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Summary: “We analyze the probabilistic variation of the multicom- modity discrete network design problem named the probabilistic network design problem in which the commodities are generated probabilistically ... methods for constructing the a priori network both in the worst case model and in the probabilistic model. ...
Automation and Remote Control
On the whole, the statements in this section permit us to inference that approximation 4 also best suits networks obeying nonexponential laws of distribution. ... queue length at some nodes of the network. ...
We illustrate this algorithm on examples used in teaching probabilistic models, computational cognitive science research, and game theory. ... We solve these equations by fixed-point iteration in topological order. ... While the queue is not empty, the algorithm takes the first task in the queue and evaluates the function call f (). ...arXiv:1206.3555v2 fatcat:vxso33pvgngw3gpbr6gvi73uae
We present probabilistic neural programs, a framework for program induction that permits flexible specification of both a computational model and inference algorithm while simultaneously enabling the use ... Probabilistic neural programs combine a computation graph for specifying a neural network with an operator for weighted nondeterministic choice. ... As with probabilistic programs, various inference algorithms can be applied to a sketch. ...arXiv:1612.00712v1 fatcat:mffogftuwzg47mqo3imqvdnnrm
Based on simulation results, the proposed method is capable of adjusting the available bandwidth by tuning the queue length, and provides a stable queue in the network. ... In this study, a data portal is considered as an application-based network, and a cognitive method is proposed to deal with congestion in this kind of network. ... During this step, the collected information in the observation phase is used by the Bayesian network model to build a probabilistic structure to predict variations of queue length. ...doi:10.4236/ijcns.2012.58058 fatcat:jkw6s7plozc6lpx5wllh6e67uq
Lecture Notes in Computer Science
Delay-based TCP CC algorithms infer congestion from delay measurements and tend to keep queue lengths low. ... improved tolerance of non-congestion related losses (86 % better goodput than NewReno in the presence of 1 % packet losses). ... Acknowledgments This work was made possible in part by a grant from the Cisco University Research Program Fund at Community Foundation Silicon Valley. ...doi:10.1007/978-3-642-20798-3_25 fatcat:cvkbhvbuhne6vfv5repqio5sfi
Abductive inference in Bayesian belief networks, also known as most probable explanation (MPE) or finding the maximum a posterior instantiation (MAP), is the task of finding the most likely joint assignment ... to all of the (nonevidence) variables in the network. ... In  , it has been shown that abductive inference in Bayesian belief networks is NP-hard. ...doi:10.1109/scis-isis.2012.6505074 dblp:conf/scisisis/PillaiS12 fatcat:uqkftqygwrb6xjoppwuqh6vgly
Lecture Notes in Computer Science
Finally, we illustrate how the proposed tool takes benefit from probabilistic inference techniques by empowering the BPT with its equivalent factor graph. ... The relevance of GraphBPT is illustrated in the context of image segmentation. ... A demonstration of empowering BPTs with probabilistic inference. ...doi:10.1007/978-3-319-18720-4_26 fatcat:ei4b5tm22bdmvnsvadxjorngpi
This paper proposes an automated four-stage data processing pipeline which takes as input raw high-precision location tracking data and which outputs a queueing network model of customer flow. ... We evaluate our method's effectiveness and accuracy in four experimental case studies. ... Together, these yield a parameterised queueing network model of the real-life system. ...doi:10.7148/2009-0664-0672 dblp:conf/ecms/HorngDJK09 fatcat:sbzgrke7izbtdntuu5367xpb74
This is an annotated bibliography on estimation and inference results for queues and related stochastic models. ... A single paper may appear in several categories simultaneously. The final section lists all works in chronological order along with short descriptions of the contributions. ... Mandjes and Żuraniewski  : Develops queueing-based procedures to (statistically) detect overload in communication networks, in a setting in which each connection consumes roughly the same amount ...arXiv:1701.08338v1 fatcat:57wwewuifndblp7aqkmf6l2aim
Queues with combined arrivals and departures. Specialized Poisson queues. Non-Possion queues. Queues with priorities for service. Tandem or series queues. Chapter 16: Queueing Theory in Practice. ... PART II: PROBABILISTIC MODELS. Chapter 11: Data Representation in Operations Research. Nature of data in OR. Forecasting techniques. Chapter 12: Decision Theory and Games. Decisions under risk. ... Chapter 7: Order Statistics in Statistical Inference. Introduction. Types of order statistics data. Order statistics and sufficiency. Maximum-likelihood estimation. ...doi:10.1016/0166-218x(93)90030-r fatcat:ss6bl44ckvh63gsk22rycr44ja
Routers are responsible for performing the direction of network traffic over the internet Congestion control mechanisms provide a better way of handling network congestion. ... The rapid growth and increased communications over internet has also increased the demand for an effective and efficient communication over the network. ... Unlike traditional queue management algorithms that drops packets when the buffer is insufficient to handle the arriving packets RED drops packets probabilistically. ...doi:10.35940/ijitee.f4054.049620 fatcat:kulg47m7jjbhjinwyx3wew2rha
Summary: “We prove several basic combinatorial identities and use them in two applications: the queue inference engine (QIE) and earliest due date rule (EDD) scheduling. R. C. ... In heavy traffic the queueing network can be successfully ap- proximated by a diffusion process, in this case a multidimensional reflected Brownian motion (RBM). ...
Delay-based TCP variants continue to attract a large amount of attention in the networking community. ... Potentially, they offer the possibility to efficiently use network resources while at the same time achieving low queueing delay and virtually zero packet loss. ... ACKNOWLEDGEMENT This work was supported by the SFI grant 07/IN.1/I901. ...doi:10.1109/tnet.2011.2159736 fatcat:onbiuyrnxnaozlib3eyxsfjr7e
2008 5th International Conference on Networked Sensing Systems
In this paper, we report our prototype of probabilistic inference engine that can detect contexts of individual pedestrian and groups of pedestrians. ... Index Terms-distributed camera system, stereo vision, realtime context analysis, pedestrian context, bayesian network model. ... The context inference by Bayesian Networks requires the heaviest processing load in our system. ...doi:10.1109/inss.2008.4610910 fatcat:pg3mq5zzurbdlmrkk3fmymbb7i
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