Based on the current standardized IEEE 802.11 distributed coordination function protocol, this paper proposes a new efficient collision resolution mechanism, called GDCF
A New Collision Resolution Mechanism to Enhance the Performance of IEEE 802.11 DCF
IEEE Transactions on Vehicular Technology, no. 4 (2004): 1235-1246
WOS SCOPUS EI
The medium-access control (MAC) protocol is one of the key components in wireless local area networks (WLANs). The main features of a MAC protocol are high throughput, good fairness, energy efficiency, and support priority guarantees, especially under distributed contention-based environment. Based on the current standardized IEEE 802.11 ...更多
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- R ECENTLY, we have witnessed a rapid development and deployment of wireless local area networks (WLANs), which in return has fueled the development in the standardization organization, such as the IEEE 802.11 working group, to improve its performance
- This paper focuses on the contention-based medium-access control (MAC) protocols used in WLAN, IEEE 802.11 distributed coordination function (DCF) 
- We propose a new collision-resolution mechanism called GDCF, which is a simple variation of 802.11 DCF, yet can significantly improve throughput and fairness
- The throughput is used to quantify the throughput gain obtained by GDCF
- This paper investigates the MAC protocol for WLAN and the corresponding collision-resolution algorithm and proposes an effective algorithm, GDCF, based on 802.11 DCF protocols
- Theoretical analysis and simulations are carried out, which show that the proposed GDCF brings several benefits: 1) it obtains higher throughput than traditional DCF, especially with a large number of competing nodes; 2) it maintains a good fairness property; 3) GDCF has a lower RTS failure ratio and issues less RTS messages than DCF in order to transmit the same information volume, so it is more energy efficient; 4) GDCF drops fewer packets in the MAC level and can extend to support priority application with the flexibility of selecting different values; and 5) GDCF is very easy to be deployed, as it does not need to estimate a competing node number or change the control message structure and access procedures in DCF
I. INTRODUCTION:R ECENTLY, the authors have witnessed a rapid development and deployment of wireless local area networks (WLANs), which in return has fueled the development in the standardization organization, such as the IEEE 802.11 working group, to improve its performance.
- In basic access mode [Fig. 1(a)], the destination node will wait for a SIFS interval immediately following the successful reception of the data frame and transmit a positive ACK back to the source node to indicate that the data packet has been received correctly.
- When the data frame is being transmitted, all the other nodes hearing the data frame adjust their network-allocation vector (NAV), which is used for virtual carrier sense at the MAC layer, correctly based on the duration field value in the data frame received.
- This includes the SIFS and ACK frame transmission time following the data frame.
II. RELATED WORK:This paper focuses on the contention-based MAC protocols used in WLAN, IEEE 802.11 DCF .
- Comparingit to IEEE 802.11 in  and self-adapt DCF in , GDCF is simpler in that it does not need to estimate network parameters such as competing node number in  and channel status in , there is a Kalman filter-based algorithm to measure the number of competing nodes in 
- Comparing it to DCF in , GDCF can support any upper protocols
- UDP) and does not need to change the RTS/CTS message structure
- Comparing it to the FCR algorithm in , GDCF achieves better fairness and simplicity and can support priority or quality-of-service (QoS) differentiation effectively.
- It does not need to estimate the competing node and channel status; it is simple for implementation
III. PROPOSED GDCF ALGORITHM:802.11 DCF resolves collision through CW and backoff stage [Fig. 2(a)]. In the initial backoff stage (stage 0), the value of.
- If the number of current competing nodes is larger than or close to CW and if the backoff stage is reset to 0 after a successful transmission, there is a high probability that some new collision(s) will happen.
- The number of current competing nodes may be smaller than CW if there are several consecutive successful transmissions at the backoff stage.
- Under this case, the authors can effectively begin to decrease the CW.
- It will decrease the collision probability and improve the system throughput
- It will obtain better fairness because GDCF maintains all the nodes in the same stage even if after several consecutive successful transmissions , especially under large node number.
- The authors prove that the short range 4 8 is the optimal value for if the number of competing nodes is larger than 10
A. Saturation Throughput:GDCF, which is equal to the ratio between “average payload duration in a slot time” and “average length of slot time,” using some similar procedures and symbols in  and .
- Can be computed for basic access mode and RTS/CTS access mode, respectively, as shown in (13) and (14) at the bottom of the page where is the packet header, is the propagation delay, and is the average length of the longest packet payload involved in a collision.
- It can be observed that the influences on throughput resulted from factors such as access mode, packet length, and value in GDCF
- For both DCF and GDCF, RTS/CTS access mode and/or large packet size will bring (a).
