System simulation of optimal path design based on dynamic network

2012 ◽  
Author(s):  
Aixia Zhang ◽  
Liang Zhao ◽  
Zheng Wang
Keyword(s):  
System Simulation ◽  
Optimal Path ◽  
Dynamic Network ◽  
Path Design

Routing in Wireless Mesh Networks based on Termites' Intelligence

2017 ◽  
Vol 8 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Sharad Sharma ◽  
Asha Malik
Keyword(s):  
High Speed ◽  
Mesh Networks ◽  
Optimal Path ◽  
Dynamic Network ◽  
Critical Issue ◽  
Mesh Network ◽  
Wireless Mesh ◽  
Heuristic Technique ◽  
Link Cost ◽  
Selection Of

Wireless Mesh Network (WMN) is envisaged to be key component of next generation wireless networks which can effectively cope with the ever increasing fast and vast growing need to access data and avail services over the network. These networks provide infrastructure less high speed internet access to the end users and have a cutting edge over the existing networks. Routing, being most critical issue in their implementation. The dynamic network conditions impose setbacks in the selection of optimal path. There is exigent requirement to tackle these routing issues in context of these networks. In this paper, the authors apply a nature inspired soft computing based meta heuristic technique called Termite Colony Optimization in WMN to find an optimal route based on the link cost. TCO approach is inspired by the emergent behaviour exhibited by the natural termite colony swarms for mound building. Experimentally TCO shows faster converges over some existing algorithms.

scholarly journals Optimized Dynamic Routing in Multimedia Vehicular Networks

2020 ◽  
Vol 02 (03) ◽  
pp. 174-182
Author(s):  
Dr. Joy Iong Zong Chen ◽  
Dr. S. Smys
Keyword(s):  
Ant Colony Optimization ◽  
Real Time ◽  
Vehicular Networks ◽  
Optimal Path ◽  
Dynamic Network ◽  
Computation Time ◽  
Dynamic Routing ◽  
Ant Colony ◽  
Intelligent Transport System ◽  
Routing Strategy

Intelligent transport system is one of thriving research domain and in particular multimedia vehicular networks gains more attention. The deployment of multimedia services in vehicle ad-hoc networks (VANETs) provides real time support to users and provides better traffic management with high safety measures. Most of the vehicles has multimedia applications such as weather sensors, real time map applications etc., and it requires adequate resources to process. Resource allocation to a static network is simple and various routing models are evolved. In case of dynamic network like VANETs, routing is still in progress in order to obtain a better model. Routing directly related to quality of services of network and user, it is essential to develop a better dynamic routing strategy for multimedia wireless networks. The proposed work aims to provide an optimized dynamic routing strategy for multimedia networks. For efficient routing, k-means clustering is used to organize the clusters and exchanges the routing information and inverted ant colony optimization is used to obtain the optimal path for multimedia access. Proposed model is experimentally verified and compared to conventional ant colony optimization and grey wolf optimization in terms of parameters such as end to end delay, throughput, target used, average computation time and efficiency.

Path Design of Large Flexible Material Handing

2000 ◽  
Author(s):  
Kuo-Chi Lin ◽  
Annie S. Wu ◽  
Zhihua Qu ◽  
Tanmoy Joshi
Keyword(s):  
Genetic Algorithm ◽  
Cantilever Beam ◽  
Optimal Path ◽  
Time Constraint ◽  
Flexible Structure ◽  
Flexible Material ◽  
Path Design

Abstract When moving a partially constrained large and flexible material, vibration is always a concern, especially if the material is brittle. This paper suggests an approach that uses a genetic algorithm (GA) to search for the optimal path for moving a flexible structure within a given time constraint. A simple cantilever beam with a moving foundation is used as the implementation example. The results show that a GA can provide a set of “good” solutions within a small number of generations of evolution. This approach can be very efficient if the mathematical optimum is not absolutely necessary.

Observer Path Design for Bearings-Only Localization with State Constraints

2013 ◽  
Vol 373-375 ◽  
pp. 1493-1496 ◽  
Author(s):  
Hong Wei Quan
Keyword(s):  
State Constraints ◽  
Fisher Information Matrix ◽  
Optimal Algorithm ◽  
Optimal Path ◽  
Information Matrix ◽  
Target Localization ◽  
Path Design ◽  
Initial States ◽  
Step Algorithm ◽  
Optimal Approach

In bearings-only target localization, observer path have an important effect on the accuracy of target localization. Based on the analysis of Fisher information matrix, an optimal approach to designing observer path is proposed. Observer path derived from the step-by-step optimal algorithm only depends on observer's initial states and state constraints. The optimal path resulted with step-by-step algorithm is demonstrated by computer simulation. Compared with traditional methods, our algorithm is not limited to the number of observations as well as terminating conditions.

Optimal path design in robot soccer environment

2004 ◽  
Author(s):  
M. Lepetic ◽  
G. Klancar ◽  
I. Skrjanc ◽  
D. Matko ◽  
B. Potocnik
Keyword(s):  
Optimal Path ◽  
Robot Soccer ◽  
Path Design

Searching time-table networks

1991 ◽  
Vol 5 (3) ◽  
pp. 189-198 ◽  
Author(s):  
Eduard Tulp ◽  
Laurent Siklóssy
Keyword(s):  
Arrival Time ◽  
Search Algorithm ◽  
Optimal Path ◽  
Dynamic Networks ◽  
Dynamic Network ◽  
Transportation Systems ◽  
Forward Search ◽  
Discrete Dynamic ◽  
Time Space ◽  
Time Table

In this paper we present an application of AI search techniques to a class of problems that arise in transportation systems analysis. Rather than adapting the time-space network formulation typically used in Operations Research, we propose a discrete dynamic network to represent a scheduled service network. In a discrete dynamic network, there are finite, discrete, predetermined possibilities for moving from one vertex to another. Visiting a vertex has a cost (possibly zero), which may depend both on how the vertex was reached and how it will be left.We describe the DYNET search algorithm for finding optimal paths in discrete dynamic networks. DYNET has been implemented in a working system (TRAINS) which searches the entire Dutch railway services network. An optimal path in a discrete dynamic network makes us arrive at our destination as early as possible (given our planned earliest departure time), and given this earliest arrival time (eat), will allow us to leave as late as possible, thereby guaranteeing a shortest path relative to the eat. DYNET first conducts a forward search to find the earliest possible arrival time, then a backward search which uses results of the forward search, to find the latest departure to arrive at that eat. Various AI techniques (symmetries, abstraction spaces, distance estimates, etc.) improve the performance of DYNET.

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