Ashish Rauniyar

• Rauniyar, Ashish; Engelstad, Paal E. & Østerbø, Olav Norvald (2019). Performance Analysis of RF Energy Harvesting and Information Transmission based on NOMA with Interfering Signal for IoT Relay Systems. IEEE Sensors Journal.  ISSN 1530-437X.  19(17), s 7668- 7682 . doi: 10.1109/JSEN.2019.2914796
• Rauniyar, Ashish; Kunwar, Jeevan; Haugerud, Hårek; Yazidi, Anis & Engelstad, Paal E. (2019). Energy Efficient Target Coverage in Wireless Sensor Networks Using Adaptive Learning, In Imem Jemili & Mohamed Mosbah (ed.),  Distributed Computing for Emerging Smart Networks.  Springer Nature.  ISBN 978-3-030-40131-3.  9.  s 133 - 147 Show summary

  Over the past few years, innovation in the development of Wireless Sensor Networks (WSNs) has evolved rapidly. WSNs are being used in many application fields such as target coverage, battlefield surveillance, home security, health care supervision, and many more. However, power usage in WSNs remains a challenging issue due to the low capacity of batteries and the difficulty of replacing or charging them, especially in harsh environments. Therefore, this has led to the development of various architectures and algorithms to deal with optimizing the energy usage of WSNs. In particular, extending the lifetime of the WSNin the context of target coverage problems by resorting to intelligent scheduling has received a lot of research attention. In this paper, we propose a scheduling technique for WSN based on a novel concept within the theory of Learning Automata (LA) called pursuit LA. Each sensor node in the WSN is equipped with an LA so that it can autonomously select its proper state, i.e., either sleep or active with the aim to coverall targets with the lowest energy cost. Through comprehensive experimental testing, we verify the efficiency of our algorithm and its ability to yield a near-optimal solution. The results are promising, given the low computational footprint of the algorithm.

• Rauniyar, Ashish; Hagos, Desta Haileselassie & Shrestha, Manish (2018). A Crowd-Based Intelligence Approach for Measurable Security, Privacy, and Dependability in Internet of Automated Vehicles with Vehicular Fog. International Journal of Mobile Information Systems.  ISSN 1574-017X.  2018, s 1- 14 . doi: 10.1155/2018/7905960 Full text in Research Archive. Show summary

  With the advent of Internet of things (IoT) and cloud computing technologies, we are in the era of automation, device-to-device (D2D) and machine-to-machine (M2M) communications. Automated vehicles have recently gained a huge attention worldwide, and it has created a new wave of revolution in automobile industries. However, in order to fully establish automated vehicles and their connectivity to the surroundings, security, privacy, and dependability always remain a crucial issue. One cannot deny the fact that such automatic vehicles are highly vulnerable to different kinds of security attacks. Also, today’s such systems are built from generic components. Prior analysis of different attack trends and vulnerabilities enables us to deploy security solutions effectively. Moreover, scientific research has shown that a “group” can perform better than individuals in making decisions and predictions. Therefore, this paper deals with the measurable security, privacy, and dependability of automated vehicles through the crowd-based intelligence approach that is inspired from swarm intelligence. We have studied three use case scenarios of automated vehicles and systems with vehicular fog and have analyzed the security, privacy, and dependability metrics of such systems. Our systematic approaches to measuring efficient system configuration, security, privacy, and dependability of automated vehicles are essential for getting the overall picture of the system such as design patterns, best practices for configuration of system, metrics, and measurements.

• Rauniyar, Ashish; Engelstad, Paal E. & Moen, Hans Jonas Fossum (2018). A New Distributed Localization Algorithm Using Social Learning Based Particle Swarm Optimization for Internet of Things. IEEE Vehicular Technology Conference (VTC) Proceedings.  ISSN 1550-2252.  2018-June, s 1- 7 . doi: 10.1109/VTCSpring.2018.8417665
• Rauniyar, Ashish; Engelstad, Paal E. & Østerbø, Olav Norvald (2018). RF Energy Harvesting and Information Transmission based on Power Splitting and NOMA for IoT Relay Systems, In  2018 IEEE 17th International Symposium on Network Computing and Applications (NCA).  IEEE conference proceedings.  ISBN 978-1-5386-7659-2.  RF Energy Harvesting.
• Rauniyar, Ashish; Engelstad, Paal E. & Østerbø, Olav Norvald (2018). RF Energy Harvesting and Information Transmission in IoT Relay Systems based on Time Switching and NOMA, In Mark A Gregory (ed.),  2018 28th International Telecommunication Networks and Applications Conference (ITNAC).  IEEE conference proceedings.  ISBN 978-1-5386-7177-1.  Internet of Things.  s 168 - 174 Show summary