- GDCF with obtains higher throughput than under the basic access mode
- Both 4 and 8 obtained nearly the same throughput under the RTS/CTS mode, so the problem is how to choose the optimal for different competing node numbers.
- (15) In order to maximize , must be minimal, so let and the authors can get the optimal value of as
B. Optimal Value for:It can be seen that the value will heavily influence the throughput performance. The problem is of which value of.
- Be the normalized average collision length in the number of slot times; the authors can obtain the optimal value of as.
- Because the optimal value of is dependent on node number and the normalized average collision length [see (16)], so the optimal value of is dependent on and.
- Under the RTS/CTS access mode, because the normalized average collision length is independent of packet length, the optimal value of is irrelevant to it, so the authors only present the results of RTS/CTS access mode, which presents the minimal and maximal value of to make the GDCF throughput higher than.
- The authors will further verify this result through simulations in Section V
C. Performance Under Priority Traffics:Assume that total competing nodes can be divided into priorities or groups.
- Through selecting different combination of for competing nodes, GDCF can make the nodes with smaller obtain lower MAC access delay and larger throughput.
- This interesting property in GDCF can be directly utilized to support differentiated QoS in the MAC layer.
- If some node needs supporting real-time applications , has better channel quality, or has lower energy, the authors can let it choose a small value of to obtain a lower delay of real-time application, optimal throughput, or higher energy efficiency and longer system alive time.
- Once every continuous successful time, on average, even if is a real number
V. SIMULATION RESULTS:Since the collision probability has more influence on the basic access mechanism than on the RTS/CTS-based access mechanism, GDCF is sure to obtain better performance improvement under the nasic access mechanism than under the RTS/CTS-based access mechanism as that shown in.
- RTS/CTS-base access mechanism to observe the performance improvement in GDCF.
- The main performance metrics of interest are system throughput, fairness index, RTS failure ratio, and QoS-supporting capability.
- The throughput is used to quantify the throughput gain obtained by GDCF.
- The authors adopt the use of fairness index defined in , as it is a commonly accepted metric.
- The RTS failure ratio (RFR) can be used to evaluate the energy cost to transmit packets.
- If RFR is large, the energy cost will be high because more RTS messages are collided and more energy will be wasted.
A. Saturation Traffic:The traffic is configured to saturate the system, so there are always some competing nodes attempting to transmit packets.
- The authors collect the RTS failure ratio, saturation throughput, and fairness for a different number of competing node.
- The results are presented in Table II and Fig. 9, respectively, for a smaller node number and large node number.
- GDCF has much better fairness than DCF, especially when [Fig. 9(b)].
- The authors collect the packet drops in the MAC layer throughout the whole simulation time and Fig. 11 presents the results for different number of competing node.
- On the selection of the value, it can be seen from the above discussions (Table II and Fig. 9) that GDCF with 1 4 has better performance when the node number is very small and 4 8 is more suitable for cases with a large node number.
- Recall that the optimal value (4 8) from theoretical in Section IV; the authors can conclude that the simulation results are very consistent with the theoretical results in Fig. 7, so the authors can choose value from 4 8 in practical deployment
B. QOS Supporting:It was shown in 802.11e and enhanced DCF (EDCF)  that it can provide QoS differentiation by configuring small and and DIFS for high- priority traffic.
- According to the analysis in Section V-A, the first group will obtain higher throughput than the second group, which has larger value of.
- There is some mismatch between analysis and simulation results, the first group with smaller does obtain higher throughput.
- It can be seen that group 1 with a smaller value of obtains higher throughput and lower delay, so GDCF provides a simple and flexible approach to supporting differentiated QoS.
- When the number of competing node is some large, GDCF has better fairness than DCF.
- GDCF can make high-priority traffics get much lower delay and delay jitter and provide differentiated QoS, and keep total higher throughput at the same time.
- The authors will plan to evaluate the priority–guarantee mechanism in GDCF and its performance under multihop environments
VI. CONCLUSION:This paper investigates the MAC protocol for WLAN and the corresponding collision-resolution algorithm and proposes an effective algorithm, GDCF, based on 802.11 DCF protocols.
- “A novel MAC protocol with fast collision resolution for wireless LANs,” in IEEE INFOCOM’03, Apr. 2003.
- Ephremides, “Energy-efficient collision resolution in wireless Ad-Hoc networks,” presented at the IEEE INFOCOM’03, Apr. 2003.
- He currently is a Visiting Professor with the Special Research Centre for Optical Internet & Wireless Information Networks (ICOIWIN), ChongQing University of Posts and Telecommunications (CQUPT), Chongqing, P.
- Since 1999, he has been an Adjunct Researcher with Microsoft Research Asia (MSRA), Beijing, China
- He has been an Editor or Guest Editor for 16 journals and is involved in the organization of about 40 conferences.
