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 NP-Hard. 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.

Highlights

  • Resource management is one of the key challenges in cloud computing and cloud data center management [1]

  • Most cloud providers use fixed price mechanisms to allocate resources to users. These mechanisms do not provide an efficient and acceptable allocation of resources, and in reality they cannot maximize the profitability of cloud resource providers

  • Cloud-based economic models are appropriate for the regulation, presentation and demand of resources

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Summary

INTRODUCTION

Resource management is one of the key challenges in cloud computing and cloud data center management [1]. Most cloud providers use fixed price mechanisms to allocate resources to users. These mechanisms do not provide an efficient and acceptable allocation of resources, and cannot maximize the profitability of cloud resource providers [2], [3]. Considering the above, the use of combinatorial double auction to allocate resources in cloud computing can be a very appropriate model [4]–[7]. Considering the above issues regarding allocation of resources in cloud computing, in this paper, a modified simulated annealing algorithm has been used to determine the winner of the auction in the allocation of cloud resources.

RELATED WORKS
PROBLEM DEFINITION
Hybrid Genetic and Simulated Annealing
Encoding
Fitness Function
Selection Operator
Crossover Operator
Mutation Operator
Temperature Initialization and Reduction
Generation of Neighboring Solutions
SIMULATION AND EXPERIMENTAL RESULTS
Findings
CONCLUSION AND FUTURE WORKS
Full Text
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