Time-Division Access Priority in CSMA/CA Andrea Vesco
Riccardo Scopigno
Control and Computer Engineering Department Politecnico di Torino – Torino, Italy Email
[email protected]
Networking Lab Istituto Superiore Mario Boella – Torino, Italy Email:
[email protected]
Abstract—This paper proposes TD-uCSMA a synchronous distributed coordination function which is meant to provide CSMA/CA with a mechanism for QoS provisioning and bandwidth management over WiFi networks. TD-uCSMA relies on synchronization among nodes and the time-driven switching of contention parameters inside nodes. The TD-uCSMA operating principles and preliminary synchronization issues are presented here together with an extensive simulation analysis showing the effectiveness of the proposed solution.
I. I NTRODUCTION Wireless provides scalable ways to extend access to the existing wired networks. This comes from clear advantages such as cheap installation costs, easy maintenance, robustness, extended coverage and always-on services provisioning. However its use to deploy broadband access networks is relative new and makes new challenges to define scalable solutions enabling (i) simple and efficient bandwidth management, especially important for operators since bandwidth is a valuable but scarce resource and (ii) high quality network services provisioning. The 802.11e standard [1] was proposed to support the increasing demand for quality of service (QoS). It introduces the Hybrid Coordination Function (HCF) that defines two channel access mechanisms, namely, HCF Controlled Channel Access (HCCA) for parametrized QoS and the Enchanced Distributed Channel Access (EDCA) for differentiated QoS provisioning. HCCA is a polling mechanism where channel access is arbitrated centrally by the hybrid controller (HC). A node willing to transmit negotiates with the HC channel access during a negotiation EDCA-based phase. The HC offers transmission opportunities (TXOPs) in response, if enough resource are available to meet QoS requirements, during the controlled access period (CAP). As a result HCCA avoids, during CAPs, collisions that can lead to breaking established QoS and degradation of the overall performances and allows the HC to implement bandwidth reservation policies enabling parametrized QoS provisioning. However the need for a centralized HC potentially increases the complexity of the solution and faces scalability issues. Moreover HCCA potentially results inefficient in dealing with short-lasting and/or high burstiness traffic and in reallocating TXOPs reserved but currently unused, due to ON/OFF traffic. In a different design a node determines individually when to access the channel; hence the decision making process This research work has been carried out within Newcom++ Project, funded by EC within the framework of FP7.
is “distributed” among all nodes. On this direction EDCA coordinates channel access in a distributed fashion and provides a flexible and scalable solution for differentiated QoS provisioning. EDCA introduces the AC concept to differentiate traffic whereas it differentiates service by prioritizing channel access using AC-specific EDCA parameters (AIF S, T XOP, CWmin and CWmax ). Several works assess the EDCA performances [2] and propose further optimizations [3] [4] [5] to minimize contention delays and collision rates, hence improving throughput and delays. Other works study the issue of tuning the EDCA parameters [6] to provide good service differentiation in specific traffic scenarios. However it is not clear yet how to implement scalable bandwidth reservation policies. In turn, the goal of QoS provisioning while assuring efficient resource management and utilization is commonly reached by combining the HCCA and EDCA paradigms. Notably solutions overcome the limitation due to a centralized coordination function as in [7], where reservation is managed in a distributed fashion, but they still suffer from the intrinsic stiffness of a reservation mechanism to cope with rapidly changing traffic profiles and propose extensions to the standardized MAC layer that potentially increase time-to-market and make a wide deployment difficult. This work proposes a synchronous distributed coordination function, called, Time-Division Unbalanced Carrier Sense Multiple Access (TD-uCSMA) [8] that combines the advantages of the controlled channel access (bandwidth management and parametrized QoS) with the ones proper of a distributed channel access (efficient resource utilization with different traffic profiles and scalability) avoiding a stiff centralized architecture and without requiring major changes to the standardized MAC layer. TD-uCSMA is shown to further generalize the concept of multiplexing in time domain by combining TDM and CSMA/CA approaches. The paper is organized as follow. Section II presents the TD-uCSMA operating principles and discusses the related synchronization issues. Extensive simulation analysis is presented in Section III whereas conclusions and future research directions are drawn in Section IV. II. T IME -D IVISION U NBALANCED CSMA A. Operating Principles and Features In the TD-uCSMA network the decision making process about channel access is distributed among all nodes following CSMA/CA rules. Each node maintains different sets
