A Cloud Computing Resource Allocation Model Based on Combinatorial Double Auction

Jia, Xu

doi:10.1109/icisce.2016.12

Cited by 5 publications

(4 citation statements)

References 12 publications

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“…The development of cloud computing has alleviated the network requirements of the metaverse, but cloud computing also aggregates a large number of online resources, such as virtual machines and CPUs. Xu et al [26] proposed a resource allocation model based on a combined double auction mechanism to solve the resource allocation problem of cloud computing. Chichin et al [27] proposed an adaptive greedy mechanism to help cloud providers allocate and price cloud resources.…”

Section: Related Workmentioning

confidence: 99%

A Truthful Mechanism for Multibase Station Resource Allocation in Metaverse Digital Twin Framework

Zhang

Zong

2022

Processes

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The concept of the metaverse has gained increasing attention in recent years, and the development of various new technologies, including digital twin technology, has made it possible to see the metaverse coming to pass. Many academics have begun to investigate various problems after realizing the importance of digital twin technology in building the metaverse. However, when utilizing digital twin technology to construct a metaverse, there remains limited research on how to allocate multibase station resources. This research translates a multibase station wireless resource allocation problem into an integer linear programming constraint model when virtual service providers construct a metaverse. In addition, the optimal VCG reverse auction (OPT-VCGRA) mechanism is designed to maximize social welfare and solve the problem of IoT devices competing for base station wireless resources. Specifically, the problem of the optimal allocation of wireless channel resources and payment rule based on the Vickrey–Clarke–Groves mechanism is solved to achieve optimal allocation and calculation of payment prices. Since the optimal allocation problem is NP-hard, this paper also designs a metaverse digital twin resource allocation and pricing (MDTRAP) mechanism based on monotonic allocation and key value theory. The mechanism sends the resource allocation results of multiple base stations to IoT devices and calculates the price payment when building a metaverse in the real world. This paper shows that both auction mechanisms have incentive compatibility and individual rationality properties. Through experiments, this paper compares the two mechanisms in terms of social welfare, the number of winners, and the overall payment. The MDTRAP mechanism performs similarly to the OPT-VCGRA mechanism in terms of social welfare, the number of winners, and channel utilization but is far superior to the OPT-VCGRA mechanism in terms of execution time and total payment. The trustful experiment also verified the truthfulness of the MDTRAP mechanism. The experimental results show that the MDTRAP mechanism can be used to solve the resource allocation problem of multiple base stations to IoT devices when building a metaverse in the real world and can effectively maximize social welfare.

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Section: Related Workmentioning

confidence: 99%

A Truthful Mechanism for Multibase Station Resource Allocation in Metaverse Digital Twin Framework

Zhang

Zong

2022

Processes

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“…• Low monetary cost Xu 54 They have determined the winner • High resource utilization • Without consideration of by a linear integer programming.…”

Section: Popular Other Types Of Auction-based Mechanismsmentioning

confidence: 99%

“…Xu has developed a combinatorial double auction mechanism for resource allocation in the cloud computing called CDA‐CCRA that satisfies the demands of users and providers. The CDA‐CCRA model is derived by a linear integer programming‐based optimization method for determining the winner.…”

Section: Resource Allocation Mechanismsmentioning

confidence: 99%

Auction‐based resource allocation mechanisms in the cloud environments: A review of the literature and reflection on future challenges

Sheikholeslami

Navimipour

2018

Concurrency and Computation

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Cloud computing is an Internet-based computing and networking model, with elasticity and scalability capabilities where the services are delivered to its users in a non-demand style. In this computing paradigm, the request and response between users and providers must be managed using the resource allocation strategies. Therefore, allocating the provided resources to the users based on their needs is the important challenge in this environment. Also, an auction in the cloud is a process of buying and vending the cloud services by offering them up for bid and then selling the service to the highest bidder. However, to the best of our knowledge, there has not been any comprehensive and detailed paper about reviewing the state-of-the-art mechanisms on this important topic and providing open issues as well. Hence, this paper provides a comprehensive survey and review of the auction-based resource allocation mechanisms, which have been employed in the cloud environments up to now. Also, we classified the important cloud resource allocation mechanisms into four categories: one-sided, double-sided, combinatorial, and other types of auction-based mechanisms. Moreover, we reviewed the main progress in these four categories and defined the new issues. Finally, the paper offers the differences among reviewed mechanisms as well as guidelines for future investigation.

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“…Xu presented CDA-CCRA, a new cloud computing resource allocation model based on combinatorial double auction mechanism for more effective resource utilization in cloud computing [15]. The CDA-CCRA model can simultaneously satisfy the users and providers requirements and significantly reduce transactions.…”

Section: Related Workmentioning

confidence: 99%

Combinatorial Double Auction Winner Determination in Cloud Computing using Hybrid Genetic and Simulated Annealing Algorithm

Kand¹,

Kazem²

2018

ijacsa

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Abstract-With the advancement of information technology need to perform computing tasks everywhere and all the time there, in cloud computing environments and heterogeneous users have access to different sources with different characteristics that these resources are geographically in different areas. Due to this, the allocation of resources in cloud computing comes to the main issue is considered a major challenge to achieve high performance. Due to the nature of cloud computing is a distributed system to account, comes to business, economic methods such as auctions are used to allocate resources for decentralization. As an important economic bilateral hybrid auction model is the perfect solution for the allocation of resources in cloud computing, on the other hand, providers of cloud resources similarly, their sources of supply combined addressing. One of the problems auction two-way combination with maximum benefit for the parties to the transaction is the efficient allocation of resources to the problem of determining an auction winner is known. Given that the winning auction is NPHard. It results in a problem, several methods have been proposed to solve it. In this dissertation, taking into account the strength simulated annealing algorithm, a modified version of it is proposed for solving the winner determination in combinatorial double auction problem in cloud computing. The proposed approach is simulated along with genetic and simulated annealing algorithms and the results show that the proposed approach finds better solutions than the two mentioned algorithms.

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A Cloud Computing Resource Allocation Model Based on Combinatorial Double Auction

Cited by 5 publications

References 12 publications

A Truthful Mechanism for Multibase Station Resource Allocation in Metaverse Digital Twin Framework

A Truthful Mechanism for Multibase Station Resource Allocation in Metaverse Digital Twin Framework

Auction‐based resource allocation mechanisms in the cloud environments: A review of the literature and reflection on future challenges

Combinatorial Double Auction Winner Determination in Cloud Computing using Hybrid Genetic and Simulated Annealing Algorithm

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