- His current research interests include wireless mobile networking supporting multimedia, video multicast, and all optical networks using WDM, in which he has published over 150 technical papers in referred journals and conference proceedings.
- Dr Li was the Co-TPC Chair for IEEE INFOCOM’04 and is a Member of the Association for Computing Machinery (ACM)
- Table1: SYSTEM PARAMETERS (802.11 DSSS)
- Table2: THROUGHPUT AND FAIRNESS: SMALL NODE NUMBER (c = 0 IS FOR DCF)
- This paper focuses on the contention-based MAC protocols used in WLAN, specifically IEEE 802.11 DCF . The analysis in  demonstrated that the throughput and fairness of 802.11 DCF could significantly deteriorate when the number of nodes increases. Several recent proposals have addressed this issue –. Furthermore, given the need to support multimedia applications and to consider the energy efficiency in mobile devices, there also are protocols to address a priority scheme in  and  and the energy efficiency issue in .
Cali et al  proposed a dynamic and distributed algorithm, IEEE 802.11 , which allows each node to estimate the number of competing nodes and to tune its contention window to the optimal value at run time. Results from simulations showed that the throughput of IEEE 802.11 is very close to the theoretical upper bound. DCF , proposed in , is a new ACK-integrated mechanism that combines the TCP ACK with MAC level ACK and obtains the improved throughput. One of the limitations is its ineffectiveness for other flows, such as UDP. It also violates the layering principle that leads to the complication in MAC ACK message structure. Peng  proposed a new measurement-based algorithm to adaptively configure the optimal value of the initial CW value to improve the throughput and fairness. However, it also needs to compute current channel status at run time and adjusts the RTS/CTS message structure. The fast collision resolution (FCR) is another MAC protocol proposed in , which actively redistributes the backoff timer for all competing nodes, thus allowing the more recent successful nodes to use smaller contention window and allowing other nodes to reduce backoff timer exponentially when they continuously meets some idle time slots, instead of reducing backoff timer by 1 after each idle time slots, as in the original IEEE 802.11 DCF. FCR can resolve collisions more quickly than 802.11 DCF and obtains higher throughput, but FCR itself can inversely affect the fairness unless it is combined with additional fair scheduling mechanism, as shown in . Residual-energy-based tree splitting (REBS)  is an energy-efficient collision-resolution algorithm that can be used in the wireless ad hoc networks. REBS differentiates and splits all the competing nodes according to their residual energy and assigns the node with the least residual energy to seize the channel with the highest priority.
- GDCF first acquires about 15%–20% higher saturation throughput than DCF
technical papers: 150
He has been an Editor or Guest Editor for 16 journals and is involved in the organization of about 40 conferences. His current research interests include wireless mobile networking supporting multimedia, video multicast, and all optical networks using WDM, in which he has published over 150 technical papers in referred journals and conference proceedings. Dr Li was the Co-TPC Chair for IEEE INFOCOM’04 and is a Member of the Association for Computing Machinery (ACM)
- A. Chandra, V. Gummalla, and J. O. Limb, “Wireless medium access control protocols,” IEEE Commun. Surveys Tutorials, vol. 3, no. 2, pp. 2–15, Apr. 2000.
- IEEE Standard for Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications, ISO/IEC 8802-11:1999(E), Aug. 1999.
- G. Bianchi, “Analysis of the IEEE 802.11 distributed coordination function,” IEEE J. Select. Areas Commun., vol. 18, pp. 535–547, Mar. 2000.
- F. Cali, M. Conti, and E. Gregori, “Dynamic tuning of the IEEE 802.11 protocol to achieve a theoritical throughput limit,” IEEE/ACM Trans. Networking, vol. 8, pp. 785–799, Dec. 2000.
- H. Wu, Y. Peng, K. Long, S. Cheng, and J. Ma, “Performance of reliable transport protocol over IEEE 802.11 wireless LAN: Analysis and enhancement,” in Proc. IEEE INFOCOM’02, vol. 2, June 2002, pp. 599–607. Lemin Li graduated from Jiaotong University, Shanghai, China, in 1952, majoring in electrical engineering.
- From 1952 to 1956, he was with the Department of Electrical Communications, Jiaotong University, Shanghai, P. R. China. Since 1956, he has been with Chengdu Institute of Radio Engineering (currently the University of Electronic Science and Technology of China), Chengdu, P. R. China. From August 1980 to August 1982, he was a Visiting Scholar with the Department of Electrical Engineering and Computer Science, University of California, San Diego, where he did research on digital and spread-spectrum communications. He currently is a Professor of Communication and Information Engineering. His research work is in the area of communication networks, including broad-band and wireless networks. Mr. Li is a Member of the Chinese Academy of Engineering.