Ashish Rauniyar

• Rauniyar, Ashish; Engelstad, Paal E. & Østerbø, Olav Norvald (2020). Capacity Enhancement of NOMA‐SWIPT IoT Relay System with Direct Links over Rayleigh Fading Channels. Transactions on Emerging Telecommunications Technologies.  ISSN 1124-318X. . doi: 10.1002/ett.3913 Show summary

  It is known that when the direct links between the base station (BS) and the users exist and are nonnegligible, consolidating direct links could significantly enhance the performance of the cooperative relaying systems. Therefore, taking the impact of direct link into account, in this article, we investigate the capacity enhancement of the nonorthogonal multiple access (NOMA) with simultaneous wireless information and power transfer (SWIPT) for the Internet of Things (IoT) relay systems over the Rayleigh fading channels. Specifically, for the considered NOMA‐SWIPT system with direct links, we study a time‐switching energy harvesting (EH) architecture in which a BS transmits two symbols to the two users through the direct links and via an EH‐based relay node. On the receiving user node, we employ maximum ratio combining (MRC) to show the capacity enhancement of the considered system. Moreover, analytical expressions for the Ergodic capacity and Ergodic Sum Capacity are mathematically derived for the MRC and single signal decoding scheme, and the analytical expressions are corroborated with the Monte‐Carlo simulation results. This not only reveals the effect of different EH parameters on the system performance but it also demonstrates the capacity enhancement of the considered NOMA‐SWIPT system compared to a similar system without direct links and to conventional OMA schemes.

• Rauniyar, Ashish; Engelstad, Paal E. & Østerbø, Olav Norvald (2020). Ergodic Sum Capacity Analysis of NOMA‐SWIPT Enabled IoT Relay Systems. Internet Technology Letters (ITL). . doi: 10.1002/itl2.218 Show summary

  Instead of using the participating relay node only for relaying the data of the source node, in this letter, we have also considered transmitting the data of the relay node along with the source node data based on time switch-ing (TS), power splitting (PS) relaying and NOMA. Therefore, in this context, we investigate the ergodic sum capacity (ESC) analysis of simultaneous wireless information and power transfer (SWIPT) based non-orthogonal multiple access (NOMA) for the Internet of Things (IoT) relay systems. Furthermore, we also study the effect of both perfect successive interference cancellation (pSIC) and imperfect SIC (ipSIC) on the proposed system. Analytical expressions for the ESC under both pSIC and ipSIC scenarios are mathematically derived and corroborated through Monte-Carlo simulations. Our result demonstrates that the PS relaying with NOMA is more energy-efficient than TS relaying with NOMAfor the proposed system.

• Rauniyar, Ashish; Engelstad, Paal E. & Østerbø, Olav Norvald (2020). On the Performance of Bidirectional NOMA-SWIPT Enabled IoT Relay Networks. IEEE Sensors Journal.  ISSN 1530-437X. . doi: 10.1109/JSEN.2020.3018905 Show summary

  In this paper, a bidirectional relaying (BR) non-orthogonal multiple access (NOMA) with simultaneous wireless information and power transfer (SWIPT) termed as BR NOMA-SWIPT is proposed and investigated for the Internet of Things (IoT) relay networks. Here, multiple NOMA users in one group can communicate or exchange information with multiple NOMA users in another group through a common energy harvesting (EH) based relay. The EH based relay exploits the radio frequency (RF) energy supplied by the two NOMA user groups to recharge itself, and then it exchanges the information between them. Specifically, the two groups of NOMA users transmit the information intended for the exchange to the relay node using the uplink NOMA protocol. The relay node first harvests the RF energy through the signals of the two group of NOMA users, and then it carries out the exchange of information between two NOMA user groups by using the downlink NOMA protocol. To the best of our knowledge, there is no existing study or research on BR NOMA with SWIPT. Therefore, in this paper, we examine in detail, the performance of BR NOMA-SWIPT enabled IoT relay networks. Specifically, we study a popular EH time switching (TS) relaying architecture with BR and NOMA. We also study the effect of both perfect successive interference cancellation (pSIC) and imperfect SIC (ipSIC) on the proposed BR NOMA-SWIPT system. Analytical expressions for the outage probability and ergodic capacity are mathematically derived. The analytical results of our proposed system model are validated by the simulation results, and representative performance comparisons are presented thoroughly, which not only provides practical insights into the effect of different system parameters on the overall network performance, but it also demonstrates that our proposed BR NOMA-SWIPT can attain significant throughput and capacity gains as compared to conventional BR multiple access schemes.

