Quantum-Inspired Algorithm CLUQOA Enhances Cloud Resource Management

Cloud computing’s performance heavily relies on resource allocation and task scheduling. To optimize these processes, a novel algorithm called Cloud-based Load balancing using Quantum artificial bee colony Optimization Algorithm (CLUQOA) has been proposed. This quantum-inspired algorithm enhances cloud computing operations by improving resource utilization and reducing makespan. When compared to other approaches, CLUQOA outperforms them, improving resource utilization by up to 356% and reducing makespan by up to 1102%. This research, conducted by Visalaxi G and Muthukumaravel A, suggests a promising future for quantum computing in cloud resource management.

What is the Role of Resource Allocation in Cloud Computing?

Cloud computing, a prominent approach for delivering applications on demand via the internet, has emerged as a transformative technology. A critical aspect of cloud computing is resource allocation, which plays a pivotal role in its overall performance. Resource allocation involves the fair distribution of workload among servers, network ports, and hard drives. This process is managed through task scheduling, a critical module of cloud computing.

Cloud computing often experiences request overloading due to dynamic computing over the internet. This challenge necessitates the development of innovative solutions for optimized resource management. One such solution is the proposed Cloud-based Load balancing using Quantum artificial bee colony Optimization Algorithm (CLUQOA). This novel algorithm aims to enhance the effectiveness of cloud computing operations by focusing on two important aspects: resource allocation and task scheduling.

By achieving load balancing between servers, CLUQOA improves reliability and lowers expenses, latency, and response times. This is a significant advancement in the field of cloud computing, as it addresses the critical issue of resource allocation and task scheduling, thereby enhancing the overall performance of cloud computing operations.

How Does the Quantum-Inspired Algorithm Enhance Cloud Computing?

The proposed CLUQOA is a quantum-inspired evolutionary algorithm designed for optimized cloud resource management. This algorithm uses principles from quantum computing, specifically the concept of qubits, to enhance the task scheduling process in cloud computing. The quantum artificial bee colony optimization algorithm is a key component of CLUQOA, contributing to its effectiveness in managing cloud resources.

The performance of CLUQOA is evaluated using key performance parameters including makespan, resource usage, task migration, task execution time, and response time. These parameters provide a comprehensive assessment of the algorithm’s effectiveness in enhancing cloud computing operations. The results of this evaluation demonstrate the superiority of CLUQOA in terms of improving resource utilization and reducing makespan.

The quantum-inspired algorithm not only addresses the challenge of resource allocation and task scheduling in cloud computing but also introduces a novel approach to cloud resource management. By leveraging principles from quantum computing, CLUQOA offers a promising solution to the challenges faced by cloud computing operations.

How Does CLUQOA Compare to Other Approaches?

The effectiveness of CLUQOA is further demonstrated through comparative comparisons with other approaches such as HUNTER (Holistic resoUrce maNagemenT technique for Energy efficient cloud computing using aRtificial intelligence), FPNSO (Flower Pollination based Non-dominated Sorting Optimization), and ProHPA (Proactive Hybrid Pod Autoscaling).

These comparisons reveal that CLUQOA outperforms these other approaches in terms of improving resource utilization and reducing makespan. Specifically, CLUQOA improves resource utilization by 356%, 264%, and 139% respectively, and reduces makespan by 1102%, 96%, and 104% respectively.

These results underscore the superiority of CLUQOA in managing cloud resources. By outperforming other approaches, CLUQOA establishes itself as a leading solution for optimized cloud resource management. This comparative analysis further validates the effectiveness of the quantum-inspired algorithm in enhancing cloud computing operations.

What is the Future of Quantum Computing in Cloud Resource Management?

The success of CLUQOA in enhancing cloud computing operations suggests a promising future for quantum computing in cloud resource management. By leveraging principles from quantum computing, CLUQOA offers a novel and effective solution to the challenges faced by cloud computing operations.

The quantum-inspired algorithm not only addresses the critical issue of resource allocation and task scheduling but also introduces a new approach to cloud resource management. This approach, which combines quantum computing with artificial bee colony optimization, offers a promising avenue for future research and development in the field of cloud computing.

The potential of quantum computing in cloud resource management is further underscored by the comparative analysis of CLUQOA with other approaches. By outperforming these other approaches, CLUQOA establishes itself as a leading solution for optimized cloud resource management. This success suggests a promising future for quantum computing in cloud resource management, opening up new possibilities for research and development in this field.

What are the Implications of this Research for the Field of Cloud Computing?

The research conducted by Visalaxi G and Muthukumaravel A from the Department of Computer Science and Engineering and the Department of Arts and Science at Bharath Institute of Higher Education and Research in Chennai, India, has significant implications for the field of cloud computing. Their work on the development and evaluation of CLUQOA contributes to the ongoing efforts to enhance the effectiveness of cloud computing operations.

The success of CLUQOA in improving resource utilization and reducing makespan suggests a promising avenue for future research and development in cloud computing. By leveraging principles from quantum computing, this research introduces a novel approach to cloud resource management, offering a promising solution to the challenges faced by cloud computing operations.

Furthermore, the comparative analysis of CLUQOA with other approaches underscores the potential of quantum computing in cloud resource management. By outperforming these other approaches, CLUQOA establishes itself as a leading solution for optimized cloud resource management. This success suggests a promising future for quantum computing in cloud resource management, opening up new possibilities for research and development in this field.