2,608 research outputs found
Performance Analysis of Swarm Intelligence-Based Routing Protocol for Mobile Ad Hoc Network and Wireless Mesh Networks
Ant colonies reside in social insect societies and maintain distributed systems that
present a highly structured social organization despite of the simplicity of their
individuals. Ants’ algorithm belongs to the Swarm Intelligence (SI), which is
proposed to find the shortest path. Among various works inspired by ant colonies, the
Ant Colony Optimization (ACO) metaheuristic algorithms are the most successful
and popular, e.g., AntNet, Multiple Ant Colony Optimization (MACO) and
AntHocNet. But there are several shortcomings including the freezing problem of the
optimum path, traffic engineering, and to link failure due to nodes mobility in
wireless mobile networks.
The metaheuristic and distributed route discovery for data load management in
Wireless Mesh Networks (WMNs) and Mobile Ad-hoc Network (MANET) are
fundamental targets of this study. Also the main aim of this research is to solve the
freezing problem during optimum as well as sub-optimum path discovery process. In
this research, Intelligent AntNet based Routing Algorithm (IANRA) is presented for routing in WMNs and MANET to find optimum and near-optimum paths for data
packet routing. In IANRA, a source node reactively sets up a path to a destination
node at the beginning of each communication. This procedure uses ant-like agents to
discover optimum and alternative paths. The fundamental point in IANRA is to find
optimum and sub-optimum routes by the capability of breeding of ants. This ability
is continuation of route that was produced by the parent ants. The new generations of
ants inherit identifier of their family, the generation number, and the routing
information that their parents get during their routing procedure. By this procedure,
IANRA is able to prevent some of the existing difficulties in AntNet, MACO and Ad
hoc On Demand Distance Vector (AODV) routing algorithms.
OMNeT++ was used to simulate the IARNA algorithm for WMNs and MANET.
The results show that the IANRA routing algorithm improved the data packet
delivery ratio for both WMNs and MANET. Besides, it is able to decrease average
end-to-end packet delay compared to other algorithms by showing its efficiency.
IANRA has decreased average end-to-end packet delay by 31.16%, 58.20% and
48.40% in MANET scenario 52.86%, 64.52% and 62.86% by increasing packet
generation rate in WMNs compared to AntHocNet, AODV and B-AntNet routing
algorithms respectively with increased network load. On the other hand, IANRA
shows the packet delivery ratio of 91.96% and 82.77% in MANET, 97.31% and
92.25% in WMNs for low (1 packet/s) and high (20 packet/s) data load respectively
Training a Feed-forward Neural Network with Artificial Bee Colony Based Backpropagation Method
Back-propagation algorithm is one of the most widely used and popular
techniques to optimize the feed forward neural network training. Nature
inspired meta-heuristic algorithms also provide derivative-free solution to
optimize complex problem. Artificial bee colony algorithm is a nature inspired
meta-heuristic algorithm, mimicking the foraging or food source searching
behaviour of bees in a bee colony and this algorithm is implemented in several
applications for an improved optimized outcome. The proposed method in this
paper includes an improved artificial bee colony algorithm based
back-propagation neural network training method for fast and improved
convergence rate of the hybrid neural network learning method. The result is
analysed with the genetic algorithm based back-propagation method, and it is
another hybridized procedure of its kind. Analysis is performed over standard
data sets, reflecting the light of efficiency of proposed method in terms of
convergence speed and rate.Comment: 14 Pages, 11 figure
CBPRS: A City Based Parking and Routing System
Navigational systems assist drivers in finding a route between two locations that is time optimal in theory but seldom in practice due to delaying circumstances the system is unaware of, such as traffic jams. Upon arrival at the destination the service of the system ends and the driver is forced to locate a parking place without further assistance. We propose a City Based Parking Routing System (CBPRS) that monitors and reserves parking places for CBPRS participants within a city. The CBPRS guides vehicles using an ant based distributed hierarchical routing algorithm to their reserved parking place. Through means of experiments in a simulation environment we found that reductions of travel times for participants were significant in comparison to a situation where vehicles relied on static routing information generated by the well known Dijkstra’s algorithm. Furthermore, we found that the CBPRS was able to increase city wide traffic flows and decrease the number and duration of traffic jams throughout the city once the number of participants increased.information systems;computer simulation;dynamic routing
On green routing and scheduling problem
The vehicle routing and scheduling problem has been studied with much
interest within the last four decades. In this paper, some of the existing
literature dealing with routing and scheduling problems with environmental
issues is reviewed, and a description is provided of the problems that have
been investigated and how they are treated using combinatorial optimization
tools
Self-organizing Routing Algorithm fo Wireless Sensors Networks (WSN) using Ant Colony Optimization (ACO) with Tinyos.
This paper describes the basic tools to work with wireless sensors. TinyOShas a componentbased architecture which enables rapid innovation and implementation while minimizing code size as required by the severe memory constraints inherent in sensor networks. TinyOS's component library includes network protocols, distributed services, sensor drivers, and data acquisition tools ? all of which can be used asia or be further refined for a custom application. TinyOS was originally developed as a research project at the University of California Berkeley, but has since grown to have an international community of developers and users. Some algorithms concerning packet routing are shown. Incar entertainment systems can be based on wireless sensors in order to obtain information from Internet, but routing protocols must be implemented in order to avoid bottleneck problems. Ant Colony algorithms are really useful in such cases, therefore they can be embedded into the sensors to perform such routing task
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