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1

Bhavadharini, R. M., S. Karthik, N. Karthikeyan, and Anand Paul. "Wireless Networking Performance in IoT Using Adaptive Contention Window." Wireless Communications and Mobile Computing 2018 (July 3, 2018): 1–9. http://dx.doi.org/10.1155/2018/7248040.

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Internet of Things (IoT) network contains heterogeneous resource-constrained computing devices which has its unique reputation in IoT environments. In spite of its distinctiveness, the network performance deteriorates by the distributed contention of the nodes for the shared wireless medium in IoT. In IoT network, the Medium Access Control (MAC) layer contention impacts the level of congestion at the transport layer. Further, the increasing node contention at the MAC layer increases link layer frame drops resulting in timeouts at the transport layer segments and the performance of TCP degrades. In addition to that, the expiration of maximum retransmission attempts and the high contentions drive the MAC retransmissions and the associated overheads to reduce the link level throughput and the packet delivery ratio. In order to deal with aforementioned problems, the Adaptive Contention Window (ACW) is proposed, which aims to reduce the MAC overhead and retransmissions by determining active queue size at the contending nodes and the energy level of the nodes to improve TCP performance. Further, the MAC contention window is adjusted according to the node’s active queue size and the residual energy and TCP congestion window is dynamically adjusted based on the MAC contention window. Hence, by adjusting the MAC Adaptive Contention Window, the proposed model effectively distributes the access to medium and assures improved network throughput. Finally, the simulation study implemented through ns-2 is compared with an existing methodology such as Cross-Layer Congestion Control and dynamic window adaptation (CC-BADWA); the proposed model enhances the network throughput with the minimal collisions.
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Sartthong, Jesada, Suvepon Sittichivapak, and Nitthita Chirdchoo. "Several Contention Window Adjustment Techniques for Improving Unsaturated throughput of Wireless LANs." Advanced Materials Research 931-932 (May 2014): 952–56. http://dx.doi.org/10.4028/www.scientific.net/amr.931-932.952.

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This paper proposes the several contention window adjustment schemes in backoff process as well-known backoff algorithm (BA) for improving the performance of wireless local area network (WLAN). In addition, this research introduces a new unsaturated discrete Markov chain model in fixed backoff stages and fixed contention window sizes technique (FBFC). The proposed contention window adjustment schemes are designed by applying the moment generating function concept in random variable and process theorem. Unsaturated throughput parameters are used to compare the performance of all contention window size adjustment techniques based on IEEE802.11b WLAN standards. The comparison results show that Bernoulli and Double adjustment schemes are good contention window size adjustments at light traffic load, and the Even contention window size adjustment operates well at high traffic load condition.
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Lin, Chun-Liang, Wei-Ting Chang, and Min-Huei Lu. "MAC Throughput Improvement Using Adaptive Contention Window." Journal of Computer and Communications 03, no. 01 (2015): 1–14. http://dx.doi.org/10.4236/jcc.2015.31001.

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4

Bhuyan, Nasimul Hyder Maruf, and Sabrina Alam. "Network Performance of Contention Window in VANET." European Journal of Engineering Research and Science 3, no. 2 (February 28, 2018): 43. http://dx.doi.org/10.24018/ejers.2018.3.2.611.

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In this paper, we tried to presented the effect of different contention window (CW) size in a realistic road environment with mobility management and different propagation loss model was implemented in ns-3. We focus on the WAVE module of ns-3. Our contribution is to create a realistic two-lane both way highway road environment surrounding by fields, low-rise commercial buildings, street lamps and road signs for vehicular safety messages are Cooperative Awareness Message (CAM) and Decentralized Event Notification Message (DENM). Medium to low traffic density. On the other section, we describe in detail the simulation setup scenario during the implementation. Finally, we present our simulation results that we obtained from the highway scenario.
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5

Gao, Renzheng, Xiaoying Lei, and Qiang Hu. "An Adaptive Contention Window Scheme for 802.11ah WLANs." ITM Web of Conferences 17 (2018): 01016. http://dx.doi.org/10.1051/itmconf/20181701016.

