Stream Scheduling Research Articles

Comments on "Dynamic Window-Constrained Scheduling of Real-Time Streams in Media Servers

For original paper see R. West et al., ibid., vol.53, no.6, p.744-759, (2004). This short report clarifies the behavior of DWCS with respect to Theorem 3 in our previously published paper and describes an alternative approach to make guarantees for arbitrary window-constraints

Practical algorithms for scheduling video data in a local area network environment

Simultaneous transmission of multiple high quality video streams from a server to the clients is becoming an increasingly important class of traffic in a network of workstations or cluster environment. With a powerful symmetric multiprocessor (SMP) as the server and a high-speed network, such transmission is practicable from a hardware point of view. However, the actual construction of such a video data server system entails tackling a number of difficult problems related to the provision of strict quality of service (QoS) guarantees. Among others, the smoothing and scheduling of multiple video packet streams are two crucial issues. Smoothing is concerned with reducing the rate variability of video streams in view of the fact that video data are usually compressed in a variable bit rate fashion. Scheduling is important to guarantee the requested QoS levels while maximizing the utilization of the resources. Although much work on smoothing has been done, it is not clear which scheduling scheme is suitable for multiplexing smoothed video data to the network. In this paper we present an extensive performance study of the EDF and RM scheduling algorithms which are modified to provide QoS guarantees for smoothed video data. With a probabilistic definition of QoS, admission control conditions are incorporated into the two algorithms. Furthermore, a counter-based scheduling module is included as the core scheduling mechanism which adaptively adjusts the actual QoS levels assigned to requests. Our theoretical analysis of the two modified algorithms, called QEDF and QRM, shows that the QRM algorithm is more robust than the QEDF algorithm for different workload and utilization conditions. We also propose to use a new metric called meta-QoS to quantify the overall performance of a packet scheduler given a set of simultaneous requests. In our experiments based on an SMP-based Linux platform, we find that the QRM algorithm can sustain a rather stable level of meta-QoS even when the workload and utilization levels are increased. On the other hand, the QEDF algorithm, due to its conservative admission control policy, is found to be not suitable for a high level of utilization and a large number of requests. In view of the lower complexity of the QRM algorithm, it seems that the QRM approach is a more suitable candidate for packet scheduling in the client-server environment considered in our study.

Supporting Interactive Video-on-Demand With Adaptive Multicast Streaming

Recent advances in multicast video streaming algorithms have opened up new ways to provision video-on-demand services to potentially millions of users. However, the spectacular efficiency of multicast streaming algorithms can only be realized by restricting or even prohibiting interactive playback control. Experiments reveal that the performance of current state-of-the-art multicast streaming algorithms will degrade significantly even at very low levels of interactivity (e.g., one control per five users). This study tackles this challenge by investigating the fundamental limitations of multicast streaming algorithms in supporting interactive playback control and presents a general solution-static full stream scheduling (SFSS)-which can be applied to many of the existing multicast streaming algorithms to substantially improve their performance when interactive playback control is to be supported. Moreover, to solve the problem of optimizing the algorithm for the often unknown client access patterns (e.g., arrival rates and interactivity rates), we present a novel just-in-time simulation (JTS) scheme to dynamically and automatically tune operating parameters of the SFSS algorithm while the system is online. This JTS scheme not only eliminates the need for a priori knowledge of the often unknown system parameters, but also can adapt to changes in the client access pattern over time. Extensive simulation results show that the proposed adaptive algorithm can reduce the admission and interactive control latencies by as much as 90%

Distortion Optimized Packet Scheduling and Prioritization of Multiple Video Streams over 802.11e Networks

This paper presents a generic framework solution for minimizing video distortion of all multiple video streams transmitted over 802.11e wireless networks, including intelligent packet scheduling and channel access differentiation mechanisms. A distortion prediction model designed to capture the multireferenced frame coding characteristic of H.264/AVC encoded videos is used to predetermine the distortion importance of each video packet in all streams. Two intelligent scheduling algorithms are proposed: the “even-loss distribution,” where each video sender is experiencing the same loss and the “greedy-loss distribution” packet scheduling, where selected packets are dropped over all streams, ensuring that the most significant video stream in terms of picture context and quality characteristics will experience minimum losses. The proposed model has been verified with actual distortion measurements and has been found more accurate than the “additive distortion” model that omits the correlation among lost frames. The paper includes analytical and simulation results from the comparison of both schemes and from their comparison to the simplified additive model, for different video sequences and channel conditions.

