scholarly journals Agent-Based Modelling for Distributed Decision Support in an IoT Network

2020 ◽  
Author(s):  
Majid Butt ◽  
Indrakshi Dey ◽  
Merim Dzaferagic ◽  
Maria Murphy ◽  
Nicholas Kaminski ◽  
...  
Keyword(s):  
Traffic Management ◽  
Autonomous Agents ◽  
Road Traffic ◽  
Mac Protocol ◽  
Spectrum Utilization ◽  
Medium Access ◽  
Modeling And Analysis ◽  
Agent Based ◽  
Traffic Management System ◽  
High Level

<div>An increasing number of emerging applications, e.g.,</div><div>Internet of Things (IoT), vehicular communications, augmented reality, and the growing complexity due to the interoperability requirements of these systems, lead to the need to change the tools used for the modeling and analysis of those networks. Agent-Based Modeling (ABM) as a bottom-up modeling approach considers a network of autonomous agents interacting with each other, and therefore represents an ideal framework to comprehend the interactions of heterogeneous nodes in a complex environment. Here, we investigate the suitability of ABM to</div><div>model the communication aspects of a road traffic management system as an example of an IoT network. We model, analyze and compare various Medium Access Control (MAC) layer protocols for two different scenarios, namely uncoordinated and coordinated. Besides, we model the scheduling mechanisms for the coordinated scenario as a high level MAC protocol by using three different approaches: Centralized Decision Maker, DESYNC and decentralized learning MAC (L-MAC). The results clearly</div><div>show the importance of coordination between multiple decision makers in order to improve the information reporting error and spectrum utilization of the system.</div>

scholarly journals Agent-Based Modelling for Distributed Decision Support in an IoT Network

2020 ◽  
Author(s):  
Majid Butt ◽  
Indrakshi Dey ◽  
Merim Dzaferagic ◽  
Maria Murphy ◽  
Nicholas Kaminski ◽  
...  
Keyword(s):  
Traffic Management ◽  
Autonomous Agents ◽  
Road Traffic ◽  
Mac Protocol ◽  
Spectrum Utilization ◽  
Medium Access ◽  
Modeling And Analysis ◽  
Agent Based ◽  
Traffic Management System ◽  
High Level

<div>An increasing number of emerging applications, e.g.,</div><div>Internet of Things (IoT), vehicular communications, augmented reality, and the growing complexity due to the interoperability requirements of these systems, lead to the need to change the tools used for the modeling and analysis of those networks. Agent-Based Modeling (ABM) as a bottom-up modeling approach considers a network of autonomous agents interacting with each other, and therefore represents an ideal framework to comprehend the interactions of heterogeneous nodes in a complex environment. Here, we investigate the suitability of ABM to</div><div>model the communication aspects of a road traffic management system as an example of an IoT network. We model, analyze and compare various Medium Access Control (MAC) layer protocols for two different scenarios, namely uncoordinated and coordinated. Besides, we model the scheduling mechanisms for the coordinated scenario as a high level MAC protocol by using three different approaches: Centralized Decision Maker, DESYNC and decentralized learning MAC (L-MAC). The results clearly</div><div>show the importance of coordination between multiple decision makers in order to improve the information reporting error and spectrum utilization of the system.</div>

scholarly journals Mobile Road Traffic Management System Using Weighted Sensor

2017 ◽  
Vol 11 (5) ◽  
pp. 147 ◽  
Author(s):  
Solomon Adegbenro Akinboro ◽  
Johnson A Adeyiga ◽  
Adebayo Omotosho ◽  
Akinwale O Akinwumi
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Urban Areas ◽  
Traffic Management ◽  
Management System ◽  
Road Traffic ◽  
Traffic Information ◽  
Traffic Light ◽  
Real Time Traffic ◽  
Traffic Management System

<p><strong>Vehicular traffic is continuously increasing around the world, especially in urban areas, and the resulting congestion ha</strong><strong>s</strong><strong> be</strong><strong>come</strong><strong> a major concern to automobile users. The popular static electric traffic light controlling system can no longer sufficiently manage the traffic volume in large cities where real time traffic control is paramount to deciding best route. The proposed mobile traffic management system provides users with traffic information on congested roads using weighted sensors. A prototype of the system was implemented using Java SE Development Kit 8 and Google map. The model </strong><strong>was</strong><strong> simulated and the performance was </strong><strong>assessed</strong><strong> using response time, delay and throughput. Results showed that</strong><strong>,</strong><strong> mobile devices are capable of assisting road users’ in faster decision making by providing real-time traffic information and recommending alternative routes.</strong></p>

scholarly journals Reconfigurable SRTM System for Road Traffic in Kingdom of Bahrain

2016 ◽  
Vol 17 (4) ◽  
pp. 298-306 ◽  
Author(s):  
Wael El-Medany ◽  
Alauddin Al-Omary ◽  
Riyadh Al-Hakim ◽  
Taher Homeed
Keyword(s):  
Traffic Management ◽  
Road Traffic ◽  
Traffic Signals ◽  
Google Maps ◽  
Traffic System ◽  
The Road ◽  
Field Programmable ◽  
Hardware Description ◽  
Traffic Management System ◽  
On The Road

Abstract This paper presents reconfigurable hardware architecture for smart road traffic system based on Field Programmable Gate Array (FPGA). The design can be reconfigured for different timing of the traffic signals according to the received and collected data read by the different sensors on the road; the design has been described using VHDL (VHSIC Hardware Description Language). The SRTM (Smart Road Traffic Management) System has some more features that help passenger to avoid traffic jamming by sending the collected information through web/mobile applications to find the best road between the start and destination points, which will be displayed on Google maps, at the same time it will also shows the points of traffic jamming on Google maps. SRTM system can also manage emergency vehicles such as ambulance and fire fighter and also can send snapshots and video streaming for different roads and junctions to show the points of traffic jamming. The design has been simulated and tested using ModelSim PE student edition 10.4. Spartan 3 FPGA starter kit from Xilinx has been used for implementing and testing the design in a hardware level.

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