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Enhanced Multi-attribute Combinative Double Auction (EMCDA) for Resource Allocation in Cloud Computing
- Source :
- Wireless Personal Communications. 122:3833-3857
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- Cloud computing is a growing technology where lot of heterogeneous resources are available and large amount of requests are submitted by the customers simultaneously. So it is difficult to match the requests and resources based on the expectations of customers and providers. This paper proposes the resource allocation using auction based technique to reduce the complexity of providing the resources for customers job execution and fulfill the expectations of both customers and providers in cloud environment. In the proposed work the Enhanced Multi-attribute Combinative Double Auction (EMCDA) resource allocation algorithm is used to conduct the auction to the customers bids with the providers bids by the cloud auctioneer for finding the best customer-providers pairs and achieves the customers and providers satisfaction using the normalization factors during price calculation in the cloud computing environment. The experimental result demonstrates that the proposed Enhanced Multi-attribute Combinative Double Auction (EMCDA) resource allocation algorithm performs efficiently than the existing Combinatorial Double Auction Resource Allocation (CDARA) model. The proposed EMCDA model is incentive-compatible, which encourage the participants of an auction to reveal their true valuation during bidding.
- Subjects :
- Operations research
business.industry
Computer science
TheoryofComputation_GENERAL
Cloud computing
Resource allocation algorithm
Bidding
Computer Science Applications
Work (electrical)
Double auction
Normalization (sociology)
Resource allocation
Electrical and Electronic Engineering
business
Valuation (finance)
Subjects
Details
- ISSN :
- 1572834X and 09296212
- Volume :
- 122
- Database :
- OpenAIRE
- Journal :
- Wireless Personal Communications
- Accession number :
- edsair.doi...........e5b2e7548ff35413c3a1e3d5300aca0a