Faculty Publications
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Item Reliable cross layer design for e-health applications—iot perspective(Springer Science and Business Media Deutschland GmbH, 2018) Sarwesh, P.; Shet, N.S.V.; Chandrasekaran, K.Of late, there has been many applications are developed by the aid of IoT technology, such as smart city, e-health, smart home, industrial automation etc. In that, e-health is one of the efficient idea that is decidedly developed for healthcare sectors. IoT devices used in e-health applications are run by battery powered smart objects and low frequency links, which says energy constrained and unreliable nature of IoT network. Thus, providing potent healthcare service (regularly following and reporting the patients’ health information) in energy constrained network environment (battery power smart objects and low frequency links) is the prime need in resource constrained networks environment. In this chapter, reliable cross layer design is introduced to prolong the lifetime of IoT devices and reliable data transfer in IoT e-health applications. In proposed cross layer model, network layer and data link layer (MAC layer) are integrated. Reliability related parameter are included in route discover process and later MAC based power control technique make use of routing information, to obtain the suitable transmission power. Our results show that proposed cross layer design is reliable and energy efficient and it is more suitable for IoT e-health applications. © Springer International Publishing AG 2018.Item Topology Control in Wireless Sensor Networks: A Survey(Springer, 2019) Mahapatra, R.K.; Shet, N.S.V.Topology control is found to be a prominent strategy, to prolong the lifetime of WSNs. It helps to control the power consumption of the sensor nodes. In this paper, topology construction and topology maintenance are taken into account as a part of review of topology control. Topology construction algorithms encompass to frame the reduced form of topology. Topology maintenance helps in providing a reduced topology intermittently, as soon as the current topology becomes no longer optimum. Simulation results demonstrate that sensor node battery lifetime can be prolonged by the appropriate use of topology control. © 2019, Springer Nature Singapore Pte Ltd.Item Envisioned Network Architectures for IoT Applications(Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2019) Sarwesh, P.; Shet, N.S.V.; Chandrasekaran, K.Internet of Things is the auspicious technology that connects different internet enabled devices in single network architecture. IoT contributes effective service in various applications such as industrial automation, health care sectors, and home automation. Availability of low cost devices makes IoT as innovative paradigm in large-scale wireless network research. Challenges in IoT applications vary from each other. For example, in smart grid applications QoS is more important, whereas for land slide monitoring applications, energy efficiency and reliability are the major requirements. Thus, in this chapter, we come up with various network architectures that are suitable for IoT applications. The network architectures are designed by combining different optimization techniques into single network design, to satisfy specific network requirements. This chapter elaborates the major issues that affect the network performance and suitable solutions for those issues by means of efficient network architectures. © 2019, Springer International Publishing AG, part of Springer Nature.Item Congestion control mechanisms in vehicular networks: A perspective on Internet of vehicles (IoV)(Elsevier, 2022) Patil, A.; Muthuchidambaranathan, P.; Shet, N.S.V.Developing congestion control in highly mobile vehicular networks is a challenging task. The network of vehicles or heavy vehicles uses different data for communication depending on the required application. These networks are one of the main components of the Internet of Things (IoT), and the aim is to connect every vehicle to every other vehicle for the purpose of improving the user’s quality of life. To provide better network accessibility, channel utilization, and speedy delivery of the information over these networks, congestion control plays a significant role. In this chapter, we present various congestion control mechanisms for vehicular networks by considering different applications in these networks. The decentralized and centralized mechanisms are presented and their use in different types of vehicular networks is also suggested. In the end, we have listed some challenges to help researchers to expand their research in this area. © 2022 Elsevier Inc.Item Hybrid Malicious Encrypted Network Traffic Flow Detection Model(Springer Science and Business Media Deutschland GmbH, 2023) Hublikar, S.; Shet, N.S.V.Encrypted communication technology has evolved as the network, and Internet applications have advanced. Malicious communication, on the other hand, employs encryption to bypass standard detection and security protection. The existing security prevention and detection technologies are unable to identify harmful communication that is encrypted. The growth of artificial intelligence (AI) in these days has enabled to employ machine learning (ML) as well as deep learning approaches to identify encrypted malicious communications without decryption, with remarkably precise detection outcomes. At this moment, research on detecting harmful encrypted traffic is mostly focused on analyzing the features of encrypted data and selecting neural network (NN) techniques. Hybrid ML is proposed in this study by merging two well-performing data mining algorithms with natural language processing tasks. Here, a new traffic flow detection method is performed by the hybrid ML technique. At first, the benchmark data is collected from public sources. The features are extracted using the convolutional layer of deep convolutional neural network (DCNN). Then, the weighted feature extraction is performed by grasshopper optimization algorithm (GOA). Employed the hybrid machine learning-based malicious detection with the “support vector machine (SVM) and neural network (NN)” is utilized in this model to detect the traffic affected by malicious activities, where the hidden neuron count of NN and kernel of SVM are tuning by the same GOA for increasing the accuracy and precision. This research provides findings from experiment, encouraging various researchers to develop the research as future work. