E. Kanniga , K. Selvaramarathnam , M. Sundararajan

Abstract

The aim of our study aims to design a wheelchair having network controlled by memes sensor with voice command and CCTV camera. This work is intended to help and blind persons. Our work enables a dumb person sitting on wheel chair can press a keypad to generate sound from voice board.

Keywords

MEMS, IRsensor, Circuit Relay

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P. T. Kasthuri Bai ¹, M. Sundararajan

Affiliations
1 Bharathiar University, Coimbatore - 641 046, Tamil Nadu, IN

Abstract

Objectives: Comparison of performance efficiency of AODV and OLSR routing protocol in MANETs using NS2 tool. The parameters considered and compared for throughput, packet delivery ratio, energy spent and delays. Methods/Analysis: Using NS2, first a sample of 50 nodes was generated and moved move randomly. Dynamic clustering was done within the sample area of 500x500sq.m. 50 nodes were set up as sink nodes and attached a local agent and loss monitor for each node. These nodes were positioned in the sample area. The nodes 17, 28, 35 were set up as source and nodes were set up as destination for transmission of packets, respectively. Findings: The four performance measures were: Energy spent, PDR, end-to-end delay and throughput with number of nodes as constant (50) and with different speed (time) of node like 2,4,6,8,10s are taken for comparison. Transmission of packet was tested using AODV and the performance metrics are traced. Similarly the performance metrics were tested with OLSR protocol. The values were tabulated and a graph was generated for each metric in Y-axis and time in X-axis. Novelty of the Study: A VMware workstation was installed and tested in unix environment using tool command language the modules were created in vi editor. They were executed using ns command. This paper is main module. Further malicious node detection and elimination was done to still prove OLSR outperforms than AODV. Conclusion: In all the above four metrics the OLSR protocol performance is efficient than AODV when data transmission occurs between nodes in MANETs. From the results obtained we can observe OLSR outperforms AODV in all four parameters irrespective of different speed (time).

Keywords

AODV (Adhoc on Demand Distance Vector), MANET (Mobile Adhoc Networks), NS (Network Simulator), OLSR (Optimized Link State Routing Protocol), PDR (Packet Delivery Ratio)

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R. Shankar ¹, M. Sundararajan ²

Affiliations
1 Bharathiar University, Coimbatore - 641 046, Tamil Nadu, IN
2 Department of Computer Science, Government Arts College, Nandanam, Chennai - 600035, IN

Abstract

Background/Objectives: This research study has been conducted in a scientific way to help manufacturing engineers and the management team to find out the hidden information from the data which are generated during the everyday manufacturing process. Methods/Statistical analysis: The methodology adopted in this activity is applying outlier analysis which is a data mining technique. The inter quartile range findings and analysis has been used here to find the hidden useful information from the process data with which a better insight could be established towards the improvement of quality of the product. The data used here have been collected from the automotive engine assembly and testing process. The study compares the results between the conventional and outlier analysis. Findings: The conventional style of checking and approving the engines based on the value pattern of Specific Fuel Consumption (SFC) which uses the design specification comparison with the actual data generally yields very minimal scope for the improvement of product quality in the perspective of design, Safety and reliability of the product because of the adherence of the same design specifications of the part drawings supplied by various suppliers. The competitive automotive manufacturing domain demands a different approach with which a better scope could be identified towards the improvement of product quality which is undoubtedly data mining. The outlier analysis using inter quartile range on the sample data of 500 engines revealed many important aspects where the improvement scope for quality has been identified as 15,000 Parts Per Million (PPM) against400 PPM of conventional quality analysis for the same data. Improvement/Application: This research is to offer an inclusive model hypothetically with actual data both for engineering and management people of manufacturing domain about the insights and benefits of employing data mining techniques towards the improvement of product quality with proven results.

Keywords

Automotive Engine Testing, Data Mining, Inter Quartile Range, Manufacturing Quality, Outlier Analysis.

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P. T. Kasthuri Bai ¹, M. Sundararajan ¹

Affiliations
1 Bharathiar University, Coimbatore - 641046, Tamil Nadu, IN

Abstract

Objectives: Mobile ad hoc networks (MANETs) is a suitable environment for unknown or unspecified communications. It is an infra-structureless network. Standard protocols like AODV, OLSR and DSR are used in routing packets. In this paper, we compare AODV protocol with SRP protocol enforcing a Black hole, worm hole and Sybil attacks. Group signature is used to authenticate the route requests and to defend the potential active attacks without exposing the node identities. During the transmission, the intermediary nodes does not know the actual destination since onion routing concept along with route verification message is used. Methods/Analysis: Using NS2, first a sample of 50 nodes is generated and is made to move randomly. Dynamic clustering is done within the sample area of 500 x 500 sq.m. Set up 50 nodes as sink nodes and attach a local agent and loss monitor for each node. Position these nodes in the sample area. The nodes 0,20,22,10 were set up as source and nodes 24, 9, 2, 14 were set up as destinations respectively for transmission of packets. Findings: The four performance measures Energy spent, Packet Delivery ratio, delay and throughput or output with 6 attacker nodes (50, 51, 52, 53, 54 and 55) with different simulation time like 2, 4, 6, 8, 10s are taken for comparison. Transmission of packet is tested using AODV and the performance metrics are traced. Similarly the performance metrics are tested with SRP protocol. The values are tabulated and a graph is generated for each metric in Y-axis and time in X-axis. From the results obtained we can observe SRP outperforms AODV in all four parameters. Novelty of the Study: A VMware workstation is installed and tested in Unix environment using tool command language the modules are created in vi editor. They are executed using ns command. This paper compares the performance of SRP with AODV enforcing attacker nodes. Conclusion: During data transmission between nodes in MANETs the SRP protocol outperforms AODV. The result analysis below shows the four performance measures Energy spent, PDR, end-to-end delay and throughput.

Keywords

AODV (Adhoc Ondemand Distance Vector), Group Signature, SRP (Secured Routing Protocol), Unidentifiability, Unlinkability.

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S. Arul Selvi ¹, M. Sundararajan ¹

Affiliations
1 Electronics and Communication Engineering, Bharath University, Chennai – 600 073, Tamil Nadu, IN

Abstract

Background/Objectives: Cognitive radio network is the evolutionary network to solve the spectrum scarcity problem. Primary User Emulation Attack is a major security issue that cause to fail the dynamic spectrum access of the cognitive radio network. Methods/Statistical Analysis: This paper proposes two level verification of the primary user signal to enhance the security of the spectrum sensing under PUEA attack. Support Vector Machine is used in the two level verification for detector classify the received data in to a location boundary and higher order statics at second level. Findings: At first level using the location information of the primary user, the primary user signal is verified for its validity. The SVM is first trained to learn the Primary user Location and with the help of known location of the Primary user it can be verified. Then the trained SVM is used to find the location boundary of the user that transmitted the signal. If the signal boundary is within the primary used location boundary it is concluded that the signal is from the primary user; else it is from the PUEA attacker .After verifying in the first level on the second level higher order statics values are calculated then using that as the feature vector the SVM classifier is used to classify the received signal as two class: one from original primary user and other from the PUEA attacker. This two level verification of the primary user signal will be more accurate method of PUEA attack detection comparing to the single level schemes. Applications/Improvements:This two level verification scheme improves the accuracy from 82% at Linear SVM kernel to 100% and also from 77% at RBF SVM kernel to 100%.

Keywords

Cognitive Radio Network, Dynamic Spectrum Access, Primary user Emulation Attack, Support Vector Machines.

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