Applying the GWO Model to Relaxed Collaborative Systems

نویسندگان

  • Constanza Prieto
  • Yadran Eterovic
چکیده

Building collaborative applications is still a challenging task. A collaborative application can be viewed as a class of distributed shared memory system. A distinctive property of these systems is their memory consistency model. In this paper, we argue that there is a relationship between different collaboration styles, on the one hand, and different memory consistency models, on the other. In particular, we propose a practical collaboration style, exemplified by a collaborative electronic organizer, that can be supported by the GWO memory consistency model, a rather relaxed model stricter only than local consistency. The advantage of the proposed style is that it reduces the amount of information that must be exchanged among the processors. Because there have been no propositions of the specific rules— i.e., the protocol—that the processors in a system must follow to implement the GWO model, we also propose a protocol that exactly matches the properties of the model.

برای دانلود 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

DisTriB: Distributed Trust Management Model Based on Gossip Learning and Bayesian Networks in Collaborative Computing Systems

The interactions among peers in Peer-to-Peer systems as a distributed collaborative system are based on asynchronous and unreliable communications. Trust is an essential and facilitating component in these interactions specially in such uncertain environments. Various attacks are possible due to large-scale nature and openness of these systems that affects the trust. Peers has not enough inform...

متن کامل

DisTriB: Distributed Trust Management Model Based on Gossip Learning and Bayesian Networks in Collaborative Computing Systems

The interactions among peers in Peer-to-Peer systems as a distributed collaborative system are based on asynchronous and unreliable communications. Trust is an essential and facilitating component in these interactions specially in such uncertain environments. Various attacks are possible due to large-scale nature and openness of these systems that affects the trust. Peers has not enough inform...

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

A Collaborative Blood Distribution System in a Network of Hospitals based on their Normal and Emergency Requests: a Mathematical Model and Solution

Background and Objectives: A blood distribution network orchestrates distribution of safe blood products to hospitals. Blood shortage and blood wastage are two important factors which may affect efficiency of blood distribution network. Service delivery time is another factor that refers to the time interval between blood request by a hospital and transfusing it to the patient....

متن کامل

A New WordNet Enriched Content-Collaborative Recommender System

The recommender systems are models that are to predict the potential interests of users among a number of items. These systems are widespread and they have many applications in real-world. These systems are generally based on one of two structural types: collaborative filtering and content filtering. There are some systems which are based on both of them. These systems are named hybrid recommen...

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

برای دانلود 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

عنوان ژورنال:
  • Computers and Artificial Intelligence

دوره 24  شماره 

صفحات  -

تاریخ انتشار 2005