Simulation of User-Driven Computer Behaviour

نویسندگان

  • Hårek Haugerud
  • Sigmund Straumsnes
چکیده

We simulate a computer system by modeling its users as individuals who have separate needs for resources like processes and login time. During the simulations the users make decisions with probabilities which depends on the time of day and on the character of the user. This makes us able to reproduce the large scale behavior measured at real computer systems as well as predicting the behavior of systems when varying the number and characters of the users.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Data-driven Method for Crowd Simulation using a Holonification Model

In this paper, we present a data-driven method for crowd simulation with holonification model. With this extra module, the accuracy of simulation will increase and it generates more realistic behaviors of agents. First, we show how to use the concept of holon in crowd simulation and how effective it is. For this reason, we use simple rules for holonification. Using real-world data, we model the...

متن کامل

CONTROL OF CHAOS IN A DRIVEN NON LINEAR DYNAMICAL SYSTEM

We present a numerical study of a one-dimensional version of the Burridge-Knopoff model [16] of N-site chain of spring-blocks with stick-slip dynamics. Our numerical analysis and computer simulations lead to a set of different results corresponding to different boundary conditions. It is shown that we can convert a chaotic behaviour system to a highly ordered and periodic behaviour by making on...

متن کامل

Evaluation and Ranking of Discrete Simulation Tools

In studying through simulation, choosing an appropriate tool/language would be a difficult task because many of them are available. On the other hand, few research works focus on evaluation of simulation tools/languages and their comparison. This paper makes a couple of evaluations and ranks more than fifty simulation tools that are currently available. The first evaluation and ranking is in th...

متن کامل

Increasing the Accuracy of Recommender Systems Using the Combination of K-Means and Differential Evolution Algorithms

Recommender systems are the systems that try to make recommendations to each user based on performance, personal tastes, user behaviors, and the context that match their personal preferences and help them in the decision-making process. One of the most important subjects regarding these systems is to increase the system accuracy which means how much the recommendations are close to the user int...

متن کامل

A NOVEL FUZZY-BASED SIMILARITY MEASURE FOR COLLABORATIVE FILTERING TO ALLEVIATE THE SPARSITY PROBLEM

Memory-based collaborative filtering is the most popular approach to build recommender systems. Despite its success in many applications, it still suffers from several major limitations, including data sparsity. Sparse data affect the quality of the user similarity measurement and consequently the quality of the recommender system. In this paper, we propose a novel user similarity measure based...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2001