Scheduling MPEG-4 Video Streams through the 802.11e Enhanced Distributed Channel Access Michael Ditze 1 , Kay Klobedanz 1 , Guido K¨amper 1 , Peter Altenbernd 2 C-LAB, F¨ urstenallee 11, 33102 Paderborn, Germany 1 Fachhochschule Darmstadt, Haardtring 100, 64295 Darmstadt, Germany 2 EMail: {michael.ditze, kay.klobedanz, guido.kaemper}@c-lab.de 1
[email protected] 2
Abstract The upcoming IEEE 802.11e standard for Wireless LAN has gained a lot of popularity, recently. It improves the Medium Access Control (MAC) of the legacy 802.11 with regard to Quality of Service (QoS) by introducing the Enhanced Distributed Channel Access (EDCA) and the HCF Controlled Channel Access (HCCA). In contrast to the legacy Distributed Coordination Function (DCF), EDCA achieves QoS by providing independent transmit queues and MAC parameters for each traffic class, and hence higher prioritized traffic has a higher probability for transmission. Crucial to the success of such a strategy is a scheduler that assigns the data traffic to the respective transmit queues. This is all the more essential in cases where priorities cannot be assigned statically before run-time, but rather require dynamic and adaptable priority assignment as this is the case for many multimedia applications, e.g. MPEG-4 video streaming. This paper develops and accommodates a new scheduler for EDCA into the MPEG-4 Delivery Framework. The scheduler dynamically determines MPEG frame priorities and assigns data packets to the EDCA transmit queues accordingly. We use the NS-2 network simulator to show that we are able to increase the amount of timely transmitted frames significantly and hence improve the QoS percepted by the user. To the best of our knowledge this is one of very few scheduling approaches that considers MPEG-4 related traffic priorization in EDCA.
1. Introduction Following its finalization in 1999, the wireless 802.11 standard, also commonly referred to as WLAN, is increasingly being established as the wireless networking protocol that allows to interoperate devices and their services in many application domains, e.g. home domain. Crucial to the commercial success of 802.11 is the degree by which application requirements can be fulfilled by the networking protocol. Multimedia applications like MPEG video streaming represent a significant share in many application domains and are increasingly being deployed in many embedded Consumer Electronics end-devices like cell phones, PDAs and set top boxes. MPEG-4 applications require QoS support on both, the enddevice and the network carriers in order to guarantee the delivery of time-sensitive video data from the source to the sink. As the legacy 802.11 does not provide any QoS guarantees due to the random-based medium access scheme in the Data Link
Layer, the 802.11e working comitee prepares major amendments to the 802.11 channel access regardless of the physical layer underneath. 802.11e allows to assign prioritized traffic to traffic categories that exhibit different MAC parameters. The proper adjustment of these parameters for each traffic category results in different probabilities to gain the medium access. In order to assign data packets to the respective traffic categories with regard to their priority derived from the application, a scheduler is required. The scheduler is easy to maintain when priorities are assigned statically before run-time. Many multimedia applications e.g. video streaming, however, benefit from dynamic scheduling policies that allow the scheduler to adjust to the varying workloads that result from video compression and user interactivity [1]. In cases where a dynamic scheduling policy is deployed that may change priorities at runtime in order to adapt to the dynamic task conditions the scheduler becomes all the more the crucial entity that ensures QoS maintenance. Dynamic scheduling policies has been proven crucial for This paper presents a new smart scheduler that dynamically determines priorities for MPEG-4 frames and assigns corresponding data packets to EDCA transmit queues accordingly. In contrast to other solutions we do not confuse the importance and the urgency of frame-tapes and hence schedule lower prioritized frames with a close deadline in the presence of higher prioritized frame in case the latter can still make its deadline. The dynamic priority assignment derives from a modification of the Least Laxity First approach which we already used to suit processor scheduling for MPEG streams on end-devices [[2], citeditze2] and now adapt for network scheduling. The laxity of a frame hereby denotes the amount of time a data packet can be delayed on its transmission and still arrive within its deadline at the receiving end-device. The scheduler relies on a statistical approach for Admission Control for 802.11e [4] and may provide soft real-time guarantees. We implemented the scheduling policy on top of the 802.11e MAC into the NS-2 network simulator. Evaluation results prove that using this approach we are able to increase the amount of timely transmitted frames significantly compared to traditional scheduling solutions. To the best of our knowledge this one of very few scheduling approaches for 802.11e. The rest of the paper is organized as follows: Section 2 gives an introduction on MPEG-4 and 802.11e. Section 3 presents related work. Section 4 describes the new approach followed by
a description on simulation in Section 5. Section 6 concludes this paper with future work.
