Cloud computing is a demanding business platform for services related to the field of IT.The goal of cloud customers is to access resources at a sustainable price,while the goal of cloud suppliers is to maximize their...Cloud computing is a demanding business platform for services related to the field of IT.The goal of cloud customers is to access resources at a sustainable price,while the goal of cloud suppliers is to maximize their services utilization.Previously,the customers would bid for every single resource type,which was a limitation of cloud resources allocation.To solve these issues,researchers have focused on a combinatorial auction in which the resources are offered by the providers in bundles so that the user bids for their required bundle.Still,in this allocation mechanism,some drawbacks need to be tackled,such as due to the lower average bid price the users are dropped from the auction process.To solve this problem,we proposed a“Negotiation based Combinatorial Double Auction Mechanism for Resource Allocation(N-CDARA)in cloud computing”.The proposed method negotiates with dropped users.Lower average bid price users are asked by our proposed mechanism to increase their bids,as by the quoted bids they will be dropped by the auctioneer.Most of the users that are close to winning accept the proposal and increase their bid prices.The proposed mechanism is implemented in a CloudSim simulation toolkit.Results are compared with the latest model and performance study shows that in our proposed scheme more users win and get their requested services and the utilization of offered services is increased up to 18.4%than the existing schemes.展开更多
The complexity of cloud environments challenges secure resource management,especially for intrusion detection systems(IDS).Existing strategies struggle to balance efficiency,cost fairness,and threat resilience.This pa...The complexity of cloud environments challenges secure resource management,especially for intrusion detection systems(IDS).Existing strategies struggle to balance efficiency,cost fairness,and threat resilience.This paper proposes an innovative approach to managing cloud resources through the integration of a genetic algorithm(GA)with a“double auction”method.This approach seeks to enhance security and efficiency by aligning buyers and sellers within an intelligent market framework.It guarantees equitable pricing while utilizing resources efficiently and optimizing advantages for all stakeholders.The GA functions as an intelligent search mechanism that identifies optimal combinations of bids from users and suppliers,addressing issues arising from the intricacies of cloud systems.Analyses proved that our method surpasses previous strategies,particularly in terms of price accuracy,speed,and the capacity to manage large-scale activities,critical factors for real-time cybersecurity systems,such as IDS.Our research integrates artificial intelligence-inspired evolutionary algorithms with market-driven methods to develop intelligent resource management systems that are secure,scalable,and adaptable to evolving risks,such as process innovation.展开更多
This article proposes a novel grid resource allocation model, in which the users and the grid service providers participate in the combinatorial double auction for the resource allocation. To obtain the detailed resou...This article proposes a novel grid resource allocation model, in which the users and the grid service providers participate in the combinatorial double auction for the resource allocation. To obtain the detailed resource allocation status and the price information, a novel pricing algorithm is designed for the allocation model. Simulation results demonstrate that the proposed algorithm completes the resource allocation and pricing efficiently, and exhibits incentive compatible characteristic. Moreover, users with the higher average price and providers with the lower average price get compensation during the pricing process.展开更多
基金This publication was supported by the Deanship of Scientific Research at Prince Sattam bin Abdulaziz University,Alkharj,Saudi Arabia.
文摘Cloud computing is a demanding business platform for services related to the field of IT.The goal of cloud customers is to access resources at a sustainable price,while the goal of cloud suppliers is to maximize their services utilization.Previously,the customers would bid for every single resource type,which was a limitation of cloud resources allocation.To solve these issues,researchers have focused on a combinatorial auction in which the resources are offered by the providers in bundles so that the user bids for their required bundle.Still,in this allocation mechanism,some drawbacks need to be tackled,such as due to the lower average bid price the users are dropped from the auction process.To solve this problem,we proposed a“Negotiation based Combinatorial Double Auction Mechanism for Resource Allocation(N-CDARA)in cloud computing”.The proposed method negotiates with dropped users.Lower average bid price users are asked by our proposed mechanism to increase their bids,as by the quoted bids they will be dropped by the auctioneer.Most of the users that are close to winning accept the proposal and increase their bid prices.The proposed mechanism is implemented in a CloudSim simulation toolkit.Results are compared with the latest model and performance study shows that in our proposed scheme more users win and get their requested services and the utilization of offered services is increased up to 18.4%than the existing schemes.
文摘The complexity of cloud environments challenges secure resource management,especially for intrusion detection systems(IDS).Existing strategies struggle to balance efficiency,cost fairness,and threat resilience.This paper proposes an innovative approach to managing cloud resources through the integration of a genetic algorithm(GA)with a“double auction”method.This approach seeks to enhance security and efficiency by aligning buyers and sellers within an intelligent market framework.It guarantees equitable pricing while utilizing resources efficiently and optimizing advantages for all stakeholders.The GA functions as an intelligent search mechanism that identifies optimal combinations of bids from users and suppliers,addressing issues arising from the intricacies of cloud systems.Analyses proved that our method surpasses previous strategies,particularly in terms of price accuracy,speed,and the capacity to manage large-scale activities,critical factors for real-time cybersecurity systems,such as IDS.Our research integrates artificial intelligence-inspired evolutionary algorithms with market-driven methods to develop intelligent resource management systems that are secure,scalable,and adaptable to evolving risks,such as process innovation.
基金supported by the Project EC-GIN,European Union(FP6-2006-IST-045256)the National Natural Science Foundation of China(60802033,60873190)
文摘This article proposes a novel grid resource allocation model, in which the users and the grid service providers participate in the combinatorial double auction for the resource allocation. To obtain the detailed resource allocation status and the price information, a novel pricing algorithm is designed for the allocation model. Simulation results demonstrate that the proposed algorithm completes the resource allocation and pricing efficiently, and exhibits incentive compatible characteristic. Moreover, users with the higher average price and providers with the lower average price get compensation during the pricing process.
