C. Fancy
SRM Institute of Science and Technology

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Journal : International Journal of Electrical and Computer Engineering

A study of remotely booking slot for vehicle using Internet of Things S. Metilda Florence; M. Uma; C. Fancy; G. Saranya
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (632.415 KB) | DOI: 10.11591/ijece.v10i5.pp5392-5399

Abstract

Internet Of Things (IoT) is a continually growing area which aids us to unite diverse objects. The proposed system exhibits the universal notion of utilizing cloud-based intellectual automotive car parking facilities in smart cities as a notable implementation of the IoT. Such services demonstrate to be a noteworthy part of the IoT and thus serving users in no small amount due to its pure commerce positioned qualities. Electromagnetic fields are being used by RFID to detect and track tags ascribed to objects automatically. The RFID technology is used in this system along with suitable IoT protocols to evade human interference, which reduces the cost. Information is bartered using readers and tags. RFID and IoT technologies are mainly used to automate the guide systems and make them strong and more accurate. Open Service Gateways can be effectively used for this module. This system established on the consequence of IoT and the purposes are solving the chaos, bewilderment, and extensive backlogs in parking spaces like malls and business parks that are customary as a consequence of the increased use of automobiles. The proposed work aims to solve these problems and offer car drivers a hassle-free and instantaneous car parking experience. While a number of nodes are positioned depends on topographical restrictions, positioning of prominent anchor sensor nodes in the smart parking is a primary factor against which the efficiency and cost of the parking system hang. A Raspberry Pi would act as a mini-computer in our system. A suitable smallest path methodology would be cast-off to obtain the shortest distance between the user and every car park in the system. Hence, the pausing time of the user is decreased. This work furthermore includes the practice of remotely booking of a slot with the collaboration of android application exercising smartphones for the communication between the Smart Parking system and the user.
Traffic-aware adaptive server load balancing for software defined networks C. Fancy; M. Pushpalatha
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2211-2218

Abstract

Servers in data center networks handle heterogenous bulk loads. Load balancing, therefore, plays an important role in optimizing network bandwidth and minimizing response time. A complete knowledge of the current network status is needed to provide a stable load in the network. The process of network status catalog in a traditional network needs additional processing which increases complexity, whereas, in software defined networking, the control plane monitors the overall working of the network continuously. Hence it is decided to propose an efficient load balancing algorithm that adapts SDN. This paper proposes an efficient algorithm TA-ASLB-traffic-aware adaptive server load balancing to balance the flows to the servers in a data center network. It works based on two parameters, residual bandwidth, and server capacity. It detects the elephant flows and forwards them towards the optimal server where it can be processed quickly. It has been tested with the Mininet simulator and gave considerably better results compared to the existing server load balancing algorithms in the floodlight controller. After experimentation and analysis, it is understood that the method provides comparatively better results than the existing load balancing algorithms.