Subash Chandra Tripathy; Suvendu Chandan Nayak; Rekah Sahu

Cost Denigration Based Data Center Allocation Policy Using Modified Parallel PSO Optimization Technique for Multi-cloud Framework

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Author(s)

Subash Chandra Tripathy ¹ Suvendu Chandan Nayak ^1,* Rekah Sahu ¹

1. Department of Computer Science and Engineering, Silicon University, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2026.03.03

Received: 2 Dec. 2025 / Revised: 27 Jan. 2026 / Accepted: 10 Apr. 2026 / Published: 8 Jun. 2026

Index Terms

Data Center (DC), Response Time, Optimization, PSO, Energy, Cost

Abstract

Most of the existing data center allocation mechanisms are either user-centric or service-provider-centric, not for both ends but in reality, both have different objectives. For example, the objective of a user is minimization of cost, response time as well as processing time whereas the objective of service provider is to maximize the profit and processing time and minimization of response time, bandwidth, energy consumption and computing overhead subject to effective resource utilization and load balancing. To address this challenge, this paper introduces a Cost Denigration-Based Data Center Allocation Policy (CD-BDAP) utilizing Particle Swarm Optimization (PSO), which simultaneously considers economic cost, response time, and energy consumption in the selection of data centers. In contrast to conventional PSO-based broker policies, CD-BDAP integrates a workload similarity-aware allocation strategy by calculating a dissimilarity index among user requests, thereby facilitating enhanced consolidation and energy efficiency. A weighted objective function is developed to balance user-centric metrics (cost and response time) with provider-centric metrics (profit and energy consumption), explicitly capturing their trade-offs. The proposed mechanism is assessed utilizing CloudAnalyst, which is constructed on CloudSim. The experimental results indicate that CD-BDAP achieves a reduction in VM cost, a decrease in response time, and an enhancement in energy efficiency, while simultaneously increasing the overall profit for service providers. The findings suggest that the integration of energy-aware cost modeling and workload similarity into PSO-based allocation can enhance both economic and performance efficiency in the selection of cloud data centers. The outcomes of CD-BDAP are compared with the existing PSO-based mechanisms and found to exhibit enhanced performance.

Cite This Paper

Subash Chandra Tripathy, Suvendu Chandan Nayak, Rekah Sahu, "Cost Denigration Based Data Center Allocation Policy Using Modified Parallel PSO Optimization Technique for Multi-cloud Framework", International Journal of Information Technology and Computer Science(IJITCS), Vol.18, No.3, pp.28-44, 2026. DOI:10.5815/ijitcs.2026.03.03

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