Realising Dynamism in MediaSense Publish/Subscribe Model for Logical-Clustering in Crowdsourcing
Journal Title: International Journal of Advanced Research in Artificial Intelligence(IJARAI) - Year 2014, Vol 3, Issue 11
Abstract
The upsurge of social networks, mobile devices, Internet or Web-enabled services have enabled unprecedented level of human participation in pervasive computing which is coined as crowdsourcing. The pervasiveness of computing devices leads to a fast varying computing where it is imperative to have a model for catering the dynamic environment. The challenge of efficiently distributing context information in logical-clustering in crowdsourcing scenarios can be countered by the scalable MediaSense PubSub model. MeidaSense is a proven scalable PubSub model for static environment. However, the scalability of MediaSense as PubSub model is further challenged by its viability to adjust to the dynamic nature of crowdsourcing. Crowdsourcing does not only involve fast varying pervasive devices but also dynamic distributed and heterogeneous context information. In light of this, the paper extends the current MediaSense PubSub model which can handle dynamic logical-clustering in crowdsourcing. The results suggest that the extended MediaSense is viable for catering the dynamism nature of crowdsourcing, moreover, it is possible to predict the near-optimal subscription matching time and predict the time it takes to update (insert or delete) context-IDs along with existing published context-IDs. Furthermore, it is possible to foretell the memory usage in MediaSense PubSub model.
Authors and Affiliations
Hasibur Rahman, Rahim Rahmani, Theo Kanter
Keywords
Related Articles
- EP ID EP110870
- DOI 10.14569/IJARAI.2014.031106
- Views 157
- Downloads 0
For a Better Coordination Between Students Learning Styles and Instructors Teaching Styles
While learning has been in the main focus of a number of educators and researches, instructors’ teaching styles have received considerably less attention. When it comes to dependencies between learning styles and t...
An Empirical Comparison of Tree-Based Learning Algorithms: An Egyptian Rice Diseases Classification Case Study
Applications of learning algorithms in knowledge discovery are promising and relevant area of research. The classification algorithms of data mining have been successfully applied in the recent years to predict Egy...
A Fuzzy Approach to Classify Learning Disability
The endeavor of this work is to support the special education community in their quest to be with the mainstream. The initial segment of the paper gives an exhaustive study of the different mechanisms of diagnosing...
Improving Performance of Free Space Optics Link Using Array of Receivers in Terrible Weather Conditions of Plain and Hilly Areas
Free-space optical (FSO) communication is a cost effective and high data rate access technique, which has been proving itself a best alternative to radio frequency technology. FSO link provides high bandwidth solut...
Trend Analysis of Relatively Large Diatoms Which Appear in the Intensive Study Area of the Ariake Sea, Japan in Winter (2011-2015) based on Remote Sensing Satellite Data
Behavior of relatively large size of diatoms which appear in the Ariake Sea areas, Japan in winter based on remote sensing satellite data is clarified. Through experiments with Terra and AQUA MODIS data derived chl...