Full-sharing: efficient bandwidth scheduling for video streaming over broadband cable networks (BCNs)

Broadband Cable Networks (BCNs) bring high-speed Internet access to home and make emerging multimedia streaming applications feasible. However, bandwidth contention is still a challenging problem in providing efficient IP-based Video-On-Demand (VOD) service on BCNs, due to the lack of effective approaches to exploit the unique characteristics of BCNs. To address the bandwidth contention issue, we propose an efficient video scheduling technique, called full-sharing scheduling in this paper. This technique fully exploits the unique characteristics of BCNs to reduce the bandwidth consumption of video sessions sharing a cable channel of fixed capacity, thereby maximizing the number of simultaneous video sessions on the single channel. Furthermore, we analyze the expected bandwidth and the session blocking probability of a video under the full-sharing scheduling. Based on this analysis, we design an efficient video assignment mechanism for maximizing the profit of a VOD system in scheduling videos on BCNs. Through both analysis and simulation, we show that our approach minimizes the bandwidth consumption of video sessions compared with the previous approaches and has significant advantages on BCNs. The proposed approach is also directly applicable on other broadcast/multicast networks in which clients have sufficient buffer and downstream bandwidth, e.g., satellite broadband networks.

Joint rate control and scheduling for wireless uplink video streaming

We solve the problem of uplink video streaming in CDMA cellular networks by jointly designing the rate control and scheduling algorithms. In the pricing-based distributed rate control algorithm, the base station announces a price for the per unit average rate it can support, and the mobile devices choose their desired average transmission rates by balancing their video quality and cost of transmission. Each mobile device then determines the specific video frames to transmit by a video summarization process. In the time-division-multiplexing (TDM) scheduling algorithm, the base station collects the information on frames to be transmitted from all devices within the current time window, sorts them in increasing order of deadlines, and schedules the transmissions in a TDM fashion. This joint algorithm takes advantage of the multi-user content diversity, and maximizes the network total utility (i.e., minimize the network total distortion), while satisfying the delivery deadline constraints. Simulations showed that the proposed algorithm significantly outperforms the constant rate provision algorithm.

Rate-distortion optimized distributed packet scheduling of multiple video streams over shared communication resources

We consider the problem of distributed packet selection and scheduling for multiple video streams sharing a communication channel. An optimization framework is proposed, which enables the multiple senders to coordinate their packet transmission schedules, such that the average quality over all video clients is maximized. The framework relies on rate-distortion information that is used to characterize a video packet. This information consists of two quantities: the size of the packet in bits, and its importance for the reconstruction quality of the corresponding stream. A distributed streaming strategy then allows for trading off rate and distortion, not only within a single video stream, but also across different streams. Each of the senders allocates to its own video packets a share of the available bandwidth on the channel in proportion to their importance. We evaluate the performance of the distributed packet scheduling algorithm for two canonical problems in streaming media, namely adaptation to available bandwidth and adaptation to packet loss through prioritized packet retransmissions. Simulation results demonstrate that, for the difficult case of scheduling nonscalably encoded video streams, our framework is very efficient in terms of video quality, both over all streams jointly and also over the individual videos. Compared to a conventional streaming system that does not consider the relative importance of the video packets, the gains in performance range up to 6 dB for the scenario of bandwidth adaptation, and even up to 10 dB for the scenario of random packet loss adaptation.

