Complexity of network synchronization
Journal of the ACM (JACM)
STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
A parallel approximation algorithm for positive linear programming
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Approximating Fractional Multicommodity Flow Independent of the Number of Commodities
SIAM Journal on Discrete Mathematics
The price of anarchy is independent of the network topology
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Semiring frameworks and algorithms for shortest-distance problems
Journal of Automata, Languages and Combinatorics
Faster and Simpler Algorithms for Multicommodity Flow and other Fractional Packing Problems.
FOCS '98 Proceedings of the 39th Annual Symposium on Foundations of Computer Science
Sequential and Parallel Algorithms for Mixed Packing and Covering
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
The Price of Stability for Network Design with Fair Cost Allocation
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
DIMES: let the internet measure itself
ACM SIGCOMM Computer Communication Review
Fast convergence to Wardrop equilibria by adaptive sampling methods
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
Greedy distributed optimization of multi-commodity flows
Proceedings of the twenty-sixth annual ACM symposium on Principles of distributed computing
Minimizing the total cost of network measurements in a distributed manner: a primal-dual approach
Proceedings of the twenty-sixth annual ACM symposium on Principles of distributed computing
Stateless distributed gradient descent for positive linear programs
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Stateless near optimal flow control with poly-logarithmic convergence
LATIN'08 Proceedings of the 8th Latin American conference on Theoretical informatics
Brief announcement: bridging the theory-practice gap in multi-commodity flow routing
DISC'11 Proceedings of the 25th international conference on Distributed computing
Link-state routing with hop-by-hop forwarding can achieve optimal traffic engineering
IEEE/ACM Transactions on Networking (TON)
Scalable, optimal flow routing in datacenters via local link balancing
Proceedings of the ninth ACM conference on Emerging networking experiments and technologies
| Hi-index | 0.00 |
A canonical distributed optimization problem is solving a Covering/Packing Linear Program in a distributed environment with fast convergence and low communication and space overheads. In this paper, we consider the following covering and packing problems, which are the dual of each other: • Passive Commodity Monitoring: minimize the total cost of monitoring devices used to measure the network traffic on all paths. • Maximum Throughput Multicommodity flow: maximize the total value of the flow with bounded edge capacities.. We present the first known distributed algorithms for both of these problems that converge to (1+ε)-approximate solutions in poly-logarithmic time with communication and space overheads that depend on the maximal path length but are almost independent of the size of the entire network. Previous distributed solutions achieving similar approximations required convergence time, communication, or space overheads that depend polynomially on the size of the entire network. The sequential simulation of our algorithm is more efficient than the fastest known approximation algorithms for multicommodity flows, e.g., Garg-Könemann [14], when the maximal path length is small.