Browsing by Author "Mohan, G."

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    A gene expression based quality of service aware routing protocol for mobile ad hoc networks
    (2013) Kubusada, Y.; Mohan, G.; Manjappa, M.; Guddeti, G.
    Mobile Ad Hoc Network (MANET) is a collection of infrastructure less multi-hop wireless mobile nodes which communicate together to achieve the global task. Despite lack of centralized control these mobile nodes still coordinate together to deliver the message to the destination node. MANET is gaining its popularity due to its easy deployment and self-organizing ability. In spite of its unique characteristics, mobility of mobile nodes causes frequent link breakups in MANET and thus makes route setup and maintenance a critical and challenging task. As real time and multimedia applications are increasing, there is a need of an efficient Quality of Service (QoS) aware routing protocol for MANET to support such applications. In the present work, the authors proposed an efficient QoS aware routing protocol for MANET based on upcoming Gene Expression Programming. In the proposed work, the information regarding the availability of resources is managed by a resource management module, which assists in selecting the resource rich path. Further, a theoretical proof is given for the proposed model for its correctness. The results are compared with the state of art artificial neural network and support vector regression methods from the performance evaluation point of view and the results are encouraging. © 2013 Springer Science+Business Media.
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    Determination of transient and steady state cutting in face milling operation using recurrence quantification analysis
    (2009) Mhalsekar, S.D.; Mohan, G.; Rao, S.S.; Gangadharan, K.V.
    Typical face milling operation involves transient and steady state cutting phases. Identification and distinction of the cutting state will primarily help in understanding the fundamentals of forced vibration, deflection and dynamic stability in milling system at the beginning and end of a cutting pass. Such type of investigation has advantages in process planning, tool geometry optimization and on-line fault diagnosis. An effort to provide estimation of transient and steady state cutting has been made using Recurrence Quantification Analysis (RQA) of vibration signals. RQA is a novel nonlinear analytical tool. It starts with construction of recurrence plot using embedded dimension and time delay. The recurrence plot is than quantified resulting in RQA. Face milling of H11 chromium steel has been carried out at two different cutting conditions and analyzed. The resulting RQA parameters could identify and distinguish transient and steady state cutting. © 2006-2009 Asian Research Publishing Network (ARPN).
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    A gene expression based quality of service aware routing protocol for mobile ad hoc networks
    (2013) Kubusada, Y.; Mohan, G.; Manjappa, K.; Ram Mohana Reddy, Guddeti
    Mobile Ad Hoc Network (MANET) is a collection of infrastructure less multi-hop wireless mobile nodes which communicate together to achieve the global task. Despite lack of centralized control these mobile nodes still coordinate together to deliver the message to the destination node. MANET is gaining its popularity due to its easy deployment and self-organizing ability. In spite of its unique characteristics, mobility of mobile nodes causes frequent link breakups in MANET and thus makes route setup and maintenance a critical and challenging task. As real time and multimedia applications are increasing, there is a need of an efficient Quality of Service (QoS) aware routing protocol for MANET to support such applications. In the present work, the authors proposed an efficient QoS aware routing protocol for MANET based on upcoming Gene Expression Programming. In the proposed work, the information regarding the availability of resources is managed by a resource management module, which assists in selecting the resource rich path. Further, a theoretical proof is given for the proposed model for its correctness. The results are compared with the state of art artificial neural network and support vector regression methods from the performance evaluation point of view and the results are encouraging. � 2013 Springer Science+Business Media.