The University of Winnipeg Medical Algorithms propose New Network Utility Maximize Problem

Transcription

1 The University of Winnipeg Applied Computer Science Candidate Presentation Amir-Hamed Mohsenian-Rad, University of Toronto Friday, March 12, :30 a.m. - 10:30 a.m. - Room 3D03 Abstract Medium access control (MAC) protocols are used to coordinate multiple wireless users accessing a shared channel in a wireless network. They are either centralized as in scheduling-based MAC protocols in cellular networks, or distributed as in contention-based random MAC protocols in wireless ad-hoc networks. Random MAC protocols are scalable and inherently flexible but they typically have poor performance due to low throughput and unfair resource allocation. Optimization-based random MAC protocols are proposed recently to improve both efficiency and fairness. In this approach, users iteratively adjust their probability of accessing the shared channel to solve a certain optimization problem, e.g., a network utility maximization (NUM) problem. However, most of the existing NUM-based random MAC protocols have one or more of the following performance bottlenecks which prevent them from being deployed in practice: (a) extensive signaling overhead, (b) crucial need for time synchronization, (c) slow convergence, and (d) supporting a limited range of user utility functions under which the NUM problem is shown to be convex. In this presentation, we introduce our recently proposed distributed wireless MAC algorithm which can overcome these performance bottlenecks in all four aspects. First, only limited amount of control message passing among users is required when they run this algorithm. Second, fully asynchronous updates of the contention probabilities are allowed among users. Furthermore, the proposed algorithm is robust to arbitrarily large control message passing delay and loss. Third, it can achieve much faster convergence speed. Finally, the proposed algorithm has provable convergence, optimality, and robustness properties under a wide range of utility functions, even if the NUM problem is essentially non-convex. ACS students welcome to attend the presentation.

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3 The University of Winnipeg Applied Computer Science Candidate Presentation Amir-Hamed Mohsenian-Rad, University of Toronto Friday, March 12, :30 a.m. - 10:30 a.m. - Room 3D03 Abstract Medium access control (MAC) protocols are used to coordinate multiple wireless users accessing a shared channel in a wireless network. They are either centralized as in scheduling-based MAC protocols in cellular networks, or distributed as in contention-based random MAC protocols in wireless ad-hoc networks. Random MAC protocols are scalable and inherently flexible but they typically have poor performance due to low throughput and unfair resource allocation. Optimization-based random MAC protocols are proposed recently to improve both efficiency and fairness. In this approach, users iteratively adjust their probability of accessing the shared channel to solve a certain optimization problem, e.g., a network utility maximization (NUM) problem. However, most of the existing NUM-based random MAC protocols have one or more of the following performance bottlenecks which prevent them from being deployed in practice: (a) extensive signaling overhead, (b) crucial need for time synchronization, (c) slow convergence, and (d) supporting a limited range of user utility functions under which the NUM problem is shown to be convex. In this presentation, we introduce our recently proposed distributed wireless MAC algorithm which can overcome these performance bottlenecks in all four aspects. First, only limited amount of control message passing among users is required when they run this algorithm. Second, fully asynchronous updates of the contention probabilities are allowed among users. Furthermore, the proposed algorithm is robust to arbitrarily large control message passing delay and loss. Third, it can achieve much faster convergence speed. Finally, the proposed algorithm has provable convergence, optimality, and robustness properties under a wide range of utility functions, even if the NUM problem is essentially non-convex. ACS students welcome to attend the presentation.

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5 The University of Winnipeg Applied Computer Science Candidate Presentation Amir-Hamed Mohsenian-Rad, University of Toronto Friday, March 12, :30 a.m. - 10:30 a.m. - Room 3D03 Abstract Medium access control (MAC) protocols are used to coordinate multiple wireless users accessing a shared channel in a wireless network. They are either centralized as in scheduling-based MAC protocols in cellular networks, or distributed as in contention-based random MAC protocols in wireless ad-hoc networks. Random MAC protocols are scalable and inherently flexible but they typically have poor performance due to low throughput and unfair resource allocation. Optimization-based random MAC protocols are proposed recently to improve both efficiency and fairness. In this approach, users iteratively adjust their probability of accessing the shared channel to solve a certain optimization problem, e.g., a network utility maximization (NUM) problem. However, most of the existing NUM-based random MAC protocols have one or more of the following performance bottlenecks which prevent them from being deployed in practice: (a) extensive signaling overhead, (b) crucial need for time synchronization, (c) slow convergence, and (d) supporting a limited range of user utility functions under which the NUM problem is shown to be convex. In this presentation, we introduce our recently proposed distributed wireless MAC algorithm which can overcome these performance bottlenecks in all four aspects. First, only limited amount of control message passing among users is required when they run this algorithm. Second, fully asynchronous updates of the contention probabilities are allowed among users. Furthermore, the proposed algorithm is robust to arbitrarily large control message passing delay and loss. Third, it can achieve much faster convergence speed. Finally, the proposed algorithm has provable convergence, optimality, and robustness properties under a wide range of utility functions, even if the NUM problem is essentially non-convex. ACS students welcome to attend the presentation.

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7 The University of Winnipeg Applied Computer Science Candidate Presentation Amir-Hamed Mohsenian-Rad, University of Toronto Friday, March 12, :30 a.m. - 10:30 a.m. - Room 3D03 Abstract Medium access control (MAC) protocols are used to coordinate multiple wireless users accessing a shared channel in a wireless network. They are either centralized as in scheduling-based MAC protocols in cellular networks, or distributed as in contention-based random MAC protocols in wireless ad-hoc networks. Random MAC protocols are scalable and inherently flexible but they typically have poor performance due to low throughput and unfair resource allocation. Optimization-based random MAC protocols are proposed recently to improve both efficiency and fairness. In this approach, users iteratively adjust their probability of accessing the shared channel to solve a certain optimization problem, e.g., a network utility maximization (NUM) problem. However, most of the existing NUM-based random MAC protocols have one or more of the following performance bottlenecks which prevent them from being deployed in practice: (a) extensive signaling overhead, (b) crucial need for time synchronization, (c) slow convergence, and (d) supporting a limited range of user utility functions under which the NUM problem is shown to be convex. In this presentation, we introduce our recently proposed distributed wireless MAC algorithm which can overcome these performance bottlenecks in all four aspects. First, only limited amount of control message passing among users is required when they run this algorithm. Second, fully asynchronous updates of the contention probabilities are allowed among users. Furthermore, the proposed algorithm is robust to arbitrarily large control message passing delay and loss. Third, it can achieve much faster convergence speed. Finally, the proposed algorithm has provable convergence, optimality, and robustness properties under a wide range of utility functions, even if the NUM problem is essentially non-convex. ACS students welcome to attend the presentation.

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