# Delay sensitive resource allocation over high speed IEEE802.11 wireless LANs

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## Abstract

We present a novel resource allocation framework based on frame aggregation for providing a statistical Quality of Service (QoS) guarantee in high speed IEEE802.11 Wireless Local Area Networks. Considering link quality fluctuations through the concept of effective capacity, we formulate an optimization problem for resource allocation with QoS guarantees, which are expressed in terms of target delay bound and delay violation probability. Our objective is to have the access point schedule down-links at minimum resource usage, i.e., total time allowance, while their QoS is satisfied. For implementation simplicity, we then consider a surrogate optimization problem based on a few accurate queuing model approximations. We propose a novel metric that qualitatively captures the surplus resource provisioning for a particular statistical delay guarantee, and using this metric, we devise a simple-to-implement Proportional–Integral–Derivative (PID) controller achieving the optimal frame aggregation size according to the time allowance. The proposed PID algorithm independently adapts the amount of time allowance for each link, and it is implemented only at the Access Point without requiring any changes to the IEEE802.11 Medium Access Control layer. More importantly, our resource allocation algorithm does not consider any channel state information, as it only makes use of queue level information, such as the average queue length and link utilization. Via NS-3 simulations as well as real test-bed experiments with the implementation of the algorithm over commodity IEEE 802.11 devices, we demonstrate that the proposed scheme outperforms the Earliest Deadline First (EDF) scheduling with maximum aggregation size and pure deadline-based schemes, both in terms of the maximum number of stations and channel efficiency by 10–30%. These results are also verified with analytical results, which we have obtained from a queuing model based approximation of the system. Applying actual video traffic from HD MPEG4 streams in both simulations and real test-bed experiments, we also show that our proposed algorithm improves the quality of video streaming over a wireless LAN, and it outperforms EDF and deadline based schemes in terms of the video metric, Peak Signal to Noise Ratio.

## Keywords

Effective capacity WLAN PID controller Link scheduling Quality of service Queuing Resource allocation## Notes

### Acknowledgements

This work was done while Seyed Vahid Azhari was visiting Sabanci University via the support of TUBITAK 2221 fellowship program. In addition, the testbed used for the experimental results of this paper was setup at Bu-Ali Sina University.

