TY - GEN
T1 - Using Ant Colony Optimization to design GPON-FTTH networks with aggregating equipment
AU - Chu, Andrej
AU - Poon, Kin Fai
AU - Ouali, Anis
PY - 2013
Y1 - 2013
N2 - With the huge demands for the provision of inexpensive and fast broadband services, Gigabit Passive Optical Network (GPON) has been considered to be the most attractive solution for providing broadband access network. However, due to the consideration of many design factors such as the number, types, positions of network elements and routing information, the optical network planning process often exhibits several challenges from the optimization point of view. This problem is generally NP-hard and cannot be solved in polynomial time by any currently known algorithms. In this paper, we present an algorithm based on the Ant Colony Optimization (ACO) method with dedicated post-processing. Given a geographical location of a Greenfield area, our proposed solution minimizes the overall GPON network deployment cost by selecting the optimum type of aggregating equipment, routing information and cost effective locations of network elements. In the result section, different network examples will be provided to illustrate the effectiveness of the ACO approach for this type of problem.
AB - With the huge demands for the provision of inexpensive and fast broadband services, Gigabit Passive Optical Network (GPON) has been considered to be the most attractive solution for providing broadband access network. However, due to the consideration of many design factors such as the number, types, positions of network elements and routing information, the optical network planning process often exhibits several challenges from the optimization point of view. This problem is generally NP-hard and cannot be solved in polynomial time by any currently known algorithms. In this paper, we present an algorithm based on the Ant Colony Optimization (ACO) method with dedicated post-processing. Given a geographical location of a Greenfield area, our proposed solution minimizes the overall GPON network deployment cost by selecting the optimum type of aggregating equipment, routing information and cost effective locations of network elements. In the result section, different network examples will be provided to illustrate the effectiveness of the ACO approach for this type of problem.
UR - https://www.scopus.com/pages/publications/84883827376
U2 - 10.1109/CICommS.2013.6582848
DO - 10.1109/CICommS.2013.6582848
M3 - Conference contribution
AN - SCOPUS:84883827376
SN - 9781467359030
T3 - Proceedings of the 2013 IEEE Symposium on Computational Intelligence for Communication Systems and Networks, CIComms 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013
SP - 10
EP - 17
BT - Proceedings of the 2013 IEEE Symposium on Computational Intelligence for Communication Systems and Networks, CIComms 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013
T2 - 2013 IEEE Symposium on Computational Intelligence for Communication Systems and Networks, CIComms 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013
Y2 - 16 April 2013 through 19 April 2013
ER -
