Scheduling strategies to mitigate the impact of bursty traffic in wireless networks
Recent work has shown that certain queue-length based scheduling algorithms, such as max-weight, can lead to poor delays in the presence of bursty traffic. To overcome this phenomenon, we consider the problem of designing scheduling policies that are robust to bursty traffic, while also amenable to...
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers (IEEE)
2013
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| Online Access: | http://hdl.handle.net/1721.1/81839 https://orcid.org/0000-0001-8238-8130 |
| _version_ | 1826217988095737856 |
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| author | Jagannathan, Krishna Prasanna Jiang, Libin Naik, Palthya Lakshma Modiano, Eytan H. |
| author2 | Massachusetts Institute of Technology. Communications and Networking Research Group |
| author_facet | Massachusetts Institute of Technology. Communications and Networking Research Group Jagannathan, Krishna Prasanna Jiang, Libin Naik, Palthya Lakshma Modiano, Eytan H. |
| author_sort | Jagannathan, Krishna Prasanna |
| collection | MIT |
| description | Recent work has shown that certain queue-length based scheduling algorithms, such as max-weight, can lead to poor delays in the presence of bursty traffic. To overcome this
phenomenon, we consider the problem of designing scheduling policies that are robust to bursty traffic, while also amenable to practical implementation. Specifically, we discuss two mechanisms, one based on adaptive CSMA, and the second based on maximum-weight scheduling with capped queue lengths. We consider a simple queueing network consisting of two conflicting links. The traffic served by the first link is bursty, and is modeled as being heavy-tailed, while traffic at the second link is modeled using a light-tailed arrival process. In this setting, previous work has shown that even the light-tailed traffic would experience heavy-tailed delays under max-weight scheduling. In contrast, we demonstrate a threshold phenomenon in the relationship between the arrival rates and the queue backlog distributions. In particular, we show that with an adaptive CSMA scheme, when the arrival rate of the light-tailed traffic is less than a threshold value, the light-tailed traffic experiences a light-tailed queue backlog at steady state, whereas for arrival rates above the same threshold, the light-tailed traffic experiences a heavy-tailed queue backlog. We also show that a similar threshold behavior for max-weight scheduling with capped queue lengths |
| first_indexed | 2024-09-23T17:11:56Z |
| format | Article |
| id | mit-1721.1/81839 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T17:11:56Z |
| publishDate | 2013 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/818392022-09-30T00:22:25Z Scheduling strategies to mitigate the impact of bursty traffic in wireless networks Jagannathan, Krishna Prasanna Jiang, Libin Naik, Palthya Lakshma Modiano, Eytan H. Massachusetts Institute of Technology. Communications and Networking Research Group Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Modiano, Eytan H. Jagannathan, Krishna Prasanna Recent work has shown that certain queue-length based scheduling algorithms, such as max-weight, can lead to poor delays in the presence of bursty traffic. To overcome this phenomenon, we consider the problem of designing scheduling policies that are robust to bursty traffic, while also amenable to practical implementation. Specifically, we discuss two mechanisms, one based on adaptive CSMA, and the second based on maximum-weight scheduling with capped queue lengths. We consider a simple queueing network consisting of two conflicting links. The traffic served by the first link is bursty, and is modeled as being heavy-tailed, while traffic at the second link is modeled using a light-tailed arrival process. In this setting, previous work has shown that even the light-tailed traffic would experience heavy-tailed delays under max-weight scheduling. In contrast, we demonstrate a threshold phenomenon in the relationship between the arrival rates and the queue backlog distributions. In particular, we show that with an adaptive CSMA scheme, when the arrival rate of the light-tailed traffic is less than a threshold value, the light-tailed traffic experiences a light-tailed queue backlog at steady state, whereas for arrival rates above the same threshold, the light-tailed traffic experiences a heavy-tailed queue backlog. We also show that a similar threshold behavior for max-weight scheduling with capped queue lengths National Science Foundation (U.S.) (Grant CNS-0915988) National Science Foundation (U.S.) (Grant CNS-1217048) United States. Army Research Office. Multidisciplinary University Research Initiative (Grant W911NF-08-1-0238) 2013-10-29T17:10:06Z 2013-10-29T17:10:06Z 2013-05 Article http://purl.org/eprint/type/ConferencePaper 978-3-901882-54-8 http://hdl.handle.net/1721.1/81839 Jagannathan, Krishna et al. "Scheduling strategies to mitigate the impact of bursty traffic in wireless networks." IEEE 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt), 2013. https://orcid.org/0000-0001-8238-8130 en_US http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6576469 Proceedings of the 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt) Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) MIT web domain |
| spellingShingle | Jagannathan, Krishna Prasanna Jiang, Libin Naik, Palthya Lakshma Modiano, Eytan H. Scheduling strategies to mitigate the impact of bursty traffic in wireless networks |
| title | Scheduling strategies to mitigate the impact of bursty traffic in wireless networks |
| title_full | Scheduling strategies to mitigate the impact of bursty traffic in wireless networks |
| title_fullStr | Scheduling strategies to mitigate the impact of bursty traffic in wireless networks |
| title_full_unstemmed | Scheduling strategies to mitigate the impact of bursty traffic in wireless networks |
| title_short | Scheduling strategies to mitigate the impact of bursty traffic in wireless networks |
| title_sort | scheduling strategies to mitigate the impact of bursty traffic in wireless networks |
| url | http://hdl.handle.net/1721.1/81839 https://orcid.org/0000-0001-8238-8130 |
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