Comparison of Revenue Sharing Mechanisms in Cloud Federation

Transcription

1 Comparison of Revenue Sharing Mechanisms in Cloud Federation Sameera Dhuria Sri Guru Granth Sahib World University, Fatehgarh Sahib Anu Gupta Panjab University, Chandigarh R.K. Singla Panjab University, Chandigarh ABSTRACT: Different Cloud Providers (CPs) collaborate with each other to form a Federation of Clouds. Cloud Federation enables resource among collaborating CPs and hence helps in overcoming limited scalability problem of a single provider Cloud. Revenue is generated from exchange of resources in Federation and is shared among CPs belonging to the Federation based on some agreed upon mechanism. With the aim to find a suitable mechanism for outsourced resources in a Federation of Clouds, this paper compares the existing strategies proposed/discussed in the literature and identifies their limitations. The identified limitations result in the requirement of a better mechanism that can overcome existing limitations and provides fair share of revenue to each participating CP. KEYWORDS: Cloud Federation, Revenue Sharing, Outsourcing, Insourcing 1. INTRODUCTION Cloud computing technology offers seemingly infinite infrastructure for hosting and deployment of Webbased applications. Using Cloud computing, service providers are relieved from the responsibility of provisioning the computational resources needed to support these applications. Companies can easily rent infrastructure resources on demand from a virtually unlimited capacity. The pay-as-you-go model is used for billing. In this model, charges are applied for the resources actually used in a given time period. In this manner, companies are able to optimize their IT (Information Technology) investment, ensure resource availability and improve scalability. Though Cloud computing provides many benefits, it has some major limitations like lack of standard interfaces which results in vendor lock-in, limited scalability etc. [1]. To overcome these limitations, the concept of Cloud Federation has been introduced. It is a new paradigm that enables Cloud providers to share resources among each other [2]. Cloud Federations are broadly classified as follows [3]: Centralised In this Federation, resource allocation is done through a central entity. All the available cloud resources are registered with this central entity; that acts as a repository and a market place for resources. Peer-to-Peer Here, different CPs directly communicate with each other without the help of any central entity. In Cloud Federation, each CP provides resources requested by its own users and also fulfills resource requirement of other members of Federation. A CP may also request resources from one or more peer members to fulfill the resource requests of its own internal users which it is not able to fulfill due to limited capacity of local resources. Such outsourcing and insourcing mechanisms result in generation of revenue. These mechanisms help providers to obtain more profit when used in an appropriate manner and contribute in the of revenue among CPs participating in Cloud Federation [2]. The strategy followed for of revenue in such a scenario must be carefully chosen. This is because CPs would outsource or insource resources in a Federation only if the revenue obtained is profitable for them 144 Sameera Dhuria, Anu Gupta, R.K. Singla

2 otherwise they would simply prefer to reject the requests for resources of their own customers or of outsourcing CPs. Apart from profit assurance, the strategy must distribute the generated revenue among participating CPs in a fair manner. Keeping this in view, the problem of in Cloud Federation needs to be thoroughly examined and a method must be found that assures the economic benefit of each CP belonging to the Federation [4]. In this context, this paper performs a literature review of the strategies in Cloud Federation. The paper is organized as follows: Section 2 provides an overview of problem in Cloud Federation. A comparative review of the work done in the area of has been made in Section 3. Existing strategies of and their limitations are discussed in Section 4. Key Findings from the Literature Review are discussed in Section 5. Section 6 concludes the paper. 2. REVENUE SHARING IN CLOUD FEDERATION Revenue of a CP in Cloud Federation can be obtained in three ways [5][6][2]: A. Provider s own resources When a service request arrives, the CP allocates as many resources as it can and thus earns revenue from its own resources. B. Outsourcing If the provider does not have sufficient resources to fulfill the request, it may outsource the request to other CP that are part of the Federation, on the basis of FLA. Here, total revenue becomes the revenue of provider itself and revenue earned from outsourcing. C. lnsourcing When the provider has underutilized resources, instead of keeping the resources idle, it may sell (insource) the extra resources. Here total revenue becomes sum of the revenue earned by fulfilling service requests of users from its own resources and revenue earned by leasing resources to other providers. Total revenue of a CP in Federation is the sum of revenue generated from provider's own resources, revenue generated from outsourcing and revenue generated from insourcing. Every CP in the Federation completely keeps the revenue earned from its own resources which may also be called standalone revenue. The revenue earned from the outsourced and insourced resources has to be shared among requesting and contributing CPs. It must be distributed appropriately using a suitable mechanism in such a manner that each participating CP gets a fair share of it. Selection of a suitable mechanism is very important because CPs would prefer to collaborate and contribute idle resources only if they obtain satisfactory revenue i.e. if their economic interest is ensured. 3. COMPARATIVE REVIEW OF REVENUE SHARING MECHANISMS Different mechanisms have been discussed/proposed in the literature. For resource and, a game theoretical approach is used in [7] and [8]. In [2], is based on pricing factor α applied to outsourced resources. In [9], an energy-aware resource and revenue mechanism based on cooperative game theory is proposed for a Cloud Federation. Double auction based mechanism is used in [10] to calculate the time-averaged revenue of a CP from selling VMs to other CPs. In [4], it is discussed that revenue earned by each CP must be on the basis of work performed by it i.e. fairness must be there. Three methods of have been discussed. The approach followed for outsourcing is that each CP in the Federation has free access to the resources of other CPs in the Federation i.e. there is no need to pay any amount for outsourced resources. Revenue is distributed through a mutually agreed scheme, generally defined in Federation Level Agreement, after a certain period of time. In [6], revenue of outsourced resources is shared based on idling capacity based dynamic pricing. A comparative review of the work done in the area of has been made in Table 1 on the basis of following attributes. 145 Sameera Dhuria, Anu Gupta, R.K. Singla

