Match!

An Ubiquitous Multi-agent Mobile Platform for Distributed Crowd Sensing and Social Mining

Published on Aug 1, 2017
· DOI :10.1109/FiCloud.2017.44
Stefan Bosse9
Estimated H-index: 9
(University of Bremen),
Evangelos Pournaras12
Estimated H-index: 12
(ETH Zurich)
View in Source
Abstract
Smart mobile devices are fundamental date sources for crowd activity tracing. Large-scale mobile networks and the Internet-of-Things (IoT) expand and become part of perva-sive and ubiquitous computing offering distributed and trans-parent services. With the IoT, Crowd Sensing is extended by Things Sensing, creating heterogeneous smart environments. A unified and common data processing and communication methodology is required so that the IoT, mobile networks, and Cloud-based environments seamlessly integrate, which can be fulfilled by self-organizing mobile agents, discussed in this work. Currently, portability, resource constraints, security, and scalability of Agent Processing Platforms (APP) are essen-tial issues for the deployment of Multi-agent Systems (MAS) in highly heterogeneous networks. Beside the operational aspects of MAS, an organizational structure is required for the deployment of MAS in crowd sensing and social mining applications. The Planetary Nervous system (Nervousnet) consists of virtual sensors building the core functionality for such applica-tions running on smart phones with a Cloud-like architecture. The virtual sensors enable a holistic composition and modelling approach. Self-organizing and adaptive mobile agents are well known as the core cells of holistic and modular systems. In this work, both concepts are combined. JavaScript agents are introduced as virtual sensors in the Nervousnet environment, evaluated with a simulation of a distributed sensor fusion use-case in a mobile network based on real-world data from Nerv-ousnet, showing the suitability of the hybrid approach, benefit-ing from local and event-based sensor processing performed by the MAS.
  • References (14)
  • Citations (3)
References14
Newest
#1Teemu Leppänen (University of Oulu)H-Index: 9
#2Jose Alvarez Lacasia (UTokyo: University of Tokyo)H-Index: 2
Last.Jukka Riekki (University of Oulu)H-Index: 22
view all 5 authors...
14 CitationsSource
#1Stefan BosseH-Index: 9
6 CitationsSource
Aug 18, 2016 in ASONAM (Advances in Social Networks Analysis and Mining)
#1Federico Musciotto (University of Palermo)H-Index: 3
#2Saverio DelprioriH-Index: 6
Last.Evangelos Pournaras (ETH Zurich)H-Index: 12
view all 4 authors...
7 CitationsSource
#1Stefan Bosse (University of Bremen)H-Index: 9
7 CitationsSource
#1Qingkai Kong (University of California, Berkeley)H-Index: 7
#2Richard M. Allen (University of California, Berkeley)H-Index: 42
Last.Young-Woo Kwon (USU: Utah State University)H-Index: 8
view all 4 authors...
70 CitationsSource
#1Dirk LehmhusH-Index: 19
#2Thorsten WuestH-Index: 12
Last.Matthias BusseH-Index: 15
view all 7 authors...
33 CitationsSource
Mar 1, 2015 in AINA (Advanced Information Networking and Applications)
#1Evangelos Pournaras (ETH Zurich)H-Index: 12
#2Izabela Moise (ETH Zurich)H-Index: 3
Last.Dirk Helbing (ETH Zurich)H-Index: 81
view all 3 authors...
12 CitationsSource
#1Stefan Bosse (University of Bremen)H-Index: 9
#2Armin Lechleiter (University of Bremen)H-Index: 18
16 CitationsSource
#1Giuseppe Cardone (UNIBO: University of Bologna)H-Index: 15
#2Luca Foschini (UNIBO: University of Bologna)H-Index: 21
Last.Reza Curtmola (NJIT: New Jersey Institute of Technology)H-Index: 23
view all 7 authors...
169 CitationsSource
#1Jiankuan XingH-Index: 1
#2Zheng QinH-Index: 2
Last.Jinxue ZhangH-Index: 10
view all 3 authors...
7 CitationsSource
Cited By3
Newest
#1Stefan Bosse (University of Bremen)H-Index: 9
#2Dirk LehmhusH-Index: 19
Source
#1Teemu Leppänen (University of Oulu)H-Index: 9
#2Claudio Savaglio (University of Calabria)H-Index: 14
Last.Giancarlo Fortino (University of Calabria)H-Index: 37
view all 7 authors...
2 CitationsSource
#1Stefan BosseH-Index: 9
#2Dirk LehmhusH-Index: 19
1 CitationsSource