QoP-Driven Scheduling for MPEG Video Decoding

MPEG video decoding algorithm has been embedded into many consumer electronic products. In this paper, we demonstrate that the completion ratio (CR) does not represent well the quality of presentation (QoP) of MPEG video. We then propose a new QoP metric, which 1) is based on frame completion ratio but 2) differentiates firm and soft deadlines and also 3) considers the frame dependency. We show that, on a set of simulated MPEG movies, the proposed QoP metric measures the QoP of the movies much better than the completion ratio. We then present a set of online scheduling algorithms that enhance QoP significantly, particularly for overloaded systems

QOS-DRIVEN SCHEDULING FOR MULTIMEDIA APPLICATIONS

Multimedia applications have intrinsic quality of service (QoS) requirements that may not be captured by the simple traditional completion ratio model. We have proposed a new quantitative QoS metric based on task completion ratio while differentiating firm and soft deadlines and taking data dependency into consideration. Using the decoding of MPEG movies as an example, we have shown that the proposed QoS metric is much better than completion ratio in measuring the quality of presentation (QoP) of the movies. Based on the new QoS metric, we present a set of new online algorithms that outperform popular scheduling algorithms (such as EDF, FCFS, and LETF) and enhance QoP significantly, particularly when the system is overloaded. All the proposed online algorithms have low computation overhead and can be easily integrated into real-time operating systems to improve multimedia embedded system’s performance and/or to save system resources

Linear TV In The Non-Linear World: The Value of Linear Scheduling Amidst the Proliferation of Non-Linear Platforms

Unprecedented technological innovations in media content consumption have had a profound impact on the network television industry. Television networks' control has waned since the advent of alternative platforms for content viewing. Audiences have been released from the clutches of the linear schedule. They now have the freedom to customize viewing based on their content and platform preferences, and availability. The purpose of this qualitative study is to assess 1) the current value of television linear scheduling and 2) the effectiveness of traditional strategies in this present phase of channel and platform proliferation. An additional goal is to identify new strategies that are employed by broadcasters to accommodate the audience's changing viewing habits. Thus, the author primarily interviewed experienced television executives who were currently in-charge of scheduling television shows. Their insights have led to the conclusion that scheduling remains relevant in this age of non-linear viewing. However, its functions adapt and its scope expands beyond linear. There are also key changes in the approaches and thought-processes in scheduling. Furthermore, new systems have been identified, which are currently utilized in attracting audiences to consume content via live television. As television insiders have differing opinions, it is suggested that the effectiveness of these new systems be researched further. Keywords: television scheduling, television programming, linear scheduling, lead-in, non-linear viewingM.S., Television Management -- Drexel University, 201

Providing QoS with Reduced Energy Consumption via Real-Time Voltage Scaling on Embedded Systems

Low energy consumption has emerged as one of the most important design objectives for many modern embedded systems, particularly the battery-operated PDAs. For some soft real-time applications such as multimedia applications, occasional deadline misses can be tolerated. How to leverage this feature to save more energy while still meeting the user required quality of service (QoS) is the research topic this thesis focuses on. We have proposed a new probabilistic design methodology, a set of energy reduction techniques for single and multiple processor systems by using dynamic voltage scaling (DVS), the practical solutions to voltage set-up problem for multiple voltage DVS system, and a new QoS metric. Most present design space exploration techniques, which are based on application's worst case execution time, often lead to over-designing systems. We have proposed the probabilistic design methodology for soft real-time embedded systems by using detailed execution time information in order to reduce the system resources while delivering the user required QoS probabilistically. One important phase in the probabilistic design methodology is the offline/online resource management. As an example, we have proposed a set of energy reduction techniques by employing DVS techniques to exploit the slacks arising from the tolerance to deadline misses for single and multiple processor systems while meeting the user required completion ratio statistically. Multiple-voltage DVS system is predicted as the future low-power system by International Technology Roadmap for Semiconductors (ITRS). In order to find the best way to employ DVS, we have formulated the voltage set-up problem and provided its practical solutions that seek the most energy efficient voltage setting for the design of multiple-voltage DVS systems. We have also presented a case study in designing energy-efficient dual voltage soft real-time system with (m, k)-firm deadline guarantee. Although completion ratio is widely used as a QoS metric, it can only be applied to the applications with independent tasks. We have proposed a new QoS metric that differentiates firm and soft deadlines and considers the task dependency as well. Based on this new metric, we have developed a set of online scheduling algorithms that enhance quality of presentation (QoP) significantly, particularly for overloaded systems

An Analytical Solution for Probabilistic Guarantees of Reservation Based Soft Real-Time Systems

We show a methodology for the computation of the probability of deadline miss for a periodic real-time task scheduled by a resource reservation algorithm. We propose a modelling technique for the system that reduces the computation of such a probability to that of the steady state probability of an infinite state Discrete Time Markov Chain with a periodic structure. This structure is exploited to develop an efficient numeric solution where different accuracy/computation time trade-offs can be obtained by operating on the granularity of the model. More importantly we offer a closed form conservative bound for the probability of a deadline miss. Our experiments reveal that the bound remains reasonably close to the experimental probability in one real-time application of practical interest. When this bound is used for the optimisation of the overall Quality of Service for a set of tasks sharing the CPU, it produces a good sub-optimal solution in a small amount of time.Comment: IEEE Transactions on Parallel and Distributed Systems, Volume:27, Issue: 3, March 201

Systems and Methods for Measuring and Improving End-User Application Performance on Mobile Devices

In today's rapidly growing smartphone society, the time users are spending on their smartphones is continuing to grow and mobile applications are becoming the primary medium for providing services and content to users. With such fast paced growth in smart-phone usage, cellular carriers and internet service providers continuously upgrade their infrastructure to the latest technologies and expand their capacities to improve the performance and reliability of their network and to satisfy exploding user demand for mobile data. On the other side of the spectrum, content providers and e-commerce companies adopt the latest protocols and techniques to provide smooth and feature-rich user experiences on their applications. To ensure a good quality of experience, monitoring how applications perform on users' devices is necessary. Often, network and content providers lack such visibility into the end-user application performance. In this dissertation, we demonstrate that having visibility into the end-user perceived performance, through system design for efficient and coordinated active and passive measurements of end-user application and network performance, is crucial for detecting, diagnosing, and addressing performance problems on mobile devices. My dissertation consists of three projects to support this statement. First, to provide such continuous monitoring on smartphones with constrained resources that operate in such a highly dynamic mobile environment, we devise efficient, adaptive, and coordinated systems, as a platform, for active and passive measurements of end-user performance. Second, using this platform and other passive data collection techniques, we conduct an in-depth user trial of mobile multipath to understand how Multipath TCP (MPTCP) performs in practice. Our measurement study reveals several limitations of MPTCP. Based on the insights gained from our measurement study, we propose two different schemes to address the identified limitations of MPTCP. Last, we show how to provide visibility into the end- user application performance for internet providers and in particular home WiFi routers by passively monitoring users' traffic and utilizing per-app models mapping various network quality of service (QoS) metrics to the application performance.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146014/1/ashnik_1.pd