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of EDCA parameters (AIF S, T XOP, CWmin and CWmax ) and all nodes have the same sets. The number of sets deployed may has an impact on TD-uCSMA performance. However this first work assumes two sets of EDCA parameters referred to as high-priority set (EDCAH ) and low-priority set (EDCAl ) whereas the study of TD-uCSMA in scenarios with multiple sets of EDCA parameters is left for future work. A TD-uCSMA node handles traffic as a single aggregate and it changes the set of EDCA parameters used for contending channel access over time. Moreover EDCA parameters in the two sets are “unbalanced”, more formally, AIF S H < AIF S l H H l l and CWmin 0.999 in the simulation under analysis and the same good results have been obtained under different configurations of i TH and/or different payload sizes. Fig. 4 shows the achievable bandwidth, i.e., the achievable goodput GA , as function of packet payload sizes at MAC layer under saturation condition. The ideal curve represents the ideal goodput Gid at MAC layer. Neglecting the propagation delay and without taking into account backoff time Gid =
R · tpayload AIF S H + 2 · tp + tmpdu + SIF S + tack
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considering only the protocol overheads. R is the data rate, tpayload and tmpdu are the payload and MPDU transmission
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times whereas tp and tack are the transmission times of PLCP and acknowledgment respectively. The results in Fig. 4 show that TD-uCSMA outperforms CSMA/CA. The goodput gain over CSMA/CA ranges from 7% to 8%, for different values of the payload size, mainly due to the reduced collision probability. In fact, the collision probability decreases from 6%, with CSMA/CA, to 2% when TDuCSMA is deployed. Moreover, since the achieved goodput is very close to Gid , TD-uCSMA leads to an efficient utilization of the available bandwidth. Considering the payload size of 1500 byte, Gid ≈15.5 Mb/s whereas the goodput achieved by H H TD-uCSMA is about 15 Mb/s when CWmin = CWmax =1 H H and 14.8 Mb/s when CWmin = 3 and CWmax = 7. This further demonstrates the usefulness of reducing backoff between two consecutive transmission during TH , since it increases goodput without causing further collisions. Fig. 5 shows the CDF of the inter-packet gap over the channel for different values of payload size, under saturation. The results confirm that TD-uCSMA efficiently uses the available bandwidth, in fact, over 95% of the packets are spaced of the minimum gap, due to MPDU size and MAC protocol overhead. Only 5% of them are spaced of longer gaps, mainly due to backoff induced by channel contention at time of EDCA parameters switching inside nodes. Given the above results the following rule of thumb can be formulated: the available bandwidth GA can be estimated by Gid considering a 5% tolerance, according to the trends shown in Fig. 4, given an a priori knowledge of the packetsize statistics, and each node can be reserved a bandwidth Gi given by Ti (3) Gi = H · GA TC At this point simulations were run to verify the validity of (3). In this scenario each node generate a traffic r = Gi ∀i = 1, 2, 3. Assuming the payload size = 1500 byte and estimating GA =15 Mb/s node 0 generates 9 Mb/s, node 1 generates traffic with rate varying from 0 to 4.5 Mb/s and node 2 generates 1.5 Mb/s. The results depicted in Fig. 6 and Fig. 7 show, as expected, that TD-uCSMA is able to get through all traffic with an overall delay less than 35 ms. On the contrary CSMA/CA is not able to manage the offered traffic, in fact, when node 1 reaches 3 Mb/s (the total load is about 13.5 Mb/s) it negatively affects delay experienced by packets transmitted by node 0. 2) Effect of Misbehaving Nodes: Further simulations were run to evaluate how TD-uCSMA reacts to misbehaving nodes,
