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(4)
Probability Density Function
Random Variable
Scheduling Algorithm
Uniform Distribution
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Biasing Effects in Schedulability Measures
Biasing Effects in Schedulability Measures,10.1109/ECRTS.2004.7,Enrico Bini,Giorgio C. Buttazzo
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Biasing Effects in Schedulability Measures
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Citations: 39
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Enrico Bini
,
Giorgio C. Buttazzo
The performance of a schedulabilty test is typically eval uated by generating a huge number of synthetic task sets and then computing the fraction of those that pass the test with respect to the total number of feasible ones. The result ing ratio, however, depends on the metrics used for evaluat ing the performance and on the method for generating ran dom task parameters. In particular, an important factor that affects the overall result of the simulation is the
probability density function
of the random variables used to generate the task set parameters. In this paper we discuss and compare three different metrics that can be used for evaluating the performance of schedulability tests. Then, we investigate how the ran dom generation procedure can bias the simulation results of some specific scheduling algorithm. Finally, we present an efficient method for generating task sets with
uniform distribution
in a given space, and show how some intuitive solutions typically used for task set generation can bias the simulation results.
Conference:
Euromicro Conference on RealTime Systems  ECRTS
, pp. 196203, 2004
DOI:
10.1109/ECRTS.2004.7
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Citation Context
(32)
...Several task set generation algorithms are discussed in [
10
]...
...An efficient method for generating task sets is UUnifast algorithm [
10
] which generates utilization values having uniform distribution...
...It keeps generating sum of ni random values, where i varies from 1 to n1, and sets Ui as the difference between the previous sum and the generated sum [
10
]...
A. Arya Paul
,
et al.
Reducing the Number of Context Switches in Real Time Systems
...For each utilization value Ui = i m where i2 [0:025; 0:05;:::; 0:975], we randomly generate a set of tasksets for which the utilization U( ) = Ui. The generation of the taskset is based on the algorithm UUnifast [
17
]...
Frederic Fauberteau
,
et al.
Laxitybased restrictedmigration scheduling
...While several algorithms for task generation have been proposed ([1],[
2
],[6]), we are not aware of a library or software package dedicated to task generation...
...Tasks can be generated by combining task periods with execution times, randomly or based on certain algorithms like the ‘UUniFast ‘algorithm [
2
] • Schedulability Tests: Several schedulability tests for different execution models have been developed over the past several years, like the popular schedulability test of Liu and Layland’s [7] and Bini et al [3] • Satisfiability Tests: Under satisfiability condition we allow researchers to ...
Chaitanya Belwal
,
et al.
An Extensible Framework for RealTime Task Generation and Simulation
...Schedulability versus utilization: For schedulability curves with respect to the utilization, we first generated a random set of task utilizations ui with UUniFast [
19
], [20]...
...pi , we considered a processor utilization of 40% (i.e., U = 0.4) and used UUniFast [
19
], [20] to obtain a set of task utilizations ui. Again, the periods were obtained with a uniform distribution in [0,1] and the execution times were computed just as before ei = uipi...
Alejandro Masrur
,
et al.
NearOptimal ConstantTime Admission Control for DM Tasks via Nonunif...
...UUniFast algorithm, described in [
5
], was used to generate each set of n tasks with individual utilizations uniformly distributed with a given total utilization Utot...
Marko Bertogna
,
et al.
Preemption Points Placement for Sporadic Task Sets
References
(17)
The Space of Rate Monotonic Schedulability
(
Citations: 32
)
Enrico Bini
,
Giorgio C. Buttazzo
Conference:
IEEE RealTime Systems Symposium  RTSS
, pp. 169178, 2002
Rate Monotonic Scheduling: The Hyperbolic Bound
(
Citations: 13
)
C Giorgio
,
M Giuseppe
Journal:
IEEE Transactions on Computers  TC
, 2003
New Strategies for Assigning RealTime Tasks to Multiprocessor Systems
(
Citations: 120
)
Almut Burchard
,
Jörg Liebeherr
,
Oh Yingfeng
,
Sang Hyuk Son
Journal:
IEEE Transactions on Computers  TC
, vol. 44, no. 12, pp. 14291442, 1995
Rate Monotonic vs. EDF: Judgment Day
(
Citations: 82
)
Giorgio C. Buttazzo
Conference:
International Workshop on Embedded Systems  EMSOFT
, pp. 6783, 2003
Utilization bound revisited
(
Citations: 26
)
Deji Chen
,
Aloysius K. Mok
,
TeiWei Kuo
Journal:
IEEE Transactions on Computers  TC
, vol. 52, no. 3, pp. 351361, 2003
Sort by:
Citations
(39)
Platformaware bandwidthoriented energy management algorithm for realtime embedded systems
Mauro Marinoni
,
Mario Bambagini
,
Francesco Prosperi
,
Francesco Esposito
,
Gianluca Franchino
,
Luca Santinelli
,
Giorgio Buttazzo
Conference:
Emerging Technologies and Factory Automation  ETFA
, pp. 18, 2011
Reducing the Number of Context Switches in Real Time Systems
A. Arya Paul
,
B. Anju S. Pillai
Conference:
International Conference on Process Automation, Control and Computing  PACC
, 2011
Laxitybased restrictedmigration scheduling
Frederic Fauberteau
,
Serge Midonnet
,
Laurent George
Conference:
Emerging Technologies and Factory Automation  ETFA
, pp. 18, 2011
An Extensible Framework for RealTime Task Generation and Simulation
Chaitanya Belwal
,
Albert M. K. Cheng
Conference:
RealTime Computing Systems and Applications  RTCSA
, vol. 1, pp. 259263, 2011
NearOptimal ConstantTime Admission Control for DM Tasks via Nonuniform Approximations
Alejandro Masrur
,
Samarjit Chakraborty
Conference:
RealTime and Embedded Technology and Applications, IEEE Symposium  RTAS
, pp. 5767, 2011