Performance Comparison of Collision Resolution Algorithms with Amount of Feedback Information Norrarat Wattanamongkhol Department of Electrical Engineering, Engineering Faculty, Burapha University, Chonburi, Thailand
[email protected]
Abstract— This paper presents the performance comparison of eight collision resolution algorithms. It can be systematically applied for random access protocols under different feedback information which includes binary, ternary and feedback of the number of accessing packets. Each algorithm is derived from the combination of uniform selection algorithm and three effective strategies, including splitting, adaptive frame size, and skipped slot. This paper aims to investigate which one strategy in these three strategies is the best effective to improve the system performance. Based on simulation results, when the information about number of accessing packets is available, significant improvement in mean access delay can be achieved. We found that the splitting strategy is the most effective strategy, following by adaptive frame size and skipped slot. Keywords–Collision resolution algorithm, tree algorithm, feedback information, MAC protocol
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INTRODUCTION
In random multiple access communication system where the multi-users share a common channel, one important problem is how to resolve the collision of packet in the operating of protocols. Collision will occur when two or more users wishing to transmit theirs packets in the same time. It is unavoidable since there is no coordination between users and the contention take place in a random fashion. The packet then is lost causing low system performance since no one receives the packets, and a retransmission process will be necessary. Accordingly, a medium access control (MAC) protocol is required to provide an efficient and fair share of packet transmission. To overcome the collision of packet problem, many random access protocols have been developed over the past years. The traditional well known protocols include Aloha [1], slotted-Aloha [2], carrier-sense multiple access (CSMA) [3], carrier-sense multiple access with collision avoidance (CSMA/CA) [4], tree-based (or stack, or splitting) algorithms [5-16]. Tree algorithm can provide higher performance and better stability than Aloha protocol. The IEEE 802.11 standard is one of the recommended international standards in Wireless Local Area Networks (WLANs). The core MAC technique of IEEE 802.11 is called distributed coordination function (DCF) [17], which is based on the CSMA/CA. It also employs a binary exponential backoff (BEB) algorithm to resolve the packet collisions and the retransmission packet.
Tree algorithms are well-known stable collision resolution algorithms (CRAs) which were introduced by Capetanakis [5] and by Tsybakov and Mikhailov [6-7]. They can be broadly classified into two types depending on how new packets are transmitted: free access and blocked access tree algorithms. Under free access, the new packets are transmitted immediately as soon as it is generated, users thus are not required to monitor the channel continuously. While under blocked access, the new packets will be forced to wait until all colliding packets have been resolved, and thus users require monitoring the channel continuously. One of the most important existing results for free access is q-ary tree algorithm [9]. For blocked access, minislots were suggested to provide better feedback on the channel status with network users. Many variations have been considered including caption channel, multi-reception [11, 16], and control minislots, etc. Other protocols such as DCF require each user starts transmission packet at a random time (backoff time) using window-based mechanism. In case of collision, DCF performs a backoff algorithm for avoiding repeated collision and retransmission packet until every packet is transmitted successfully or rejected from the system. While tree algorithm is organized the retransmission of colliding packets algorithmically until it eventually succeeds transmission with finite delay. Accordingly, every user in the system is aware of collision since there is feedback broadcasted to all users informing the packet transmission results. In addition, feedback may also contain successful transmission or idle channel. Successful transmission occurs when exactly one packet is transmitted while the idle represents channel status where there is no transmission from any user. When a packet is successfully transmitted, it will be removed from the group of unsuccessful users. For case of idle, channel resources are wasted since no one uses it and, the retransmission of colliding packets is needed in case of collision. Channel feedback [15] can be classified into three types depending on the quantity of feedback information, namely binary, ternary, and known multiplicity feedback. Binary feedback provides two channel statuses; collision/ no collision (C/NC) informs the users only whether or not there was a collision in the channel, success/ no success (S/NS) informs the users whether or not a packet is successfully transmitted through the channel. Ternary provides three statuses of channel; success, idle and collision. In practical, it is difficult for the users to know the number of
contending users as they are geographically distributed. However, this number can be estimated by the novel estimation method [18]. These feedbacks of transmission packet results are commonly utilized in the MAC protocols for improving the system performance by avoiding and resolving the collision. In this paper, we propose eight collision resolution algorithms, including UNI, UNI+SS, UNI+SP, UNI+SP+SS, UNI+AFS, UNI+SS+AFS, UNI+SP+AFS, and UNI+SP+SS+ AFS, when UNI, SS, and AFS stands for an uniform selection algorithm, a skipped slot strategy, and an adaptive frame size strategy, respectively. The UNI+SP and UNI+SP+AFS is also the tree algorithm and modified tree algorithm, respectively. These proposed algorithms are extended from UNI algorithm which has the mechanism of accessing channel similar as IEEE 802.11 DCF. Since, each strategy which added in UNI algorithm corresponding with the amount of feedback information, can improve the system performance. This paper also investigates which one strategy in these three strategies; splitting, skipped slot, and adaptive frame size, is the best effective strategy. The rest of this paper is organized as follows. We describe our system model and the proposed algorithm in Section II. We provide the simulation results and discussions of the proposed algorithm in Section III. We conclude in Section IV. II.