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i.e., nodes that transmit more traffic than reserved. Here the network and traffic parameters are set as in the previous scenario but node 0 generates 10 Mb/s of traffic, 1 Mb/s higher than the reserved bandwidth. The results in Fig. 8 show that, as the total offered load is less than GA , TD-uCSMA gets through all the traffic from node 0. This means that TD-uCSMA is adaptive and intrinsically implements bandwidth re-use mechanisms. However as node 1 increases its traffic rate, TD-uCSMA behaves fairly by policing exceeding traffic generated by node 0, in fact, when node 1 generates exactly 4.5 Mb/s, the goodput of node 1 is reduced to 9 Mb/s. Conversely CSMA/CA cannot carry out any policy mechanisms, as depicted in Fig. 8. 3) Effect of Packet Length: Packet Length has indeed an effect on the overall goodput performance in a WiFi network. Thus simulations were carried out to evaluate this effect both for TD-uCSMA and CSMA/CA. In the simulations the network parameters are the same as in the previous scenario but node 0 generates 9 Mb/s and node 2 generates 1.5 Mb/s, both with payload size equal to 1500 byte, whereas node 1 generates traffic with payload size equal to 500 byte. Again the traffic rate of node 1 varies from 0 to 4.5 Mb/s in the simulations. The results in Fig. 9 show that in CSMA/CA the difference in packet length affects the goodput achieved by all nodes. On the contrary this negative effect is prevented by TD-uCSMA, in fact, it gets through all the traffic from node 0 and node 2, whereas only node 1 decreases its goodput. Given a payload size of 500 bytes, GA ≈6.2 Mb/s (see Fig. 4); 1 moreover, considering that TH = 3TFs over a time cycle of 10 TFs, node 1 should get a goodput of about 1.86 Mb/s by means of (3). This result is in accordance to simulation
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result in Fig. 9. Notably in TD-uCSMA, when a node transmits shorter packets, it does not affect the efficiency in bandwidth i exploitation of the other nodes during their TH . C. Asymmetric Scenario To provide a more complete set of results, simulations were run assuming the network scenario depicted in Fig. 2(b) where 5 nodes share the same collision domain and traffic is not evenly distributed among them. In these simulations the time cycle is divided into 20 TFs of duration equal to 5ms. The payload size is set to 1000 byte hence GA ≈11 Mb/s, see 0 1 2 3 Fig. 4. Moreover, TH = TH = TH = 3 TFs, TH = 6 TFs 4 and TH = 5 TFs to reserve 1.65 Mb/s to nodes 0-2, 3.3 Mb/s to node 3 and 2.75 Mb/s to node 4. All nodes generate CBR traffic coherently with their reservation. Node 3 varies its traffic rate from 0 to 3.3 Mb/s and distributes evenly its traffic toward node 0 and node 2. The results depicted in Fig. 10 show again that the bandwidth reservation mechanism in TD-uCSMA works well and the overall traffic is better handled than with CSMA/CA. This is further confirmed by the analysis of delays in Fig. 11. In fact, in CSMA/CA, when node 3 reaches 2 Mb/s (the total load is about 9.5 Mb/s) it affects node 4 first – the delay gets to ∞ – and then node 3. On the contrary TD-uCSMA keeps delays under control. All the packets experience an overall delay less than 35ms. In turn these results show that TDuCSMA is effective independently on the number of nodes in the collision domain and the traffic distribution among them. IV. C ONCLUSIONS AND F UTURE W ORK This paper has proposed a synchronous distributed coordination function, called TD-uCSMA. Simulations results have
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shown that TD-uCSMA leads to an efficient resource utilization and it is effective in sharing available bandwidth, hence enabling implementation of bandwidth management policies. Moreover TD-uCSMA intrinsically implements traffic policy and bandwidth re-use mechanisms and notably is backward compatible to CSMA/CA nodes. As a result TD-uCSMA seems a good candidate to enable flexible and parametrized QoS provisioning over WiFi networks. Besides the open issues highlighted, further work is required to extend the simulation analysis to more complex scenarios involving higher number of nodes, realistic traffic profiles, transmission errors and multi-hop communications. R EFERENCES [1] “IEEE Std 802.11e-2005, Part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications Amendment 8: medium access control (MAC) quality of service enhancements,” Nov. 2005. [2] S. Mangold, C. Sunghyun, G. Hiertz, O. Klein, and B. Walke, “Analysis of IEEE 802.11e for QoS support in wireless LANs,” IEEE Wireless Commun. Mag., vol. 10, no. 6, pp. 40–50, Dec. 2003. [3] H. Zhu, G. Cao, A. Yener, and A. Mathias, “EDCF-DM: A Novel Enhanced Distributed Coordination Function for Wireless Ad Hoc Networks,” in Proc. IE ICC ’04, Jun. 2004, pp. 3866–3890. [4] L. Romdhani, Q. Ni, and T. Turletti, “Adaptive EDCF: Enhanced Service Differentiation for IEEE 802.11 Wireless Ad-Hoc Networks,” in Proc. IEEE WCNC ’03, vol. 2, Mar. 2003, pp. 1373–1378. [5] R. Pries, S. Menth, D. Staehle, M. Menth, and P. Tran-Gia, “Dynamic Contention Window Adaptation (DCWA) in 802.11e Wireless Local Area Networks,” in Proc. IEEE ICCE ’08, Jun. 2008, pp. 92–97. [6] C. Casetti and C. Chiasserini, “Improving Fairness and Throughput for Voice Traffic in 802.11e EDCA,” in Proc. IEEE PIMRC’04, Sep. 2004. [7] E. Carlson, C. Prehofer, C. Bettstetter, H. Karl, and A. Wolisz, “A Distributed End-to-End Reservation Protocol for IEEE 802.11-Based Wireless Mesh Networks,” IEEE J. Sel. Areas Commun., vol. 24, no. 11, pp. 2018–2027, Nov. 2006. [8] R. Scopigno - ISMB, “Italian pending patent TO2009A000568.”
