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AIPS
2006
15 years 7 months ago
Combining Stochastic Task Models with Reinforcement Learning for Dynamic Scheduling
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...
Malcolm J. A. Strens
P2P
2006
IEEE
153views Communications» more  P2P 2006»
16 years 8 days ago
Internet-Scale Storage Systems under Churn -- A Study of the Steady-State using Markov Models
Content storage in a distributed collaborative environment uses redundancy for better resilience and thus provides good availability and durability. In a peer-to-peer environment,...
Anwitaman Datta, Karl Aberer
TASE
2011
IEEE
14 years 10 months ago
Multiresource Shop Scheduling With Resource Flexibility and Blocking
—This paper proposes a general scheduling model that extends job-shop scheduling models to incorporate important features of real manufacturing systems. More precisely, each oper...
Yazid Mati, Xiaolan Xie
RTSS
2006
IEEE
16 years 8 days ago
An Optimal Real-Time Scheduling Algorithm for Multiprocessors
We present an optimal real-time scheduling algorithm for multiprocessors — one that satisfies all task deadlines, when the total utilization demand does not exceed the utilizat...
Hyeonjoong Cho, Binoy Ravindran, E. Douglas Jensen
GLOBECOM
2006
IEEE
16 years 9 days ago
On the Optimal Scheduling for Media Streaming in Data-driven Overlay Networks
—The Internet has witnessed a rapid growth in deployment of data-driven overlay network (DON) based streaming applications during recent years. In these applications, each nodes ...
Meng Zhang, Yongqiang Xiong, Qian Zhang, Shiqiang ...