Bilal Khan
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Bilal Khan has a total of 10 co-authors. Here are the top co-authors by number of shared publications:
- Chaudhry Arshad Mehmood
Department of Electrical Engineering , COMSATS University Islamabad , Abbottabad Campus, Abbottabad , Pakistan , comsats.edu.pk
2 shared publications - Sahibzada M. Ali
Electrical And Computer Engineering, COMSATS Institute of Information Technology - Abbottabad, 72592 Abbottabad, KPK Pakistan
2 shared publications - John Anthony Rossiter
Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK
1 shared publication - Muhammad Bilal Qureshi
Department of Electrical and Computer Engineering, COMSATS University Islamabad, Abbottabad Campus, Abbottabad 22060, Pakistan
1 shared publication - Muhammad Jawad
Department of Electrical and Computer Engineering, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan
1 shared publication - Muhammad Usman Shahid Khan
National University of Sciences and Technology (NUST)
1 shared publication
Latest Publications
- 7 November 2018
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Cloud Computing
- Vol. 9 (2) , 447-460
A Robust Optimization Technique for Energy Cost Minimization of Cloud Data Centers
Power consumption cost constitutes significant portion of a data center's total operational cost. Variations in parameters, such as power demand, electricity price, and renewable power generation effects the data center's power consumption cost. Therefore, in this paper, a smart power management system based on a robust energy cost optimization algorithm is proposed for the data center. The designed robust optimization algorithm coordinates data center workload, battery bank, diesel generators, renewable power, and trade electricity price in real-time and day-ahead power market to reduce expected energy consumption cost. The uncertain parameters, such as data center workload and renewable power are computed using forecasting algorithms. The optimization algorithm is used to limit unbalance power purchase from real-time power market due to uncertainty of real-time electricity price. The algorithm formulation is obtained using mix-integer linear programming. Moreover, a model to calculate prices to be used in service level agreements with data centers' clients for on-demand cloud services is designed considering operational cost of the data center. Simulations are performed on actual data center workload, weather parameters, and electricity price. The results have shown that the proposed methodology is an effective tool to minimize data center operational cost.
- 7 November 2018
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Cloud Computing
- Vol. 9 (2) , 447-460
A Robust Optimization Technique for Energy Cost Minimization of Cloud Data Centers
Power consumption cost constitutes significant portion of a data center's total operational cost. Variations in parameters, such as power demand, electricity price, and renewable power generation effects the data center's power consumption cost. Therefore, in this paper, a smart power management system based on a robust energy cost optimization algorithm is proposed for the data center. The designed robust optimization algorithm coordinates data center workload, battery bank, diesel generators, renewable power, and trade electricity price in real-time and day-ahead power market to reduce expected energy consumption cost. The uncertain parameters, such as data center workload and renewable power are computed using forecasting algorithms. The optimization algorithm is used to limit unbalance power purchase from real-time power market due to uncertainty of real-time electricity price. The algorithm formulation is obtained using mix-integer linear programming. Moreover, a model to calculate prices to be used in service level agreements with data centers' clients for on-demand cloud services is designed considering operational cost of the data center. Simulations are performed on actual data center workload, weather parameters, and electricity price. The results have shown that the proposed methodology is an effective tool to minimize data center operational cost.
- 5 June 2018
- Published by Springer Nature in Arabian Journal for Science and Engineering
- Vol. 44 (3) , 2103-2113
Switching Control Paradigms for Adaptive Cruise Control System with Stop-and-Go Scenario
- 5 June 2018
- Published by Springer Nature in Arabian Journal for Science and Engineering
- Vol. 44 (3) , 2103-2113
Switching Control Paradigms for Adaptive Cruise Control System with Stop-and-Go Scenario
- 1 January 2014
- Published by Elsevier in IFAC Proceedings Volumes
- Vol. 47 (3) , 8347-8352
Structured optimisation dynamics for robust triple mode predictive control
- 1 January 2014
- Published by Elsevier in IFAC Proceedings Volumes
- Vol. 47 (3) , 8347-8352
Structured optimisation dynamics for robust triple mode predictive control