International Journal of Computer Networks and Communications Security

Volume 5, Issue 9, September 2017

 

 

Improve the Routing Algorithm in Wireless Sensor Networks Using a Reinforcement Learning Strategy
 

Improve the Routing Algorithm in Wireless Sensor Networks Using a Reinforcement Learning Strategy

Pages: 188-197 (10) | [Full Text] PDF (378 KB)
S Zeinali, MDavoudi-Monfared
Department of Computer Sciences, Islamic Azad University, Tafresh Branch, Tafresh, Iran
Department of Mathematics and Computer Sciences, Islamic Azad University, Tafresh Branch, Tafresh, Iran

Abstract -
Recent developments in the field of electronic and wireless communications have the ability to design and manufacture sensors with low power consumption, small size, reasonable prices and various data uses. These small sensors, which have the ability to perform actions such as receiving various environmental information based on the sensor type, processing and sending it, monitoring and monitoring, etc., have led to the emergence of ideas for the creation and expansion of networks known as wireless sensor networks. A sensor network consists of a large number of sensor nodes that are widely distributed in an environment that collects information from the environment. The location of sensor nodes is necessarily predefined and not known. Such a feature allows us to release them in hazardous or inaccessible places. Another unique feature of sensor networks is the ability to collaborate and coordinate sensor nodes. Each node of the sensor has a processor on its board, and if it uses related algorithms, instead of sending all the raw data to the center, it first performs its initial and simple processing on them and then sends the semi-processed data.
 
Index Terms - Wireless Sensor Networks, Clustering, Clustering, Energy Balance, Lifetime

Citation - S Zeinali, MDavoudi-Monfared. "Improve the Routing Algorithm in Wireless Sensor Networks Using a Reinforcement Learning Strategy." International Journal of Computer Networks and Communications Security 5, no. 9 (2017): 188-197.

Liveness Authentication of Iris Template: A Data Mining Approach
 

Liveness Authentication of Iris Template: A Data Mining Approach

Pages: 198-204 (7) | [Full Text] PDF (365 KB)
M Mahmud
Department of Managment Information Systems (MIS), College of Business Adminsitration (CBA), Imam Abdulrahman Bin Faisal (IAF) University, Dammam, Kingdom of Saudi Arabia

Abstract -
The liveness authentication is very important in the surveillance environment, especially in border crossings and places where there is a buffer zone or war area. In this paper, it is determined how to test the liveness of the iris template to avoid fraud. Various data mining can be used to achieve this phenomenon. There are basically two methods for liveness authentication i.e. static and dynamic. A method is proposed in this paper based on the combination of static and dynamic methods. A data mining tool is used to generate graphical results based on combination of classification and clustering algorithms. Twenty features were defined to authenticate the liveness authentication. The visual results are presented to validate the results. It was found that J48 is the best classification algorithm for determining the liveness detection rather than DBSCAN. It is concluded that liveliness of iris can be determined by using the soft biometrics.
 
Index Terms - Biometrics, Iris Liveness Detection, Classification, Clustering, Data mining, WEKA

Citation - M Mahmud . "Liveness Authentication of Iris Template: A Data Mining Approach." International Journal of Computer Networks and Communications Security 5, no. 9 (2017): 198-204.

Repairing Field Coverage for Static WSNs by Using Mobile Nodes
 

Repairing Field Coverage for Static WSNs by Using Mobile Nodes

Pages: 205-215 (11) | [Full Text] PDF (647 KB)
R Katsuma, Y Tsuchiya
Graduate school of science, Osaka Prefecture University

Abstract -
In wireless sensor networks (WSNs), sensor nodes periodically sense, record, and transmit environmental information. WSNs require long lifetime and adequate field coverage, which can be problematic under certain conditions. Several studies have addressed these problems using energy harvesting, wireless charging, or mobile sensor nodes. In particular, mobile nodes are effective for adequate field coverage: however, appropriate node movement is critical. In addition, mobile nodes with wireless charging devices can charge the batteries of other nodes. We formulate the problem to extend lifetime and maintain field coverage by determining the positions of mobile nodes that can cover the field effectively and charge the batteries of other nodes simultaneously. We propose a coverage algorithm that can cover a field with a minimal number of nodes and a movement algorithm that determines an efficient mobile node movement schedule to charge static nodes. Simulation results, confirm that the energy charging system used by the proposed method can extend WSN lifetime up to 66%.
 
Index Terms - Wireless Sensor Networks, Mobile Nodes, Network Lifetime, Energy Harvesting, Coverage

Citation - R Katsuma, Y Tsuchiya. "Repairing Field Coverage for Static WSNs by Using Mobile Nodes ." International Journal of Computer Networks and Communications Security 5, no. 9 (2017): 205-215.