MOSDEN: A Scalable Mobile Collaborative Platform for Opportunistic Sensing Applications

Journal Title: EAI Endorsed Transactions on Collaborative Computing - Year 2015, Vol 1, Issue 1

Abstract

Mobile smartphones along with embedded sensors have become an efficient enabler for various mobile applications including opportunistic sensing. The hi-tech advances in smartphones are opening up a world of possibilities. This paper proposes a mobile collaborative platform called MOSDEN that enables and supports opportunistic sensing at run time. MOSDEN captures and shares sensor data acrossmultiple apps, smartphones and users. MOSDEN supports the emerging trend of separating sensors from application-specific processing, storing and sharing. MOSDEN promotes reuse and re-purposing of sensor data hence reducing the efforts in developing novel opportunistic sensing applications. MOSDEN has been implemented on Android-based smartphones and tablets. Experimental evaluations validate the scalability and energy efficiency of MOSDEN and its suitability towards real world applications. The results of evaluation and lessons learned are presented and discussed in this paper.

Authors and Affiliations

Prem Prakash Jayaraman, Charith Perera, Dimitrios Georgakopoulos, Arkady Zaslavsky

Keywords

Related Articles

Automated Dimension Determination for NMF-based Incremental Collaborative Filtering

The nonnegative matrix factorization (NMF) based collaborative filtering t e chniques h a ve a c hieved great success in product recommendations. It is well known that in NMF, the dimensions of the factor matrices have t...

A Hybrid Model Ranking Search Result for Research Paper Searching on Social Bookmarking

Social bookmarking and publication sharing systems are essential tools for web resource discovery. The performance and capabilities of search results from research paper bookmarking system are vital. Many researchers use...

Collaborating with executable content across space and time

Executable content is of growing importance in many domains. How does one share and archive such content at Internet-scale for spatial and temporal collaboration? Spatial collaboration refers to the classic concept of us...

A Game Theoretic Approach for Modeling Privacy Settings of an Online Social Network

Users of online social networks often adjust their privacy settings to control how much information on their profiles is accessible to other users of the networks. While a variety of factors have been shown to affect the...

Impact of window to walls ratios on thermal comfort and energy consumption in tropical zone

This paper investigated the impact of Window to Wall Ratios (WWR) an the thermal comfort and energy lighting demand of a building in tropical zone. Simulations were carried out for a reference office proposed by Task 27...

Download PDF file
  • EP ID EP45679
  • DOI http://dx.doi.org/10.4108/cc.1.1.e6
  • Views 467
  • Downloads 0

How To Cite

Prem Prakash Jayaraman, Charith Perera, Dimitrios Georgakopoulos, Arkady Zaslavsky (2015). MOSDEN: A Scalable Mobile Collaborative Platform for Opportunistic Sensing Applications. EAI Endorsed Transactions on Collaborative Computing, 1(1), -. https://europub.co.uk/articles/-A-45679