3 1.) Revenue strategy discussed/proposed in each paper. 2.) Federation Scenario where strategy is used. 3.) The VM type being used for revenue calculation. 4.) Whether the proposed strategy has been implemented. The schemes mentioned in the below table are discussed in Section 4. Paper Table 1: Comparative Review of Strategies Revenue strategy discussed/ proposed Federation Scenario VM Type outsourced Implementation Zant et al.[4] Outsourcing factor alpha based, Proportional and Shapley value Peer to Peer On demand Numerical Analysis via Simulation Toosi et al.[6] Dynamic Pricing based Cloud Exchange On demand Simulation Goiri et al.[2] Pricing factor alpha based Peer to Peer (using scheduler on each CP) On demand Simulation Hassan et al.[9] Li et al.[10] Tang and Chen[11] Broker s strategically decided price based Double Auction Bid pricing based Double Auction Bid pricing based Broker based On demand Simulation Broker based On demand Theoretical Broker based On demand Numerical Analysis based Validation 4. EXISTING STRATEGIES AND THEIR LIMITATIONS A brief overview of different strategies and the limitations associated with them are discussed in the below table: Table 2: Revenue Sharing Strategies and their Limitations Paper Strategy Brief Description Limitations Outsourcing factor alpha An outsourcing factor α, with a fixed value, is associated to each CSP for pricing. The revenue of outsourcing and insourcing CPs is obtained based on this value e.g. a value of 0.7 of α means that outsourcing CP will get a share of 70% of the generated revenue and host CSP will get 30% share. 1. The total generated revenue is divided among collaborating CPs based on value of α irrespective of the number of VMs contributed by each. 2. This may cause loss to outsourcing CPs if they get less revenue as compared to the VMs contributed. 3. It may also cause host CPs to obtain very less revenue despite running maximum VMs by themselves and outsourcing very less no. of VMs. 146 Sameera Dhuria, Anu Gupta, R.K. Singla

4 Proportional Each CSP gets revenue proportional to the work performed which is equal to number of working hours in this strategy. 1. Apart from the revenue obtained from shared resources, stand alone revenue of each CP is also included in the approach. 2. No consideration is given to the origin of request and the number of VMs contributed in Federation. This may force a CP to reject the request than to outsource if revenue incentives are not considerable. Zant et al.[4] Shapley value Based on coalitional game theory, this technique has been proposed for the problem. Players create a coalition and cooperate with each other to earn extra profit and revenue. Contribution of each player to all possible sub-coalitions is taken into account and Shapley value of each player is calculated using Shapley Equation. 1. Coalitional game must be superadditive to ensure the stability of solution provided by the Shapley value. Toosi et al.[6] Dynamic Pricing Here own and outsourced revenue is calculated by multiplying fixed VM price with no. of VMs. Revenue from insourcing is calculated by multiplying dynamic VM price with no. of VMs. Time for which VMs are provided is not considered. 1. Dynamic pricing of resources in revenue for outsourced resources may cause loss to CP in situations where idling capacity of insourcing CP is very low. Goiri et al.[2] Pricing factor alpha based Here own and outsourced revenue is calculated by multiplying fixed VM price with no. of VMs and time duration. Revenue from insourcing is calculated by multiplying alpha based VM price with no. of VMs and time duration. 1. Price of all CPs is fixed. In real scenario price of collaborating CPs would be different. So it is important to decide the CP (outsourcing or insourcing) with which alpha will be used. 2. The value of alpha is also significant. On what basis and how this value is calculated, is not mentioned. Hassan et al.[9] Broker s strategically decided price An energy-aware resource and revenue mechanism based on cooperative game theory is proposed. 1. Federation scenario considered is not appropriate. Strategy is not applicable in centralized/peer to peer Federation. 2. Pricing doesn t involve consent of CPs. Li et al.[10] Tang and Chen [11] Double auction CPs acting as buyer and seller, present buy bid and sell bid. A broker in Cloud Federation (assuming the role of the auctioneer) collects all buy and sell bids, executes a double auction to decide the set of successful buy and sell bids and their clearing prices. Revenue is shared based on these prices that are different in each time slot. 1. Applicable on broker based Federation scenario. 2. CPs may strategically manipulate the bid prices and volumes to maximize their profit. 147 Sameera Dhuria, Anu Gupta, R.K. Singla

