Gaurav Baranwal

A fair multi-attribute combinatorial double auction model for resource allocation in cloud computing

Abstract Recently, Cloud computing has emerged as a market where computing related resources are treated as a utility and are priced. There is a big competition among the Cloud service providers and therefore, the providers offer the services strategically. Auction, a market based resource allocation strategy, has received the attention among the Cloud researchers recently. The auction principal of resource allocation is based on demand and supply. This work proposes a multi-attribute combinatorial double auction for the allocation of Cloud resources, which not only considers the price but other quality of service parameters also. Auctioneer extends some of the parameters to the offered bids from the bidders in order to provide fairness and robustness. In case of not meeting the assured quality, a penalty is imposed on the provider and customer is compensated. The reputation of the provider also diminishes in the forthcoming rounds. Performance study of the proposed model is done by simulation which reflects the usefulness of the method.

A systematic study of double auction mechanisms in cloud computing

A detailed study of the double auction mechanisms in cloud is provided.A framework for double auction in cloud is proposed for a future cloud market.A model TMDA is proposed to infer how a truthful double auction can be designed.TMDA is asymptotically efficient, individual rational, truthful and budget-balanced.Various challenges and future scope in double auction in cloud are also presented. The cloud system is designed, implemented and conceptualized as a marketplace where resources are traded. This demands efficient allocation of resources to benefit both the cloud users and the cloud service providers. Accordingly, market based resource allocation models for cloud computing have been proposed. These models apply economy based approaches e.g. auction, negotiation etc. This work makes a detailed study of the double auction mechanisms and their applicability for the cloud markets. A framework for a future cloud market using double auction is also proposed. As most of the existing works in double auction confines only resource allocation, therefore, a Truthful Multi-Unit Double Auction mechanism (TMDA) is proposed that would help researchers to understand how a truthful double auction mechanism can be designed. TMDA is proven to be asymptotically efficient, individual rational, truthful and budget-balanced. TMDA would also encourage researchers to contribute in this emerging area. The performance of TMDA, which addresses the interests of both the cloud user and the provider, has been validated through simulation study. Various challenges in the realization of double auction mechanisms in cloud computing along-with the future possibilities are also presented.

Admission control in cloud computing using game theory

Cloud computing is emerging as a promising platform for ubiquitous computing where various types of resources are offered on pay-per-use basis. Cloud services are basically offered at three levels; infrastructure, platform and software. Service providers of these services are often interested to maximize their revenue and at the same time Cloud users expect for optimum quality of services. Sometimes, these two may conflict and admission of the requests is to be done that satisfies both Cloud providers and consumers. Game theory is a mathematical study of strategic decision making in which two players are involved in decision making based on their strategic moves. This work, applies the concept of game theory in admission control for Cloud requests. A model has been proposed and its performance study is done by simulating it in CloudSim simulator. Results are encouraging and may suggest for its possible inclusion in the Cloud middleware.

A negotiation based dynamic pricing heuristic in cloud computing

Over the years, cloud computing has emerged as a good business platform for IT related services. In cloud, prices of computing resource act as lever to control the utilisation of the resources. That is the reason, when the number of cloud customers started increasing, cloud service providers started offering resources with various pricing schemes to attract customers. This work proposes a negotiation based heuristic for dynamic pricing that considers behaviour of both the service provider and the customer and tries to optimally satisfy both for pricing. Both customer and provider are reluctant to reveal information about their utility to each other. The designed utility function for provider considers payment offered by customer and opinion of the provider about customer. Similarly, utility function for customer considers price offered by the provider and opinion of customer about provider. This will encourage both to offer their true value. Performance study indicates that the proposed method performs well and is a potential candidate for its implementation in a real cloud.

A Truthful and Fair Multi-Attribute Combinatorial Reverse Auction for Resource Procurement in Cloud Computing

Resource procurement using reverse auction in Cloud computing is an interesting but a complex problem as it involves many attributes and constraints. Reverse auction is a mechanism in which a customer prepares call for proposal of resource requirement and publicizes it in order to get the attention of eligible service providers. This work proposes a multi-attribute combinatorial reverse auction for Cloud resource procurement which considers price as well as non-price attributes such as quality of service parameters, reputation etc. in the determination of winning service providers. For this, the problem is formulated using approximation algorithm and near optimal solution is obtained in polynomial time. Auction mechanism allows providers to reveal true information in order to maximize their profit. It also imposes a penalty on the providers who cheat i.e., do not offer the agreed upon services. This makes the system robust as it maintains the utility of the customer. It also maintains a healthy competition among the providers. Performance evaluation and a comparative study with some base line models exhibit that the proposed method performs better.