  A huge expansion of billions of Internet of Things (IoT) sensor and devices is expected over the next few years which will consume more power. Therefore, energy efficiency is a major concern for the development of fifth generation (5G) wireless systems. In wireless communication systems, energy harvesting (EH) is an emerging paradigm that allows the sensor nodes to recharge themselves through radio frequency (RF) signals directed to them from the source node and then relaying or transmitting the information. Although a myriad of works have been carried out in the literature for EH, the absolute vast majority of those works only consider RF EH at relay node and transmission of source node data successfully to its destination node. Those approaches do not consider the data transmission of the relay node that may be an IoT node which needs to transmit its data along with the source node data to their respective destinations. Thus, such approaches are clearly ineffective for energy efficient IoT relay systems. In this paper, we rather focus on RF EH and information transmission based on time switching (TS) relaying and non-orthogonal multiple access (NOMA) for IoT relay systems. A source node information data is relayed through power constrained IoT relay node that first harvests the energy from source node RF signal using TS protocol and then transmits source node information along with its information using NOMA protocol. We have mathematically derived analytical expressions for outage probability, throughput and sum-throughput for our proposed system. We have also formulated an algorithm to find out optimal TS factor that maximizes the sum-throughput for our proposed system. Our proposed system analytical results are validated by the simulation results.

• Rauniyar, Ashish; Engelstad, Paal E. & Østerbø, Olav Norvald (2018). RF energy harvesting and information transmission based on NOMA for wireless powered IoT relay systems. Sensors.  ISSN 1424-8220.  18:3254(10), s 1- 22 . doi: 10.3390/s18103254 Full text in Research Archive.
• Rauniyar, Ashish & Shin, Soo Young (2018). Cooperative spectrum sensing based on adaptive activation of energy and preamble detector for cognitive radio networks. APSIPA Transactions on Signal and Information Processing.  ISSN 2048-7703.  7(2), s 1- 7 . doi: 10.1017/ATSIP.2018.5
• Rauniyar, Ashish; Irfan, Mohammad; Saputra, Oka Danil; Kim, Jin Woo; Lee, Ah Ra; Jang, Jae Min & Shin, Soo Young (2017). Design and Development of a Real-Time Monitoring System for Multiple Lead–Acid Batteries Based on Internet of Things. Future Internet.  ISSN 1999-5903.  9(3), s 1- 16 . doi: 10.3390/fi9030028 Show summary

  In this paper, real-time monitoring of multiple lead-acid batteries based on Internet of things is proposed and evaluated. Our proposed system monitors and stores parameters that provide an indication of the lead acid battery’s acid level, state of charge, voltage, current, and the remaining charge capacity in a real-time scenario. To monitor these lead–acid battery parameters, we have developed a data acquisition system by building an embedded system, i.e., dedicated hardware and software. The wireless local area network is used as the backbone network. The information collected from all the connected battery clients in the system is analyzed in an asynchronous transmission control protocol/user datagram protocol-based C♯ server program running on a personal computer (server) to determine important parameters like the state of charge of the individual battery, and if required, appropriate action can be taken in advance to prevent excessive impairment to the battery. Further, data are also displayed on an Android mobile device and are stored in an SQL server database. We have developed a real prototype to devise an end product for our proposed system.

• Rauniyar, Ashish; Engelstad, Paal E.; Feng, Boning & Do, van Thanh (2016). Crowdsourcing-based Disaster Management using Fog Computing in Internet of Things Paradigm, In Randall Bilof (ed.),  2016 IEEE 2nd International Conference on Collaboration and Internet Computing (CIC).  IEEE.  ISBN 978-1-5090-4607-2.  Workshop: CIC-DM 2016.  s 490 - 494
• Rauniyar, Ashish & Shin, Soo Young (2015). Multiple Antenna-Aided Cascaded Energy and Matched Filter Detector for Cognitive Radio Networks. International Journal of Distributed Sensor Networks.  ISSN 1550-1329.  11(9) . doi: 10.1155/2015/175943 Show summary

  A new multiple antenna-aided cascaded energy and matched filter detector (MCEM) for cognitive radio networks is proposed. Our proposed scheme is equipped with multiple receive antennas employing energy efficient energy detector (ED) and reliable matched filter (MF) to mitigate the channel fading and increase the detection performance of the secondary users (SUs). Partial decisions are first made by using cascaded energy and matched filter detector (CEM) at each antenna and then the final collaborative decision is made based on those partial decisions. The probability of detection/false alarm of the proposed scheme is presented in terms of the complementary receiver operating characteristics (ROCs). The performance of MCEM scheme is explored via MATLAB simulations that implement the clear channel assessment (CCA) modules for IEEE 802.15.4. Simulation results showed that our proposed MCEM scheme improves the detection performance and is more energy efficient as compared to CEM scheme employing single antenna and other conventional schemes.

