S. Brandt and G. Nutt, "A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage," IEEE Real-Time Systems Symposium, Dec 1998.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....to the design of computing systems. For example, several papers [2] 9] 14] 15] 20] 34] 36] presented adaptive CPU scheduling techniques to improve digital control system performance. These techniques are tailored to the specific characteristics of digital control systems. Several other papers [4][13][31] 32] 35] presented adaptive QoS management architectures for computing systems such as multimedia and communication systems. These solutions are mostly concerned with absolute metrics such as deadline miss ratio and CPU bandwidth utilizations rather than relative delays. In [1] a least ....

S. Brandt and G. Nutt, "A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage," IEEE Real-Time Systems Symposium, Dec 1998.

....adjusts the rates of method invocations on remote application objects, based on measured performance feedback. Our choice of this adaptation mechanism is motivated by the fact that in many DRE applications, e.g. digital feedback control loops [5] 22] sensor data display, and video streaming [3], task rates can be adjusted on line without causing instability or system failure. Other QoS adaptation mechanisms such as online task admission control can also be incorporated easily into the FCS nORB service. Specifically, this paper makes three main contributions: Design documentation of a ....

S. Brandt and G. Nutt, "A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage," IEEE Real-Time Systems Symposium, December 1998.

....QoS adaptation. However, their optimization algorithms assume that the resource requirement of every QoS level is a priori known. In contrast, our FCS framework provides performance guarantees even when the resource requirements are unknown or deviate from the estimations. Several other works [8][21][25] 78] developed feedback based adaptation algorithms that do not depend on completely accurate knowledge about workloads. However, their feedback loops were based on heuristics and they did not establish time domain analysis on the efficiency of QoS adaptation in response to runtime variations. ....

....software applications, components, and device drivers when accurate information on their execution time and invocation rates is 46 unavailable. A motivation for applying FCS framework to real time CPU scheduling is the observation that many existing feedback based scheduling algorithms [8][21][25] are based on heuristics rather than a theoretical foundation. These algorithms often depend on laborious design tuning testing iterations, and may still fail to handle unexpected or untested conditions at run time. While the design methodology for automatic feedback control systems has been ....

S. Brandt and G. Nutt, "A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage," IEEE Real-Time Systems Symposium, December 1998.

....Failure to meet performance guarantees may result in Supported in part by NSF grants CCR 9901706 and EIA9900895, and contract IJRP 9803 6 from the Ministry of Information and Communication of Korea. loss of customers, financial damage, or liability violations. Adaptive real time systems [1 8, 12, 13, 1719, 20, 23, 26] have been developed as a promising approach to achieve performance guarantees in unpredictable environments. While early research on real time computing was concerned with guaranteeing complete avoidance of undesirable effects such as overload and deadline misses, adaptive real time systems are ....

....transient response settles. Several research efforts addressed the characterization and improvement of dynamic behavior of real time systems. For example, Rosu et al. 20] proposed a set of performance metrics to capture the transient responsiveness and the steady sate impact of adaptations. In [8], Brandt, et al. evaluated a dynamic QoS manager by measuring the transient performance of applications in response to QoS adaptations. However, to the authors knowledge, no unified framework exists to date for designing an adaptive system from performance specifications of desired dynamic ....

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S. Brandt and G. Nutt, "A dynamic quality of service middleware agent for mediating application resource usage," 19 th 1EEE Real-Time Systems Symposium, December 1998.

....systems. In this report, we consider using the best effort model to support applications with periodic deadlines. Previous research on the Dynamic QoS Level Resource Management (DQM) system demonstrates that it is possible to robustly execute soft real time applications on best effort systems [6, 7, 8]. This system uses a middleware framework that allows applications to dynamically adjust their resource usage based on the available resources. By adjusting resource usage such that the set of running applications use less than 100 of the available resources, a best effort scheduler is able to ....

Scott Brandt, Gary Nutt, Toby Berk, and James Mankovichr. A dynamic quality of service middleware agent for mediating application resource usage. In Proceedings of the 19th IEEE Real-Time Systems Symposium (RTSS 1998.

