Dynamic Resource Allocation in Market Oriented Cloud using Auction Method

Transcription

1 2016 International Conference on Micro-Electronics and Telecommunication Engineering Dynamic Resource Allocation in Market Oriented Cloud using Auction Method Neethu B Dept. of Information Technology Govt. Engineering College Painavu, Idukki, India neethumangalath@gmail.com Abstract Cloud Computing provides low cost unlimited computing/storage service for the computing world. Market oriented cloud is a business technique for cloud customers for providing economical and low computing service based on customer demand. Market oriented cloud only focus on the business class users. In this paradigm customers directly interact with service provider and accessing services from the providers with expected cost and qualities. This paper focused on a better online marketing for the both customers and providers for resource allocation. Combinatorial auction with dynamic resource allocation is the main aspects of this paper for resource provisioning. Market oriented cloud computing mainly focused on Infrastructure as a Service (IaaS) layer. It also considers and an intelligent dynamic resource allocation based on the current market rate based on demand. The modified combinatorial double auction method used for detecting an honest cloud service consumers and cloud service providers. Optimal price detection and finding whose the winner of the auction is are the important steps in this method. Here modified Paddy Field Algorithm (PFA) is used for detecting a best consumer and provider. The rest results shows that the proposed system provides better service satisfaction and honest for the consumers and better financial benefit for the service providers. Keywords cloud computing; price matching; price prediction; combinatorial auction; winner determination. I. INTRODUCTION Market oriented cloud computing is an emerging technique of distributed computing environment for the customer satisfaction and optimal price formation. The computing resources, either software or hardware, are virtualized and dynamically allocated the services from provider to consumer. Today cloud computing is the advanced computing technique for the allocation of computing resources to the world with support of internet. The evolution of market oriented cloud is based on the demand of computing resources. Market oriented cloud is method for allocating the computing as a services (IaaS, SaaS, PaaS), sharing the resources and also process, storage and manage large amount of data efficiently in high speed at customer satisfied price. Cloud computing is everlasting continues process for parallel and dynamic distribution of computing resources to the consumers. Resources allocation in cloud computing is obey the computing rules and protocols. Market oriented cloud is major evolution of cloud computing. Market cloud is only focused on business class users, this technique can provide the K.R RemeshBabu Dept. of Information Technology Govt. Engineering College Painavu, Idukki, India remeshbabu@yahoo.com service satisfaction for the consumers and providers at the same time. Online marketing is a big branch of the cloud computing and most probably implemented in Infrastructure as a Services (IaaS) environment. Market oriented cloud is a new model of market balancing system for the participated consumer and provider in the online transaction. The need of market oriented cloud is, provide high quality of services to the consumer wanted and manage the quality of provide services from providers. Providers will need to consider the different service quality parameter of individual consumers and that s way they can achieve the customer satisfaction. Market oriented cloud resource management is necessary to manage supply demand ratio of cloud resource to reach market equilibrium. This paper focused on participant s preference in the auction for selling and buying resources with satisfied price of chooses resources. The system using combinatorial auction in consumer side and producer side at same time and both of them can involve in auction at a time. The identifier of both consumers and producers are important factor of this system, the identifiers can detect a best consumer and producer from the auction and eliminate dishonest participants from the auction. The society can approaches the system when the system participants are trusted and at the same time system responsible for the provision of high quality computing resources. The main problems of existing systems are price allocation and winner determination problem. This system uses paddy field algorithm [19] for winner determination among cloud providers. This paper uses price allocation and price matching algorithm for solving price formulation problem. II. PROBLEM STATEMENT In each round of the auction, the consumers and providers submit their bidding and asking prices for the selected resources. Both price-related factor and non-price factors can significantly influence their asking and bidding price. The pricing decision of customer is not only depend on the supply demand ratio but also historical experience is affected. Price formation mechanism is more affected the customer satisfaction and host. This paper explained the benefit of combinatorial double auction used in the customer and provider at the same time to provide customer satisfaction and revenue of providers. Combinatorial double auction is useful for the consumer and the producers for their truthful auctions. Customers have service satisfaction and trust in their auction is the major asset /16 $ IEEE DOI /ICMETE

