M
Masakiyo Miyazawa
Researcher at Tokyo University of Science
Publications - 146
Citations - 2275
Masakiyo Miyazawa is an academic researcher from Tokyo University of Science. The author has contributed to research in topics: Stationary distribution & Queueing theory. The author has an hindex of 23, co-authored 143 publications receiving 2161 citations. Previous affiliations of Masakiyo Miyazawa include University of the Sciences & University of Tokyo.
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Queueing networks- customers, signals, and product form solutions
TL;DR: The development of queueing network theory and its applications have become intimately connected with performance analysis of complex systems in Computer and Communication Sciences, both at the hardware and software levels.
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Reflecting Brownian Motion in Two Dimensions: Exact Asymptotics for the Stationary Distribution
Jim Dai,Masakiyo Miyazawa +1 more
TL;DR: In this article, a two-dimensional semimartingale reflecting Brownian motion (SRBM) in the nonnegative quadrant is considered, and the authors show that for a given direction, the marginal tail distribution has the exact asymptotic of the form bxκ exp(−αx) as x goes to infinity, where α and b are positive constants and κ takes one of the values −3/2, −1/2 or 0, or 1.
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The stationary tail asymptotics in the GI/G/1-type queue with countably many background states
TL;DR: In this paper, the authors considered the asymptotic behavior of the stationary tail probabilities in the discrete-time GI/G/1-type queue with countable background state space.
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Tail Decay Rates in Double QBD Processes and Related Reflected Random Walks
TL;DR: This work solves the problem of the tail decay behavior of the stationary distribution of the double QBD process in the coordinate directions and that of its marginal distributions using the matrix analytic method.
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The derivation of invariance relations in complex queueing systems with stationary inputs
TL;DR: In this article, a method of obtaining invariance relations in complex systems by using the theory of point processes is discussed, and new formulae are given for obtaining them generally, and in particular in many-stage models such as tandem and network queues.