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In order to cope with the rapid development of the Internet of things, IEEE working group has proposed a new wireless network technology, 802.11ah. IEEE 802.11ah operates at sub 1GHz band, and can provide long transmission range, wide coverage, while supporting more than 6,000 of station to be connected. In order to alleviate the high collision probability, 802.11ah MAC protocol involves in the RAW (restricted access window) mechanism combined with grouping mechanism. However, in 802.11ah WLAN (wireless local area network), most of the stations operate at sleep mode, and it is expected that at the start of a BI, the network suffers much higher collision probability than at the latter period of the BI. In order to improve these drawbacks, we propose an adaptive contention window scheme based on which an optimum contention window size is adapted at the start of the BI, and then gradually halved when the transmission completes successfully. Through conducting simulations, we prove that our proposed protocol can enhance the performance of 802.11ah WLAN.
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6

Nithya, B., A. Justin Gopinath, Venkatesh Kameswaran, and P. Yogesh. "Optimized tuning of contention window for IEEE 802.11 WLAN." International Journal of Engineering, Science and Technology 9, no. 2 (May 29, 2017): 15. http://dx.doi.org/10.4314/ijest.v9i2.2.

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7

Pudasaini, Subodh, Moonsoo Kang, Seokjoo Shin, and John A. Copeland. "COMIC: Intelligent Contention Window Control for Distributed Medium Access." IEEE Communications Letters 14, no. 7 (July 2010): 656–58. http://dx.doi.org/10.1109/lcomm.2010.07.100287.

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8

Deng, Der-Jiunn, Chih-Heng Ke, Hsiao-Hwa Chen, and Yueh-Min Huang. "Contention window optimization for ieee 802.11 DCF access control." IEEE Transactions on Wireless Communications 7, no. 12 (December 2008): 5129–35. http://dx.doi.org/10.1109/t-wc.2008.071259.

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9

Babich, F., and M. Comisso. "Optimum contention window for 802.11 networks adopting Directional Communications." Electronics Letters 44, no. 16 (2008): 994. http://dx.doi.org/10.1049/el:20081505.

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10

Lukyanenko, Andrey, Andrei Gurtov, and Evsey Morozov. "An Adaptive Backoff Protocol with Markovian Contention Window Control." Communications in Statistics - Simulation and Computation 41, no. 7 (August 2012): 1093–106. http://dx.doi.org/10.1080/03610918.2012.625817.

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11

Kim, Meejoung, and Wooyong Lee. "Optimal contention window size for IEEE 802.15.3c mmWave WPANs." Wireless Networks 20, no. 6 (December 20, 2013): 1335–47. http://dx.doi.org/10.1007/s11276-013-0682-x.

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12

Pei, Zhonghui, Xiaojun Wang, Zhen Lei, Hongjiang Zheng, Luyao Du, and Wei Chen. "Joint Optimization of Multi-Hop Broadcast Protocol and MAC Protocol in Vehicular Ad Hoc Networks." Sensors 21, no. 18 (September 11, 2021): 6092. http://dx.doi.org/10.3390/s21186092.

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Beacon messages and emergency messages in vehicular ad hoc networks (VANETs) require a lower delay and higher reliability. The optimal MAC protocol can effectively reduce data collision in VANETs communication, thus minimizing delay and improving reliability. In this paper, we propose a Q-learning MAC protocol based on detecting the number of two-hop neighbors. The number of two-hop neighbors in highway scenarios is calculated with very little overhead using the beacon messages and neighbor locations to reduce the impact of hidden nodes. Vehicle nodes are regarded as agents, using Q-learning and beacon messages to train the near-optimal contention window value of the MAC layer under different vehicle densities to reduce the collision probability of beacon messages. Furthermore, based on the contention window value after training, a multi-hop broadcast protocol combined with contention window adjustment for emergency messages in highway scenarios is proposed to reduce forwarding delay and improve forwarding reliability. We use the trained contention window value and the state information of neighboring vehicles to assign an appropriate forwarding waiting time to the forwarding node. Simulation experiments are conducted to evaluate the proposed MAC protocol and multi-hop broadcast protocol and compare them with other related protocols. The results show that our proposed protocols outperform the other related protocols on several different evaluation metrics.
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13