....layers above [31,38] 2.3. Predictability and Adaptability Underlying all of these considerations is the fundamental challenge of coping with the uncertainty of synchrony. In principle, this can be achieved by adaptation. However, while there is an increasing body of research on QoS adaptation [4,5,6], most work has focused on protocol or application level heuristics, and does not provide any guarantees on how well the system adapts. The applications we intend to support require predictability about timeliness. This means that even if the timeliness of the system is degrading, it should do so ....

Scott Brandt, Gary Nutt, Toby Berk and James Mankovich. A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage. Proceedings of the 19th IEEE Real-Time Systems Symposium. pp.307-317. Madrid, Spain. Dec 1998.

....nodes, yield high CPU utilization, and promptly react to load change. 5. Performance Evaluation with Previous Known Algorithms To further evaluate the performance of DFCS, we compare NCLOSE with two other well known scheduling algorithms, QoS negotiation [1] and Dynamic QoS Management (DQM)[4]. We first present a brief summary of these two algorithms. QoS Negotiation: The task model in QoS negotiation is similar to our current task model. A distributed system is assumed in which tasks can arrive at any node. There are several QoS levels for each task. These levels are specified upon ....

....as a primary mechanism to adjust resource allocation in the absence of a priori knowledge of resource supply and demand. This is in contrast to early optimization based QoS adaptation techniques that assumed accurate models of application resource requirements. Examples of such approaches include [4][7] In [7] a transaction scheduler called AED monitors the system deadline miss ratio and adjusts task priorities to improve the performance of EDF in overload. The DQM algorithm [4] features a feedback mechanism that changes task QoS levels according to the sampled CPU utilization or deadline ....

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S.Brandt and G.Nutt. A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage. In Real-Time Systems Symposium, pages 307--317, Madrid, Spain,December 1998.

....a hierarchical adaptation model for complex real time systems and algorithms for optimizing multi dimensional adaptation cost. An end to end QoS model is presented in [32] in the context of a middleware approach to QoS management that requires application cooperation. The approach is extended in [21] to account for practical limitations such as inaccuracies in estimating application resource requirements. These architectures, however, generally required a rather detailed model of the application, which may not be available for web servers. Operating systems support for server QoS has been ....

....and resource containers [15] In contrast, we develop a resource management architecture in middleware which can run on top of any standard operating system, thereby creating a more portable solution. Our work [5, 6, 3, 40] differs from prior approaches to middleware resource management, such as [21] in that it offers performance guarantees that are based on well understood theoretical foundations derived from feedback control theory. Recently, there has been a lot of resurgent interest in control theory as a vehicle for performance control in distributed computing systems. For example, in ....

S. Brandt and G. Nutt. A dynamic quality of service middleware agent for mediating application resource usage. In Real-Time Systems Symposium, pages 307--317, Madrid, Spain, December 1998.

....a hierarchical adaptation model for complex real time systems and algorithms for optimizing multi dimensional adaptation cost. An end to end QoS model is presented in [17] in the context of a middleware approach to QoS management that requires application cooperation. The approach is extended in [9] to account for practical limitations such as inaccuracies in estimating application resource requirements. In [14] a dynamic distillation method is proposed to adapt to network and client variability via on line compression techniques. In the multimedia community several systems were described ....

S. Brandt and G. Nutt. A dynamic quality of service middleware agent for mediating application resource usage. In Real-Time Systems Symposium, pages 307--317, Madrid, Spain, December 1998.

....[12] proposes various extensions to standard CORBA components and services, in order to support adaptation, delegation and renegotiation services to shield QoS variations. The work applies particularly in the case of remote method invocations to objects over a wide area network. The work noted in [2] builds a series of middleware level agent based services, collectively referred to as Dynamic QoS Resource Manager, that dynamically monitors system and application states and switches execution levels within a computationally intensive application. These switching capabilities maximize the ....

S. Brandt, G. Nutt, T. Berk, and J. Mankovich. A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage. In Proceedings of 19th IEEE RealTime Systems Symposium, pages 307--317, Dec. 1998.

