Analysis of Transmissions Scheduling with Packet Fragmentation

We investigate a scheduling problem in which packets, or datagrams, may be fragmented. While there are a few applications to scheduling with datagram fragmentation, our model of the problem is derived from a scheduling problem present in data over CATV networks. In the scheduling problem datagr...

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Main Authors: Nir Menakerman, Raphael Rom
Format: Article
Language:English
Published: Discrete Mathematics & Theoretical Computer Science 2001-12-01
Series:Discrete Mathematics & Theoretical Computer Science
Online Access:http://www.dmtcs.org/dmtcs-ojs/index.php/dmtcs/article/view/153
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spelling doaj-a3a0f1f9b175441bbe61a8d32d31cd792020-11-24T23:54:36ZengDiscrete Mathematics & Theoretical Computer ScienceDiscrete Mathematics & Theoretical Computer Science1462-72641365-80502001-12-0142Analysis of Transmissions Scheduling with Packet FragmentationNir MenakermanRaphael RomWe investigate a scheduling problem in which packets, or datagrams, may be fragmented. While there are a few applications to scheduling with datagram fragmentation, our model of the problem is derived from a scheduling problem present in data over CATV networks. In the scheduling problem datagrams of variable lengths must be assigned (packed) into fixed length time slots. One of the capabilities of the system is the ability to break a datagram into several fragments. When a datagram is fragmented, extra bits are added to the original datagram to enable the reassembly of all the fragments. We convert the scheduling problem into the problem of bin packing with item fragmentation, which we define in the following way: we are asked to pack a list of items into a minimum number of unit capacity bins. Each item may be fragmented in which case overhead units are added to the size of every fragment. The cost associated with fragmentation renders the problem NP-hard, therefore an approximation algorithm is needed. We define a version of the well-known Next-Fit algorithm, capable of fragmenting items, and investigate its performance. We present both worst case and average case results and compare them to the case where fragmentation is not allowed. http://www.dmtcs.org/dmtcs-ojs/index.php/dmtcs/article/view/153
collection DOAJ
language English
format Article
sources DOAJ
author Nir Menakerman
Raphael Rom
spellingShingle Nir Menakerman
Raphael Rom
Analysis of Transmissions Scheduling with Packet Fragmentation
Discrete Mathematics & Theoretical Computer Science
author_facet Nir Menakerman
Raphael Rom
author_sort Nir Menakerman
title Analysis of Transmissions Scheduling with Packet Fragmentation
title_short Analysis of Transmissions Scheduling with Packet Fragmentation
title_full Analysis of Transmissions Scheduling with Packet Fragmentation
title_fullStr Analysis of Transmissions Scheduling with Packet Fragmentation
title_full_unstemmed Analysis of Transmissions Scheduling with Packet Fragmentation
title_sort analysis of transmissions scheduling with packet fragmentation
publisher Discrete Mathematics & Theoretical Computer Science
series Discrete Mathematics & Theoretical Computer Science
issn 1462-7264
1365-8050
publishDate 2001-12-01
description We investigate a scheduling problem in which packets, or datagrams, may be fragmented. While there are a few applications to scheduling with datagram fragmentation, our model of the problem is derived from a scheduling problem present in data over CATV networks. In the scheduling problem datagrams of variable lengths must be assigned (packed) into fixed length time slots. One of the capabilities of the system is the ability to break a datagram into several fragments. When a datagram is fragmented, extra bits are added to the original datagram to enable the reassembly of all the fragments. We convert the scheduling problem into the problem of bin packing with item fragmentation, which we define in the following way: we are asked to pack a list of items into a minimum number of unit capacity bins. Each item may be fragmented in which case overhead units are added to the size of every fragment. The cost associated with fragmentation renders the problem NP-hard, therefore an approximation algorithm is needed. We define a version of the well-known Next-Fit algorithm, capable of fragmenting items, and investigate its performance. We present both worst case and average case results and compare them to the case where fragmentation is not allowed.
url http://www.dmtcs.org/dmtcs-ojs/index.php/dmtcs/article/view/153
work_keys_str_mv AT nirmenakerman analysisoftransmissionsschedulingwithpacketfragmentation
AT raphaelrom analysisoftransmissionsschedulingwithpacketfragmentation
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