2 of this proposed system. The user satisfaction and trust that depend on the number of customer and provider involved in the auction. Combinatorial auction used to solve the problem customer satisfaction and trust. The other benefit of this system is usage of paddy field algorithm for solving the winner determination problem A. Customer Satisfaction and Trust The customer satisfaction is based on number of customers included in the auction and buying the resources. Customer satisfaction is the best objective of this paper. Market oriented cloud is a best approaches for this world for buying and selling their resources use of internet. Online marketing provide honest and dishonest services because the usage of internet. Use of combinatorial auction to identifies the truth full service provider and consumers from the huge number of consumer and provider participated in the auction. Customer satisfaction which means the customer satisfied in the quality of product or services within the time frame. Combinatorial auction with winner determination used to identifies the honest providers and eliminate dishonest participants to achieve customer satisfaction. B. Combinatorial Double Auction Auction is method for selling and buying the resources considering the user preferences. Auction method is very useful method for selling the resources and also to provide a better financial benefit for the service providers. Historical auction method is a single side auction and participated restricted number users and computing resources and price of service is only depend on the consumers demands, Sometimes this method is not satisfies the providers. The problem was addressed by the system propose a combinatorial double auction. The double combinatorial auction is method for the providers and consumers can put the price of differed resources. III. RELATED WORKS The cloud is parallel and distributed system contain virtual computer and inter connected computer are dynamically allocated. The change of cloud computing to market oriented cloud [1] [6] is based on the demand of the computing resources and market oriented cloud is a one type of cloud model. A market is moving in a success way, that depend on the parameters are customer satisfaction, quality of service, price formation and revenue of the providers. The price formation [4] [13] in the cloud market is expressed as chromosomes representation in human body. The determination of price formation function of computing resources is same as the number of genes presented in the chromosomes. This method is expressed using three issues in the gene determination such as define a chromosomes, evaluating the chromosomes and select and reproduction of the chromosomes. The first issue o is define the chromosomes, that contain the parameters are influence the pricing factor [13] of the cloud computing and the factors are fixed price, random price utility maximization and genetic pricing. The second issue is evaluating chromosomes is, the evaluation of the huge number of chromosomes representation and that is compare with reference value of the market. Reference value is the lowest price when the consumer will to pay for the last transaction in cloud market. Selection and reproduction of chromosomes is determine the better chromosomes from enormous amount of chromosomes and remix it with other chromosomes to develop a better chromosomes set. The development of market place [6] [7] [14] depend on the involvement of IT in the world. The paradigms of information technology and internet used to allocate the computing resource to customers. The allocations of computing resources in the form of services are platform, software and infrastructure to all around the world. The computing resources are allocated in parallel and dynamically [2] [8][12] [3] to manage the service level agreement (SLA). The cloud computing transferred to market oriented cloud with pricing model [4] and open cloud exchange [6]. Virtualization is the main aspect of the cloud computing that used to develop the cloud stacks are Infrastructure as a Service (IaaS), Software as s Service (SaaS) and Platform as a Service (PaaS). Now the market oriented cloud focused on the combinatorial auction [5][7][8].The auction changed to combinatorial auction based on the multiple users [10] in the marketing. Auction is a method for selling and buying the resources with support of demanded an asking price of consumer and provider. In a single auction restricted amount of computing resources is possible. Now the combinatorial double auction used for the allocation of computing resources with unrestricted number of resources and participants in the auction. The consumer and provider have the freedom for determine the price of demanded services and supplied services. At single auction the revenue of the providers is reduced but the use of double auction to balance the asking price and bidding price of the resources and increases the revenue of providers [13]. Market oriented