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Ramesh, K.
- Real Time Traffic Analysis of Online Social Networks
Authors
1 Department of Information Technology, V.R.S. College of Engineering & Technology, Villupuram, Tamilnadu, IN
Source
Networking and Communication Engineering, Vol 8, No 4 (2016), Pagination: 91-94Abstract
Social networks have been recently employed as a source of information for event detection, with particular reference to road traffic congestion and car accidents. In this paper, we present a real-time monitoring system for traffic event detection from Twitter stream analysis. The system fetches tweets from Twitter according to several search criteria; processes tweets, by applying text mining techniques; and finally performs the classification of tweets. The aim is to assign the appropriate class label to each tweet, as related to a traffic event or not. The traffic detection system was employed for real-time monitoring of several areas of the Italian road network, allowing for detection of traffic events almost in real time, often before online traffic news web sites. We employed the support vector machine as a classification model, and we achieved an accuracy value of 95.75% by solving a binary classification problem (traffic versus non-traffic tweets). We were also able to discriminate if traffic is caused by an external event or not, by solving a multiclass classification problem and obtaining an accuracy value of 88.89%.
Keywords
Social Networks, Tweets, Facebook, Traffic Detection, Vector Machine, Service Oriented Architecture, Intelligent Transport Machine, Natural Language Processing, Support Vector Machines.
- Performance Analysis of OFZ-LEACH to Extend Network Lifetime in Wireless Sensor Networks
Authors
1 Department of ECE, Nandha Engineering College, Erode, IN
2 Department of CSE, Jaya Engineering College, Chennai, IN
Source
Networking and Communication Engineering, Vol 4, No 3 (2012), Pagination: 97-101Abstract
In Wireless Sensor Network, sensor nodes life time is the most critical parameter. Many researches on these lifetime extension are motivated by LEACH scheme. Rotation based cluster head election method in LEACH-C improves the life time of the network. But that doesn't provide mobility prediction which leads to disconnection of a cluster from the network. This will create data loss and routing problem. Proposed system increases the Cluster head life time. In such network, routing is largely based on nodal contact probability. The basic idea of this WSN is to distribute the grou mobile node with similar mobility pattern into a cluster. A new energy efficient clustering protocol is used which eliminates above problem by forming Far-Zone. Far-Zone is a group of sensor nodes which are placed at locations where their energies are less than a threshold and Double Exponentially Moving Average (DEMA) scheme is employed for on-line updating nodal contact.