C. Lee, J. Lehoezky, R. Rajkumar, and D. Siewiorek. On quality of service optimization with discrete QoS options. In Proceedings of the 5th Real-Time Technology and Applications Symposium (RTAS), 1999.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....di#erence between utility measurement and utility formulation. Another challenge related to video utility measurement is the 11 lack of online utility measurement methods that can operate at network adaptation time scales. Previous work on video utility measurement is based on o# line procedures [87, 66, 106, 65]. Online utility measurement methods [15] on the other hand, generate utility functions over very short time intervals (e.g. tens of milliseconds for each video frame) due to the scene changes associated with video flows. Network adaptation, however, typically operates over much longer intervals ....

....scenario where i C and rewrite the constraint as i=1 x i = C because u i (x i ) is monotonically increasing in x i . The case where i = C is trivially solved by giving u i (x i ) b i . This maximization problem with target functions that are not always concave is an NP hard [66] problem. In the case of convex utility functions, the optimal solution lies at the extreme points of the convex hull with the optimal solution only being found by enumerating through all the possible extreme points. In the Q RAM project [66] various approximation algorithms have been ....

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C. Lee, J. P. Lehoczky, R. Rajkumar, and D. Siewiorek. On Quality of Service Optimization with Discrete QOS Options. In Proc. IEEE Real-time Technology and Applications Symposium, June 1999.

....of the scarceness preciousness of the respective resources, it is able to adapt its resource consumption patterns in order to execute its task accordingly. In this regard, the evaluative nature of the entities is revealed. During decision making, each entity is aware of several resource tradeo#s [LLRS99] so that, the assessment of the respective resources given, it is able to determine the most e#cient way to process its task. The notion of resource assessment may also be applied to the services that are provided to the upper entity. Apparently, this becomes necessary if entities consume added ....

Chen Lee, John Lehoczky, Ragunathan Rajkumar, and Dan Siewiorek. On Quality of Service Optimization with Discrete QoS Options. In IEEE Real Time Technology and Applications Symposium, pages 276-- 285, 1999.

....is proposed in [12] in addition to the mechanism for immediate reservation. One of our next steps is to extend our multi resource reservation framework to support advance reservations. Taking a more theoretical approach, Lee et al. also study the problem of resource allocation for QoS guarantee [13,14]. Particularly, in [13] the problem of apportioning multiple finite resources to satisfy the QoS needs of multiple applications along multiple QoS dimensions is studied. However, their model does not consider multiple service components, which contribute transitively to the end to end QoS of an ....

C. Lee, J. Lehoczky, R. Rajkumar and D. Siewiorek, On quality of service optimization with discrete QoS options, in: Proc. IEEE RealTime Technology and Applications Symposium (RTAS '99) (1999).

....assist multimedia applications in QoS setup and enforcement by utilizing QoS services in networks and operating systems if available, or by providing adaptation services if best effort services exist only. Two major types of QoS middleware systems have been developed: 1) Reservation based Systems [27, 34] get the QoS specifications in the form of system resource requirements, reserve the specified resources and enforce the delivery of requested QoS during runtime; and (2) Adaptation based Systems [6, 4, 29] get the QoS specifications in the form of bounds on resource utilization, ....

C. Lee, J. Lehoczky, R. Rajkumar, and D. Siewiorek. On Quality of Service Optimization with Discrete QoS Options. Proceedings of the IEEE Real-time Technology and Applications Symposium, 1999.

....taking into consideration wireless access networks. The use of utility functions has been widely cited in the literature as a means of capturing application specific behavior in adaptive networking environments (e.g. Internet [17,18] mobile networks [2] and ATM networks [9] The Q RAM project [10] proposes a utility based mechanism that allocates resources to operating system processes with the aim of maximizing the total system utility. Unlike utility maximizing allocation algorithms, which maximize the global utility, our previous work [7] exploits utility fair allocation . This ....

C. Lee, J.P. Lehoczky, R. Rajkumar and D. Siewiorek, On Quality of Service optimization with discrete QoS options, in: Proc. IEEE Realtime Technology and Applications Symposium (June 1999).

....it into and use it as the structuring paradigm for an operating system. And we know of no attempt to use imprecise computations for any other resource than CPU cycles. The problem of expressing and assuring different levels of quality was addressed first by algorithms using time value functions [8, 16, 9]. Such functions express the gained quality depending on of the required resources for that quality. The solutions are of a rather static nature, because the different achievable levels of quality are considered only at admission time of jobs. That means, the solutions do not consider the jitter ....

....and concave functions can be specified. They are used to maximize a global objective with given resources. By defining a minimal required level of quality, the mandatory parts of the imprecise computation model can be emulated. Rajkumar relaxes the assumptions on the time value functions in [9]. He supports discrete QoS operating points which may be obtained by measurements, and are therefore more appropriate than the artificial time value functions. All these solutions utilize the varying execution times of jobs but changing system load is not taken into account. A system adapting to ....

C. Lee, J. Lehoczky, R. Rajkumar, and D. Siewiorek. On quality of service optimization with discrete qos options. In Proceedings of the 20th IEEE Real-Time Systems Symposium, 1999.

