On Stochastic Bounds for Monotonic Processor Sharing Networks
نویسندگان
چکیده
منابع مشابه
Stochastic Neural Networks with Monotonic Activation Functions
We propose a Laplace approximation that creates a stochastic unit from any smooth monotonic activation function, using only Gaussian noise. This paper investigates the application of this stochastic approximation in training a family of Restricted Boltzmann Machines (RBM) that are closely linked to Bregman divergences. This family, that we call exponential family RBM (Exp-RBM), is a subset of t...
متن کاملStochastic Bounds for Fast Jackson Networks
We consider a Jackson-type network, each of whose nodes contains N identical channels with a single server. Upon arriving at a node, a task selects m of the channels at random, and enters the one with the shortest queue. We provide stochastic bounds for the distribution of the state of the network in terms of the behaviour of independent nodes of the same type. The bounds are asymptotically tig...
متن کاملUnstructured peer-to-peer networks for sharing processor cycles
Motivated by the needs and success ofprojects such as SETI@llOme and genome@home, we propose an architecturefor a sustainable large-scale peer-to-peer environment for distributed cycle sharing among Internet hosts. Such networks are characterized by highly dynamic state due to high arrival and departure rates. This makes it difficult to build and maintain structured networks and to use statebas...
متن کاملFuzzy completion time for alternative stochastic networks
In this paper a network comprising alternative branching nodes with probabilistic outcomes is considered. In other words, network nodes are probabilistic with exclusive-or receiver and exclusive-or emitter. First, an analytical approach is proposed to simplify the structure of network. Then, it is assumed that the duration of activities is positive trapezoidal fuzzy number (TFN). This paper com...
متن کاملClosed-Form Deterministic End-to-End Performance Bounds for the Generalized Processor Sharing Scheduling Discipline
The Generalized Processor Sharing (GPS) scheduling discipline is an important scheduling mechanism that can support both class isolation and bandwidth sharing among different service classes, thus making it an appealing choice for networks providing multiple services with Quality-of-Service guarantees. In this paper, we study a broad class of GPS networks known as Consistent Relative Session Tr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Queueing Systems
سال: 2004
ISSN: 0257-0130
DOI: 10.1023/b:ques.0000032802.41986.c6