Upadhyay, Raksha, Prakash D. Vyavahare, and Sanjiv Tokekar. "Collision Resolution Schemes with Nonoverlapped Contention Slots for Heterogeneous and Homogeneous WLANs." Journal of Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/852959.

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CSMA/CA-based DCF of 802.11 MAC layer employs a best-effort delivery model, in which stations compete for channel access with the same priority. In a heterogeneous network, providing different priorities to different applications for required quality of service is a challenging task, since heterogeneous conditions result in unfairness among stations and degradation in the throughput. This paper proposes a class of collision resolution schemes for 802.11 having contention window control with nonoverlapped contention slots. In the first scheme, window ranges of two consecutive stages are nonoverlapped, and it is called nonoverlapped contention slots (NOCS) scheme. In the other scheme, termed as NOCS-offset, an offset is introduced between window ranges of two stages. Selection of a random value by a station for its contention with discontinuous distribution results in reduced probability of collision. Analytical and simulation results show that the proposed scheme exhibits higher throughput and fairness with reduced delay and collision probability in homogeneous and heterogeneous networks. Performance of the proposed scheme is evaluated for mix traffic and high data rate environment with advanced back-off management techniques to meet the requirements of the present applications.
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14

Lim, Wan-Seon, Dong-Wook Kim, Young-Joo Suh, and Dong-Hee Kwon. "A Contention Window Adjustment Algorithm for Improving Fairness between Uplink and Downlink in IEEE 802.11 WLANs." Journal of Korean Institute of Communications and Information Sciences 36, no. 4A (April 30, 2011): 329–36. http://dx.doi.org/10.7840/kics.2011.36a.4.329.

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15

Anbazhagan, Rajesh, and Nakkeeran Rangaswamy. "Investigation on Mutual Contention Bandwidth Request Mechanisms in Two-Hop Relay Network with ITU-R Path Loss Models." ISRN Communications and Networking 2013 (May 29, 2013): 1–13. http://dx.doi.org/10.1155/2013/417132.

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The performance of two-hop contention based bandwidth request (BR) mechanism for WiMAX relay networks is investigated under ITU-R path loss models. In conventional WiMAX systems, the mobile stations (MS) update their contention window irrespective of their transmission failures. Those systems update their contention window on collision and due to channel error or unavailability of bandwidth. Further, these failure models have been suggested for single hop networks. The failure model in two-hop systems becomes complex since it may include additional failure events such as improper detection of codes and channel error due to varying path loss. Interestingly, these failure events (collision, channel error, unavailability of bandwidth, and improper detection of codes) do not occur evenly for both hops of a link. Hence, to set the contention window effectively, unique failure models are developed by considering the characteristics of BR mechanism and hop at which the BR is performed. In the proposed system, the two-hop BR is carried out with all combinations of message and code bandwidth request schemes. Among them, the message-code BR mechanism performs better under suburban fixed and outdoor to indoor or pedestrian environment, and code-code BR scheme performs better for vehicular environment.
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16

Abu-Khadrah, Ahmed Ismail, Zahriladha Zakaria, Mohdazlishah Othman, and Mohd Shahril Izuan Mohd Zin. "Enhance the Performance of EDCA Protocol by Adapting Contention Window." Wireless Personal Communications 96, no. 2 (April 21, 2017): 1945–71. http://dx.doi.org/10.1007/s11277-017-4277-1.

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17

Kouka, Neji, Tarek Guesmi, K. Ashokkumar, and Ouajdi Korbaa. "An Improvement of Contention Window for IEEE 802.15.6 CSMA/CA." Journal of Computational and Theoretical Nanoscience 17, no. 8 (August 1, 2020): 3333–36. http://dx.doi.org/10.1166/jctn.2020.9181.