....selections over the various elements. While this approach will not (in general) result in the optimal use of available resources, it does seek to satisfy the user s needs, as expressed in their preferences. A more in depth analysis of selection algorithms for resource management is presented in [12]. 4 TESTS AND RESULTS 4.1 Test Environment We chose to simulate a series of network environments, rather than take results from actual network tests. While removing some sense of realism, it provides clearer results without a large scale deployment. Finding a range of typical , or even stable, ....

C. Lee, J. Lehoczky, R. Rajkumar, and D. Siewiorek, "On Quality of Service Optimization with Discrete QoS Options," presented at IEEE Real-time Technology and Applications Symposium, 1999.

....elements by preference, and reinstating utility to the more important elements by preference once resource requirements are met, user satisfaction should be maintained, and consistent behaviour experienced. A more in depth analysis of selection algorithms for resource management is presented in [12]. An illustration of the use of our selection technique is presented in section 4. 3.6 Resource Management and Monitoring For wireless networks, where the underlying QoS is highly variable, monitoring feeds into the network resource models. As a model of effective parameters is built up, the ....

C. Lee, J. Lehoczky, R. Rajkumar, and D. Siewiorek, "On Quality of Service Optimization with Discrete QoS Options," presented at IEEE Real-time Technology and Applications Symposium, 1999.

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C. Lee, J. Lehoezky, R. Rajkumar, and D. Siewiorek. On quality of service optimization with discrete QoS options. In Proceedings of the 5th Real-Time Technology and Applications Symposium (RTAS), 1999.

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C. Lee, J. Lehoczky, R. Rajkumar and D. Siewiorek, On quality of service optimization with discrete QoS options, in: Proceedings of the IEEE Real-Time Technology and Applications Symposium (June 1999).

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C. Lee, J. Lehoezky, R. Rajkumar, and D. Siewiorek. On quality of service optimization with discrete QoS options. In Proceedings of the 5th Real-Time Technology and Applications Symposium (RTAS), 1999.

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Lee C, Lehoczky J, Rajkumar R and Siewiorek D (1999) On quality of service optimization with discrete QoS options. In: Proceedings of the IEEE Real Time Technology and Applications Symposium (RTAS'99), Vancouver, British Columbia, Canada, June 1999

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C. Lee, J. Lehoczky, R. Rajkumar, and D. Siewiorek. On quality of service optimization with discrete qos options. In Proceedings of the IEEE Real-time Technology and Applications Symposium, June 1999.

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C. Lee, J. Lehoczky, R. Rajkumar, and D. Siewiorek, "On Quality of Service Optimization with Discrete QoS Options," Proc. IEEE Real-Time Technology and Applications Symp., pp. 276-286, June 1999.

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C. Lee, J. Lehoczky, R. Rajkumar, and D. Siewiorek. On Quality of Service optimization with discrete QoS options. In Proc. IEEE Real-time Technology and Applications Symposium, Jun. 1999.

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C. Lee, J. Lehoczky, R. Rajkumar, and D. Siewiorek, "On Quality of Service Optimization with Discrete QoS Options," Proceedings of IEEE Real-Time Technology and Applications Symposium (RTAS'99), June 1999. 128

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Lee, C., Lehoczky, J., Rajkumar, R., Siewiorek, D.: On Quality of Service Optimization with Discrete QoS Options. In: IEEE Real Time Technology and Applications Symposium. (1999) 276--285

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C. Lee, J. Lehoczky, R. Rajkumar, and D. Siewiorek. On quality of service optimization with discrete qos options. In Proceedings of the IEEE Real-Time Technology and Applications Symposium. IEEE, June 1999.

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Lee C, Lehoczky J, Rajkumar R and Siewiorek D (1999) On quality of service optimization with discrete QoS options. In: Proceedings of the IEEE Real Time Technology and Applications Symposium (RTAS'99), Vancouver, British Columbia, Canada, June 1999

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C. Lee, R. Rajkumar, J. P. Lehoczky and D. P. Siewiorek. On Quality of Service Optimization with Discrete QoS Options. In Proceedings of the IEEE Real-Time Technology and Applications Symposium, June 1998.

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C. Lee, J. Lehoczky, R. Rajkumar, and D. P. Siewiorek, " On quality of service optimization with discrete QoS options," 5th IEEE Real-Time Technology and Applications Symposium, June 1999, pp. 276-286.

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C. Lee, J. Lehoczky, D. Siewiorek, R. Rajkumar, "On Quality of Service Optimization with Discrete QoS Options," Proceedings of the Fifth IEEE Real-Time Technology and Applications Symposium, pages 276-286, 1999.

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Chen Lee, "On Quality of Service Optimization with Discrete QoS Options," Ph.D. Thesis, Carnegie Mellon University, 1999.

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C. Lee, J. Lehoczky, R. Rajkumar, and D. P. Siewiorek, "On quality of service optimization with discrete QoS options," 5th IEEE Real-Time Technology and Applications Symposium, June 1999, pp. 276-286.

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C. Lee, J. Lehoczky, R. Rajkumar, and D. Siewiorek, "On Quality of Service Optimization with Discrete QoS Options," in Proc. Fifth IEEE Real-Time Technology and Applications Symposium (IEEE Computer Society, Los Alamitos, CA, 1999), pp. 276-286.

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