Title
Using Cellular Automata to Reduce Congestion for Tourist Navigation Systems in Mobile Environments
Abstract
Tourist navigation systems have become an important area of research because they help people increase the quality of their travel. This work proposes an adaptive recommendation mechanism that relies on a congestion-aware scheduling method for multiple groups of travelers on multi-destination trips. The recommendation scheme uses the cell (number of groups) mechanism of the cellular automata model for group system distribution. To reduce congestion while visiting multiple destinations, we present a tour group with adaptive recommendations from a system to yield a high quality tour experience. When faced with congestion, the system proposes a path by which the group visits a secondary destination first and then visits the primary destination. Simulation results reveal the strengths of the proposed "adaptive recommendation mechanism" model in terms of decreasing the average wait time, congestion, and the ratio of congestion avoidance to the number of groups.
Year
DOI
Venue
2013
10.1007/s11277-013-1196-7
Wireless Personal Communications
Keywords
Field
DocType
Congestion,Tourist navigation,Adaptive recommendation,Distributed groups,Cellular automata (CA)
Cellular automaton,Slow-start,Computer science,Scheduling (computing),Computer network,Tourism,TRIPS architecture,Destinations
Journal
Volume
Issue
ISSN
73
3
0929-6212
Citations 
PageRank 
References 
1
0.36
7
Authors
4
Name
Order
Citations
PageRank
Sheng-Tzong Cheng129344.23
Yin-Jun Chen2164.11
Gwo-Jiun Horng39923.82
Chi-Hsuan Wang4304.32