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The IEEE 802.15.6 standard is become an essential wireless access technology for the WBAN networks, with an objective to adapt wireless communications to the recent applications. This paper proposes an improvement of the well known CSMA/CA procedure with an idea to give a new size of its contention window length. Simulation results show that, compared with standard IEEE 802.15.6, the delay time, packet loss rate of the improved CSMA/CA are be significantly reduced.
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18

Lee, Myung Woo, and Ganguk Hwang. "Adaptive Contention Window Control Scheme in Wireless Ad Hoc Networks." IEEE Communications Letters 22, no. 5 (May 2018): 1062–65. http://dx.doi.org/10.1109/lcomm.2018.2813361.

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19

Hong, Kunho, SuKyoung Lee, Kyungsoo Kim, and YoonHyuk Kim. "Channel Condition Based Contention Window Adaptation in IEEE 802.11 WLANs." IEEE Transactions on Communications 60, no. 2 (February 2012): 469–78. http://dx.doi.org/10.1109/tcomm.2012.012012.100472.

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20

Balador, Ali, Sam Jabbehdari, Ali Movaghar, and Dimitris Kanellopoulos. "A Novel Contention Window Control Scheme for IEEE 802.11 WLANs." IETE Technical Review 29, no. 3 (2012): 202. http://dx.doi.org/10.4103/0256-4602.98862.

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21

Rao, Yuan, Cheng Deng, Jun Su, Yan Qiao, Jun Zhu, and Ru-chuan Wang. "Setting strategy of delay-optimization-oriented SMAC contention window size." PLOS ONE 12, no. 7 (July 21, 2017): e0181506. http://dx.doi.org/10.1371/journal.pone.0181506.

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22

Wu, Chien-Min, Yen-Chun Kao, and Kai-Fu Chang. "A Multichannel MAC Protocol for IoT-enabled Cognitive Radio Ad Hoc Networks." Advances in Technology Innovation 5, no. 1 (January 1, 2020): 45–55. http://dx.doi.org/10.46604/aiti.2020.3946.

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Cognitive radios have the ability to dynamically sense and access the wireless spectrum, and this ability is a key factor in successfully building Internet-of-Things (IoT)-enabled mobile ad hoc networks. This paper proposes a contention-free token-based multichannel MAC protocol for IoT-enabled Cognitive Radio Ad Hoc Networks (CRAHNs). In this, secondary users of CRAHNs detect activity on the wireless spectrum and then access idle channels licensed by primary users. CRAHNs are divided into clusters, and the channel to use for transmission is determined dynamically from the probability of finding idle primary-user channels. The token-based MAC window size is adaptive, with adjustment according to actual traffic, which reduces both end-to-end MAC contention delay and energy consumption. High throughput and spatial reuse of channels can also be achieved using a dynamic control channel and dynamic schemes for contention windows. We performed extensive simulations to verify that the proposed method can achieve better performance in mobile CRAHNs than other MAC schemes can.
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23

Khan, Bilal, Rana Rehman, and Byung-Seo Kim. "A Joint Strategy for Fair and Efficient Energy Usage in WLANs in the Presence of Capture Effect." Electronics 8, no. 4 (March 30, 2019): 386. http://dx.doi.org/10.3390/electronics8040386.