Utilizing multi-channel multicast to provide scheduled video delivery

In reality, not all users require instant video access. People are used to planning ahead, including when they wish to watch videos. This fact triggered the creation of a new video-scheduling paradigm, named Scheduled Video Delivery (SVD). It lures clients into making requests as early as possible in order to increase stream scheduling flexibility and pricing-based resource utilization. The existing SVD single-channel request scheduling algorithms, such as MEDF and LPF, have already successfully demonstrated the feasibility of SVD. In this paper, we propose the Multi-Channel Multicast Delivery (MCMD) stream-scheduling algorithm for SVD. With MCMD, a client can receive segments of the same requested video being transmitted on channels. Its patching and multi-channel receiving capabilities further improve resource utilization and the degree of multicast in delivering continuous media. The performance study shows that MCMD has a lower rejection rate and higher channel utilization than MEDF and LPF on SVD, both with and without price incentives.

Radio Link Buffer Management and Scheduling for Wireless Video Streaming

In this paper we compare strategies for joint radio link buffer management and scheduling for wireless video streaming. Based on previous work in this area [8], we search for an optimal combination of scheduler and drop strategy for different end-to-end streaming options including timestamp-based streaming and ahead-of-time streaming, both with variable initial playout delay. We will show that a performance gain versus the two best drop strategies in Liebl et al. [8], i.e. drop the HOL packet or drop the packet with the lowest priority starting from HOL, is possible: Provided that some basic side-information on the structure of the incoming video stream is available, a more sophisticated drop strategy removes packets from an HOL group of packets in such a way that the temporal dependencies usually present in video streams are not violated. This advanced buffer management scheme yields significant improvements for almost all investigated scheduling algorithms and streaming options. In addition, we will demonstrate the importance of fairness among users when selecting a suitable scheduler, especially if ahead-of-time streaming is to be applied: Given a reasonable initial playout delay at the streaming media client, both the overall achievable quality averaged over all users, as well as the individual quality of users with bad channel conditions can be increased significantly by trading off fairness with maximum throughput of the system.

Streaming video packet scheduling by Geo/sup Y//G//sub ∞/ input process modeling

We introduce Geo/sup Y//G//spl infin/ input process with beta-distributed batch size and Weibull-like autocorrelation function in order to model video traffic. Investigating the overflow probability of queueing system by large deviation theory, we develop a streaming scheduling algorithm by applying the overflow analysis result to estimating the packet deadline-missing probability. Through experiments with 30-second long movie traces, we show that our proposed scheduling scheme outperforms existing schemes based on fractional Brownian motion and Markovian models.

Design and performance analysis of multimedia document retrieval strategies for networked Video-on-Reservation systems

Video-on-Reservation (VOR) systems serve as an attractive service providing scheme for multimedia network based services. As opposed to on-demand systems, in VOR, requests arrive in advance to their viewing times so that the network resources can be better utilized by carefully scheduling the resources. In this paper, we address the problem of optimizing the per user service cost and maximizing the number of requests that can be served by VOR systems. In order to provide a guaranteed QoS, generation of multicast trees with end-to-end delay constraints is recommended to minimize the costs. Since such an issue has been proved to be NP-complete, we propose two efficient and practically realizable heuristic algorithms, referred to as Source-Based Stream Scheduling (SBS) algorithm and Destination-Based Stream Scheduling (DBS) algorithm to solve the problem in polynomial time. Both SBS and DBS algorithms judiciously combine the concept of multicast routing and network caching, so that the copies of Multimedia Documents (MMDs) can be dynamically cached in the network. To analyze the trade-off between caching cost and transmission cost, we present a mathematical model and show that service cost can be minimized by adjusting offset time according to the network characteristics. When network resources (cache space and link bandwidth) are constraints, acceptance ratio can be improved significantly by combining video partitioning with SBS or DBS. We analyze and quantify the performance under several influencing parameters such as link availability, cache capacity and MMD availability. Our simulation results conclusively show that all the proposed algorithms can reduce the service cost, balance the network load and achieve a high acceptance ratio.