## References

- 1.CISCO. (2015). Cisco visual networking index: Forecast and methodology.
*2014–2019 White Paper*.Google Scholar - 2.IEEE standard for information technology. (2009). Local and metropolitan area networks—Specific requirements—Part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications amendment 5: Enhancements for higher throughput.
*IEEE Std 802.11n-2009 (Amendment to IEEE Std 802.11-2007 as amended by IEEE Std 802.11k-2008, IEEE Std 802.11r-2008, IEEE Std 802.11y-2008, and IEEE Std 802.11w-2009)*(pp. 1–565).Google Scholar - 3.U. It. ITU-T recommendation G.114. Technical report, International Telecommunication Union, 1993.Google Scholar
- 4.Wu, D., & Negi, R. (2006). Effective capacity-based quality of service measures for wireless networks.
*Mobile Networks and Applications*,*11*(1), 91–99.CrossRefGoogle Scholar - 5.Ku, E., Chung, C., Kang, B., & Kim, J. (2016). Throughput enhancemnet with optimal fragmented MSDU size for fragmentation and aggregation scheme in WLANs. In
*2016 international SoC design conference (ISOCC)*(pp. 287–288).Google Scholar - 6.Olariu, C., Fitzpatrick, J., Ghamri-Doudane, Y., & Murphy, L. (2016). A delay-aware packet prioritisation mechanism for voice over IP in wireless mesh networks. In
*2016 IEEE wireless communications and networking conference*(pp. 1–7).Google Scholar - 7.Loch, A., & Sim, G. H. (2016). Millimeter-wave blind spots: Mitigating deafness collisions using frame aggregation. In
*2016 IEEE conference on computer communications workshops (INFOCOM WKSHPS)*(pp. 158–163).Google Scholar - 8.Cai, L. X., Ling, X., Shen, X. S., Mark, J. W., & Cai, L. (2009). Supporting voice and video applications over IEEE 802.11 n WLANs.
*Wireless Networks*,*15*(4), 443–454.CrossRefGoogle Scholar - 9.Sarret, M. G., Ashta, J. S., Mogensen, P., Catania, D., & Cattoni, A. F. (2013). A multi-QoS aggregation mechanism for improved fairness in WLAN. In
*2013 IEEE 78th vehicular technology conference (Vtc Fall)*(pp. 1–5).Google Scholar - 10.Seytnazarov, S., & Kim, Y. T. (2018). QoS-aware adaptive A-MPDU aggregation scheduler for enhanced VoIP capacity over aggregation-enabled WLANs. In
*NOMS 2018–2018 IEEE/IFIP network operations and management symposium*(pp. 1–7).Google Scholar - 11.Wang, P., & Petrova, M. (2016). Cross talk MAC: A directional MAC scheme for enhancing frame aggregation in mm-wave wireless personal area networks. In
*2016 IEEE international conference on communications workshops (ICC)*(pp. 602–607).Google Scholar - 12.Ksentini, A., Guéroui, A., & Naimi, M. (2005). Adaptive transmission opportunity with admission control for IEEE 802.11 e networks. In
*Proceedings of the 8th ACM international symposium on modeling, analysis and simulation of wireless and mobile systems*(pp. 234–241).Google Scholar - 13.Liu, H., & Zhao, Y. (2006). Adaptive EDCA algorithm using video prediction for multimedia IEEE 802.11 e WLAN. In
*International conference on wireless and mobile communications, 2006. ICWMC’06*(pp. 10–10). IEEE.Google Scholar - 14.Ferng, H.-W., & Leonovich, A. (2014). Periods scheduling under the HCCA mode of IEEE 802.11e.
*IEEE Transactions on Wireless Communications*,*13*(12), 7037–7049.CrossRefGoogle Scholar - 15.Kuo, W.-K. (2008). Traffic scheduling for multimedia transmission over IEEE 802.11 e wireless LAN.
*IET Communications*,*2*(1), 92–97.CrossRefGoogle Scholar - 16.Liu, J., Yao, M., & Qiu, Z. (2016). Adaptive a-MPDU retransmission scheme with two-level frame aggregation compensation for IEEE 802.11n/ac/ad WLANs.
*Wireless Networks*,*24*(1), 1–12.CrossRefGoogle Scholar - 17.Sharon, O., Alpert, Y., & Coupled, I. E. E. E. (2016). 802.11ac and TCP performance evaluation in various aggregation schemes and access categories.
*Computer Networks*,*100*, 141–156.CrossRefGoogle Scholar - 18.Wang, W., Chen, Y., Zhang, Q., Wu, K., & Zhang, J. (2016). Less transmissions, more throughput: Bringing carpool to public WLANs.
*IEEE Transactions on Mobile Computing*,*15*(5), 1168–1181.CrossRefGoogle Scholar - 19.Grilo, A., Macedo, M., & Nunes, M. (2003). A scheduling algorithm for QoS support in ieee802. 11 networks.
