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Open AccessArticle

An Intelligent Content Prefix Classification Approach for Quality of Service Optimization in Information-Centric Networking

1
Department of Electronic System Engineering, Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia
2
Department of Advanced Informatics School, Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia
3
Department of Communications and Computer Engineering, Faculty of Science and Engineering, Waseda University, Shinjuku-ku, Tokyo 169-0051, Japan
*
Author to whom correspondence should be addressed.
Future Internet 2018, 10(4), 33; https://doi.org/10.3390/fi10040033
Received: 1 March 2018 / Revised: 26 March 2018 / Accepted: 2 April 2018 / Published: 9 April 2018
This research proposes an intelligent classification framework for quality of service (QoS) performance improvement in information-centric networking (ICN). The proposal works towards keyword classification techniques to obtain the most valuable information via suitable content prefixes in ICN. In this study, we have achieved the intelligent function using Artificial Intelligence (AI) implementation. Particularly, to find the most suitable and promising intelligent approach for maintaining QoS matrices, we have evaluated various AI algorithms, including evolutionary algorithms (EA), swarm intelligence (SI), and machine learning (ML) by using the cost function to assess their classification performances. With the goal of enabling a complete ICN prefix classification solution, we also propose a hybrid implementation to optimize classification performances by integration of relevant AI algorithms. This hybrid mechanism searches for a final minimum structure to prevent the local optima from happening. By simulation, the evaluation results show that the proposal outperforms EA and ML in terms of network resource utilization and response delay for QoS performance optimization. View Full-Text
Keywords: information-centric networking (ICN); Intelligent classifications; artificial intelligence (AI); quality of service (QoS) information-centric networking (ICN); Intelligent classifications; artificial intelligence (AI); quality of service (QoS)
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MDPI and ACS Style

Safitri, C.; Yamada, Y.; Baharun, S.; Goudarzi, S.; Ngoc Nguyen, Q.; Yu, K.; Sato, T. An Intelligent Content Prefix Classification Approach for Quality of Service Optimization in Information-Centric Networking. Future Internet 2018, 10, 33. https://doi.org/10.3390/fi10040033

AMA Style

Safitri C, Yamada Y, Baharun S, Goudarzi S, Ngoc Nguyen Q, Yu K, Sato T. An Intelligent Content Prefix Classification Approach for Quality of Service Optimization in Information-Centric Networking. Future Internet. 2018; 10(4):33. https://doi.org/10.3390/fi10040033

Chicago/Turabian Style

Safitri, Cutifa; Yamada, Yoshihide; Baharun, Sabariah; Goudarzi, Shidrokh; Ngoc Nguyen, Quang; Yu, Keping; Sato, Takuro. 2018. "An Intelligent Content Prefix Classification Approach for Quality of Service Optimization in Information-Centric Networking" Future Internet 10, no. 4: 33. https://doi.org/10.3390/fi10040033

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