Dynamic window-constrained scheduling of real-time streams in media servers

We describe an algorithm for scheduling packets in real-time multimedia data streams. Common to these classes of data streams are service constraints in terms of bandwidth and delay. However, it is typical for real-time multimedia streams to tolerate bounded delay variations and, in some cases, finite losses of packets. We have therefore developed a scheduling algorithm that assumes streams have window-constraints on groups of consecutive packet deadlines. A window-constraint defines the number of packet deadlines that can be missed (or, equivalently, 'must be met) in a window of deadlines for consecutive packets in a stream. Our algorithm, called dynamic window-constrained scheduling (DWCS), attempts to guarantee no more than re out of a window of y deadlines are missed for consecutive packets in real-time and multimedia streams. Using DWCS, the delay of service to real-time streams is bounded, even when the scheduler is overloaded. Moreover, DWCS is capable of ensuring independent delay bounds on streams, while, at the same time, guaranteeing minimum bandwidth utilizations over tunable and finite windows of time. We show the conditions under which the total demand for bandwidth by a set of window-constrained streams can exceed 100 percent and still ensure all window-constraints are met. In fact, we show how it is possible to strategically skip certain deadlines in overload conditions, yet fully utilize all available link capacity and guarantee worst-case per-stream bandwidth and delay constraints. Finally, we compare DWCS to the "distance-based" priority (DBP) algorithm, emphasizing the trade-offs of both approaches.

Constructing a video server with tertiary storage: practice and experience

Handling a tertiary storage device, such as an optical disk library, in the framework of a disk-based stream service model, requires a sophisticated streaming model for the server, and it should consider the device-specific performance characteristics of tertiary storage. This paper discusses the design and implementation of a video server which uses tertiary storage as a source of media archiving. We have carefully designed the streaming mechanism for a server whose key functionalities include stream scheduling, disk caching and admission control. The stream scheduling model incorporates the tertiary media staging into a disk-based scheduling process, and also enhances the utilization of tertiary device bandwidth. The disk caching mechanism manages the limited capacity of the hard disk efficiently to guarantee the availability of media segments on the hard disk. The admission controller provides an adequate mechanism which decides upon the admission of a new request based on the current resource availability of the server. The proposed system has been implemented on a general-purpose operating system and it is fully operational. The design principles of the server are validated with real experiments, and the performance characteristics are analyzed. The results guide us on how servers with tertiary storage should be deployed effectively in a real environment.

Competitive On-line Scheduling of Continuous-Media Streams

Multimedia applications require a guaranteed level of service for accessing continuous-media data. To obtain such guarantees, the database server where the data are residing must employ an admission control scheme to limit the number of clients that can be served concurrently. We investigate the problem of on-line admission control, where the decision of whether to accept or reject a request must be made without any knowledge about future requests. Employing competitive analysis techniques, we address the problem in its most general form with the following key contributions: (1) We prove a tight upper bound on the competitive ratio of the conventional Work-Conserving (WC) policy, showing that it is within a factor 1+Δ1−ρ of the optimal clairvoyant strategy, where Δ is the ratio of the maximum to minimum request length (i.e., time duration), and ρ is the maximum fraction of the server's bandwidth that a request can demand; (2) we prove a lower bound of Ω(logΔ1−ρ) on the competitive ratio of any deterministic or randomized admission control scheme, demonstrating an exponential gap between greedy and optimal on-line solutions; (3) we propose simple deterministic schemes based on the idea of bandwidth prepartitioning that guarantee competitive ratios within a small constant factor of logΔ (i.e., they are provably near-optimal) if ρ<1/⌈logΔ⌉; and (4) we introduce a novel admission control policy that partitions the server bandwidth based on the expected popularities of different request lengths and experimentally demonstrate its benefits compared to WC.

Neural Network-Based Software Sensor for Feed Identification in Crude Distillation Unit

A predictive method of identifying the feed and product using neural network-based software sensor is proposed, which is able to provide the information for down stream scheduling, production, and control. Data preprocessing and postprocessing methods are also utilized to enhance the predictability of the software sensor model. Implementation is conducted by using Borland C++(3.0) Builder. The simulation results demonstrate the effectiveness of the proposed neural network-based software sensor.

Burst-based scheduling algorithms for non-blocking ATM switches with multiple input queues

This letter quantitatively evaluates two alternative approaches to the scheduling of traffic streams in a high-speed ATM switch with multiple input queues. Specifically, we compare a previously proposed algorithm, called parallel iterative matching (PIM)-which is a cell-based scheduling algorithm-with our newly proposed algorithm-which is a burst-based variation of the PIM scheduling algorithm. Extensive simulation results demonstrate that burst-based PIM scheduling outperforms cell-based PIM scheduling under a variety of realistic parameters.

