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https://doi.org/10.1109/sfcs.2...
Article . 2001 . Peer-reviewed
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Source routing and scheduling in packet networks

Source routing and scheduling in packet networks.
Authors: Antonio Fernández; Ashish Goel; Matthew Andrews; Lisa Zhang;

Source routing and scheduling in packet networks

Abstract

We study routing and scheduling in packet-switched networks. We assume an adversary that controls the injection time, source, and destination for each packet injected. A set of paths for these packets is admissible if no link in the network is overloaded. We present the first on-line routing algorithm that finds a set of admissible paths whenever this is feasible. Our algorithm calculates a path for each packet as soon as it is injected at its source using a simple shortest path computation. The length of a link reflects its current congestion. We also show how our algorithm can be implemented under today's Internet routing paradigms.When the paths are known (either given by the adversary or computed as above), our goal is to schedule the packets along the given paths so that the packets experience small end-to-end delays. The best previous delay bounds for deterministic and distributed scheduling protocols were exponential in the path length. In this article, we present the first deterministic and distributed scheduling protocol that guarantees a polynomial end-to-end delay for every packet.Finally, we discuss the effects of combining routing with scheduling. We first show that some unstable scheduling protocols remain unstable no matter how the paths are chosen. However, the freedom to choose paths can make a difference. For example, we show that a ring with parallel links is stable for all greedy scheduling protocols if paths are chosen intelligently, whereas this is not the case if the adversary specifies the paths.

Keywords

Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, Network design and communication in computer systems, C.2.1; C.2.6; F.2.2, Deterministic scheduling theory in operations research, Computer Science - Networking and Internet Architecture, C.2.1, Computer Science - Distributed, Parallel, and Cluster Computing, C.2.6, Distributed, Parallel, and Cluster Computing (cs.DC), F.2.2, Performance evaluation, queueing, and scheduling in the context of computer systems

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    29
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
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    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
29
Average
Top 10%
Top 10%
Green
bronze