On the core of the multicommodity flow game
Proceedings of the 4th ACM conference on Electronic commerce
Adaptive AIMD congestion control
Proceedings of the twenty-second annual symposium on Principles of distributed computing
On the core of the multicommodity flow game
Decision Support Systems - Special issue: The fourth ACM conference on electronic commerce
Online client-server load balancing without global information
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Pricing for fairness: distributed resource allocation for multiple objectives
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Greedy distributed optimization of multi-commodity flows
Proceedings of the twenty-sixth annual ACM symposium on Principles of distributed computing
Distributed algorithms for multicommodity flow problems via approximate steepest descent framework
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Stateless distributed gradient descent for positive linear programs
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Online Primal-Dual Algorithms for Covering and Packing
Mathematics of Operations Research
Foundations and Trends® in Networking
On the core of the multicommodity flow game
Decision Support Systems - Special issue: The fourth ACM conference on electronic commerce
Stateless near optimal flow control with poly-logarithmic convergence
LATIN'08 Proceedings of the 8th Latin American conference on Theoretical informatics
Fully Distributed Algorithms for Convex Optimization Problems
SIAM Journal on Optimization
Bandwidth allocation in networks: a single dual update subroutine for multiple objectives
CAAN'04 Proceedings of the First international conference on Combinatorial and Algorithmic Aspects of Networking
Optimal flow distribution among multiple channels with unknown capacities
Theoretical Computer Science
Distributed algorithms for multicommodity flow problems via approximate steepest descent framework
ACM Transactions on Algorithms (TALG)
| Hi-index | 0.00 |
Congestion control in the current Internet is accomplished mainly by TCP/IP. To understand the macroscopic network behavior that results from TCP/IP and similar end-to-end protocols, one main analytic technique is to show that the the protocol maximizes some global objective function of the network traffic.Here we analyze a particular end-to-end, MIMD (multiplicative-increase, multiplicative-decrease) protocol. We show that if all users of the network use the protocol, and all connections last for at least logarithmically many rounds, then the total weighted throughput (value of all packets received) is near the maximum possible. Our analysis includes round-trip-times, and (in contrast to most previous analyses) gives explicit convergence rates, allows connections to start and stop, and allows capacities to change.