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  1. Autonomous Agents and Multi-Agent Systems
  2. Autonomous Agents and Multi-Agent Systems : Volume 31
  3. Autonomous Agents and Multi-Agent Systems : Volume 31, Issue 1, January 2017
  4. Mobile crowdsensing with mobile agents
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Autonomous Agents and Multi-Agent Systems : Volume 31
Autonomous Agents and Multi-Agent Systems : Volume 31, Issue 3, May 2017
Autonomous Agents and Multi-Agent Systems : Volume 31, Issue 2, March 2017
Autonomous Agents and Multi-Agent Systems : Volume 31, Issue 1, January 2017
Mobile crowdsensing with mobile agents
Filtering unfair ratings from dishonest advisors in multi-criteria e-markets: a biclustering-based approach
Exact and heuristic methods for solving Boolean games
Strategies for utility maximization in social groups with preferential exploration
Negotiation strategy for continuous long-term tasks in a grid environment
Evaluating fault tolerance approaches in multi-agent systems
Autonomous Agents and Multi-Agent Systems : Volume 30
Autonomous Agents and Multi-Agent Systems : Volume 29
Autonomous Agents and Multi-Agent Systems : Volume 28
Autonomous Agents and Multi-Agent Systems : Volume 27
Autonomous Agents and Multi-Agent Systems : Volume 26
Autonomous Agents and Multi-Agent Systems : Volume 25
Autonomous Agents and Multi-Agent Systems : Volume 24
Autonomous Agents and Multi-Agent Systems : Volume 23
Autonomous Agents and Multi-Agent Systems : Volume 22
Autonomous Agents and Multi-Agent Systems : Volume 21
Autonomous Agents and Multi-Agent Systems : Volume 20
Autonomous Agents and Multi-Agent Systems : Volume 19
Autonomous Agents and Multi-Agent Systems : Volume 18
Autonomous Agents and Multi-Agent Systems : Volume 17
Autonomous Agents and Multi-Agent Systems : Volume 16
Autonomous Agents and Multi-Agent Systems : Volume 15
Autonomous Agents and Multi-Agent Systems : Volume 14
Autonomous Agents and Multi-Agent Systems : Volume 13
Autonomous Agents and Multi-Agent Systems : Volume 12
Autonomous Agents and Multi-Agent Systems : Volume 11
Autonomous Agents and Multi-Agent Systems : Volume 10
Autonomous Agents and Multi-Agent Systems : Volume 9
Autonomous Agents and Multi-Agent Systems : Volume 8
Autonomous Agents and Multi-Agent Systems : Volume 7
Autonomous Agents and Multi-Agent Systems : Volume 6
Autonomous Agents and Multi-Agent Systems : Volume 5
Autonomous Agents and Multi-Agent Systems : Volume 4
Autonomous Agents and Multi-Agent Systems : Volume 3
Autonomous Agents and Multi-Agent Systems : Volume 2
Autonomous Agents and Multi-Agent Systems : Volume 1

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Mobile crowdsensing with mobile agents

Content Provider SpringerLink
Author Leppänen, Teemu Álvarez Lacasia, José Tobe, Yoshito Sezaki, Kaoru Riekki, Jukka
Copyright Year 2015
Abstract We introduce mobile agents for mobile crowdsensing. Crowdsensing campaigns are designed through different roles that are implemented as mobile agents. The role-based tasks of mobile agents include collecting data, analyzing data and sharing data in the campaign. Mobile agents execute and control the campaign autonomously as a multi-agent system and migrate in the opportunistic network of participants’ devices. Mobile agents take into account the available resources in the devices and match participants’ privacy requirements to the campaign requirements. Sharing of task results in real-time facilitates cooperation towards the campaign goal while maintaining a selected global measure, such as energy efficiency. We discuss current challenges in crowdsensing and propose mobile agent based solutions for campaign execution and monitoring, addressing data collection and participant-related issues. We present a software framework for mobile agents-based crowdsensing that is seamlessly integrated into the Web. A set of simulations are conducted to compare mobile agent-based campaigns with existing crowdsensing approaches. We implemented and evaluated a small-scale real-world mobile agent based campaign for pedestrian flock detection. The simulation and evaluation results show that mobile agent based campaigns produce comparable results with less energy consumption when the number of agents is relatively small and enables in-network data processing with sharing of data and task results with insignificant overhead.
Starting Page 1
Ending Page 35
Page Count 35
File Format PDF
ISSN 13872532
Journal Autonomous Agents and Multi-Agent Systems
Volume Number 31
Issue Number 1
e-ISSN 15737454
Language English
Publisher Springer US
Publisher Date 2015-10-24
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Distributed computing Multi-agent systems Mobile computing Mobile agents Mobile crowdsensing Artificial Intelligence (incl. Robotics) Computer Systems Organization and Communication Networks Computing Methodologies Software Engineering/Programming and Operating Systems User Interfaces and Human Computer Interaction
Content Type Text
Resource Type Article
Subject Artificial Intelligence
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