B. Splitting strategy The basic principle of the standard tree algorithm [5, 9, 12] is that the colliding users are resolved by splitting process, until each user receives own slot or successful transmission. The users are informed of the transmission result at the end of each timeslot unlike the uniform selection algorithm. If the transmission was successful, the corresponding user will stop participating in the resolution process. If the transmission was unsuccessful, a contending frame with fixed size M (slots) will be inserted immediately after the current slot to resolve the collision. Those users who involved in a collision will reinitiate the same collision resolution process using the inserted frame, while other pending users defer retransmission by M slots every time there is a collision. The performance of tree algorithm was investigated by Mathys and Floajolet [9] and they found that the binary tree algorithm provides the optimum performance when the splitting factor, M = 3. Fig. 2 illustrates a possible standard tree algorithm for an initial collision of seven users (A, B, C, D, E, F, and G) with the splitting factor, M = 3. They are resolved the collision following the rules of standard tree algorithm which is mentioned above. As a result, the fifteen contention slots are used in the collision resolution process for resolving of seven colliding users. A, B, C, D, E, F, G
SYSTEM MODEL AND PROPOSED ALGORITHM
In our system model, the channel is assumed to be slotted; that is, the channel time is divided into equal segments called slots. The length of each slot equals that of a packet, and it is assumed that each source is synchronized to the channel and transmits a packet within only one slot. A packet can only be transmitted at the beginning of each slot. At the end of each slot, feedback information is broadcasted to all users. We consider all three types of feedback information mentioned in section I. We assume that the new access users are handled as the blocked access channel and the number of colliding users (N) can be known by the base station before starting the collision resolution process. A. Uniform selection algorithm It is a simple CRA and uses a contention frame size of M time slots. At the beginning of each frame, each user chooses a transmission timeslot which is uniformly distributed between 1 and M. At the end of each frame, feedback information about transmission success is sent to the users. Total collided packets will move to the next frame for collision resolution and this process repeats till all packets are successfully sent over the shared channel. From the collision resolution process, this scheme is referred to as uniform selection algorithm (UNI) and it can be considered as in Fig. 1.
Figure 1. Example of the uniform selection algorithm (UNI) when M = 3.
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Figure 2. Example of the tree algorithm (UNI+SP) when M = 3.
C. Skipped slots strategy Skipped slots strategy is introduced to apply with the tree algorithm for improving delay performance by skipping slot in two cases. In Fig. 3(a), at the last slot of a frame, if more than one user (R ≥ 2) is waiting to transmit a packet, a collision will surely occur so this slot can be skipped and the users immediately begin in a new contention frame. In Fig. 3(b), all collided users have transmitted the packets within the first k slot of a frame and all remaining slots will be omitted. Then, a new contention frame will be produced again to solve the collision packet. In the skipped slots strategy, the number of k used slots in each splitting process can be known by the base station that it is the additional feedback information. However, the first case only has the same idea as the proposed algorithm in [10].
D. Adaptive frame size strategy One reason for the reduced performance of the standard tree algorithm is due to the fixed the number of subgroups (M) although will be set as M = 3 which maximizes the system performance. In particularly at the starting of collision resolution process, to alleviate of the collision problem, the adaptive frame size scheme is presented to properly adjust the number of contention slots according to the number of remaining collided users. It has been proven that the optimal size of the contention window is equal to the number of contending users that maximizes the number of successful transmissions in a contention frame [4]. A, B, C, D, E, F, G
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Figure 4. An example of adaptive frame size scheme is used in conjunction with the standard tree algorithm when N = 7.
