Tata Institute of Fundamental Research
System Utility Maximisation With Fast Network and User Adaptation
STCS Colloquium
Speaker:
Rajesh Sundaresan (Indian Institute of Science
Dept. of Electrical Communicatin Engineering
Bangalore 560012)
Organiser:
Vinod M. Prabhakaran
Date:
Tuesday, 19 Jan 2016, 15:30 to 16:30
Venue:
A-201 (STCS Seminar Room)
(Scan to add to calendar)
Abstract:
Abstract: Kelly, Maulloo, and Tan (1998) proposed a decomposition of a system utility maximisation problem into a network utility maximisation problem, to be solved by a network entity, and a set of decoupled user optimisation problems, to be solved by the individual users. They proposed an iterative scheme where the users signal their willingness to pay (a scalar quantity) while the network signals the charges per unit flow. Their scheme involves a slow adaptation by the network and a fast adaptation by the users. Their scheme converges to the system optimal solution and has the advantage that the network entity need not know the users' utility functions and the individual users need not know the network state or utility functions of other users. In this talk, we will discuss a special case and a modified algorithm where the network also makes a fast adapation. We will then show that the algorithm converges to the global optimum solution.
| Speaker: | Rajesh Sundaresan (Indian Institute of Science Dept. of Electrical Communicatin Engineering Bangalore 560012) |
| Organiser: | Vinod M. Prabhakaran |
| Date: | Tuesday, 19 Jan 2016, 15:30 to 16:30 |
| Venue: | A-201 (STCS Seminar Room) |
(Scan to add to calendar)
Abstract:
Abstract: Kelly, Maulloo, and Tan (1998) proposed a decomposition of a system utility maximisation problem into a network utility maximisation problem, to be solved by a network entity, and a set of decoupled user optimisation problems, to be solved by the individual users. They proposed an iterative scheme where the users signal their willingness to pay (a scalar quantity) while the network signals the charges per unit flow. Their scheme involves a slow adaptation by the network and a fast adaptation by the users. Their scheme converges to the system optimal solution and has the advantage that the network entity need not know the users' utility functions and the individual users need not know the network state or utility functions of other users. In this talk, we will discuss a special case and a modified algorithm where the network also makes a fast adapation. We will then show that the algorithm converges to the global optimum solution.