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Capture effect has been shown as a physical layer (PHY) phenomenon of modern wireless devices that improves the performance of wireless local area networks (WLANs) in terms of throughput. In this paper, however, we explore the effect of PHY capture in the domain of energy efficiency. Analysis model that takes into account the effect of PHY capture is backed up by ns-2 simulations show that capture effect improves energy efficiency of WLAN by 20%. This improvement, however, results in unfairness, i.e, a group of nodes located far away from the Access Point (AP) is three times less energy efficient than the group of nodes located closer to the AP. To resolve the unfairness caused by the capture effect, furthermore, this paper proposes a joint strategy of adaptive transmission power control (ATXPR) and contention window adjustment (CWADJ). Namely, a node that suffers transmission failure due to another node capturing the channel steps up its transmission power according to the transmission power control algorithm and refrains from increasing its contention window according to contention window adjustment mechanism, respectively. Our proposed joint strategy is 99% fair while maintaining overall energy efficiency of the network.
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24

CHOI, Seung-Sik. "Performance Analysis of NAV Based Contention Window in IEEE 802.11 LAN." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E97.A, no. 1 (2014): 436–39. http://dx.doi.org/10.1587/transfun.e97.a.436.

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25

Saraireh, Mohammad, Ja`afer AL-Saraire, and Saleh Saraireh. "A Novel Adaptive Contention Window Scheme for IEEE 802.11 MAC Protocol." Trends in Applied Sciences Research 9, no. 6 (June 1, 2014): 275–89. http://dx.doi.org/10.3923/tasr.2014.275.289.

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26

MAO, Jian-bing, Yu-ming MAO, and Su-peng LENG. "Bandwidth allocation by optimal contention window setting for IEEE 802.11 EDCA." Journal of Computer Applications 29, no. 1 (May 31, 2009): 1–4. http://dx.doi.org/10.3724/sp.j.1087.2009.00001.

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27

Kalaiarasi, R., Getsy S. Sara, S. Neelavathy Pari, and D. Sridharan. "Performance Analysis of Contention Window Cheating Misbehaviors in Mobile Adhoc Networks." International Journal of Computer Science and Information Technology 2, no. 5 (October 29, 2010): 31–42. http://dx.doi.org/10.5121/ijcsit.2010.2503.

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28

Zhang, Xin Ming, Wen Bo Zhu, Na Na Li, and Dan Keun Sung. "TCP Congestion Window Adaptation Through Contention Detection in Ad Hoc Networks." IEEE Transactions on Vehicular Technology 59, no. 9 (November 2010): 4578–88. http://dx.doi.org/10.1109/tvt.2010.2070522.

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29

Syed, Ikram, and Byeong-hee Roh. "Adaptive Backoff Algorithm for Contention Window for Dense IEEE 802.11 WLANs." Mobile Information Systems 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/8967281.

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The performance improvement in IEEE 802.11 WLANs in widely fluctuating network loads is a challenging task. To improve the performance in this saturated state, we develop an adaptive backoff algorithm that maximizes the system throughput, reduces the collision probability, and maintains a high fairness for the IEEE 802.11 DCF under dense network conditions. In this paper, we present two main advantages of the proposed ABA-CW algorithm. First, it estimates the number of active stations and then calculates an optimal contention window based on the active station number. Each station calculates the channel state probabilities by observing the channel for the total backoff period. Based on these channel states probabilities, each station can estimate the number of active stations in the network, after which it calculates the optimal CW utilizing the estimated active number of stations. To evaluate the proposed mechanism, we derive an analytical model to determine the network performance. From our results, the proposed ABA-CW mechanism achieved better system performance compared to fixed-CW (BEB, EIED, LILD, and SETL) and adaptive-CW (AMOCW, Idle Sense) mechanisms. The simulation results confirmed the outstanding performance of the proposed mechanism in that it led to a lower collision probability, higher throughput, and high fairness.
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30

Sharma, Gokarna, and Costas Busch. "Window-based greedy contention management for transactional memory: theory and practice." Distributed Computing 25, no. 3 (February 2, 2012): 225–48. http://dx.doi.org/10.1007/s00446-012-0159-7.

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31

Qureshi, Imran Ali, and Sohail Asghar. "A genetic fuzzy contention window optimization approach for IEEE 802.11 WLANs." Wireless Networks 27, no. 4 (March 13, 2021): 2323–36. http://dx.doi.org/10.1007/s11276-021-02572-8.

