Scheduling data transfers in a network and the set scheduling problem
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A method is proposed for the optimal scheduling of collective data exchanges relying on the knowledge of the underlying network topology. The concept of liquid schedules is introduced. Liquid schedules ensure the maximal utilization of a network's bottlene ...
For a class of sensor networks, the task is to monitor an underlying
physical phenomenon over space and time through a
noisy observation process. The sensors can communicate back
to a data collector over a noisy channel. The key parameters
in such a se ...
Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2004
The min-cut, max-flow theorem states that a source node can send a commodity through a network to a sink node at the rate determined by the flow of the min-cut separating the source and the sink. Recently it has been shown that by liner re-encoding at node ...
The upper limit of a network's capacity is its liquid throughput. The liquid throughput corresponds to the flow of a liquid in an equivalent network of pipes. However, the aggregate throughput of a collective communication pattern (traffic) scheduled accor ...
Institute of Electrical and Electronics Engineers Inc., Piscataway, NJ 08855-1331, United States2004
In this paper we consider the online ftp problem. The goal is to service a sequence of file transfer requests given bandwidth constraints of the underlying communication network. The main result of the paper is a technique that leads to algorithms that opt ...
Routing as well as the management of communication networks that support hybrid types of communications requiring quality of service is a hard problem. We present here a framework1 that decomposes the network into a hierarchy of abstract views of the netwo ...
The famous min-cut, max-flow theorem states that a source node can send a commodity through a network to a sink node at the rate determined by the flow of the min-cut separating the source and the sink. Recently it has been shown that by linear re-encoding ...
