Fragmentation in Distributed Database Design Based on Ant Colony Optimization Technique

2019 ◽  
Vol 9 (2) ◽  
pp. 28-37
Author(s):  
Van Nghia Luong ◽  
Vijender Kumar Solanki ◽  
Nguyen Ha Huy Cuong

Distributed database design solutions depend heavily on the exploitation of input data sources by using clustering techniques in data mining. A new approach of biomimetic computation systems such as ant colony optimization (ACO) for this solution is of interest to informatics experts. Using ACO techniques for this solution has the advantages such as faster algorithms thanks to the randomness of ant colony behavior. The use of random numbers based on heuristic information to pickup (drop) points will facilitate the flexible search on a large data space, so that it provides us with a better answer. In this article, the authors present ACO algorithms application solutions to clustering techniques for the problem of vertical fragmentation of distributed data.

1987 ◽  
Vol 75 (5) ◽  
pp. 533-546 ◽  
Author(s):  
S. Ceri ◽  
B. Pernici ◽  
G. Wiederhold

Author(s):  
Bachir Benhala ◽  
Ali Ahaitouf ◽  
Abdellah Mechaqrane ◽  
Brahim Benlahbib ◽  
Farid Abdi ◽  
...  

Author(s):  
Nadim Diab

Swarm intelligence optimization techniques are widely used in topology optimization of compliant mechanisms. The Ant Colony Optimization has been implemented in various forms to account for material density distribution inside a design domain. In this paper, the Ant Colony Optimization technique is applied in a unique manner to make it feasible to optimize for the beam elements’ cross-section and material density simultaneously. The optimum material distribution algorithm is governed by two various techniques. The first technique treats the material density as an independent design variable while the second technique correlates the material density with the pheromone intensity level. Both algorithms are tested for a micro displacement amplifier and the resulting optimized topologies are benchmarked against reported literature. The proposed techniques culminated in high performance and effective designs that surpass those presented in previous work.


2020 ◽  
Vol 1 (1) ◽  
pp. 1-10
Author(s):  
Nisreen L. Ahmed

Swarm intelligence is a relatively new approach to problem solving that takes inspiration from the social behaviors of insects and other animals. Ants, in particular, have inspired a number of methods and techniques among which the most studied and successful is the general-purpose optimization technique, also known as ant colony optimization, In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs.  Ant Colony Optimization (ACO) algorithm is used to arrive at the best solution for TSP. In this article, the researcher has introduced ways to use a great deluge algorithm with the ACO algorithm to increase the ability of the ACO in finding the best tour (optimal tour). Results are given for different TSP problems by using ACO with great deluge and other local search algorithms.


Author(s):  
Rohini Sharma ◽  
D. K. Lobiyal

A main characteristic of wireless sensor network (WSN) is its limited battery power. Non-uniform energy depletion in WSN, leads to formation of energy holes in certain areas of network. For a uniform consumption of energy among sensor nodes, some points should be considered like the residual energy of the nodes, energy consumed in the communication and route length. In this work, the authors has achieved the uniform consumption of energy by using dissimilar transmission power levels for communication between cluster heads and the sink node, and for intra- cluster communication. Further, they have used ant colony optimization technique for routing between the base station and sensors which are not the member of any cluster. They have proposed dual transmission power levels and ant colony optimization based (DTP-ACO) protocol to improve the lifespan of the network. Results demonstrate that DTP-ACO protocol outperforms LEACH protocol in provisions of the life span, residual energy, packets sent to the base station and throughput of the network.


Sign in / Sign up

Export Citation Format

Share Document