloud services. 4.6. Performance In clouds there will be numerous different solutions and characteristic presented via providers of clouds addressing the IT needs of different organizations and companies. Every solution has different performance in its cloud services in expressions of functionality. Precision and time of service response. 4.7. Security The hosting data and protect it in other organizations is always critical issues which require rigorous security policies by Cloud providers. 4.8. Accountability That is representing major factor to build trust between customers and service providers, the accountability very important to make confidence of a customer on the cloud. V. Case study In our case study we will work on three cloud providers and three user requirements, the cloud providers are Rackspace, windows azure and amazon EC2 they are have geographical distributed and redundant data centers prevalence around the world [11][12][13]. The global availability and failover is provided to customers by them, the data in our case study is aggregated from three cloud providers we mentioned in above for Infrastructure as a Service (IaaS) [14]. We set different priorities and numeric weights for users requirements and we will calculate all steps to ranking computation process for Cloud services under our case study. But in the first we will explain the model will used to compute all these attributes. The relative ranking model for each type of quality of service attributes will be [9]:- 5.1. Boolean: si/sj = 1 if vi vj = wq if vj = 1 and vi = 0 = 1/wq if vj = 0 and vi = 1 5.2. Numeric: Numeric can describe in two types If higher is better than it is vi / vj is the value of si/sj. If lower value is better, vj/vi is the value of si/sj. 5.3. Unordered set: Size (vi) Si/sj = Size (vj) 5.4. Range type: Len (vi vr) Si/sj = Len (vj vr) Wq be the weights given by the user. Vi and vj are the values of the attributes q for cloud services i and j 2013, IJARCST All Rights Reserved 196 www.ijarcst.com

Si and sj be the cloud services,si/sj indicate relative rank of si over sj. Vr be the required value specified by the user. By using compression matrix in above we will get one to one compression of every cloud service for specific attributes. In first step we will calculate the ranking matrix for accountability via data in table 1 for accountability that is showed in figure 2. This window connects to other window has the ranking matrix for all weights of user and weights of cloud services and will compute ranking matrix with the weights of user 1. Fig. 4 : Compute ranking vector for user requirement one Fig. 2: ranking matrix for accountability Ranking Vector for accountability will be: (0.2777-0. 3889-0. 3333) In related way compute ranking vector of other quality of service attributes: Security, agility, assurance, cost, performance, reliability and scalability Security (0. 3333-0.4166-0.2500) agility (0. 3291-0. 3664-0. 3043), assurance (0.3257-0.3372-0.3369), cost (0.3164-0.3208-0.3207), performance (0.3712-0.2158-0.4129), reliability (0.2325-0.4117-0.3530), scalability (0.3571-0.2857-0.3571) In the last, the total ranking vector of all the attributes will be: 0.2777 0. 3333 0. 3291 0.3257 0.3164 0. 3712 0.2325 0.3571 0.3889 0.4166 0. 3664 0.3372 0.3208 0. 2158 0.4117 0.2857 0.3333 0.2500 0. 3043 0.3369 0.3207 0. 4129 0.3530 0.3571 After that we will add all user requirements in other windows application which is illustrated in figure 3 For user requirement one (1): (1.157150 1.303300 1.24585 0). In related way the ranking vector for user requirement two (2) by compute ranking matrix with the weights of user 2. For user requirement two (2): (1.162345 1.165920 1.219585). In related way the ranking vector for user requirement three (3) by compute ranking matrix with the weights of user 3. For user requirement three (3): (1.152385-1.140530 1.141140). For user requirement 1: The values will be (1.157150 1.303300 1.245850). Based on the user requirement 1, the ranked for services of cloud will be Service two (2) > service three (3) >service one (1). For user requirement two 2: The values will be (1.162345 1.165920 1.219585). Based on the user 2 user requirements, the ranked for services of cloud will be Service three (3) >Service two (2)>Service one (1) For user requirement three 3: The values will be (1.152385-1.140530 1.141140). Based on the user requirement three (3), the ranked for services of cloud will be Service one (1) >Service three (3)> service two (2). In this step we will show all comparisons for all user requirements in figure 4 For user requirement one (1) Cloud service 2 will be better in security and reliability. For user requirement two(2) Cloud service 3 will be better in agility and accountability. For user requirement three(3) Cloud service 1 will be better in security and agility. Fig. 3 : user requirement www.ijarcst.com 197