2. Introduction to 802.11e and MPEG This section gives s short introduction on the general working principles of the 802.11e EDCA and MPEG-4.
2.1. Introduction to 802.11e The legacy 802.11 standard provides detailed medium access control and operation at the physical layer for Wireless LANs. The fundamental medium access function is referred to as Distributed Coordination function (DCF). DCF operates in contention periods where each station may autonomously access the medium. Contention periods alternate over time with contention free periods where a central Point Coordinator uses the Point Coordination Function (PCF) to poll stations for medium access. As PCF is rarely implemented in current 802.11 chipsets, we will only consider DCF for the remaining of this paper. DCF defines a Carrier Sense Multiple Access - Collision Avoidance (CSMA/CA) listen-before-talk scheme where each station needs to sense the medium as being idle for a DIFS-time (DCF Interframe Space) before transmission. To keep multiple stations from accessing the medium simultaneously in the same slot after a successful transmission, a random binary exponential backoff procedure is performed where each station choses a backoff timer within a predefined temporal range referred to as the Contention Window (CW) which is a multiple of the physical slot time. The backoff timer is decremented while the medium is being sensed as idle. Once it reaches zero, the station re-initiates the transmission. Each transmitted packet will be acknowledged by the receiving station in order to account for the unreliable wireless transmission medium. In case a transmission remains unacknowledged for the duration of a Short IFS (SIFS) which is shorter than DIFS, a collision is presumed and the packet is queued for re-transmission. According to the backoff procedure the CW is doubled after each unsuccessful transmission as long as it does not exceed the maximum CW size and a new random backoff timer is set. As medium access is controlled through a random-based arbitration scheme that does not support traffic differentiation , DCF does neither allow to prioritize traffic nor does it provide timing guarantees and hence QoS to the applications. As a consequence, the 802.11e working group is in the process of developing a new improved medium access scheme for contention periods referred to as Enhanced Distributed Channel Access (EDCA). In contrast to DCF, EDCA allows to prioritize traffic by introducing four different Access Categories (ACs) to each QoS station (QSTA) [5]. Each AC maintains a separate transmit queue and a dedicated channel access function that features AC-specific parameters. These parameters include different values for minimum and maximum Contention Windows, Arbitration Interframe Spaces (AIFS) and a Transmission Opportunity (TXOP) duration [6]. AIFS, that is generally larger than DIFS, hereby denotes an individual time for sensing the medium that can be adjusted for each AC. Hence, in order to allow for traffic priorization in 802.11e, higher priority ACs receive shorter AIFSs and lower CWs to increase the probability of a successful channel access
(see Fig.1). The channel access itself remains similar to DCF. A TXOP is usually allocated by the QoS Access Point (QAP) and, in contrast to the legacy DCF, hereby grants a station the right to use the medium at a defined point in time for a defined maximum duration. Higher prioritized ACs are granted larger TXOPs which results in a larger throughput per AC. In case of an internal collision i.e. the backoff timer of at least two ACs simultaneously reaches zero, an internal scheduler grants the access rights to the higher prioritized AC and forces the other station to enter backoff procedure.