• Upreti, Ramesh; Rauniyar, Ashish; Kunwar, Jeevan; Haugerud, Hårek; Engelstad, Paal E. & Yazidi, Anis (2020). Adaptive Pursuit Learning for Energy‐efficient Target Coverage in Wireless Sensor Networks. Concurrency and Computation.  ISSN 1532-0626. . doi: 10.1002/cpe.5975 Show summary

  With the proliferation of technologies such as wireless sensor networks (WSNs) and the Internet of things (IoT), we are moving towards the era of automation without any human intervention. Sensors are the principal components of the WSNs that bring the idea of IoT into reality. Over the last decade, WSNs are being used in many application fields such as target coverage, battlefield surveillance, home security, health care monitoring, and so on. However, the energy efficiency of the sensor nodes in WSN remains a challenging issue due to the use of a small battery. Moreover, replacing the batteries of the sensor nodes deployed in a hostile environment frequently is not a feasible option. Therefore, intelligent scheduling of the sensor nodes for optimizing its energy-efficient operation and thereby extending the lifetime of WSN has received a lot of research attention lately. In particular, this article investigates extending the lifetime of the WSN in the context of target coverage problems. To tackle this problem, we propose a scheduling technique for WSN based on a novel concept within the theory of learn-ing automata (LA) called pursuit LA. Each sensor node in the WSN is equipped with anLA so that it can autonomously select its proper state, that is, either sleep or active, with an aim to cover all targets with the lowest energy cost possible. Our comprehensive experimental testing of the proposed algorithm not only verifies the efficiency of our algorithm, but it also demonstrates its ability to yield a near-optimal solution. The results are promising, given the low computational footprint of the algorithm.

• Pokhrel, Ramesh; Rauniyar, Ashish & Yazidi, Anis (2019). In the Quest of Trade-off between Job Parallelism and Throughput in Hadoop: A Stochastic Learning Approach for Parameter Tuning on the Fly, In Hui Tian; Hong Shen & Wee Lum Tan Tan (ed.),  2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies.  IEEE conference proceedings.  ISBN 978-1-7281-2616-6.  5C.  s 448 - 453 Show summary

  With the emergence of the concept of big data, Hadoop MapReduce has been the de facto standard programming model for processing a large amount of data stored on the different cluster nodes in a distributed manner. It is known that the implementation of MapReduce operation with the default configuration yields a low number of parallel running jobs. In fact, poor resource utilization and overall low performance are usually induced by the default configuration. Although a myriad of works has been carried out in the literature for optimally configuring Hadoop MapReduce, the absolute vast majority of those works only consider offline and static configuration. Those approaches are clearly ineffective as the load might change during execution requiring tuning again the configuration parameters. In this work, we rather focus on dynamical and adaptively configuring Hadoop MapReduce by changing the system level Maximum Application Master Resource in Percent (MARP) parameter on the fly. We show that adaptively tuning the MARP parameter yields a good trade-off between job parallelism and throughput. To achieve this, an optimal design which we call Adaptive Parameter Tuning of Hadoop (APTH) based on a novel variant of the Tsetlin Automata is devised. Comprehensive experimental results show that the resources are optimally and appropriately utilized, resulting in better job parallelism and throughput. Furthermore, it is found that our APTH approach spends 47% less time for job execution as compared to the default configuration.

• 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 Full text in Research Archive.
• 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 Full text in Research Archive. 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 (SIP).  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 (IJDSN).  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 (IJDSN).  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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