cloud [1] [6] is model of cloud computing to deliver the computing resources in a similar manner to traditional utilities such as gas, electricity and water etc. The marketing using the characteristics of information technology for the computing resource allocation [7] [15] [16].The cloud marketing is using cloud service is Infrastructure as a Service(IaaS) and the market demand the Quality of service (QoS) [14].The Multiple consume and provider [16]included in the marketing to reduce the quality of services. The problem solved by using combinatorial auction, price prediction [17] and winner determination [15]. Usage of information technology paradigms to develop the architecture and model of market oriented cloud. IV. SYSTEM DESIGN The parallel and dynamic resource allocation system framework is proposed to comprehensive deal with denote the resource allocation challenges, and multiple user demand problem. An improved combinational double auction protocol is used to enable various kinds of computing resources with multiple consumers and multiple providers.. A price formation mechanism is devised. A prediction algorithm is proposed with initial price and random price and non-price factor considered

3 to make bidding and tasking reasonable, a price matching algorithm is used to determine eligible transaction relationship with customer and providers. The PFA (Paddy Field Algorithm) is improved to WDA (Winner Determination Algorithm) is proposed, expressed WDAPFA (Winner Determination Problem paddy field algorithm). Participants who can bring the maximum market surplus is preferred to be winners in the auction. Thus, the proposed system is customer satisfied, efficient and trusted. The system considers of the customer satisfaction and trust in the auction. Combinatorial double auction method is very useful method than the static auction. Our proposed reputation system obeys the following intuitions. If a participant participated in auction frequently and his turnover is high and reputation is also high. If a participant participated all transaction are successful and his reputation is high. The proposed system uses combinatorial auction for huge number of participants. The advantages of combinatorial auction is A combinatorial auction mechanism is proposed for achieve a customer satisfied and trusted system. Simulate truthful and computationally efficient auction mechanisms for cloud resource pricing in market. A reputation system is used to eliminate dishonest participants. Input the buyer submit bidding price and provider submit their asking price to the Agent of theirs. Auctioneer announces start of the auction to the participants of the auction. Agents of cloud consumers and providers send their bids and asking price to the auctioneer. Winner determination using pricing adjustment algorithm. Buyer and provider agree the beneficial value and allocated the resource otherwise find out a threshold price for the resources. Price adjustment will be calculated and both are agree the threshold price and allotted the resources. V. COMBINATORIAL DOUBLE AUCTION An auction is a process of buying and selling of commodities by providing a bid and then selling the resources to the highest bidder from the collected bid and this is used in cloud and market oriented cloud. It can be closed or open. Auction can be classified as single side auction and double side auction. In a double auction, both buyers and sellers select bids and ask price for the resources and these auctions are continuous because it called as combinatorial double auction. Double auction based resource allocation mechanism is an appropriate market-based model for cloud computing and allows double-sided auction competition and bidding on an unrestricted number of resource selection. The architecture for the proposed system is more efficient for resource utilization and the financial benefit for the providers and users. Combinatorial double auction based mechanism is best suited for resource allocation in clouds market because they can provide customer satisfaction for the consumers. However, the proposed system to overcome certain challenges while using combinatorial auction-based mechanisms such as price formation, revenue of the providers. Fig. 3 defined the flow chart. A. Algorithm Discription Based on the flow chart, how the double auction possible is described below. Fig 1.The CDA System Framework B. Tender Description Here the auction is based on two types of tenders for customer and provider. The demand of the consumer is mentioned in the customer tender. Their bidding price, CPU speed, memory requirement and storage requirement are mentioned in this tender. The provider tender contains the details of their demanding price, CPU speed, memory, and storage specifications. C. Price Formation The pricing decision of customer is not only depend on the supply demand ratio but also historical experience is also affected. Price formation mechanism is more affected the customer service satisfaction and trust. Price formation technique is the main fact of market equilibrium. The coordination of consumer price and provider price can control or balancing the marketing

