cs 21(20): e5

Research Article

Advanced Mechanism to Achieve QoS and Profit Maximization of Brokers in Cloud Computing

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  • @ARTICLE{10.4108/eai.23-6-2021.170244,
        author={Akanksha Sathish and Diana Dsouza and K. Ramitha Ballal and Archana M and Tarun Raj Singh and Glen Joshua Monteiro},
        title={Advanced Mechanism to Achieve QoS and Profit Maximization of Brokers in Cloud Computing},
        journal={EAI Endorsed Transactions on Cloud Systems},
        keywords={Cloud Broker, Cloud Computing, Multiplexing, Profit Maximization, Quality of Service},
  • Akanksha Sathish
    Diana Dsouza
    K. Ramitha Ballal
    Archana M
    Tarun Raj Singh
    Glen Joshua Monteiro
    Year: 2021
    Advanced Mechanism to Achieve QoS and Profit Maximization of Brokers in Cloud Computing
    DOI: 10.4108/eai.23-6-2021.170244
Akanksha Sathish1,*, Diana Dsouza1, K. Ramitha Ballal1, Archana M1, Tarun Raj Singh2, Glen Joshua Monteiro3
  • 1: Computer Science and Engineering, Sahyadri College of Engineering and Management, Mangalore, Karnataka, India
  • 2: Computer and Communication Engineering, Manipal University of Jaipur, Rajasthan, India
  • 3: Electronics and Telecommunication Engineering, St. Francis Institute of Technology, Mumbai, Maharashtra, India
*Contact email: akankshasathish315@gmail.com


Cloud computing is a widely used technology today and thus, large number of applications are being stored in the cloud. To cater to the needs of the consumers an intermediate role known as cloud broker has been introduced. It helps to cut down overall expenses of the cloud users. The proposed system concentrates on configuration of the cloud broker to improve profit. This maximization scheme depends upon various factors like customer request, selling price of the resource, purchasing price of the resource, intensity of the request and so on. The system developed, aims at maximizing the profit of the cloud broker who services consumer requirements by providing cloud infrastructure at a lower cost from an infrastructure vendor. Availing pay-as-you-go schemes or on-demand payment has proven to be useful. The complex cloud landscape along with various billing schemes paves a way for a profit maximization model that incorporates temporal multiplexing by a middleman entity for a better economic upfront. The resource multiplexing is further enhanced by incorporating M/D/c queueing model and short-term and long-term renting schemes to optimize the resource allocation. The entire application has been implemented using Java especially the NetBeans IDE 8.2. Different algorithms were compared to further enhance the pricing scheme selection. Finally, Hill-Climbing algorithm is used to allocate the resources dynamically. The system further notifies the cloud broker on resource shortage through dynamic disk utilization graph. The proposed system considers quality of service and price of service as the determining factors in maximizing the net profit of the cloud broker.