Optimal frame size analysis for fragmentation and aggregation algorithm

Eunbi Ku; Chulho Chung; Byungcheol Kang; Jaeseok Kim

doi:10.1109/TENCON.2016.7848646

Optimal frame size analysis for fragmentation and aggregation algorithm

Eunbi Ku, Chulho Chung, Byungcheol Kang, Jaeseok Kim

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

In the IEEE 802.11 medium access control (MAC) layer, the reliability as well as the throughput is also important. The fragmentation and aggregation (F&A) algorithm to improve the throughput while ensuring the reliability in the environment with error uses the MAC service data unit (MSDU) fragmentation scheme of the upper layer and the MAC protocol data unit (MPDU) aggregation scheme of the MAC layer. The aggregation technique reduces the overhead of the frame format and improves the throughput. The fragmentation technique increases the transmission success probability and improves the reliability. When using F&A algorithm, the network throughput can be further improved. Although there were a lot of research on the F&A algorithm, these didn't cover the fragment size. Then it is left as user's choice. Furthermore, there is always a tradeoff between fragmentation and aggregation for wireless local area network (WLAN). We study this tradeoff and propose an optimal fragment size for aggregate-MPDU (A-MPDU), which can maximize the throughput by selecting the optimized fragment length based on different channel conditions.

Original language	English
Title of host publication	Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3228-3231
Number of pages	4
ISBN (Electronic)	9781509025961
DOIs	https://doi.org/10.1109/TENCON.2016.7848646
Publication status	Published - 2017 Feb 8
Event	2016 IEEE Region 10 Conference, TENCON 2016 - Singapore, Singapore Duration: 2016 Nov 22 → 2016 Nov 25

Publication series

Name	IEEE Region 10 Annual International Conference, Proceedings/TENCON
ISSN (Print)	2159-3442
ISSN (Electronic)	2159-3450

Other

Other	2016 IEEE Region 10 Conference, TENCON 2016
Country/Territory	Singapore
City	Singapore
Period	16/11/22 → 16/11/25

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

All Science Journal Classification (ASJC) codes

Computer Science Applications
Electrical and Electronic Engineering

Access to Document

10.1109/TENCON.2016.7848646

Cite this

Ku, E., Chung, C., Kang, B., & Kim, J. (2017). Optimal frame size analysis for fragmentation and aggregation algorithm. In Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016 (pp. 3228-3231). [7848646] (IEEE Region 10 Annual International Conference, Proceedings/TENCON). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TENCON.2016.7848646

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abstract = "In the IEEE 802.11 medium access control (MAC) layer, the reliability as well as the throughput is also important. The fragmentation and aggregation (F&A) algorithm to improve the throughput while ensuring the reliability in the environment with error uses the MAC service data unit (MSDU) fragmentation scheme of the upper layer and the MAC protocol data unit (MPDU) aggregation scheme of the MAC layer. The aggregation technique reduces the overhead of the frame format and improves the throughput. The fragmentation technique increases the transmission success probability and improves the reliability. When using F&A algorithm, the network throughput can be further improved. Although there were a lot of research on the F&A algorithm, these didn't cover the fragment size. Then it is left as user's choice. Furthermore, there is always a tradeoff between fragmentation and aggregation for wireless local area network (WLAN). We study this tradeoff and propose an optimal fragment size for aggregate-MPDU (A-MPDU), which can maximize the throughput by selecting the optimized fragment length based on different channel conditions.",

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Ku, E, Chung, C, Kang, B & Kim, J 2017, Optimal frame size analysis for fragmentation and aggregation algorithm. in Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016., 7848646, IEEE Region 10 Annual International Conference, Proceedings/TENCON, Institute of Electrical and Electronics Engineers Inc., pp. 3228-3231, 2016 IEEE Region 10 Conference, TENCON 2016, Singapore, Singapore, 16/11/22. https://doi.org/10.1109/TENCON.2016.7848646

Optimal frame size analysis for fragmentation and aggregation algorithm. / Ku, Eunbi; Chung, Chulho; Kang, Byungcheol et al.

Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 3228-3231 7848646 (IEEE Region 10 Annual International Conference, Proceedings/TENCON).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - In the IEEE 802.11 medium access control (MAC) layer, the reliability as well as the throughput is also important. The fragmentation and aggregation (F&A) algorithm to improve the throughput while ensuring the reliability in the environment with error uses the MAC service data unit (MSDU) fragmentation scheme of the upper layer and the MAC protocol data unit (MPDU) aggregation scheme of the MAC layer. The aggregation technique reduces the overhead of the frame format and improves the throughput. The fragmentation technique increases the transmission success probability and improves the reliability. When using F&A algorithm, the network throughput can be further improved. Although there were a lot of research on the F&A algorithm, these didn't cover the fragment size. Then it is left as user's choice. Furthermore, there is always a tradeoff between fragmentation and aggregation for wireless local area network (WLAN). We study this tradeoff and propose an optimal fragment size for aggregate-MPDU (A-MPDU), which can maximize the throughput by selecting the optimized fragment length based on different channel conditions.

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Optimal frame size analysis for fragmentation and aggregation algorithm

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