A unified approach to approximating resource allocation and scheduling
Journal of the ACM (JACM)
Wavelength assignment and generalized interval graph coloring
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
STOC '83 Proceedings of the fifteenth annual ACM symposium on Theory of computing
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
Algorithmic aspects of bandwidth trading
ACM Transactions on Algorithms (TALG)
Approximating the Traffic Grooming Problem with Respect to ADMs and OADMs
Euro-Par '08 Proceedings of the 14th international Euro-Par conference on Parallel Processing
Scheduling Algorithms
The regenerator location problem
Networks - Network Optimization (INOC 2007)
Approximating the traffic grooming problem
ISAAC'05 Proceedings of the 16th international conference on Algorithms and Computation
Optimizing regenerator cost in traffic grooming
OPODIS'10 Proceedings of the 14th international conference on Principles of distributed systems
Optimizing regenerator cost in traffic grooming
Theoretical Computer Science
On the complexity of the regenerator cost problem in general networks with traffic grooming
OPODIS'11 Proceedings of the 15th international conference on Principles of Distributed Systems
Online optimization of busy time on parallel machines
TAMC'12 Proceedings of the 9th Annual international conference on Theory and Applications of Models of Computation
An online parallel scheduling method with application to energy-efficiency in cloud computing
The Journal of Supercomputing
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We consider a scheduling problem in which a bounded number of jobs can be processed simultaneously by a single machine. The input is a set of n jobs J={J"1,...,J"n}. Each job, J"j, is associated with an interval [s"j,c"j] along which it should be processed. Also given is the parallelism parameter g=1, which is the maximal number of jobs that can be processed simultaneously by a single machine. Each machine operates along a contiguous time interval, called its busy interval, which contains all the intervals corresponding to the jobs it processes. The goal is to assign the jobs to machines so that the total busy time is minimized. The problem is known to be NP-hard already for g=2. We present a 4-approximation algorithm for general instances, and approximation algorithms with improved ratios for instances with bounded lengths, for instances where any two intervals intersect, and for instances where no interval is properly contained in another. Our study has application in optimizing the switching costs of optical networks.