5 5. FINDINGS FROM THE REVIEW Ideally, a policy in Cloud Federation must consider following aspects: 1. Participating CPs must always get profitable revenue from outsourcing. 2. Revenue must be shared on the basis of number of VMs contributed by the CPs i.e. each CP should get revenue based on its work performed. 3. Time for which VMs are used must be included in calculation of revenue. 4. Suitable pricing mechanism must be used as price of outsourced resources plays an important role in revenue generation. From the discussion in Section 3 and 4, it is evident that there is no scheme proposed/implemented in the literature that considers all the above aspects while distributing revenue among CPs. Instead, existing solutions of have so many other problems associated with them, discussed in Table 2. As a whole, no existing scheme of revenue distribution is suitable to be used as such in Cloud Federation. Therefore, there is a requirement of finding a better mechanism (either new or a modified version of existing mechanism) that overcomes limitations of existing solutions and ensures a fair share of revenue to each participating CP, considering all the above discussed aspects. This will encourage resource contribution in Federation; and prevent rejection of service requests of internal users as well as of peer CPs. 6. CONCLUSION Cloud Federation allows different CPs to share their resources among each other. Sharing of resources in Cloud Federation results in exchange of revenues. Strategy for should be carefully chosen so that revenue is divided among CPs in an appropriate way and profitability of collaborating CPs is ensured. Review of various mechanisms in the literature has been performed and the limitations of each approach have been discussed. None of the mechanisms in the literature is found to be suitable for generating fair share of revenue for all the participating CPs. This generates the need of designing a new and better mechanism that overcomes the limitations (related to Federation scenario, dynamic pricing etc.) of existing solutions. REFERENCES [1] Rochwerger, B., Breitgand, D., Levy, E., Galis, A., Nagin, K., Llorente, I.M., Montero, R., Wolfsthal, Y., Elmroth, E., Caceres, J. and Ben-Yehuda, M.: The reservoir model and architecture for open federated cloud computing. IBM Journal of Research and Development. 53(4), 4-1 (2009). [2] Goiri, I., Guitart, J. and Torres, J., 2010, July. Characterizing cloud federation for enhancing providers' profit. In Cloud Computing (CLOUD), 2010 IEEE 3rd International Conference on (pp ). IEEE. [3] Grozev, N. and Buyya, R., Inter Cloud architectures and application brokering: taxonomy and survey. Software: Practice and Experience, 44(3), pp [4] El Zant, B., Amigo, I. and Gagnaire, M., 2014, March. Federation and in cloud computing environment. In Cloud Engineering (IC2E), 2014 IEEE International Conference on (pp ). IEEE. [5] Patel, K.S. and Sarje, A.K., 2012, July. VM provisioning policies to improve the profit of cloud infrastructure service providers. In Computing Communication & Networking Technologies (ICCCNT), 2012 Third International Conference on (pp. 1-5). IEEE. [6]Toosi, A.N., Calheiros, R.N., Thulasiram, R.K. and Buyya, R., 2011, September. Resource provisioning policies to increase iaas provider's profit in a federated cloud environment. In High Performance Computing and Communications (HPCC), 2011 IEEE 13th International Conference on (pp ). IEEE. [7] Niyato, D., Vasilakos, A.V. and Kun, Z., 2011, May. Resource and with coalition formation of cloud providers: Game theoretic approach. In Cluster, Cloud and Grid Computing (CCGrid), th IEEE/ACM International Symposium on (pp ). IEEE. [8] Lu, Z., Wen, X. and Sun, Y., 2012, October. A game theory based resource scheme in cloud computing environment. In Information and Communication Technologies (WICT), 2012 World Congress on (pp ). IEEE. [9] Hassan, M.M., Abdullah-Al-Wadud, M., Almogren, A., Song, B. and Alamri, A., Energy-aware resource and revenue management in federated cloud: a game-theoretic approach. IEEE Systems Journal, 11(2), pp [10] Li, H., Wu, C., Li, Z. and Lau, F.C., 2013, April. Profit-maximizing virtual machine trading in a federation of selfish clouds. In INFOCOM, 2013 Proceedings IEEE (pp ). IEEE. [11] Tang, L. and Chen, H., 2015, June. Double auction mechanism for request outsourcing in cloud federation. In Communication Workshop (ICCW), 2015 IEEE International Conference on (pp ). IEEE. 148 Sameera Dhuria, Anu Gupta, R.K. Singla