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Articles by N. Karthikeyan
Total Records ( 9 ) for N. Karthikeyan
  R.M. Bhavadharini , S. Karthik and N. Karthikeyan
  Congestion in the network is a severe problem that affects the performance of MANET applications. When, a packet loss occurs in the wired medium, it clearly signs congestion in the network and suitable measures are taken to alleviate the effect of congestion. In a wireless environment, a packet can be lost for the factors such as wireless link error probability, link breakages, energy depletion, MAC contention fading and interference, etc. Due to various reasons contributing to the packet loss, Transmission Control Protocol (TCP) is unable to efficiently exploit the available network capacity in MANET. Across-layer congestion control algorithm with efficient Bandwidth Allocation and Dynamic Congestion Window Adaptation (CC-BADWA) is proposed in this study that uses TCP receiver’s prediction of bandwidth availability in the network and the receiver advertised window size back to the sender which then adjusts sender window. The timeout and the delayed acknowledgement can differently able the sender to predict the level of congestion in the network. When the acknowledgement is not received due to congestion in the network, the sender can estimate the transmission probability, adopt the dynamic congestion window size and transmit the packets. This improves the network throughput since, the sending rate is adjusted consistent to the currently prevailing network status. The bandwidth allocation uses the currently available bandwidth based on the present active connections and the route optimization proposed in this research selects the optimal path for data forwarding. The receiver’s timeliness helps to improve the network performance parameters throughput, end to end delay, packet delivery ratio of the existing method. The proposed algorithm is analyzed through ns 2 simulation tool.
  A. Kanmani , N. Karthikeyan and S. Geetha
  In this study, we propose a novel high capacity separable data hiding scheme that facilitates one to embed large amounts of data into the digital cover images. A natural image exhibits a property where neighbor pixel values are mostly similar and so, their differences are found to be close or equal to zero. Data is embedded into this difference histogram in a repetitive manner multiple times and thus the proposed scheme provides higher embedding capacity compared to the conventional histogram based techniques. The embedding is performed in the integer wavelet transform domain so as to make the system robust to attacks. Further, the proposed scheme uses minimal side information for restoring the cover image and the secret payload compared to the conventional schemes. Performance comparisons with other existing schemes are provided to demonstrate the superiority of the proposed scheme.
  R. Roopa Chandrika , N. Karthikeyan and S. Karthik
  Medical decision support system is a complex medical image analysis system that requires an efficient pattern classification tool that is easier to represent and to perform better classification of abnormalities present in medical images. Fuzzy Cognitive Map (FCM) is a simple, efficient cognitive tool used recently to model such complex and dynamic systems. FCM is integrated with medical decision support system that requires grading of suspicious tissues present in human body. FCM is used in this research to grade suspicious breast cancer cells with the texture properties extracted from digital mammograms. The map is constructed using the texture properties as its concepts and are interconnected based on the causal relationship among the concepts. The patterns or the features extracted from the digital mammogram are based on statistical measures suitable to distinguish between normal and abnormal tissues. GLCM (Gray Level Co-occurrence Matrix) and laws energy measures are statistical methods used in this research to obtain the textural features. The texture concepts used as input for the FCM tool have shown to classify the severity of abnormality present in digital mammograms better than the other classifiers that used training algorithms like neural network, decision trees, etc. The outcome of the automated reasoning of FCM is similar to the qualitative assessment tool used by the medical experts.
  C. Ram Kumar , S. Karthik and N. Karthikeyan
  Designing a sensor network as per the customer needs is the challenging task. While designing, we have to maintain some parameters like network life time, throughput, packet drop, congestion control, fairness and node energy. Congestion leads to the main issues in the network at both sender side and also in the receiver side. Congestion occurs due to more sensors, packet drop, receiving more packets than transmitting and buffer queue size. Here, we propose a fairness aware scheme with MRCCAP that shares the resource allocation, channel bandwidth. FACC protocol controls the congestion at base station which provides the support for QoS. Intermediate nodes are placed nearer to source and sink nodes to determine the flow rate, arrival time and queue size. Congestion avoidance algorithm deals with the ratio of the number of upstream nodes to the number of downstream nodes. In connection with gained weight buffer management with a probabilistic algorithm, it will provide efficient fairness and better network performance. The simulation results show that the proposed model provides better throughput, packet loss and network lifetime compared to the previous technique.
