Gunasekaran P.

Viswanathan S.

Viswanathan K.S.

Samuel A.A.

Prabaharan S.R.S.

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

2017 International Conference on Nextgen Electronic Technologies: Silicon to Software (ICNETS2)

[Front matter]

Background In opportunistic networks, there is no complete path between source and destination and all the nodes are in mobility. Opportunistic networks exploit the potential capability of existing mobile nodes, such as data forwarding without any preplanted infrastructures. In gradient-based routing, relay nodes are selected using a gradient value that leads to less assurance to reaching the destination. So finding the location of the relay node is an important criterion, which resolves to loop the packets within the network. Localization is one of the critical issues for handling emergency rescue message in opportunistic networks. Method In gradient-based localization, choose the best neighbor node that is near to the sink as a relay node. Nodes are two types in the network; they are anchor nodes and sensor nodes. Anchor node is equipped with GPS receiver, and sensor nodes are randomly deployed in canvas. Anchor position is considered as a reference, and in turn sensor nodes position is computed using a hybrid approach. Hybrid approach maps the anchor node coordinates, ToT (time of transmission), AoA (angle of arrival), and ToA (time of arrival) into a Cartesian plane in order to localize the sensor node position. After finding the sensor position, the relay node selection was based on near to the sink, which maximizes the emergency message discrimination toward the sink. Results Proposed localization and relay node selection were extensively simulated in OMNeT++. The simulation profile consists of 20 anchor nodes and 30 sensor nodes in the considered terrain dimension. The simulation result shows that the performance metric such as a Packet Delivery Ratio, throughput, and End-to-End Delay is enhanced and compared with existing gradient-based approach. This proposed scheme is most suitable for dissemination of a rescue message with least delay during emergency cases such as floods, volcano, and earthquake scenario. © Springer Nature Singapore Pte Ltd. 2019.

Wireless Communication Networks and Internet of Things Lecture Notes in Electrical Engineering

Gradient-Based Localization and Relay Nodes Selection in Delay Tolerant Mobile Opportunistic Networks for Emergency Rescue

The transportation of materials from/to storage and unloading points usually requires human for operating forklifts. There is a need for robotic automated guided vehicle (AGV) to minimize the human intervention and also a secured transmission system between the user and the AGV. The objective of this study is to develop wireless data acquisition and communication system for AGV. The core of the system lies in the wireless communication protocol and requires secure transmission of data to be exchanged between the user and the AGV, hence the Transmission Control Protocol/Internet Protocol (TCP/IP). The data acquisition from the AGV is accomplished with the help of sensors mounted on the vehicle that can continuously collect the incoming signals along the path, and they are transmitted wirelessly via Wi-Fi and the information is displayed to the user on a laptop. The DC to DC converter helps in charging the rechargeable battery to the nominal voltage. The warehouse management system is achieved with the MS access at the backend and the LabVIEW at the front end for creating, inserting, deleting, and updating the data wirelessly via Wi-Fi. The analog data from the sensors was collected with each sensor having a threshold level for obtaining the maximum or minimum level that is encountered during the travel. The data from the AGV is obtained to the user by establishing connection through IP address. The warehouse management system provides more accuracy and prevents human blunders when compared to traditional system. They are able to insert or update in fraction of second, and these data can be viewed by anyone. The battery management system is able to charge the rechargeable battery at a faster rate. The AGV is able to transport goods from one location to the other in a predefined path. The data acquisition from the sensors provides a means of navigation system for the vehicle. These vehicles are mainly used in the industrial warehouse that reduces the labor cost and enhances accuracy. © Springer Nature Singapore Pte Ltd. 2019.

Wireless Data Acquisition and Communication System for Automated Guided Vehicle

In this paper, the significance of the CSI feedback acquisition at the WLAN AP is highlighted. CSI is the channel state information obtained from the physical layer to support the throughput enhancement in the upper layer. However, this information should be optimized in order to mitigate the feedback overhead with the increasing number of users. Here, a survey of existing CSI feedback algorithms with the current 802.11 WLAN standards is done by considering factors like overhead, delay, and throughput performance. We also discussed the user selection and scheduling in MU-MIMO-based WLANs. The scheduling is usually performed with the help of feedback CSI from selected users. However, acquiring CSI from all user STAs results in large overhead and grows linearly with the channel sounding interval and with the increased number of users. The current literature is more focused on reducing CSI overhead. In order to fully realize the benefit of MU-MIMO and guarantee the required QoS, it is important to acquire updated CSI from all the users. Hence, there exists a trade-off between efficiency of scheduler and CSI overhead. Generally, the AP limits the number of users based on feedback CSI. The best user CSI and suitable channels are needed to be obtained before the user is scheduled. © Springer Nature Singapore Pte Ltd. 2019.

Contention-Based CSI Feedback Mechanisms in MU-MIMO WLANs: A Survey

Analysis on LTE/Wi-Fi Data Offloading in Hetnets

Objectives Traffic signals are pre-timed/fixed cycle in which the duration of green light and red light is fixed irrespective of the number of vehicles at the traffic signal, which causes congestion in most cases. Most of the research done on pre-timed traffic signal focuses on deriving formulas for the better estimation of the delay experienced by vehicles. Proposed method of adaptive traffic signals can be used to minimize the congestion problem occurring at the intersection due to pre-timed traffic signal, thereby minimizing the delay to a greater extent. Methods/Statistical Analysis In this paper, the vehicles are considered to arrive based on a Poisson distribution. The probability generating function of queue lengths at the beginning of kth and k + 1th cycle is derived. Based on the queue length for each direction, the optimal duration of red and green light is derived. Findings In the proposed work, it is showed that the performance of adaptive queue length-based switching is efficient than the pre-timed/fixed traffic signaling. Based on the traffic arrival pattern, the threshold of the red and green light can be set to minimize the delay/congestion. Application/Improvements In this proposed work, the congestion problem is minimized by using the adaptive signal switching and the performance of system can be improved in heavy traffic scenario. © Springer Nature Singapore Pte Ltd. 2019.

Journal	Data powered by Typeset2017 International Conference on Nextgen Electronic Technologies: Silicon to Software (ICNETS2)
Publisher	Data powered by TypesetIEEE
Open Access	0