4 D. Winner Determination Winner determination is main problem of the online marketing. In this paper defined the problem formulation and winner determination algorithm. The PDF algorithm is given in fig. 2. Initialization: Population: p plants each located randomly in the search space; Set maxiter_value and n; Set generation_counter iteration = 1; repeat Calculate fitness of each plant (yi) and store in vector N (Ni = f itness(yi : i = 1,..., p)); Sort N : (Ni : i = 1,..., p) into descending order (Objective is to maximise fitness); for i = 1 : n (top n plants) do Generate seeds for each selected plant; Implement pollination step; Disperse pollinated seeds; end Replace old population with new plants; iter = iter+1; until iter = maxiter_value ; Output the best location found; Fig. 2. Modified Paddy Field algorithm Fig. 3. Double Auction Flow Chart VI. EXPERIMENTAL SETUP AND PERFORMANCE ANALYSIS The proposed system is implemented based on net beans on java platform. The project that implemented using net bean tool.tool used to represent the project out lines. It contains four level of logins is possible consumer, provider, two identifiers and admin. The two identifiers can follow the reputations of this paper. The identifier to check both provider and consumers are trusted or not illegal. The consumer and provider can log into the project and they can auction it the providers adding the product. The reputation system of this project that depend on the identifiers,the identifiers can check the providers product quality and product value compare with other sites or the real world value of the product. Then can provide the facilities for the bidding if any illegal issues find out at the time of checking they can inform to the admin for removing the consumer or the provider using the customer id. In order to evaluate economic efficiency and trustfulness of proposed system, the system to verify its effectiveness and compare its performance with SCDA (Stable Continuous Double Auction) to resource allocation Resource allocation among self-interested participants in a dynamic and distributed market, and resource providers and consumers have their own asking/bidding strategies. Due to the online marketing and auction nature, the proposed system chooses SCDA as the comparison benchmark. The performance of proposed system is based on the number of customers using the system at different time. A. Tools Used Free cloud server used to implement this project in java platform. This project using a account for storing the information in server. First Net beans used to simulate the project using java. Then the created project hosted in free cloud using the created account. 1) NetBeans :NetBeans is a platform for the development of software and written in Java. The NetBeans Platform is allows the applications to be developed from a set of modular software components called modules. Applications based on the NetBeans Platform, with the NetBeans integrated development environment (IDE), can be extended by third party developers. The NetBeans IDE is initially intended for development in Java, but also using other languages, that are PHP, C/C++ and HTML5. NetBeans is also a cross-platform and runs on Microsoft Windows platform, Mac OS X, Linux, Solaris and other platforms are using a compatible JVM. The NetBeans Team actively support the product and seek feature suggestions from the wider population. Every release is come before by a time for Community testing and feedback 2) Java:Java is a new type of computer programming language developed by Sun Micro systems. Java has a good chance to reach at first really successful new computer program in several uncomfortable environment. Advanced programmers like this new language for the development of software because the language contain a clean and welldesigned definition. Business likes the language because it promote an important new software application like Web programming. 3) Hosting with EATJ The characteristics EATJ is defined below, Reliable: EATJ used in business for 9 years. The proposed system never had any advertisement. All our customers are from referral or web search engine. The

5 proposed system data center is California, USA. All servers are backed by N+1 redundant UPS Systems in additional to support by the Diesel Generators. Recently record is 100% uptime. Support: the system has knowledge team to provide 24x7 technical support. The participants can send or live chat. B. Experimental Results The experiment of this project based on compare performance between IEDA and existing system, the project use the relative values of transaction number and runtime overhead. 