  R. Roopa Chandrika, , N. Karthikeyan and S. Karthik
  Medical decision support system is a complex medical image analysis system that requires an efficient pattern classification tool that is easier to represent and to perform better classification of abnormalities present in medical images. Fuzzy Cognitive Map (FCM) is a simple, efficient cognitive tool used recently to model such complex and dynamic systems. FCM is integrated with medical decision support system that requires grading of suspicious tissues present in human body. FCM is used in this work to grade suspicious breast cancer cells with the texture properties extracted from digital mammograms. The map is constructed using the texture properties as its concepts and are interconnected based on the causal relationship among the concepts. The patterns or the features extracted from the digital mammogram are based on statistical measures suitable to distinguish between normal and abnormal tissues. GLCM (Gray Level Co-occurrence Matrix) and Laws energy measures are statistical methods used in this work to obtain the textural features. The texture concepts used as input for the FCM tool have shown to classify the severity of abnormality present in digital mammograms better than the other classifiers that used training algorithms like neural network, decision trees etc. The outcome of the automated reasoning of FCM is similar to the qualitative assessment tool used by the medical experts.
  I. Kala , N. Karthikeyan and S. Karthik
  In a disaster recovery scenario, there may be some static wireless nodes at special service providing locations such as a medical camps or helipads and the other mobile nodes such as mobile equipment carried by a rescue personal or any transport vehicle. This forms a Quasi MANET in which the mobile nodes periodically communicate to the static nodes with some critical priority. In Quasi MANET under consideration, there are some percentage of node which are not at all mobile throughout whole time of operation. This research work main scope is to design and implement a location based AODV routing model for Quasi MANET scenario and evaluate its performance with normal AODV routing protocol and other MANET routing protocols. Hence implemented a Region based Route Request Processing in AODV (RRRP_AODV) and compared its performance with normal AODV. The arrived result verifies the noteworthy progress in performance of RRRP_AODV.
  S. Manikandan , N. Karthikeyan , K.S. Suganthi and K.S. Rajan
  Experiments were carried out with Fe2O3-water nanofluids to study possible enhancement in volumetric mass transfer coefficient for transfer of oxygen from air bubble to nanofluid, in an agitated, aerated bioreactor. The nanoparticles concentration was varied in the range of 0.022 to 0.065 wt.%, while the reactor was operated at three operating conditions viz. 200 rpm and 1.5 L min-1 of air flow, 100 rpm and 1.5 L min-1 of air flow and 200 rpm and 0.75 L min-1 of air flow. Nanoparticles were found to contribute to enhance oxygen transfer through ‘grazing effect’. An enhancement of 63% was observed for 0.065 wt.% Fe2O3-water operated at 200 rpm and 0.75 L min-1 air flow.
  N. Karthikeyan , S. Manikandan , M. Ganesh Kumar and S. Prabakaran
  Metal oxide materials are widely used as sensing material. Experimental studies have been conducted to explore the potential of fine metal oxide powders obtained by stirred bead milling for sensing of oxygen towards the thin film technique. Though the results indicate the potential of these materials for sensing, further optimization with respect to milling parameters and pelletizing are required to develop these as sensor materials.
  N. Karthikeyan , V. Palanisamy and K. Duraiswamy
 

Problem statement: Network wide broadcasting is an important function in Mobile Ad Hoc Networks (MANET), which attempts to deliver packets from a source node to all other nodes in the network. Broadcasting is often very useful for route discovery, naming, addressing and helping multicast operations in all kinds of networks. For designing broadcast protocols for ad hoc networks, one of the primary goal is to reduce the overhead (redundancy, contention and collision) while reaching all the nodes in network.
Approach: We had discussed many approaches in network wide broadcasting namely flooding, probability based, area based, network knowledge and cluster based broadcasting methods. The implementations and analysis will be made on Linux using the Network Simulator NS2.
Results: In this study, cluster based flooding algorithm had been proposed and its metrics were namely routing load and packet delivery ratio was compared with two common flooding algorithms namely simple flooding and probability based flooding.
Conclusion/Recommendations: It was concluded that simple flooding required each node to rebroadcast all packets. Probability based methods used some basic understanding of network topology, assigning a probability to node to rebroadcast. Cluster broadcasting algorithm for mobile ad hoc networks guaranteed to deliver messages from a source node to all nodes of network.

 
 
 
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