A Dynamic Priority Assignment Technique for Streams with (m,k)-Firm Deadlines

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A Dynamic Priority Assignment Technique for Streams with (m,k)-Firm Deadlines (1994)

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by Moncef Hamdaoui , Parameswaran Ramanathan

Venue:	IEEE Transactions on Computers
Citations:	178 - 2 self

Citations

256	Algorithms for scheduling imprecise computations,” - Liu, Yu, et al. - 1991 (Show Context) Citation Context ...s percentage requirement can be met even if a large number of consecutive customers miss their deadlines. Streams with (m; k)-firm deadlines can also be serviced using the imprecise computation model =-=[4,7,6]-=-. In this model, customers are statically classified as either mandatory or optional. Mandatory customers are always serviced. Optional customers are serviced on a best-effort basis. A stream with (m;...
241	Characterizing superposition arrival processes in packet multiplexers for voice and data - Sriram, Whitt - 1986 (Show Context) Citation Context ... durations of the ON and the OFF states are exponentially distributed with averages ON ave and OFF ave , respectively. Such a stream is often used to model a stream of voice samples in a conversation =-=[9,11]-=-. The ON state corresponds to a talkspurt and the OFF state corresponds to a silence period. We first consider the case where all streams in the system have the same timing requirements. We also assum...
139	Scheduling periodic jobs that allow imprecise results - Chung, Liu, et al. - 1990 (Show Context) Citation Context ...s percentage requirement can be met even if a large number of consecutive customers miss their deadlines. Streams with (m; k)-firm deadlines can also be serviced using the imprecise computation model =-=[4,7,6]-=-. In this model, customers are statically classified as either mandatory or optional. Mandatory customers are always serviced. Optional customers are serviced on a best-effort basis. A stream with (m;...
112	RealTime Communication in Packet-Switched Networks,” - Aras, Kurose, et al. - 1994 (Show Context) Citation Context ...their deadlines in a window of k j consecutive customers is increased. To accomplish Streams Server Service Queue Figure 1: System Model this, several different scheduling policies have been proposed =-=[1]-=-. Most of these policies can be abstracted as follows. There is a separate First-In First-Out queue for each stream (see Fig. 1). These queues ensure that customers from a given stream are serviced in...
52	Scheduling policies for real-time and non-real time trac in a statisticalmultiplexer. - Chipalkatti, Kurose, et al. - 1989 (Show Context) Citation Context ...o other work in the literature because of the new model. Many schemes have been proposed to meet a specified maximum allowable loss percentage, where the loss includes customers with missed deadlines =-=[2,3,5,8,10]-=-. As indicated earlier, however, the problem with this model is that the loss percentage requirement can be met even if a large number of consecutive customers miss their deadlines. Streams with (m; k...
47	Survey of traffic control schemes and protocols - Bae, Suda - 1991 (Show Context) Citation Context ...o other work in the literature because of the new model. Many schemes have been proposed to meet a specified maximum allowable loss percentage, where the loss includes customers with missed deadlines =-=[2,3,5,8,10]-=-. As indicated earlier, however, the problem with this model is that the loss percentage requirement can be met even if a large number of consecutive customers miss their deadlines. Streams with (m; k...
17	Congestion control for real-time traffic in high-speed networks - Schulzrinne, Kurose, et al. - 1990 (Show Context) Citation Context ...o other work in the literature because of the new model. Many schemes have been proposed to meet a specified maximum allowable loss percentage, where the loss includes customers with missed deadlines =-=[2,3,5,8,10]-=-. As indicated earlier, however, the problem with this model is that the loss percentage requirement can be met even if a large number of consecutive customers miss their deadlines. Streams with (m; k...
15	Optimal packet discarding: An ATM-oriented analysis model and initial results. - Petr, Frost - 1990 (Show Context) Citation Context ...o other work in the literature because of the new model. Many schemes have been proposed to meet a specified maximum allowable loss percentage, where the loss includes customers with missed deadlines =-=[2,3,5,8,10]-=-. As indicated earlier, however, the problem with this model is that the loss percentage requirement can be met even if a large number of consecutive customers miss their deadlines. Streams with (m; k...
6	Imprecise computations: A means to provide scheduling flexibility and enhance dependability - Liu, Lin, et al. - 1993 (Show Context) Citation Context ...s percentage requirement can be met even if a large number of consecutive customers miss their deadlines. Streams with (m; k)-firm deadlines can also be serviced using the imprecise computation model =-=[4,7,6]-=-. In this model, customers are statically classified as either mandatory or optional. Mandatory customers are always serviced. Optional customers are serviced on a best-effort basis. A stream with (m;...
6	Simulation analysis of a communication link with statistically multiplexed bursty voice sources - Saleh, Habib, et al. - 1993 (Show Context) Citation Context ... durations of the ON and the OFF states are exponentially distributed with averages ON ave and OFF ave , respectively. Such a stream is often used to model a stream of voice samples in a conversation =-=[9,11]-=-. The ON state corresponds to a talkspurt and the OFF state corresponds to a silence period. We first consider the case where all streams in the system have the same timing requirements. We also assum...
4	Congestion control for bursty video traffic in ATM networks - Kubota, Murata, et al. - 1992 (Show Context) Citation Context ...o other work in the literature because of the new model. Many schemes have been proposed to meet a specified maximum allowable loss percentage, where the loss includes customers with missed deadlines =-=[2,3,5,8,10]-=-. As indicated earlier, however, the problem with this model is that the loss percentage requirement can be met even if a large number of consecutive customers miss their deadlines. Streams with (m; k...