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32

ABEYSEKERA, B. A. Hirantha Sithira, Takahiro MATSUDA, and Tetsuya TAKINE. "Dynamic Contention Window Control Scheme in IEEE 802.11e EDCA-Based Wireless LANs." IEICE Transactions on Communications E93-B, no. 1 (2010): 56–64. http://dx.doi.org/10.1587/transcom.e93.b.56.

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33

Verma, Poonam, Neeta Singh, Riya Lamba, and Somendra Prakash Singh. "Dynamic Contention Window based Safety-Application Model for Vehicular Ad-hoc Networks." Procedia Computer Science 132 (2018): 421–28. http://dx.doi.org/10.1016/j.procs.2018.05.161.

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34

Shangjuan, Lin, Wen Xiangming, Hu Zhiqun, and Lu Zhaoming. "Improving throughput through dynamically tuning contention window size in dense wireless network." Journal of China Universities of Posts and Telecommunications 24, no. 4 (August 2017): 27–33. http://dx.doi.org/10.1016/s1005-8885(17)60220-6.

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35

Youngmi Jin and G. Kesidis. "Distributed Contention Window Control for Selfish Users in IEEE 802.11 Wireless LANs." IEEE Journal on Selected Areas in Communications 25, no. 6 (August 2007): 1113–23. http://dx.doi.org/10.1109/jsac.2007.070806.

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36

Syed, Ikram, Seung-hun Shin, Byeong-hee Roh, and Muhammad Adnan. "Performance Improvement of QoS-Enabled WLANs Using Adaptive Contention Window Backoff Algorithm." IEEE Systems Journal 12, no. 4 (December 2018): 3260–70. http://dx.doi.org/10.1109/jsyst.2017.2694859.

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37

Yan, Xiaojing, Hui Tian, Cheng Qin, and Arogyswami Paul. "Constrained Stochastic Game in Licensed-Assisted Access for Dynamic Contention Window Adaptation." IEEE Communications Letters 22, no. 6 (June 2018): 1232–35. http://dx.doi.org/10.1109/lcomm.2017.2758375.

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38

Khatua, Manas, and Sudip Misra. "D2D: Delay-Aware Distributed Dynamic Adaptation of Contention Window in Wireless Networks." IEEE Transactions on Mobile Computing 15, no. 2 (February 1, 2016): 322–35. http://dx.doi.org/10.1109/tmc.2015.2416172.

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39

Jang, In Sik, Seok Hong Min, Bong Gyu Kim, Hyung Suk Choi, Jong Sung Lee, Byung Chul Kim, and Jae Yong Lee. "TCP Fairness Improvement Scheme using Adaptive Contention Window in Wireless Mesh Networks." Journal of the Korea Institute of Military Science and Technology 16, no. 3 (June 5, 2013): 322–31. http://dx.doi.org/10.9766/kimst.2013.16.3.322.

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40

Grover, Vandita, and Sugandha Gupta. "Service Differentiation based on Contention Window with Enhanced Collision Resolution LR-WPANs." International Journal of Computer Trends and Technology 19, no. 2 (January 25, 2015): 86–90. http://dx.doi.org/10.14445/22312803/ijctt-v19p116.

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41

Hyunhee Park, Sangheon Pack, and Chul-Hee Kang. "Dynamic adaptation of contention window for consumer devices in WiMedia home networks." IEEE Transactions on Consumer Electronics 57, no. 1 (February 2011): 28–34. http://dx.doi.org/10.1109/tce.2011.5735477.

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Yoon, Sung-Guk, and Saewoong Bahk. "Adaptive Rate Control and Contention Window-Size Adjustment for Power-Line Communication." IEEE Transactions on Power Delivery 26, no. 2 (April 2011): 809–16. http://dx.doi.org/10.1109/tpwrd.2010.2094629.

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43

Cheng, Yu, Xinhua Ling, Lin X. Cai, Wei Song, Weihua Zhuang, Xuemin Shen, and Alberto Leon-Garcia. "Statistical multiplexing, admission region, and contention window optimization in multiclass wireless LANs." Wireless Networks 15, no. 1 (February 16, 2007): 73–86. http://dx.doi.org/10.1007/s11276-007-0026-9.