....be applied when the QoS mapping profiles (used to map the QoS specification to resource usage) are unknown. In this case, we believe that the only way to control the QoS experienced by each task is to use some form of feedback (implicitly reconstructing the QoS mapping profiles on line) In [5], the authors present a feedback based QoS manager, DQM, which does not require any support from the operating system. DQM is a middleware solution aimed at supporting soft real time applications in a conventional OS (Linux) The DQM middleware can change some applications execution level based ....

S. Brandt, G. Nutt, T. Berk, and J. Mankovich. A dynamic quality of service middleware agent for mediating application resource usage. In Proceedings of the IEEE Real Time Systems Symposium, December 1998.

....[1] proposes various extensions to standard CORBA components and services, in order to support adaptation, delegation and renegotiation services to shield QoS variations. The work applies particularly in the case of remote method invocations to objects over a wide area network. The work noted in [13] builds a series of middleware level agent based services, collectively referred to as Dynamic QoS Resource 13 Manager, that dynamically monitors system and application states and switches execution levels within a computationally intensive application. These switching capabilities maximize the ....

S. Brandt, G. Nutt, T. Berk, and J. Mankovich, "A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage," in Proceedings of 19th IEEE Real-Time Systems Symposium, Dec. 1998, pp. 307--317. 15

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S. Brandt, G. Nutt, T. Berk, and J. Mankovich. A dynamic quality of service middleware agent for mediating application resource usage. In Proceedings of IEEE Real-Time Systems Symposium (RTSS '98), pages 307--317, December 1998.

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S. Brandt, G. Nutt, T. Berk, and J. Mankovichr. A dynamic quality of service middleware agent for mediating application resource usage. In Proceedings of the 19th IEEE RealTime Systems Symposium (RTSS 1998.

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S. Brandt, G. Nutt, T. Berk, and J. Mankovich. A dynamic quality of service middleware agent for mediating application resource usage. In Proceedings of IEEE Real-Time Systems Symposium (RTSS 1998.

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S. Brandt, G. Nutt, T. Berk, and J. Mankovich, \A dynamic quality of service middleware agent for mediating application resource usage," in Proceedings of the 19th IEEE Real-Time Systems Symposium, pp. 307-317, Dec. 1998.

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S. Brandt and G. Nutt, "A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage," IEEE Real-Time Systems Symposium, Dec 1998.

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S. Brandt, G. Nutt, T. Berk, and J. Mankovich, "A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage," Proc. IEEE Real-Time Systems Symp., pp. 307-317, Dec. 1998.

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Scott Brandt, Gary Nutt, Toby Berk, and James Mankovich. A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage. In 19th IEEE Real-Time Systems Symposium, December 1998.

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S. Brandt, G. Nutt, T. Berk, and J. Mankovich, "A dynamic quality of service middleware agent for mediating application resource usage, " in Proceedings of the 19th IEEE Real-Time Systems Symposium (RTSS '98), Madrid, Spain, Dec. 1998, pp. 307--317.

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S. Brandt, G. Nutt, T. Berk, and J. Mankovich, "A dynamic quality of service middleware agent for mediating application resource usage, " in Proceedings of the 19th IEEE Real-Time Systems Symposium (RTSS '98), Madrid, Spain, Dec. 1998, pp. 307--317.

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S. Brandt, G. Nutt, T. Berk, and J. Mankovich, "A dynamic quality of service middleware agent for mediating application resource usage, " in Proceedings of the 19th IEEE Real-Time Systems Symposium (RTSS '98), Madrid, Spain, Dec. 1998, pp. 307--317.

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S. Brandt, G. Nutt, et al., "A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage," Proceedings of the IEEE Real-Time Systems Symposium, pp. 307-317, December 1998.

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S. Brandt, G. Nutt, et al., "A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage," Proceedings of the IEEE Real-Time Systems Symposium, pages 307-317, December 1998.

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S. Brandt and G. Nutt, "A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage," IEEE Real-Time Systems Symposium, December 1998.

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