2.2. Introduction to MPEG The MPEG standards developed by the Motion Pictures Experts Group have grown to become a world-wide standard for video compression reducing the workload on processors and networks by exploiting the intrinsic redundancy between consecutive video pictures. MPEG-4 covers a wide area of bit-rates ranging from below 64 Kbits/sec for applications with extremely low bandwidth up to 4 Mbit/sec for video streaming applications [7]. As the allocated encoding bit-rate in MPEG-4 is not fixed, it may be further increased. In contrast to its predecessors, MPEG-4 [7] allows for the decomposition of video scenes into single audio-visual objects. Each object can be separately encoded and transmitted as a series of frames in one or several Elementary Streams (ES). ESs then pass the Sync Layer before they are transmitted through the Delivery Multimedia Integration Framework that encapsulates them into native transmission protocols, e.g. RTP/IP. In order to exploit the redundancy in video streams, MPEG-4 defines three particular types of Video Object Planes (VOP) that are temporal instances of an audio-visual object. These VoPs exhibit different compression ratios and are referred to as I(ntrapicture)-VOPs, P(redicted picture)-VOPs and B(idirectional predicted picture)- VOPs. I-VOPs serve as reference VOPs to P-and B-VOPs whereas P-VOPs are predicted VOPs that collect relevant information encoded in former I-VOPs. They also serve as reference VOPs to B-VOPs. Consequently, I-VOPs and P-VOPs are also referred to as reference VOPs. B-VOPs can be either forward or backward predicted and likewise exploit redundant information encoded in previous or subsequent VOPs. Since B-VOPs can be either forward-, backward-predicted or a combination of both, the MPEG standard distinguishes the order in which VOPs are encoded (Display Order) and the order in which they are transmitted (Transmission Order). Fig.2 further illustrates the interdependencies among the different VOP-types in Transmission Order. The reference VOP a particular VOP relies on for decoding is denoted by the shaded boxes on the top right and the arrows pointing to that VOP. A Group of VOPs (GOV) is a sequence of VOPs ranging from one I-VOP to the next. It complies with Groups of Pictures in MPEG-2. Even if MPEG does not standardize the GOV pattern, numerous streams often show the same fixed sequence. While fixed spacing and/or the use of GOVs is not required by the standard, it is so widely used, that a pair of parameters describes the spacing between I-VOPs and P-VOPs. As each GOV may be self-contained, it is independent of others which allows for decoding without any knowledge about other groups.
Figure 1. EDCA Parameters MPEG-4 can be encoded in constant bit-rate (CBR) or variable bit-rate (VBR). Whereas CBR encodes every VOP at the same fixed bit-rate, VBR allows the bit-rate to vary, and hence ensures the same steady picture quality even in scenes that are hard to encode. As VBR reaches better compressionrates, we proceed on the assumption that MPEG-4 streams are encoded likewise.
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Figure 2. Transmission and Display Order in a GOV
3. Related Work A lot of work has addressed the topic of scheduling for Multimedia Applications, recently, e.g. [[1],[3],[8],[9]]. This section describes previously published relevant work in the area of Admission Control and scheduling for 802.11e. Ansel et al. [10] present a new scheduling algorithm for the contention-free Hybrid Coordinated Channel Access (HCCA) in 802.11e that aims to be fair at CBR and VBR video flows. Their approach contains a node scheduler and a QAP scheduler. The QAP scheduler exploits queue length estimation for each QSTA to control the time allocation to stations. It estimates the varying queue length for each QSTA before every service interval and compares this value to the ideal queue length. Based on a window of previous estimation errors for each TC, the QAP adapts the computation of TXOPs allocation to a certain QSTA. The QSTA may then redistribute the unused time among the different TCs. In contrast to Ansel we introduce a scheduling mechanism that operates under the contention-based EDCA which is more practical as the past has shown that many manufactures do not implement contention-free MAC due to cost limitations. Further, [10] relies on an average sending rate for
VBR applications. Their approach behaves well in stable conditions but is condemned to fail in situations with abrupt workload changes as it is often the case in MPEG scene transitions. Besides relying on EDCA, we assume a maximum sending rate per frame-type over a predefined time window. Likewise, we are able to estimate the sending rate per flow more accurately and hence achieve a more efficient resource utilization. Hertrich developed a simple prioritizing scheme for the transmission of MPEG-4 video over the legacy 802.11 [12]. He prioritizes frame types and adapts the 802.11 data link layer parameters such as the quality of the MPEG4 video at the receiving end-device is kept as good as possible, even and especially when non-optimal link quality affects radio transmission. Hence, he adjusts the amount of re-transmission attempts with regard to the frame priority, preferring I-VOPs over P- and B-VOPs. Hertrich uses a static priority assignment scheme that does only consider