An econometric based model for resource scarcity problem in Cloud computing

Resource provisioning in Cloud computing is an important problem as the resources are scarce. Better utilization of the existing unutilized resources may solve the future resource scarcity problem. To decide, how much percentage of unutilized allocated resources the Cloud manager can take back to solve the problem of scarcity of resource in future, an econometric model of distributive justice is identified and mapped to resource redistribution in Cloud computing. The proposed model uses a Probit model to get the value of coefficient which helps to determine the percentage of unutilized allocated resources to be taken back. Data is increasing at the enormous rate warranting mass storage. Thus, Cloud storage has been considered an important scarce resource. The proposed model focuses on the Cloud storage as a resource. It is assumed that service provider must reserve certain amount of resource to accept sharply increased resource request. The proposed model also identifies this constraint and proposes a model of distributive justice that addresses this. Experimental results reveal the efficacy of the proposed model.

A Truthful Combinatorial Double Auction-based Marketplace Mechanism for Cloud Computing

Abstract Designing market-based mechanism that benefits both the cloud customer and cloud provider in a cloud market is a fundamental but complex problem. Double auction is one such mechanism to allocate resources that prevents monopoly and is used to design an unbiased optimal market strategy for cloud market. This work proposes a truthful combinatorial double auction mechanism for allocation and pricing of computing resources in cloud. For resource allocation, utilitarian social welfare maximization problem is formulated using Integer Linear Programming (ILP) and a near optimal solution is obtained using Linear Programming based padded method. For payment, truthful and novel schemes are designed for both customers and providers. Moreover, the proposed mechanism is individual rational, computationally tractable, weakly budget-balance and asymptotic efficient. Performance evaluation and comparative study exhibit that the proposed mechanism is effective on various performance metrics such as utilitarian social welfare, total utility, customers’ satisfaction, providers’ revenue and hence is applicable in real cloud environments.

Reverse Auction-Based Cloud Resource Provisioning

Out of many auction techniques, reverse auction is the one in which providers act as bidders. In this chapter, a detailed description of reverse auction and its benefits to Cloud providers and customers are discussed. Various attributes of reverse auction are presented in the Cloud scenario for its applicability. Various auction properties, an auction designer vies to achieve, have also been listed and deliberated. A detailed and comparative survey of existing works in reverse auction on the basis of auction properties is given to better understand the state of the art of reverse auction in Cloud. A truthful combinatorial reverse auction model is also presented to help in understanding and designing a reverse auction mechanism for the Cloud researchers in order to achieve a defined goal. Open research issues are highlighted to provide an insight for the future research work in this area.

Double Auction-Based Cloud Resource Provisioning

In double auction, both the user and the provider bid in the market. In this chapter, a detailed description of double auction mechanisms and their applicability in Cloud market is discussed. Various auction properties, that a double auction mechanism should satisfy, have also been discussed and deliberated. A detailed survey of related work in double auction-based Cloud resource provisioning and pricing is provided. A truthful multi-unit double auction-based model is also presented to help and motivate the Cloud researchers/academicians to design such efficient and truthful mechanisms for the Cloud market. Finally, research challenges and issues are identified with future research possibilities.

Forward Auction-Based Cloud Resource Provisioning

Forward auction, also known as “sell-side auction”, has multiple buyers and single seller in the auction market. The buyers compete by bidding their valuations for the required quantity of resources. In Cloud computing, Amazon sells its unutilized capacity using forward auction. In this chapter, a description of combinatorial forward auction with their relevance and applicability in Cloud is discussed in detail. A combinatorial auction-based formulation is given for the VM provisioning and pricing problem in Cloud market. Some possible allocation algorithms and pricing schemes are discussed for the formulated problem. A detailed survey of existing combinatorial auction mechanisms in Cloud computing is given. Finally, research challenges and issues are discussed to explore future possibilities.