*IEEE Wireless Communications*,*10*(3), 36–43.CrossRefGoogle Scholar - 20.Ju, K., Lee, D., & Chung, K. (2012). Dynamic TXOP allocation to support QoS based on channel conditions in wireless networks. In
*2012 8th international conference on computing technology and information management (ICCM)*(Vol. 2, pp. 721–724). IEEE.Google Scholar - 21.Bhatia, R., Lakshman, T. V., Netravali, A., & Sabnani, K. (2014). Improving mobile video streaming with link aware scheduling and client caches. In
*2014 Proceedings IEEE INFOCOM*(pp. 100–108). IEEE.Google Scholar - 22.Arora, A., Yoon, S.-G., Choi, Y.-J., & Bahk, S. (2010). Adaptive TXOP allocation based on channel conditions and traffic requirements in ieee 802.11e networks.
*IEEE Transactions on Vehicular Technology*,*59*(3), 1087–1099.CrossRefGoogle Scholar - 23.Zhou, X., & Boukerche, A. (2017). Aflas: An adaptive frame length aggregation scheme for vehicular networks.
*IEEE Transactions on Vehicular Technology*,*66*(1), 855–867.Google Scholar - 24.Abdallah, S., & Blostein, S. D. (2016). Joint rate adaptation, frame aggregation and MIMO mode selection for ieee 802.11ac. In
*2016 IEEE wireless communications and networking conference*(pp. 1–6).Google Scholar - 25.Davy, A., Meskill, B., & Domingo-Pascual, J. (2012). An empirical study of effective capacity throughputs in 802.11 wireless networks. In
*2012 IEEE global communications conference (GLOBECOM)*(pp. 1770–1775). IEEE.Google Scholar - 26.Charfi, E., Gueguen, C., Chaari, L., Cousin, B., & Kamoun, L. (2015). Dynamic frame aggregation scheduler for multimedia applications in ieee 802.11n networks.
*Transactions on Emerging Telecommunications Technologies, 28*(2), e2942.Google Scholar - 27.Annese, A., Boggia, G., Camarda, P., Grieco, L. A., & Mascolo, S. (2004). Providing delay guarantees in ieee 802.11 e networks. In
*2004 IEEE 59th vehicular technology conference, 2004. VTC 2004-Spring*(Vol. 4, pp. 2234–2238). IEEE.Google Scholar - 28.Azhari, S. V., Gurbuz, O., & Ercetin, O. (2016). QoS based aggregation in high speed ieee802.11 wireless networks. In
*2016 Mediterranean Ad Hoc networking workshop (Med-Hoc-Net)*(pp. 1–7).Google Scholar - 29.Choudhury, G. L., Lucantoni, D. M., & Whitt, W. (1996). Squeezing the most out of ATM.
*IEEE Transactions on Communications*,*44*(2), 203–217.CrossRefGoogle Scholar - 30.Dapeng, W., & Negi, R. (2003). Effective capacity: A wireless link model for support of quality of service.
*IEEE Transactions on Wireless Communications*,*2*(4), 630–643.CrossRefGoogle Scholar - 31.Wang, H. S., & Moayeri, N. (1995). Finite-state markov channel-a useful model for radio communication channels.
*IEEE Transactions on Vehicular Technology*,*44*(1), 163–171.CrossRefGoogle Scholar - 32.IEEE standard for information technology. (2013). Telecommunications and information exchange between systemslocal and metropolitan area networks—Specific requirements—Part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications—Amendment 4: Enhancements for very high throughput for operation in bands below 6 ghz.
*IEEE Std 802.11ac-2013 (Amendment to IEEE Std 802.11-2012, as amended by IEEE Std 802.11ae-2012, IEEE Std 802.11aa-2012, and IEEE Std 802.11ad-2012)*(pp. 1–425).Google Scholar - 33.Aström, K. J., & Hägglund, T. (1995).
*PID controllers: Theory, design, and tuning*(2nd ed.). Pittsburgh: ISA.Google Scholar - 34.Rachedi, A., & Gueguen, C. (2016). Scheduling algorithm based on PID controller for OFDM wireless networks. In
*2016 international wireless communications and mobile computing conference (IWCMC)*(pp. 880–885).Google Scholar - 35.Domingo-Prieto, M., Chang, T., Vilajosana, X., & Watteyne, T. (2016). Distributed PID-based scheduling for 6tisch networks.
*IEEE Communications Letters*,*20*(5), 1006–1009.CrossRefGoogle Scholar - 36.Nguyen, V. A. Q., & Tran, T. V. (2017). Analysis of packet loss on scheduling over wireless real-time control system. In
*2017 seventh international conference on information science and technology (ICIST)*(pp. 29–31).Google Scholar - 37.Li, Y., Ang, K. H., & Chong, G. C. Y. (2006). PID control system analysis and design.
*IEEE Control Systems*,*26*(1), 32–41.CrossRefGoogle Scholar - 38.Kleinrock, L. (1975).
*Queueing systems*(Vol. 1). New York: Wiley.zbMATHGoogle Scholar