Kongu Engineering College

About: Kongu Engineering College is a based out in . It is known for research contribution in the topics: Cluster analysis & Control theory. The organization has 2001 authors who have published 1978 publications receiving 16923 citations.

Numerical and experimental investigation of temperature distribution inside a heating oven

Abstract: Commercial bakery ovens are used mainly to keep the foodstuffs warm. Minimum variations in temperature distribution among the foodstuffs and minimum energy consumption are the essential requirements. Heating ovens are presently available with heating coils placed at bottom. Temperature distribution inside the heating oven is not uniform. In order to make temperature distribution uniform, numerical and experimental investigations are carried out by keeping the heating coils at side, middle and bottom position of heating oven. From the investigations, minimum variations in temperature distribution have been found for side position and energy consumption is less compared with other positions. PRACTICAL APPLICATIONS Commercial bakery ovens are used mainly to keep the foodstuff in warm condition. An attempt is made in this paper to make the temperature distribution uniform among the various foodstuff inside the oven. The foodstuff inside the oven gets heat from the heating coils. The heating coil positions are reorganized in order to reduce the variation in temperature distribution and also to reduce the energy consumption. The experimental model used is similar to one that is used in the bakery shops. The outcomes of this paper are very useful in future fabrication of oven for preservation of foodstuff.

A proposed framework for cloud-aware multimodal multimedia big data analysis toward optimal resource allocation

Abstract: The main goal of this paper is to demonstrate the structural design of Multimodal Multimedia Services in Cloud Platform (MMSCP). Thus, our proposed MMSCP architecture is built of three levels such as, Service Platform, Execution Platform and Structural platform. The functionality of service platform is to gather different forms of video files generated by the media creators and to store these files on the local platform. The second execution platform integrates both the Hadoop and Mapreduce functionalities. Finally, QoS based cloud computing functionalities (i.e. load balancing, security, resource allocation and network traffic management) is employed at the third structural platform. Likely, we introduced the Crow Search Algorithm (CSA) in structural platform for optimal allocation of resources. We adapt a Hadoop cluster to perform the experiment. Also, to conduct the resource allocation experiment we used some of the conventional optimization algorithms such as, ABC, GA and PSO for comparison with our proposed CSA algorithm imposed on the structural platform. However, to evaluate the performance of the algorithms we configured the CloudAnalyst tool. The simulation results illustrate that the proposed algorithm can allocate the virtual machine (VM) optimally to attain a minimal response time.

Encrypted Network Traffic Classification and Resource Allocation with Deep Learning in Software Defined Network

Abstract: The climate has changed absolutely in every area in just a few years as digitized, making high-speed internet service a significant need in the future. Future Internet is supposed to face exponential growth in traffic, and highly complicated infrastructure, threatening to make conventional NTC approaches unreliable and even counterproductive. In recent days, AI Stimulated state-of-the-art breakthroughs with the ability to tackle extensive and multifarious challenges, and the network community is initiated by considering the NTC prototype from legacy rule-based towards a novel AI-based. Design and execution are applied to interdisciplinary become more essential. A smart home network supports various applications and smart devices within the proposed work, including e-health devices, regular computing devices, and home automation devices. Many devices accessible through the Internet by Home GateWay for Congestion (HGC) in a smart home. Throughout this paper, a Software-Defined Network Home GateWay for Congestion (SDNHGC) architecture for improved management of remote smart home networks and protection of the significant network's SDN controller. It enables effective network capacity regulation, focused on real-time traffic analysis and core network resource allocation. It cannot control the Network in dispersed smart homes. Our innovative SDNHGC expands power across the connectivity network, a smart home network enabling improved end-to-end monitoring of networks. The planned SDNHGC directly will gain centralized device identification by classifying traffic through a smart home network. Several of the current traffic classifications approach, checking deep packets, cannot have this real-time device knowledge for encrypted data to solve this issue.

A Feedback Aware Reliable Transport Protocol with Improved Window Increment Mechanism for Inter Vehicular Wireless Network

Abstract: In recent years, inter vehicular networking technologies are gaining momentum due to its merger with wireless internet through infrastructure gateways. A large quantity of internet data traffic heavily relies on transmission control protocol (TCP) due to reliable connection oriented services. TCP with sluggish window growth and weakly shaped congestion control mechanism fails under multi-hop inter vehicular conditions due to disjoint links and wireless channel errors. This paper introduces inter vehicular access network (IVAN) TCP, designed to suppress the limitations of congestion control and window increment algorithm in the multi-hop inter vehicular wireless environment. The IVAN’s flexible window increment algorithm newer growth pattern achieves a faster increase in the transmission rate. Furthermore, IVAN’s congestion control algorithm reduces the transmission rate based on sender’s window utility and relay router’s explicit congestion notification. The simulation results confirm the significant rise in IVAN’s throughput performance, substantial reduction in the queue packet drop and packet latency against standard TCP variants under inter vehicular environment.