About The Forum
Calendar 2009 Poster Sessions : Transport Mechanisms for Data Centers
Student Name : Mohammadreza Alizadeh Attar, Abdul Kabbani
Advisor : Balaji Prabhakar
Research Areas: Computer Systems, Information Systems
Advisor : Balaji Prabhakar
Research Areas: Computer Systems, Information Systems
Abstract:
Data Center Networks present a novel, unique and rich environment for algorithm development and deployment. Projects are underway in the IEEE 802.1 standards body, especially in the Data Center Bridging Task Group, to define new switched Ethernet functions for data center use.
One such project is IEEE 802.1Qau, the Congestion Notification project, whose aim is to develop an Ethernet congestion control algorithm for hardware implementation. A major contribution of this work is the description and analysis of the congestion control algorithm—QCN, for Quantized Congestion Notification— which has been developed for this purpose.
A second contribution of this work is an articulation of the Averaging Principle: a simple method for making congestion control loops stable in the face of increasing lags. This contrasts with two well-known methods of stabilizing control loops as lags increase; namely, (i) increasing the order of the system by sensing and feeding back higher-order derivatives of the state, and (ii) to determine the lag and then choose appropriate loop gains. These methods are either undesirable or infeasible in the Ethernet context. The Averaging Principle provides a simple alternative, one which we are able to theoretically characterize.
Bio:
Abdul is a 3rd-year Ph.D. student at Stanford University working on congestion control and buffer sizing problems. Prior to joining Stanford, Abdul finished his M.Sc. degree from Rice University and his B.E. degree from the Lebanese American University.
Mohammad is a 3rd-year Ph.D. student at Stanford University working on high-performance networking protocols in general and congestion management protocols in particular. Prior to joining Stanford, Mohammad finished his B.Sc. degree from Sharif University of Technology.
Mohammad is the recipient of the Numerical Technologies Fellowship and the Fabian Pease Stanford Graduate Fellowship.
Data Center Networks present a novel, unique and rich environment for algorithm development and deployment. Projects are underway in the IEEE 802.1 standards body, especially in the Data Center Bridging Task Group, to define new switched Ethernet functions for data center use.
One such project is IEEE 802.1Qau, the Congestion Notification project, whose aim is to develop an Ethernet congestion control algorithm for hardware implementation. A major contribution of this work is the description and analysis of the congestion control algorithm—QCN, for Quantized Congestion Notification— which has been developed for this purpose.
A second contribution of this work is an articulation of the Averaging Principle: a simple method for making congestion control loops stable in the face of increasing lags. This contrasts with two well-known methods of stabilizing control loops as lags increase; namely, (i) increasing the order of the system by sensing and feeding back higher-order derivatives of the state, and (ii) to determine the lag and then choose appropriate loop gains. These methods are either undesirable or infeasible in the Ethernet context. The Averaging Principle provides a simple alternative, one which we are able to theoretically characterize.
Bio:
Abdul is a 3rd-year Ph.D. student at Stanford University working on congestion control and buffer sizing problems. Prior to joining Stanford, Abdul finished his M.Sc. degree from Rice University and his B.E. degree from the Lebanese American University.
Mohammad is a 3rd-year Ph.D. student at Stanford University working on high-performance networking protocols in general and congestion management protocols in particular. Prior to joining Stanford, Mohammad finished his B.Sc. degree from Sharif University of Technology.
Mohammad is the recipient of the Numerical Technologies Fellowship and the Fabian Pease Stanford Graduate Fellowship.