the importance of particular frame-types but neglects their urgency. As a consequence lower prioritized frames will be skipped in the presence of a high priority frame even if the low prioritized frame could have been transmitted without causing the latter to miss its deadline. Further, the approach is restricted to the legacy 802.11 MAC. In our approach we rely on a dynamic scheduling strategy that considers the urgency and the importance of a frame. Hence, frames are assigned pre-defined priorities that may dynamically change according to the frame laxity. Likewise, frames are transmitted if they are guaranteed not to interfere with higher prioritized frames. Moreover, we exploit the differentiated traffic mechanisms as provided by the 802.11e. As our scheduling approach relies on an accurate estimation of available bandwidth in order to prioritize data traffic accordingly, the following approaches are also relevant for this work: Bianchi provides an analytical model to compute the 802.11 DCF saturation throughput in the assumption of ideal channel conditions and a finite number of terminals [11]. The saturation throughput hereby denotes the maximum load a system can carry in stable conditions as the offered load increases. Bianchi first determines the stationary probability T that a station transmits a packet in a generic slot time and then calculates the throughput by studying the events that may occur within the generic slot time. Pong and Moors extend this approach to make it suitable for 802.11e by estimating the per-flow throughput for EDCA [4]. A flow is defined as the set of packets belonging to the same AC. They determine the transmission probability of a flow and calculate its achievable throughput at saturation conditions as the proportion of time for transmitting data payload
the queues. Initially, considering the importance, packets are assigned as follows:
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Table 1. Access Categories for MPEG-4 data packets
Figure 3. MPEG-4 EDCA Scheduler embedded in the MPEG Delivery Framework
in respect to idle, collision and header transmission time during a cycle of frame exchange. We exploit this approach to estimate the medium access time for a packet in a particular flow.
4. A MPEG Scheduler for EDCA Fig.3 illustrates a simplified architecture that accommodates the MPEG-4 EDCA scheduler into the MPEG-4 Delivery Framework. The scheduler also complies with the latest 802.11e draft [5]. The compression layer encodes VOPs that represent Audio Visual Objects and passes them via the Sync Layer and the DMIF API directly to the new scheduler. The Sync Layer hereby performs time stamp assignment and VOP packet fragmentation. The task of the scheduler is to dynamically determine the priority of each packet according to a scheduling policy that is suited for MPEG-4 and assign the fragmented VOP packets to the EDCA AC transmit queues.
4.1. Priorities and Access Categories Assignment We use a priority-based scheduling policy that does not confuse the importance of data packets and their urgency. Urgent MPEG-4 packets are those packets that have a close deadline while important packets are required for further frame decoding. As a consequence, I-VOPs usually exhibit the highest importance as the whole GOV cannot be decoded without having decoded this I-VOP first. B-VOPs on the contrary may temporarily be more urgent as they appear more frequently and have closer deadlines (see Section 2.2). Corresponding to the EDCA ACs, the scheduler maintains 4 internal working queues WQ that feed the the transmit queues of each AC. The scheduler deploys a Least-Laxity-First (LLF)-extended scheduling policy in order to dynamically assign packets to
Similar to the 802.11e ACs, WQ[3] represents the highest priority and WQ[0] the lowest priority queue. I- and P-VOPs data packets are assigned to top priority WQ[3], whereas BVOP packets that can be skipped occasionally in favour of other data packets are inserted into the WQ[2] queue. Other remaining packets that do not have a priority are inserted in the WQ[1] queue and hence do not need to undergo Admission Control. The different priorization of VOP packets hereby adheres to the uni- and bidirectional predictive encoding of MPEG. Further, we prioritize data packets in the working queues of each AC in priority order, serving packets with the highest priority first. Priorities are derived as follows: • WQ[3] gives I-VOP data packets priority over P-VOP data packets. If packets belong to different streams but have the same priority and share the same deadline, they build ordered sets of data packets. Within each such set the lower-sized VOP packets are scheduled first. This is to ensure that large-sized VOPs do not interfere lowsized VOPs with the same priority. Other scheduling policies may chose to prefer VOPs of streams that exhibit a higher priority within the ordered set and hence allow for a higher throughput rate of these streams. • WQ[2] also builds ordered sets of B-VOP packets in case they belong to different streams and share the same deadline and priority. Similar to WQ[3], lower sized BVOPs are preferred. Building ordered sets has a an impact of the throughput performance of MPEG-4 data packets as it allows to use the available bandwidth more efficiently or permits to distinguish between streams with different priorities.