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44

Ghazvini, Mahdieh, Naser Movahhedinia, and Kamal Jamshidi. "GCW: A Game Theoretic Contention Window Adjustment Approach for IEEE 802.11 WLANs." Wireless Personal Communications 83, no. 2 (March 29, 2015): 1101–30. http://dx.doi.org/10.1007/s11277-015-2441-z.

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45

Olotu, Samuel Ibukun, Olumide Sunday Adewale, and Bolanle Adefowoke Ojokoh. "A Fuzzy-Based Congestion Control Scheme for Vehicular Adhoc Network Communication." International Journal of Smart Vehicles and Smart Transportation 4, no. 1 (January 2021): 1–15. http://dx.doi.org/10.4018/ijsvst.2021010101.

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Vehicular ad hoc network (VANET) is a self-organized, multi-purpose, service-oriented communication network that enables communication between vehicles and between vehicles and roadside infrastructures for the purpose of exchanging messages. In a dense traffic scenario, the message traffic may generate a load higher than the available capacity of the transmission medium leading to channel congestion problem. This situation leads to a rise in packet loss rates and transmission delay. Some existing congestion control schemes adapt the transmission power, transmission rate, and contention window parameters by making comparison with neighboring values through classical logic. However, the approach does not consider points between two close parameter values. This work uses fuzzy logic to improve the adaptation process of the network contention window parameter. The proposed scheme achieved a 15% higher in-packet delivery ratio and 10ms faster transmission compared with related work in terms end-to-end delay.
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46

Jin, Li, Guoan Zhang, and Xiaojun Zhu. "Formal analysis and evaluation of the back-off procedure in IEEE802.11P VANET." Modern Physics Letters B 31, no. 19-21 (July 27, 2017): 1740063. http://dx.doi.org/10.1142/s0217984917400632.

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The back-off procedure is one of the media access control technologies in 802.11P communication protocol. It plays an important role in avoiding message collisions and allocating channel resources. Formal methods are effective approaches for studying the performances of communication systems. In this paper, we establish a discrete time model for the back-off procedure. We use Markov Decision Processes (MDPs) to model the non-deterministic and probabilistic behaviors of the procedure, and use the probabilistic computation tree logic (PCTL) language to express different properties, which ensure that the discrete time model performs their basic functionality. Based on the model and PCTL specifications, we study the effect of contention window length on the number of senders in the neighborhood of given receivers, and that on the station’s expected cost required by the back-off procedure to successfully send packets. The variation of the window length may increase or decrease the maximum probability of correct transmissions within a time contention unit. We propose to use PRISM model checker to describe our proposed back-off procedure for IEEE802.11P protocol in vehicle network, and define different probability properties formulas to automatically verify the model and derive numerical results. The obtained results are helpful for justifying the values of the time contention unit.
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47

Adnan, Muhammad, and Eun-Chan Park. "Improving Energy Efficiency in Idle Listening of IEEE 802.11 WLANs." Mobile Information Systems 2016 (2016): 1–15. http://dx.doi.org/10.1155/2016/6520631.

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This paper aims to improve energy efficiency of IEEE 802.11 wireless local area networks (WLANs) by effectively dealing with idle listening (IL), which is required for channel sensing and is unavoidable in a contention-based channel access mechanism. Firstly, we show that IL is a dominant source of energy drain in WLANs and it cannot be effectively alleviated by the power saving mechanism proposed in the IEEE 802.11 standard. To solve this problem, we propose an energy-efficient mechanism that combines three schemes in a systematic way: downclocking, frame aggregation, and contention window adjustment. The downclocking scheme lets a station remain in a semisleep state when overhearing frames destined to neighbor stations, whereby the station consumes the minimal energy without impairing channel access capability. As well as decreasing the channel access overhead, the frame aggregation scheme prolongs the period of semisleep time. Moreover, by controlling the size of contention window based on the number of stations, the proposed mechanism decreases unnecessary IL time due to collision and retransmission. By deriving an analysis model and performing extensive simulations, we confirm that the proposed mechanism significantly improves the energy efficiency and throughput, by up to 2.8 and 1.8 times, respectively, compared to the conventional power saving mechanisms.
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48

Vignan, B. Suvarna, and B. Lalu Naick. "Enhanced Distributed Coordination Function of MAC for VoIP Services Using IEEE802.11 Networks." Advanced Materials Research 433-440 (January 2012): 2304–9. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.2304.

