On-line routing of virtual circuits with applications to load balancing and machine scheduling
Journal of the ACM (JACM)
Better bounds for online scheduling
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Approximation schemes for scheduling
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
Ancient and new algorithms for load balancing in the Lp norm
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
All-Norm Approximation Algorithms
SWAT '02 Proceedings of the 8th Scandinavian Workshop on Algorithm Theory
Server scheduling in the Lp norm: a rising tide lifts all boat
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Multi-processor scheduling to minimize flow time with ε resource augmentation
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Selfish load balancing and atomic congestion games
Proceedings of the sixteenth annual ACM symposium on Parallelism in algorithms and architectures
All-norm approximation algorithms
Journal of Algorithms
The Price of Routing Unsplittable Flow
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
Convex programming for scheduling unrelated parallel machines
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
Fairness and optimality in congestion games
Proceedings of the 6th ACM conference on Electronic commerce
Approximation Algorithms for Scheduling on Multiple Machines
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
Welfare maximization in congestion games
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Semi-matchings for bipartite graphs and load balancing
Journal of Algorithms
Minimizing average latency in oblivious routing
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Better bounds for online load balancing on unrelated machines
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Efficient coordination mechanisms for unrelated machine scheduling
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
A unified approach to scheduling on unrelated parallel machines
Journal of the ACM (JACM)
Semi-matchings for bipartite graphs and load balancing
Journal of Algorithms
Nonadaptive selfish routing with online demands
CAAN'07 Proceedings of the 4th conference on Combinatorial and algorithmic aspects of networking
How to allocate goods in an online market?
ESA'10 Proceedings of the 18th annual European conference on Algorithms: Part II
Tight bounds for parallel randomized load balancing: extended abstract
Proceedings of the forty-third annual ACM symposium on Theory of computing
Algorithms and hardness for subspace approximation
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
Tight bounds for selfish and greedy load balancing
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part I
Congestion games, load balancing, and price of anarchy
CAAN'04 Proceedings of the First international conference on Combinatorial and Algorithmic Aspects of Networking
Uncoordinated load balancing and congestion games in p2p systems
IPTPS'04 Proceedings of the Third international conference on Peer-to-Peer Systems
Finding social optima in congestion games with positive externalities
ESA'12 Proceedings of the 20th Annual European conference on Algorithms
Algorithms for hub label optimization
ICALP'13 Proceedings of the 40th international conference on Automata, Languages, and Programming - Volume Part I
| Hi-index | 0.00 |
In the load balancing problem, there is a set of servers, and jobs arrive sequentially. Each job can be run on some subset of the servers, and must be assigned to one of them in an online fashion. Traditionally, the assignment of jobs to servers is measured by the L/sub /spl infin// norm; in other words, an assignment of jobs to servers is quantified by the maximum load assigned to any server. In this measure the performance of the greedy load balancing algorithm may be a logarithmic factor higher than the offline optimal. In many applications, the L/sub /spl infin// norm is not a suitable way to measure how well the jobs are balanced, If each job sees a delay that is proportional to the number of jobs on its server, then the average delay among all jobs is proportional to the sum of the squares of the numbers of jobs assigned to the servers. Minimizing the average delay is equivalent to minimizing the Euclidean (or L/sub 2/) norm. For any fixed p, 1/spl les/p/spl infin/, we show that the greedy algorithm performs within a constant factor of the offline optimal with respect to the L/sub p/ norm. The constant grows linearly with p, which is best possible, but does not depend on the number of servers and jobs.