Queueing Characteristics of the Best Effort Network Coding Strategy
Asynchronous network coding has the potential to improve wireless network performance compared with simple routing. However, to achieve the maximum network coding gain, the encoding node consumes a few computing and storage resources that may be unaffordable for wireless sensor networks such as Cube...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2016-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/7574263/ |
| _version_ | 1819171741048504320 |
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| author | Xianxu Li Qing Chang Yong Xu |
| author_facet | Xianxu Li Qing Chang Yong Xu |
| author_sort | Xianxu Li |
| collection | DOAJ |
| description | Asynchronous network coding has the potential to improve wireless network performance compared with simple routing. However, to achieve the maximum network coding gain, the encoding node consumes a few computing and storage resources that may be unaffordable for wireless sensor networks such as CubeSats. An analogous threshold strategy, called best effort network coding (BENC), which requires only minimal storage resources and no computing resources, is investigated in this paper as an efficient and convenient method of network coding. In this strategy, a new packet arrival evicts the head packet when the queue is full to avoid excessively long waits. Moreover, in contrast to other methods that require a queue for each flow, the BENC uses only one queue for the two coded flows. In addition, the problem of time interval distribution for the output flow, which combines two independent flows, is investigated, and the network coding gain is then analyzed. While the maximum coding gain requires infinite buffer capacity under two independent Poisson arrivals with the same transmission rates, the calculation results show that the BENC needs only 4 buffers to achieve 90% of the maximum coding gain and can reach 99% of the maximum coding gain using 50 buffers. These results are verified by numerical simulations. |
| first_indexed | 2024-12-22T19:56:06Z |
| format | Article |
| id | doaj.art-4746fcb0e4974de29ade5e133abfa7ce |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T19:56:06Z |
| publishDate | 2016-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-4746fcb0e4974de29ade5e133abfa7ce2022-12-21T18:14:25ZengIEEEIEEE Access2169-35362016-01-0145990599710.1109/ACCESS.2016.26116197574263Queueing Characteristics of the Best Effort Network Coding StrategyXianxu Li0https://orcid.org/0000-0002-0241-3154Qing Chang1Yong Xu2School of Electronic and Information Engineering, Beihang University, Beijing, ChinaSchool of Electronic and Information Engineering, Beihang University, Beijing, ChinaSchool of Electronic and Information Engineering, Beihang University, Beijing, ChinaAsynchronous network coding has the potential to improve wireless network performance compared with simple routing. However, to achieve the maximum network coding gain, the encoding node consumes a few computing and storage resources that may be unaffordable for wireless sensor networks such as CubeSats. An analogous threshold strategy, called best effort network coding (BENC), which requires only minimal storage resources and no computing resources, is investigated in this paper as an efficient and convenient method of network coding. In this strategy, a new packet arrival evicts the head packet when the queue is full to avoid excessively long waits. Moreover, in contrast to other methods that require a queue for each flow, the BENC uses only one queue for the two coded flows. In addition, the problem of time interval distribution for the output flow, which combines two independent flows, is investigated, and the network coding gain is then analyzed. While the maximum coding gain requires infinite buffer capacity under two independent Poisson arrivals with the same transmission rates, the calculation results show that the BENC needs only 4 buffers to achieve 90% of the maximum coding gain and can reach 99% of the maximum coding gain using 50 buffers. These results are verified by numerical simulations.https://ieeexplore.ieee.org/document/7574263/Network codingbest effortqueueing analysisqueue capacitywireless sensor networks |
| spellingShingle | Xianxu Li Qing Chang Yong Xu Queueing Characteristics of the Best Effort Network Coding Strategy IEEE Access Network coding best effort queueing analysis queue capacity wireless sensor networks |
| title | Queueing Characteristics of the Best Effort Network Coding Strategy |
| title_full | Queueing Characteristics of the Best Effort Network Coding Strategy |
| title_fullStr | Queueing Characteristics of the Best Effort Network Coding Strategy |
| title_full_unstemmed | Queueing Characteristics of the Best Effort Network Coding Strategy |
| title_short | Queueing Characteristics of the Best Effort Network Coding Strategy |
| title_sort | queueing characteristics of the best effort network coding strategy |
| topic | Network coding best effort queueing analysis queue capacity wireless sensor networks |
| url | https://ieeexplore.ieee.org/document/7574263/ |
| work_keys_str_mv | AT xianxuli queueingcharacteristicsofthebesteffortnetworkcodingstrategy AT qingchang queueingcharacteristicsofthebesteffortnetworkcodingstrategy AT yongxu queueingcharacteristicsofthebesteffortnetworkcodingstrategy |