Distributed Coordination of a Multi-Agent System With Intermittent Communication: A Switched Systems Approach

2018 ◽  
Author(s):  
Federico M. Zegers ◽  
Hsi-Yuan Chen ◽  
Patryk Deptula ◽  
Warren E. Dixon
Keyword(s):  
Service Provider ◽  
Switched Systems ◽  
Systems Approach ◽  
Information Service ◽  
Multi Agent System ◽  
Distributed Coordination ◽  
Mobile Information ◽  
Multi Agent ◽  
Mobile Information Service ◽  
Intermittent Communication

In this paper, a novel switched systems approach is taken to enable the distributed coordination of a multi-agent system with intermittent communication. A mobile information service provider switches between various (follower) agents in the network to provide them with state feedback when they are within close proximity. The follower agents do not have navigational sensors but are still proven to converge to a desired goal through open-loop control with intermittent error correction by the leader. A switched systems stability analysis is performed to determine the maximum dwell-time the mobile information service provider can intermittently communicate information to the agents to ensure convergence to the desired goal. Simulation results are included to demonstrate the development.

scholarly journals A Cloud Information Monitoring and Recommendation Multi-Agent System with Friendly Interfaces for Tourism

2019 ◽  
Vol 9 (20) ◽  
pp. 4385
Author(s):  
Kune-Yao Chen ◽  
Sheng-Yuan Yang
Keyword(s):  
Recommendation System ◽  
Information Service ◽  
Open Data ◽  
Tourism Industry ◽  
Multi Agent System ◽  
Agent System ◽  
Service Architecture ◽  
Intelligent Decision Making ◽  
Information Monitoring ◽  
Multi Agent

The tourism statistics of Taiwan’s government state that the tourism industry is one of the fastest growing economic sources in the world. Therefore, the demand for a tourism information system with a friendly interface is growing. This research implemented the construction of a cloud information service platform based on numerous practical developments in the Dr. What-Info system (i.e., a master multi-agent system on what the information is), which developed universal application interface (UAI) technology based on the Taiwan government’s open data with the aim of connecting different application programming interfaces (APIs) according to different data formats and intelligence through local GPS location retrieval, in support of three-stage intelligent decision-making and a three-tier address-based UAI technology comparison. This paper further developed a novel citizen-centric multi-agent information monitoring and recommendation system for the tourism sector. The proposed system was experimentally demonstrated as a successful integration of technology, and stands as an innovative piece of work in the literature. Although there is room for improvement in experience and maybe more travel-related agents, the feasibility of the proposed service architecture has been proven.

scholarly journals Implementasi Sistem Load Balancing Menggunakan Metode Least Time First Byte Dan Multi-Agent System Pada Lingkungan Virtual

2019 ◽  
Vol 4 (2) ◽  
pp. 63-70
Author(s):  
Dyah Ayu Wiranti ◽  
Kurnia Siwi Kinasih ◽  
Shinta Rizki Firdina Sugiono
Keyword(s):  
Information System ◽  
Load Balancing ◽  
Response Time ◽  
Service Provider ◽  
The Internet ◽  
Multi Agent System ◽  
Agent System ◽  
Time Value ◽  
Multi Agent ◽  
Modern Era

In this modern era, the technology is growing rapidly, the Internet is misled. This condition will be related to the service provider or commonly referred to as a server. Increasing the number of clients, the server also has to work heavier so that it often occurs overload. The Load Balancing mechanism uses the Least Time First Byte and Multi Agent system methods. This mechanism allows the server to overcome the number of users who perform service requests so that the load from the server can be resolved. This solution is considered efficient and effective because the request process on the information system will be shared evenly on multiple server back ends. The results of the research that can be proved if using this mechanism the server can work well when the request is from a user or client dating, this method successfully distributes the balancer evenly through the server backend. So the server is no longer experiencing overload. This can be proved when a system that has used the load balancing method with 300 connections generates a throughput of 123.1 KB/s as well as response time value of 4.72 MS and a system that does not use the load balancing method has a throughput of 108.4 KB/s as well as a response time value of 120.3 Ms. Therefore by implementing load balancing the performance of the system can always be improved.

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