An Effective Network Traffic Data Control Using Improved Apriori Rule Mining - Circuits and Systems

CS > Vol.7 No.10, August 2016

An Effective Network Traffic Data Control Using Improved Apriori Rule Mining ()

HTML XML

Download as PDF (Size: 1716KB) PP. 3162-3173

DOI: 10.4236/cs.2016.710269 2,111 Downloads 3,331 Views Citations

Author(s)

Subbiyan Prakash¹, Murugasamy Vijayakumar²

Affiliation(s)

¹Department of Information Technology, Sri Shakthi Institute of Engineering and Technology, Coimbatore, India.
²Department of Computer Science and Engineering, Nandha College of Technology, Erode, India.

ABSTRACT

The increasing usage of internet requires a significant system for effective communication. To pro- vide an effective communication for the internet users, based on nature of their queries, shortest routing path is usually preferred for data forwarding. But when more number of data chooses the same path, in that case, bottleneck occurs in the traffic this leads to data loss or provides irrelevant data to the users. In this paper, a Rule Based System using Improved Apriori (RBS-IA) rule mining framework is proposed for effective monitoring of traffic occurrence over the network and control the network traffic. RBS-IA framework integrates both the traffic control and decision making system to enhance the usage of internet trendier. At first, the network traffic data are ana- lyzed and the incoming and outgoing data information is processed using apriori rule mining algorithm. After generating the set of rules, the network traffic condition is analyzed. Based on the traffic conditions, the decision rule framework is introduced which derives and assigns the set of suitable rules to the appropriate states of the network. The decision rule framework improves the effectiveness of network traffic control by updating the traffic condition states for identifying the relevant route path for packet data transmission. Experimental evaluation is conducted by extrac- ting the Dodgers loop sensor data set from UCI repository to detect the effectiveness of theproposed Rule Based System using Improved Apriori (RBS-IA) rule mining framework. Performance evaluation shows that the proposed RBS-IA rule mining framework provides significant improvement in managing the network traffic control scheme. RBS-IA rule mining framework is evaluated over the factors such as accuracy of the decision being obtained, interestingness measure and execution time.

KEYWORDS

Network Traffic, Internet, Traffic Condition, Rule Mining, Decision Rule Framework, Interestingness, Traffic Data, Web Log

Share and Cite:

Prakash, S. and Vijayakumar, M. (2016) An Effective Network Traffic Data Control Using Improved Apriori Rule Mining. Circuits and Systems, 7, 3162-3173. doi: 10.4236/cs.2016.710269.

Journals Menu

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Journals Menu

Home

About SCIRP

Service

Policies