1) Customer Satisfaction and Trust Comparison of transaction numbers between IEDA and existing system under different supply and demand relations with medium scale. It can be seen that the number of transactions successfully dealt with in IEDA is the same as that in existing system, one CSC demanded service can be partitioned to and carried out by multiple CSPs in IEDA, and then more transactions are accommodated. Customer satisfaction is always depending on the Number of transactions. The cloud resource allocation using double auction can provide a better customer satisfaction for purchasing the product, because using double auction method used for a better treatment for the provider and consumer at a time, the service provider and service consumer can put there on value for the product. The price allocation method used to detect a threshold value for the product compare with the real time value of the product otherwise the service provider satisfied the value of the product they can provide the product for the consumer. This system can provide a better customer satisfaction for the consumers Number of customers Time(hr) Fig. 4 Customer Satisfaction SCDA IEDA Number of customers 2) Runtime Overhead Fig. 5. Customer Trust Comparison of runtime overhead of proposed system and existing system under different market scales with balanced supply and demand relation. number of transaction Time(hr) Time(hr) Fig. 6. Runtime Overhead IEDA SCDA SCDA IEDA It can be seen that the runtime overhead of proposed system is larger than SCDA. Runtime overhead of proposed system is some time slower than SCDA, because of the number of transaction is increases but that not affected the advantages of proposed system. VII. CONCLUSION Based on the customer satisfaction and revenue of providers with price prediction algorithm, combinatorial double auction based dynamic resource allocation approach is proposed for cloud services. The system framework is devised to provide a better solution. A reputation system is used to eliminate honest participants. A price formation mechanism is proposed to predict price and determine eligible transaction relationship of customer and providers. WDP is optimally solved by the improved PFA in the proposed system. Simulation results validate the customer satisfaction and runtime overhead. A. Future Work Combinatorial double auction used in the proposed system to achieve customer satisfaction and revenue of the providers. The future work of this proposed system is based on combinatorial double auction with modified price prediction used to provide a financial benefit project for the providers. The modified price prediction depends on the market surplus to balance the bidding price of customers and asking price of the providers

6 REFERENCES [1] R. Buyya, C. S. Yeo, and S. Venugopal, Market-oriented cloud computing: Vision, hype, and reality for delivering IT services as computing utilities, IEEE Trans. Conf. High Perform. Comput. Commun., vol. A247, pp , [2] S. Zaman and D. Grosu, A combinatorial auction-based mechanism for dynamic VM provisioning and allocation in clouds, IEEE Trans. Cloud Comput., vol. 1, no. 2, pp , Oct [3] I. Fujiwara, K. Aida, and I. Ono, Applying double-sided combinational auctions to resource allocation in cloud computing, IEEE/IPSJ Int. Symp. Appl. Internet,pp.7-14, [4] Maci as and J. Guitart, A genetic model for pricing in cloud computing markets, ACM Symp. Appl. Comput., [5] Teimourib, and M. Mukhtara, A combinatorial double auction resource allocation model in cloud computing, Inf. Sci., [6] A. Bestavros and O. Krieger, Toward an open cloud marketplace vision and rst steps, IEEE Internet Comput., vol. 18, no. 1, pp , Jan./Feb [7] S. F. Shang, J. L. Jiang, Y. W. Wu, G. W. Yang, and W. M. Zheng, A knowledge-based continuous double auction model for cloud market, in Proc. IEEE 6th Int. Conf. Semantics Knowl. Grid, pp ,2010. [8] [1] W. J. Shi, L. Q. Zhang, C. Wu, Z. P. Li, and F. C. M. Lau, An online auction framework for dynamic resource provisioning in cloud computing, ACM SIGMETRICS Perform. Eval. Rev., vol. 42, no. 1, pp , [9] [1] M. Mac as and J. Guitart, Cheat-proof trust model for cloud computing markets, Econom. Grids, Clouds, Syst., Services Lecture Notes Comput. Sci., vol. 7714, pp , [10] [1] S. Di and C. L. Wang, Dynamic optimization of multi-attribute resource allocation in self-organizing clouds, IEEE Trans. Parallel Distrib. Syst., vol. 24, no. 3, pp , Mar [11] G. S. Atsalakis and K. P. Valavanis, Surveying stock market forecasting techniques-part II: Soft computing methods, Expert Syst. Appl., vol. 36, no. 3, pp , 2009 [12] H. Zhang, B. Li, H. B. Jiang, F. M. Liu, A. V. Vasilakos, and J. C. Liu, A framework for truthful online auctions in cloud computing with heterogeneous user demands, IEEE INFOCOM, pp ,2013. [13] H. Xu and B. C. Li, Dynamic cloud pricing for revenue maximization, IEEE Trans. Cloud Comput., vol. 1, no. 2, pp , Jul. Dec [14] T. Hobfeld, R. Schatz, M. Varela, and C. Timmerer, Challenges of QoE management for cloud applications, IEEE Commun. Mag., vol. 50, no. 4, pp , Apr [15] L. Q. Zhang, Z. P. Li, and C. Wu, Dynamic resource provisioning in cloud computing: A randomized auction approach, IEEE INFOCOM, pp ,2014. [16] W. J. Shi, L. Q. Zhang, C. Wu, Z. P. Li, and F. C. M. Lau, An online auction framework for dynamic resource provisioning in cloud computing, ACM SIGMETRICS Perform. Eval. Rev., vol. 42, no. 1, pp , [17] [1] K. Y. Chan, T. S. Dillon, J. Singh, and E. Chang, Neuralnetworkbased models for short-term traf c ow forecasting using a hybrid exponential smoothing and Levenberg Marquardt algorithm, IEEE Trans. Intell. Transp. Syst., vol. 13, no. 2, pp , Jun [18] Xingwei Wang, Xueyi Wang, Hao Che, Keqin Li, Min Huang, and Chengxi Gao, "An Intelligent Economic Approach for Dynamic Resource Allocation in Cloud Services", IEEE Transaction on Cloud Computing, vol. 3, pp , July-September [19] Upeka Premaratne, Jagath Samarabandu, Tarlochan Sidhu, "A new biologically inspired optimization algorithm", International Conference on Industrial and Information Systems (ICIIS), pp ,