ISSN : 2347-8446 (Online) Fig. 5: Clouds services comparison VI. Conclusion The major advantage of our proposed framework will provide ranking and reservation schemes which the customer can access the right resources at right time without any failure, so our proposed framework exhibits an improvement over existing frameworks already being employed. Else, will assist cloud customers to select the best service provider who fulfills their quality of service requirements. Moreover, for the user who wants to select the best providers based on his requirements must use our proposed framework by ignoring all unnecessary attributes or by increasing the weight of their required attributes. References [1] M. L opez-sanz, C.J. Acu na,c. E. Cuesta, E.Marcos, Modelling of Service-Oriented Architectures with UML, Electronic Notes in Theoretical Computer Science, Elsevier, vol.194,no. 4, pp. 23 37, 2008. [2] A Malik, M. Mohsin, Security Framework for Cloud Computing Environment: A Review, Vol. 3, No. 3, pp. 390-394, March, 2012. [3] Takhellambam Martin Singh, MTech Md Nurul Hasan, MTech Subhranshu sekhartripathy, MTech Better Ranking Of Qos Feedback System in Cloud Computing,International Journal of Advanced Research (2014), Volume 2, Issue 4,1128-1136. [4] Arezoo Jahani, Leyli Mohammad Khanli, Seyed Naser Razavi W_SR: A QoS Based Ranking Approach for Cloud Computing Service ISSN: 2252-4274 [5] F. Chen, X. Bai, and B. Liu, Efficient Service Discovery for Cloud Computing Environments, Advanced Research on Computer Science and Information Engineering Communications in Computer an Information Science, Springer, vol. 153, pp. 443-448, 2011. [6] Security Guidance for Critical Areas of Focus in Cloud Computing, in Cloud Security Alliance (ASA), April, 2009. [7] Mr. K. Saravanan, M.Lakshmi Kantham, An enhanced QoS Architecture based Framework for Ranking of Cloud Services, in the Proceedings International Journal of Engineering Trends and Technology (IJETT), Vol. 4, Issue 4, pp. 1022-1031, April, 2013. [8] Zibin Zheng, Xinmiao Wu, Yilei Zhang, Michael R. Lyu and Jianmin Wang, QoS Ranking Prediction for Cloud Services, Published in IEEE Transactions on Parallel and Distributed Systems, Vol. 24, No. 6, pp. 1213-1222, June, 2013. [9] S. Kumar, S. Versteeg, R. Buyya A framework for ranking of cloud computing services, in Future Generation Computer Systems; Vol. 29, No. 4, pp. 1012-1023. June, 2013. [10] Mamoun Hussein Mamoun, Eslam Mohamed Ibrahim A Proposed Framework for Ranking and Reservation of Cloud Services International Journal of Engineering and Technology Volume 4 No. 9, September, 2014. [11] J. Saurabh Kumar Garg, Steve Versteeg and Rajkumar Buyya, A Framework for Ranking of Cloud Computing Services, in ELSEVIER of Future Generation Computer Systems Vol. 29, No. 4, pp. 1012-1023, June, 2013 [12] A. Li, X. Yang, S. Kandula, M. Zhang, CloudCmp: comparing public cloud providers, in Proceeding of The 10th ACM SIGCOMM conference on Internet measurement, Melbourne, Australia, pp. 1-14, Nov.,2010. [13] A. Iosup, N. Yigitbasi, D. Epema, On the performance variability of production cloud services, in Proceedings of IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CA, USA, pp. 104-113, May, 2011. [14] http://redmondmag.com/articles/2013/03/01/back-up- yoursystems-to-the- public-cloud.aspx last visited 6-2-1014 [15] J. Saurabh Kumar Garg, Steve Versteeg and Rajkumar Buyya, SIMCloud: A Framework for Comparing And Ranking Cloud Services in 4th IEEE International Conference in Utility and Cloud Computing, pp. 210-218, Dec., 2013. Table 1 : User request weight weight user request Accountability w1 Security w2 Agility w3 Assurance w4 w5 Performance w6 Reliability W7 Scalability W8 User Requirement1 0.50 0.40 0.70 0.40 0.30 0.20.60.50 User Requirement2 0.10 0.50 0.40 0.75 0.30 0.80.40.30 User Requirement3 0.20 0.10 0.50 0.55 0.70 0.85.20.95 Table 2: Case Study high Level QoS 1st Level Attributes 2nd Level Attributes Service 1 (S1) Service 2 (S2) Service 3 (S3) Requirement1 Requirement 2 Requirement3 2013, IJARCST All Rights Reserved 198 www.ijarcst.com

Accountability (Weight 1) Security (Weight 2) Agility (Weight 3) Assurance (Weight 4) Capacity (0.6) Elasticity (4) Availability (0.7) Service Stability CPU Disk (1) Upload CPU (0.4) 5 7 6 4 4 8 8 10 6 4 4 8 10.6 11.8 9.8 6.4 GHZ 9 GHZ 8.5 GHZ 12 13 16 10 GB 12 GB 10 GB 1700 2050 650 500 GB 700 GB 750 GB 80-120 520-780 20-200 60-120 Sec 60-120 Sec 99.95% 60-120 Sec 99.99% 100% 99.9% 99% 99% 13.6 15 21 -- -- -- 17.9 16 23 -- -- -- Serviceability (0.1) Free Support (0.7) 7 12 5 -- -- -- 1 1 1 -- -- --,,, (Weight 5) On-Going VM (0.6) Data Storage 0.68 0.96 0.96 <1 $/hour <1 $/hour <1 $/hour 10 10 8 100 GB/ 120 GB/ 110 GB/ 12 15 15 1000 GB 1000 GB 700 GB Performance (Weight 6) Service Range Average Value 80-120 520-780 20-200 60-120 Sec 60-120 Sec 78 50 80 -- -- - 60-120 Sec Reliability(Weight 7) 4 7 6 5 7 6 Scalability(Weight 8) 5 4 5 7 4 4 www.ijarcst.com 199