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Voice over Internet Protocol (VoIP) is an important service with strict Quality-of-Service (QoS) requirements with in wireless local area networks. The popular Distributed Coordination Function (DCF) of IEEE802.11 Medium Access Control (MAC) protocol adopts Multiplicative Increase and linear Decrease procedure to reduce the packet collision probability in WLANs. In DCF, the size of contention window is doubled upon a collision regardless of the network loads. This paper presents an enhanced DCF scheme to improve the QoS of VoIP in WLANs. This scheme applies a threshold of the collision rate to switch between two different functions for increasing the size of contention window based on the status of network loads. The performance of this scheme investigated and compared to the original DCF using the network simulator NS-2. Under the high traffic loads the packet loss probability decreases with the enhanced DCF compared to the original DCF. Some other parameters like throughput and access delay is decreased with the enhanced DCF.
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49

Ali, Iqtidar, Tariq Hussain, Kamran Khan, Arshad Iqbal, and Fatima Perviz. "The Impact of IEEE 802.11 Contention Window on The Performance of Transmission Control Protocol in Mobile Ad-Hoc Network." ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 9, no. 3 (August 7, 2020): 29–48. http://dx.doi.org/10.14201/adcaij2020932948.

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A Mobile Ad-hoc Network (MANET) is a group of nodes connected via ad-hoc fashion for communicating with each other through wireless interface. The communication among the nodes in such network take place by using multi-hop in the absence of fixed infrastructure. TCP faces some hurdles and complexities in multi-hop ad-hoc networks particularly congestion and route failures. The incompatibility between the MAC and TCP are previously noticed by the research community. This research study focuses on the impact of MAC layer contention window on TCP in MANET by using variation in network density and velocity of nodes respectively. Simulation has been carried out to quantify and analyze the impact of Contention Window (CW) sizes that affects the performance of TCP by using NS-2 simulator. The impact of CW is investigated on TCP in multi-hop networks by means of performance evaluation parameters i.e. average delay, average packet drops and average throughput.
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50

Cheng, Yujun, Huachun Zhou, and Dong Yang. "CA-CWA: Channel-Aware Contention Window Adaption in IEEE 802.11ah for Soft Real-Time Industrial Applications." Sensors 19, no. 13 (July 8, 2019): 3002. http://dx.doi.org/10.3390/s19133002.

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In 2016, the IEEE task group ah (TGah) released a new standard called IEEE 802.11ah, and industrial Internet of Things (IoT) is one of its typical use cases. The restricted access window (RAW) is one of the core MAC mechanisms of IEEE 802.11ah, which aims to address the collision problem in the dense wireless networks. However, in each RAW period, stations still need to contend for the channel by Distributed Coordination Function and Enhanced Distributed Channel Access (DCF/EDCA), which cannot meet the real-time requirements of most industrial applications. In this paper, we propose a channel-aware contention window adaption (CA-CWA) algorithm. The algorithm dynamically adapts the contention window based on the channel status with an external interference discrimination ability, and improves the real-time performance of the IEEE 802.11ah. To validate the real-time performance of CA-CWA, we compared CA-CWA with two other backoff algorithms with an NS-3 simulator. The results illustrate that CA-CWA has better performance than the other two algorithms in terms of packet loss rate and average delay. Compared with the other two algorithms, CA-CWA is able to support industrial applications with higher deadline constraints under the same channel conditions in IEEE 802.11ah.
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