4.2. Scheduling Policy Data packets in WQ[3] and WQ[2] are concurrently scheduled by an extension to the LLF algorithm. This policy that is often applied in real-time operating systems schedules the most urgent data packet, i.e. the data packet with the smallest laxity Y. The laxity hereby denotes the maximum time a data packet can be delayed on its transfer to be transmitted and decoded at the receiver within its deadline. In addition to that our policy
• skips B-VOP packets in WQ[2] if their deadline has already passed or exhibit a negative urgency Y. • may move single data packets from WQ[2] to WQ[3] in case they can be transferred and decoded without causing the latter to miss their deadline and are kept in order of appearance. Due to the forward precedences in MPEG, WQ[2] VOP packets may only be inserted before those VOP packets that WQ[2] depends on for decoding. • prefers lower-sized VOPs in case two VOPs in the same AC are equally prioritized and share the same deadline.
4.3. Admission Control and Throughput Analysis The scheduling approach relies on an Admission Control that founds on a throughput analysis for 802.11e. The throughput analysis estimates the available throughput at saturation conditions [4](see Section 3). It exploits the statistical collision probability for a flow in an AC in order to compute the transmission probability in a slot and may likewise derive the achievable throughput τj for (ACj ) on the proportion of time for transmitting data payload in respect to idle, collision and header transmission times. We use the available throughput analysis per AC in order to determine if WQ[2] packets can be moved to WQ[3] (and hence AC[3]) without causing WQ[3] packets to miss their deadline
where Di denotes the deadline of a packet i and derives from the frame-per-second rate of the video stream. As a consequence, the scheduler may move data packets from WQ[2] to WQ[3], if the estimated processing time Tp2 of data packets belonging to a VOP is less than the urgency Y[i]3 of a corresponding packet i in WQ[3].
4.4. EDCA Scheduler Activity Diagram Fig.5 describes the transmission process MPEG-4 VOPs in UML notation. MPEG-4 VOPs are generated by the MPEG4 Compression Layer or by a respective MPEG-4 traffic generator in our simulation environment. The scheduler decides in which queue each VOP will be inserted according the static priority assignment scheme as introduced in Section 4.2. The scheduling policy checks the deadline of each generated VOP, in particular B-VOPs that exhibit the less impact on the video quality, and may decide to reject VOPs that are expected to miss their deadlines. In case of B-VOPs the scheduler further determines the average processing time of the B-VOP which is then compared with the urgency values of queued AC[3]-packets as determined in Eq.2-4. In case the transmission time of the B-VOPs is less than the urgency of subsequent packets in AC[3], the B-VOP is inserted in AC[3]. Otherwise it will be sent by the AC[2]-queue with a lower priority.
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We then define the expected processing Time Tp[i]j for each data packet i in a Working Queue j as the expected time required to gain medium access TM AC[i]j in ACj , its expected transmission time TTi and the worst-case decoding time of the frame the packet belongs to Ci at the receiving device Tp[i]j = TM AC[i]j + TTi + Ci
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Figure 4. NS-2 MPEG-4 Scheduler Implementation
References [1] Baiceanu, V., Cowan, C.,McNamee, D.,Pu, C.,Walpole, J.: Multimedia Applications Require Adaptive CPU Scheduling. In Workshop on Resource Allocation Problems in Multimedia Systems, Washington D.C., December 1996. [2] Ditze, M.: ”A New Method for the Real Time Scheduling and Admission Control of MPEG-2 Streams” M.Sc. thesis, School of Computer Science, Paderborn University, December 2001.