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item Experimental analysis of RSSI-based distance estimation for wireless sensor networks(Institute of Electrical and Electronics Engineers Inc., 2016) Mahapatra, R.K.; Shet, N.S.V.Research in Wireless Sensor Networks (WSNs) has revealed the location information of the sensor nodes seems to be the critical and the most important aspect, for the applications like environment monitoring, object tracking, health care etc. Estimation accuracy is needed in these kind of applications. In general, Signal strength decreases with the increase in distance. Hence the correlation that exists between the RSSI (Received Signal Strength Indication) value and distance is the key parameter for the ranging and localization of WSNs. This paper presents a model based on RSSI, which provides the distance estimation between sensor nodes in WSNs. Analysis of the model and performance evaluation is done in a real system, deployed in indoor environment using IRIS mote. Results of these evaluation would help to achieve accuracy in location estimation of WSNs. © 2016 IEEE.Item Analysis of series-fed microstrip array antennas(Presses Polytechniques Et Universitaires Romandes, 2016) Faisalbin Abdulmajeed, N.; Shet, N.S.V.; Rao, P.H.Series-fed array of square patches designed at 10 GHz, with three different configurations has been analyzed for sidelobe level and cross-polarization characteristics. A series-fed 8×2 planar array is analyzed to provide a sidelobe level of - 24.2dB and cross-polarization level of -21.8dB. The second configuration; a 2-line series array of 8 elements oriented back to back and fed with 180° out of phase exhibits a sidelobe level of - 25dB and low cross-polarization better than -51.6dB over all the angles. In the third configuration, a single line series array of 8 elements displaced on both the sides of the feed line is analyzed. The sidelobe level has been increased to -13.3dB with maximum cross-polarization level -27.7dB. The impedance bandwidth of 220MHz, 270MHz and 350MHz for a VSWR of 2, is observed for the three antenna types respectively. © 2016 IEEE.Item Energy aware routing protocol for resource constrained wireless sensor networks(Association for Computing Machinery acmhelp@acm.org, 2016) Prasad, S.; Jaiswal, S.; Shet, N.S.V.; Sarwesh, P.Wireless sensor network (WSN) is a developing technology that improves the resource utilization in various fields such as home automation, e-health, smart grid, precision agriculture etc. It consists of sensor devices, which works autonomously with its sensing, communication and computation capabilities. In most of the sensor network applications the nodes will be deployed in remote areas (land slide monitoring, wildlife monitoring etc.), so replacing the battery often is impossible in many WSN scenarios. Hence energy is considered as a valuable resource in resource constrained wireless sensor networks. In this paper, we propose a new routing methodology to improve the energy efficiency in resource constrained WSN. The proposed technique uses SNR (Signal to Noise Ratio), node degree and residual energy as routing parameters, to find an energy efficient and reliable path for data transmission. The combination of the parameters used in the proposed routing technique is done based on weighted sum approach. The proposed framework has been implemented on and compared with a number of standard energy efficient protocols and our results show considerable improvement in comparison to the existing techniques. © 2016 ACM.Item An index coded approach for reducing number of broadcasts in vehicular networks(Institute of Electrical and Electronics Engineers Inc., 2017) Patil, A.; Shekar, N.; Shet, N.S.V.Vehicular network standard demands a short range reliable vehicle-to-vehicle (V2V) communication with high mobility, also increasing amount of downloaded data in short encounters. Satisfying demands of clients with minimum number of transmissions using index coding has proven notable significance in wireless ad-hoc networks. The proper encoding at the server with side information leads to simultaneous satisfaction of clients with reduced amount of broadcasts. MERLIN (Maximum Expected download over Random LINks) is one of the fundamental protocols developed for optimizing downloads in vehicular networks over random encounter durations [1]. In this paper, we present I-MERLIN (Index coding based MERLIN) protocol and analyze its performance over MERLIN. We show that same amount of data can be downloaded from server in reduced number of transmissions, for single server multiple clients scenario. We also show that, I-MERLIN works well to satisfy multiple clients in minimum number of requests, which can be applicable for real road scenarios. © 2017 IEEE.Item Clustering and cooperative data transfer in VANETs using index coding(Inderscience Publishers, 2018) Patil, A.; Shet, N.S.V.Along with the prime aim of providing on-road safety, vehicular ad hoc networks have enabled the infotainment applications due to increasing demands from various travellers. The high mobility of nodes demands fast and efficient broadcasting of data. In this paper, we use index coding with clustering and cooperative downloading to satisfy various demands of travelling vehicles in reduced number of transmissions. The proposed index coding based protocol achieves better download throughput through V2V data exchange between clusters. Simulation results show that the proposed design achieves higher throughput than previously defined IEEE 1609.4 and Vehicular Enhanced Multichannel MAC (VEMMAC) protocols by reducing the total number of transmissions at the server. © © 2018 Inderscience Enterprises Ltd.