This paper describes the AutoQoS mechanism, which improves the timeliness of disk accesses for multimedia applications without requiring any explicit information about their constraints. Multimedia applications typically have periodic time constraints, meaning that they must complete data processing at periodic intervals in order to function correctly. This requirement extends to the disk system, because the application must access data on time in order to meet deadlines. By using Quality of Service algorithms for disk services, an application may receive enough bandwidth and isolation from other disk accesses to read data on time. Nevertheless, past approaches are restrictive because they require that disk bandwidth or deadlines be known and specified in advance. Our system infers from I/O behavior the bandwidth requirement of multimedia streams, and automatically adjusts allocations in order to provide Quality of Service without knowing the constraints or requiring intervention from the application.
It is common to run multimedia and other periodic, soft real-time applications on general-purpose computer systems. These systems use best-effort scheduling algorithms that cannot guarantee applications will receive responsive scheduling to meet deadline or timing requirements. We present a simple mechanism called Missed Deadline Notification (MDN) that allows applications to notify the system when they do not receive their desired level of responsiveness. Consisting of a single system call with no arguments, this simple interface allows the operating system to provide better support for soft real-time applications without any a priori information about their timing or resource needs. We implemented MDN in three different schedulers: Linux, BEST, and BeRate. We describe these implementations and their performance when running real-time applications and discuss policies to prevent applications from abusing MDN to gain extra resources.
Algorithms for allocating CPU bandwidth to soft real-time processes exist, yet best-effort scheduling remains an attractive model for both application developers and users. Best-effort scheduling is easy to use, provides a reasonable trade-off between fairness and responsiveness, and imposes no extra overhead for specifying resource demands. However, best-effort schedulers provide no resource guarantees, limiting their ability to support processes with timeliness constraints. Reacting to the need for better support of soft real-time multimedia applications while recognizing that the best-effort model permeates desktop computing for very good reasons, we have developed BEST, an enhanced best-effort scheduler that combines desirable aspects of both types of computing. BEST provides the well-behaved default characteristics of best-effort schedulers while significantly improving support for periodic soft real-time processes. BEST schedules using estimated deadlines based on the dynamically detected periods of processes exhibiting periodic behavior, and assigns pseudo-periods to non-periodic processes to allow for good response time. This paper discusses the BEST scheduling model and our implementation in Linux and presents results demonstrating that BEST outperforms the Linux scheduler in handling soft real-time processes, outperforms real-time schedulers in handling best-effort processes, and sometimes outperforms both, especially in situations of processor overload.
The complexity and congestion of current transportation systems often produce traffic situations that jeopardize the safety of the people involved. These situations vary from maintaining a safe distance behind a leading vehicle to safely allowing a pedestrian to cross a busy street. Environmental sensing plays a critical role in virtually all of these situations. Of the sensors available, vision sensors provide information that is richer and more complete than other sensors, making them a logical choice for a multisensor transportation system. In this paper we present robust techniques for intelligent vehicle-highway applications where computer vision plays a crucial role. In particular, we demonstrate that the controlled active vision framework can be utilized to provide a visual sensing modality to a traffic advisory system in order to increase the overall safety margin in a variety of common traffic situations. We have selected two application examples, vehicle tracking and pedestrian tracking, to demonstrate that the framework can provide precisely the type of information required to effectively manage the given situation.
Conventional fieldable signal processing systems utilize custom hardware manufactured
and configured specifically for a single signal processing application. Developing new
systems or reconfiguring existing systems involves great expense and time expenditure.
We at Alliant Techsystems have developed a signal processing system based on
commercially available hardware which is completely software programmable and yet small
and fast enough to be used in fieldable multisensor signal processing applications. This
paper will discuss Alliant's reconfigurable signal processing system.
Conference Committee Involvement (4)
Multimedia Computing and Networking 2009
19 January 2009 | San Jose, California, United States
Multimedia Computing and Networking 2006
18 January 2006 | San Jose, California, United States
Multimedia Computing and Networking 2005
19 January 2005 | San Jose, California, United States
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