Towards a formal model of volunteer computing systems

Author(s):  
Yu Wang ◽  
Haiwu He ◽  
Zhijian Wang
Author(s):  
Stefania Bandini ◽  
Gianluca Colombo ◽  
Alessandro Mosca ◽  
Matteo Palmonari

Pervasive Computing systems are characterized by possibly mobile components distributed in the environment and are devoted to collect, process and manage information in order to support users in different kind of activities. High-level correlation of information in such context can be defined, exploiting a formal model arising from the spatial disposition of information sources, as a form of commonsense spatial reasoning. With respect to this model, a Hybrid Logic to formalize commonsense spatial reasoning in these context has been defined. Here, on the basis of relevant analogies among Pervasive Computing and human practice in handling spatial knowledge, we suggest to provide the term “commonsense” with a positive meaning, showing that our logical framework captures some features of non-mathematical reasoning when spatially qualified information is concerned. The focus on such features and the analogies mentioned above suggest to qualify our approach to (commonsense) spatial reasoning as an informational approach.


2018 ◽  
Vol 14 (1) ◽  
pp. 35-62 ◽  
Author(s):  
Abdeldjalil Ledmi ◽  
Hakim Bendjenna ◽  
Hemam Sofiane Mounine

This article describes how in volunteer cloud computing systems, some resources are volunteered by the hosts. These systems became more powerful and attractive because they provide a highest power computing. However, to satisfy the user requirements and the system performance in this kind of the system is a crucial challenge. In this article, the authors propose a new architecture for the volunteer cloud computing systems to allow balancing the load between volunteer clouds in a decentralized manner, and between resources inside a volunteer cloud in centralized manner. Moreover, their proposal shows more advantages: First, selecting a resource according to the user requirements and to the system performance. Second, estimating the volunteer resource failure probability by using the stochastic process Markov chain model. Experimental results using the PeerSim Simulator is established to verify the efficacy of the proposed system and promising results are obtained.


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