Figure 5. NS-2 MPEG-4 Scheduler Implementation
5. Testbed and Evaluation We evaluated the new scheduling policy with the NS-2 network simulator. As a MPEG-4 traffic generator, we chose a model that exploits the Transform Expand Sample Methodology [15] to fill the working queues of the scheduler that is implemented as a class in NS-2. Fig.5 illustrates the architectural design of the scheduler implementation in NS-2. The traffic generator uses additional separate NS-2 output agents for each VOP-type. This allows to generate graph diagrams in order to analyze the throughput behaviour per VOP-type. The traffic generator then passes the frame packets to the scheduler. The scheduler is built on top of the 802.11e implementation as described in [14]. It routes the VOPs to the EDCA AC queues according to the scheduling policy introduced in the last section. Each of the AC agents then uses the mandatory sendmsg method to transmit the queued packets. Furthermore, at the receiving client, we extended the NS-2 Loss Monitor by an outp()-function and by a separate counter for MPEG-4 VOPs and traffic. This allows us to compare the generated video traffic throughput and the actual data received at the client, and hence the packet loss can be accurately determined. At the receiver node a second LossMonitor records the incoming data and frames. Due to those records and the informations of the first LossMonitor we can evaluate the behaviour and results of the scheduling. The first experiments showed promising results and will be available when further progress in the simulation model will have been made.
6. Summary and Future Work This paper presented work on a new scheduling policy for 802.11 EDCA. It is especially designed to dynamically prioritize MPEG traffic and assign it to the EDCA ACs in order to improve the resource utilization and the timely transfer of MPEG data frames. It relies on a statistical analysis of the available throughput per flow at saturation conditions. In future we will further evaluate the policy with the NS-2 simulator. We will further develop more accurate methods to estimate the MPEG traffic per AC in order to determine the urgency more precisely.
[3] Ditze, M., Altenbernd, P., Loeser, C.: Improving Resource Utilization for MPEG Decoding in Embedded End-Devices In Proceedings of the TwentySeventh Australasian Computer Science Conference (ACSC2004), Dunedin, New Zealand, January, 2004. [4] Pong, D., Moors, T.: ”Call Admission Control for the IEEE 802.11 Contention Access Mechanism” In Proceedings of the Globecom 2003, pp. 174-8, December, 2003. [5] IEEE Standard for Information Technology - Part 11: Wireless Medium Access Control (MAC) and Physical Layer (PHY) specifications Amendment7: Medium Access Controll (MAC) Quality of Service (QoS) Enhancements IEEE 802.11e/D9.0, August, 2004. [6] Mangold, S., Choi, S., May, P., Klein, O., Hiertz, G., Stibor, L.: ”IEEE 802.11e Wireless LAN for Quality of Service” IEEE Wireless Communications Magazine, Special Issue on Evolution of Wireless LANs and PANs, vol. 10, no. 6, December 2003. [7] International Organisation For Standardisation ”Information Technolgy -Generic Coding Of Audio-Visual Objects Part 2: Visual” ISO/IEC JTC1/SC29/WG11. [8] Nieh, J.,Lam, M.S.: The Design, Implementation and Evaluation of SMART: A Scheduler for Multimedia Applications. In Proc. of the 16th ACM Symposium on Operating Systems Principles, St-Malo, France, pp. 184197, Oct. 1997. [9] Bavier, A., Peterson, L., Mosberger, D.: BERT : A Scheduler for Best Effort and Realtime Tasks. Technical Report TR-587-98, Princeton University, August 1998. [10] Ansel, P., Ni, Q., Turletti, T.: An Efficient Scheduling Scheme for IEEE 802.11e In Proceedings of the WiOpt (Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks), Cambridge, UK, March 2004. [11] Bianchi, G.: ”Performance Analysis of the 802.11 Distributed Coordination Function” In IEEE Journal on Selected Areas in Communications, Vol 18, No.3, March 2000. [12] Hertrich, D.: ”MPEG4 video transmission in wireless LANs: Basic QoS support on the data link layer of 802.11b” Minor Thesis, Technical University of Berlin, October, 2002. [13] Altenbernd, P., Burchard, L., Stappert, F.: WorstCase Execution Times Analysis of MPEG-2-Decoding 12th Euromicro Conference on Real Time Systems, Stockholm, Sweden. [14] Wiethoelter, S., Hoene, C.: Design and Verification of an IEEE 802.11e EDCF Simulation Model in ns-2.26 Technical Report TKN-03-019, Technische Universitaet Berlin, November 2003.
[15] Matrawy, A., Lambadaris, I., Huang, C.: MPEG4 Traffic Modeling Using The Transform Expand Sample Methodology In Proceedings of the 4th IEEE International Workshop on Networked Appliances, IEEE IWNA4, Gaithersburg, MD, January 2002.