• Triwicaksono, Dimas; Rauniyar, Ashish & Shin, Soo Young (2015). Cascaded Energy Detector and Matched Filter-Clear Channel Assessment for Wireless Network. Wireless personal communications.  ISSN 0929-6212.  84(4), s 2427- 2443 . doi: 10.1007/s11277-015-2713-7 Show summary

  In this paper, a novel cascaded-clear channel assessment (CCA) method: cascaded energy detector matched filter (CEM) is proposed for wireless network. CEM cartel the advantages of two CCA mechanisms, energy efficient energy detector (ED) and reliable matched filter (MF) to devise a new approach of CCA in wireless network. The probability of detection and false alarm of CEM are depicted in receiver operation curves and are compared with other CCA methods such as ED, MF, preamble detection (PD), and cascaded CCA (Shin et al. in Trans Internet Inf Syst 5(8):1404–1422, 2011) through simulations and analytic calculations. The performance of CEM is evaluated via simulations that implement CCA modules and medium access control protocol for IEEE 802.15.4 as a representative example. Throughput, energy consumption and energy efficiency are used for the performance measurement of our proposed CEM detector. Simulation results show that CEM has higher energy efficiency among other CCA methods and higher throughput compared to Shin et al. (Trans Internet Inf Syst 5(8):1404–1422, 2011).

• Rauniyar, Ashish & Shin, Soo Young (2015). A Novel Energy-Efficient Clustering Based Cooperative Spectrum Sensing for Cognitive Radio Sensor Networks. International Journal of Distributed Sensor Networks.  ISSN 1550-1329.  11, s 1- 8 . doi: 10.1155/2015/198456 Show summary

  Cognitive radio has been proposed as a promising way to effectively utilize the scarce spectrum resources. A cognitive radio sensor network (CRSN) is a wireless sensor network that is equipped with cognitive radio capability. Clustering is a popular technique that can be applied to wireless sensor networks, although it has been proven to be a challenge to implement it in CRSNs. Moreover, few proposals have successfully applied energy-efficient clustering techniques in CRSNs. Therefore, with the aim of increasing energy efficiency, network lifetime, network stability, and optimal cluster-head selection process, this paper proposes a novel energy-efficient clustering based on cooperative spectrum sensing (ECS) for CRSNs. The proposed ECS scheme utilizes the concept of pairing among sensor nodes and switches between Awake and Sleep modes for energy efficiency. A comprehensive simulation in MATLAB was carried out to validate the proposed method. The simulation results show that, compared with conventional methods, the proposed method is more energy efficient and that the overall CRSN's lifetime is prolonged.

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• Rauniyar, Ashish; Jeong, Dae Ro; Chand, G.S.L. Krsihna & Shin, Soo Young (2015). Performance Analysis of Cascaded Energy and Matched Filter Detector With Malicious Users in Cognitive Radio Networks. Show summary

  The inefficient use of valuable and scarce spectrum resources can be exploited by cognitive radio (CR) technology. For CR technology, an energy-efficient detection techniques with reliable detection performance can guarantee the protection of primary users (PU) from secondary users (SU) and prolong the lifetime of the networks. Also, such CR networks are prone to different kinds of attacks which put down the effective operation of the network. In this paper, we consider the performance analysis of cascaded energy and matched filter (CEM) detector in the presence of malicious users (MU). The observable sensing operation of CEM detector i.e., probability of detection is analyzed with the incorrect sensing information of the MUs. To bring down the consequence of MUs on the spectrum sensing efficiency, we suggest the use of authentication code which will be validated by the fusion center (FC) for overall decision-making process. We also showed that there lies an optimum authentication code required for the detection efficiency as the number of MU increases in the network. The equations for cooperative CEM detector’s false alarm and miss detection probabilities are formulated in the presence of MUs. Simulation results show the validity of suggested authentication code scheme for cooperative CEM detectors with MUs.

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