Integrated dynamic scheduling of hard and QoS degradable real-time tasks in multiprocessor systems

Abstract Many time-critical applications require predictable performance and tasks in these applications have deadlines to be met. For tasks with hard deadlines, a deadline miss can be catastrophic while for Quality of Service (QoS) degradable tasks (soft real-time tasks) timely approximate results of poorer quality or occasional deadline misses are acceptable. Imprecise computation and ( m , k )-firm guarantee are two workload models that quantify the trade-off between schedulability and result quality. In this paper, we propose dynamic scheduling algorithms for integrated scheduling of real-time tasks, represented by these workload models, in multiprocessor systems. The algorithms aim at improving the schedulability of tasks by exploiting the properties of these models in QoS degradation. We also show how the proposed algorithms can be adapted for integrated scheduling of multimedia streams and hard real-time tasks, and demonstrate their effectiveness in quantifying QoS degradation. Through simulation, we evaluate the performance of these algorithms using the metrics – success ratio (measure of schedulability) and quality . Our simulation results show that one of the proposed algorithms, multilevel degradation algorithm , outperforms the others in terms of both the performance metrics.

Scheduling and bandwidth allocation for the distribution of archived video in VOD systems

Providing cost?effective video?on?demand (VOD) services necessitates reducing the required bandwidth for transporting video over high?speed networks. In this paper, we investigate efficient schemes for transporting archived MPEG?coded video over a VOD distribution network. A video stream is characterized by a time?varying traffic envelope, which provides an upper bound on the bit rate. Using such envelopes, we show that video streams can be scheduled for transmission over the network such that the per?stream allocated bandwidth is significantly less than the source peak rate. In a previous work [13], we investigated stream scheduling and bandwidth allocation using global traffic envelopes and homogeneous streams. In this paper, we generalize the scheduling scheme in [13] to include the heterogeneous case. We then investigate the allocation problem under window?based traffic envelopes, which provide tight bounds on the bit rate. Using such envelopes, we introduce three stream?scheduling schemes for multiplexing video connections at a server. The performance of these schemes is evaluated under static and dynamic scenarios. Our results indicate a significant reduction in the per?stream allocated bandwidth when stream scheduling is used. While this reduction is obtained through statistical multiplexing, the transported streams are guaranteed stringent, deterministic quality of service (i.e., zero loss rate and small, bounded delay). In contrast to video smoothing, our approach requires virtually no buffer at the set?top box since frames are delivered at their playback rate.

Design and analysis of a look-ahead scheduling scheme to support pause-resume for video-on-demand applications

In a video-on-demand (VOD) system, subscribers can choose both the movie they wish to view and the time they wish to view it. In such an environment there are invariably “hot” videos which are requested by many viewers. The requirement that each viewer be able to independently pause the video at any instant and later resume the viewing with little delay can cause difficulties in batching viewers for each showing. Under batching, a single video stream is shared by multiple concurrent viewers and a resume request has to wait for additional stream capacity to become available before actual resumption can occur. The conventional approach to the support of on-demand pause-resume provides one video access stream to disks for each video request. This can greatly increase the disk arm requirements of a VOD system. In this paper, we propose a more efficient mechanism to support the pause-resume feature usinglook-ahead scheduling withlook-aside buffering. The idea is to use buffering to increase the number of concurrent viewers supportable. The concept of look-ahead scheduling is not to back up each viewer with a real stream capacity so he can pause and resume at any time, but rather with a (look-ahead) stream that is currently being used for another showing which is close to completion. Before the look-ahead stream becomes available, the pause and resume features have to be supported by the original stream through (look-aside) buffering of the missed content. It is shown via simulations that the proposed scheme can provide a substantially greater throughput than the approach without batching. Furthermore, for a given amount of buffer, the improvement in throughput grows more than linearly with the stream capacity of the server. In other words, the look-ahead stream scheduling scheme operates with good economy of scale because it is easier to form look-ahead streams for video servers with larger stream capacity.