The system model is assumed that the feedback system returns the number of users who transmit a packet in each timeslot. With the initial knowledge of the number of colliding users, each user can employ the feedback in order to keep track of the number of the users who have not transmitted their packet in each timeslot. III.
SIMULATION RESULTS AND DISCUSSIONS
In this section we shall show the delay performance of the proposed CRA and discuss the effect of the feedback type on this delay performance. Since the blocked access algorithm is adopted, we evaluate the system performance as in the mean access delay which represents the average number of used slots for resolution process with N colliding users, where N is a variable. In order to know which one strategy is the best effective strategy, we also investigate the mean access delay of each algorithm when added amount of different feedback information. In Figure 5, delay performance of UNI, UNI+SS, UNI+SP, and UNI+SP+SS, is graphically represented. For different
Mean access delay (slots)
Figure 3. Two scenarios of skipping slot with M slots in a frame.
frame size (M), graphs have been plotted for mean access delay versus the number of contending users (N). UNI has the worst performance especially with more contending users. Increasing of the contention window size certainly improves the performance but the trend remains, thus making UNI unsuitable for the large number of users. UNI+SP, (tree algorithm), overcomes the exponential rise issue from the graph and dramatically improves the performance. The best performance occurs when the window size is three (M = 3) and these results corroborate those of already published papers [3]. UNI+SS performs slightly better than UNI but have poor performance than tree algorithm. Exponential trend is also observed unlike tree algorithm for all values of M. UNI+SP+SS performs well even for large number of users. The best performance for UNI+SP+SS occurs when M = 2 and it is the best out of all four algorithms, because the probability of skipping slot is 0.5 and will decrease when M > 2. Figure 6 shows the performance of number of algorithms including UNI+AFS, UNI+SS+AFS, UNI+SP+AFS, and UNI+SP+SS+AFS, in which adaptive frame size has been used in conjunction with first four algorithms. In case UNI optimum and UNI+SS optimum, we provide the number of contention slots corresponding with the number of remaining collided users where it obtains the best performance, for each attempting access channel. From the graph it is evident that UNI+SP+SS+AFS which is the combination of skipping, adaptive size and tree algorithm performs the best with least average delay. UNI+SP+SS which is tree algorithm in conjunction with skipping timeslot with a window size of M equals to two performs best next to UNI+SP+SS+AFS. Skipping strategy is very useful in the resolution process when it is incorporated with the tree algorithm. When AFS is introduced in uniform selection, the algorithm performance is similar to tree algorithm. UNI+SP+AFS, and UNI+SP with M equals to 3 has similar performances but not as good as that of Algorithm UNI+SP+SS and UNI+SP+SS+AFS. It can be concluded that when tree algorithm is in conjunction with skipping and AFS, it reduces the time taken for collision resolution thus and hence improves system performance.
Figure 5. Delay performance of UNI, UNI+SS, UNI+SP, and UNI+SP+SS,
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Mean access delay (slots)
[2] [3]
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[7] Figure 6. Comparing the delay performance of all proposed algorithms.
When comparing the effect of each strategy, it can be notices that the performance of UNI+SP is rather the same as UNI+AFS and higher performance than UNI+SS but UNI+SP uses a little feedback information. UNI+SP uses only collision and no collision while the other two strategies; skipped slot and adaptive frame size, need to know the number of collided users. IV.
CONCLUSION
In this paper, three strategies that can utilize the additional feedback information have been proposed to improve mean access delay of the uniform selection algorithms. Simulation results shown that the use of feedback information can clearly improve the system performance that it is measured in term of the number of used slots for the resolution process. It can be seen that the UNI+SP+SS+AFS is clearly the best effective algorithm, because it consumes the most number of feedback information. Further, when ordering the most effective strategy among splitting, skipped slot, and adaptive frame size, we found that the splitting strategy is the first, following by the adaptive frame size and skipped slots strategy, respectively. The splitting mechanism can much decrease the opportunity of collision by distribution the quantity of colliding users into different contention slot while it consumes a little feedback information. ACKNOWLEDGMENT The work has been supported in part by Faculty of Engineering, Burapha University Research Fund and Grant No. 6/2556.
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