i-manager Publications

i-manager's Journal on Wireless Communication Networks (JWCN)

Current Issue Vol. 13 Issue 1

Most Cited

A Review on Optimized FFT/IFFT Architectures for OFDM Systems
Balanced Unequal Clustering AlgorithmFor Wireless Sensor Network
HHT and DWT Based MIMO-OFDM for Various ModulationSchemes: A Comparative Approach
Study and Comparison of Distributed Energy Efficient Clustering Protocols in Wireless Sensor Network: A Review
Diagnosis of Anemia using Non-Invasive Anemia Detector through Parametrical Analysis

Volume 8 Issue 1 April - June 2019

Research Paper

Wireless Scada Using Raspberry Pi 3 and Arduino Nano V3

Ch. Venkateswara Rao* , Jamin Santiago**

* Department of Electrical and Electronics Engineering, Salalah College of Technology, Salalah, Sultanate of Oman.

** Department of Electrical Engineering, Salalah College of Technology, Salalah, Sultanate of Oman.

Rao, V., & Santiago, J.(2019). Wireless Scada Using Raspberry Pi 3 and Arduino Nano V3.i-manager’s Journal on Wireless Communication Networks, 8(1), 1-8. https://doi.org/10.26634/jwcn.8.1.16515

Abstract

SCADA or Supervisory Control And Data Acquisition is a system that allows companies to monitor and control industrial processes locally or at remote locations, gather and process real-time data, interact with devices such as sensors, valves, pumps, and motors through a human-machine interface (HMI) software, and record events into a log file. This project demonstrates a wireless SCADA system using a Raspberry Pi 3 Model B as the main unit which communicates with a Remote Terminal Unit (RTU) controlled by Arduino Nano. The graphical user interface (GUI) for central monitoring and control is hosted in the main unit while the RTU is equipped with sensors and actuators. The results indicate that the communication between the main and remote terminal units is a significant and potentially troublesome aspect of the system which must be carefully designed considering ease-of-use, latency, reliability, efficiency, and security. The study concluded that a Raspberry Pi 3 is a viable solution for implementing a wireless SCADA system together with microcontrollers and suitable communication modules.

References

[1]. Arduino. (2019). Arduino Nano. Retrieved from https://store.arduino.cc/usa/arduino-nano

[2]. Balsom, P. (2017, October 4). Wired vs. Wireless SCADA: The Future of Telemetry. Retrieved from https://htt.io/wired-vs-wireless-scada-the-future-oftelemetry/

[3]. Bentek Systems. (n.d.). An Introduction to SCADA. Retrieved from https://www.scadalink.com/support/ knowledge-base/an-introduction-to-scada/

[4]. Brook, C. (2018, December 5). What is SCADA Security? [Blog post] Retrieved from https://digital guardian.com/blog/what-scada-security

[5]. Douglas. (2016, October 28). Raspberry Pi 3 unable to Connect to Arduino with HC-06. Retrieved from https://www.raspberrypi.org/forums/viewtopic.php?p=10 59542

[6]. Fouda, H. (2010). Improving SCADA Operations Using Wireless Instrumentation. Schneider Electric. Retrieved fromhttps://www.automation.com/pdf_articles/SEWhitePaper- 8.5x11-ImprovingSCADA-V003.pdf

[7]. FreeWave Technologies, Inc. (2017, October 6). Where is SCADA Headed? Retrieved from https://freewave.com/where-is-scada-headed/

[8]. Raspberry Pi Foundation. (n.d.). Raspberry Pi 3 Model B. Retrieved from https://www.raspberrypi.org/products/ raspberry-pi-3-model-b/

[9]. Ray, B. (2015, March 5). Definitive Guide to Cellular SC ADA [Blog post]. Retrieved https://www.linklabs. com/blog/definitive-guide-to-cellular-scada

[10]. Sierra Wireless Inc. (2011). Wireless Communications in SCADA Systems. Retrieved from http://usatcorp.com/ pdf/Wireless-Comm-SCADA.pdf

[11]. TCCA. (2018). Technical Primer - Current and Emerging SCADA Wireless Bearers. TCCA. Retrieved from https://tcca.info/documents/2018-march_technical_ primer_current_and_emerging_scada_wireless_bearers. pdf/

[12]. Tsang, R. (2012, August 13). Cyberthreats, Vulnerabilities and Attacks on SCADA Networks. Retrieved from http://gspp.berkeley.edu/iths/Tsang_SCADA Attacks. pdf

[13]. Vaishnav, J. (2017). WiFi controlled LED using Raspberry Pi 3. Retrieved from https://www.instructables. com/id/Wifi-Controlled-LED-Using-Raspberry-Pi-3/

[14]. Watt, S. T., Loehner, H., Achanta, S. V., Kivi, A., & Rowland, B. (2015). Extending SCADA Networks Using Wireless Communications. In Power and Energy Automation Conference. Retrieved from http://cdn. selinc.com/assets/Literature/Publications/Technical Papers/6680_ExtendingSCADA_STW_20150123_ Web2.pdf?v=20170303-171956

[15]. Zingleman, E. J. (2000, December 28). Making the Right Choices for your Wireless SCADA System. Retrieved from https://wqpmag.com/making-right-choices-yourwireless- scada-system

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Research Paper

DOE to Identify the Most Significant Factor to Enhance the Performance of Defacto Star for Manets to Support Real Time Communication

C. P. V. N. J. Mohan Rao* , S. Pallam Setty **

*Department of Computer Science and Engineering, Avanthi Institute of Engineering and Technology, Narsipatnam, Andhra Pradesh, India.

**Department of Computer Science and Systems Engineering, AUCE (A), Andhra University, Visakhapatnam, Andhra Pradesh, India.

Rao, C., P., V., N., J., M., & Setty , S., P. (2019). DOE to Identify the Most Significant Factor to Enhance the Performance of Defacto Star for Manets to Support Real Time Communication. i-manager’s Journal on Wireless Communication Networks , 8(1),9-16. https://doi.org/10.26634/jwcn.8.1.16554

Abstract

MANETs are infrastructure less networks where each node must cooperate in the multi- hop routing process. Due to inherent characteristics such as dynamic topologies, band-width constraints, Energy constraints and distributed operation makes it a challenging area. Among the different categories of routing protocols, proactive routing protocols category is opted for the present study. In proactive routing protocols, Source Tree Adaptive Routing (STAR) with Least Overhead Routing approach (LORA) is chosen because it has less Network load when compared to Optimum Routing Approach (ORA). From the previous study of STAR routing protocol, it has a significant affect at lower mobility for all network sizes. In this paper, the most significant factor is identified to enhance the performance of defacto STAR routing protocol to support real time communication considering network size, mobility speed and Time to live (TTL) with response metrics Throughput, End-to-End Delay, Average Jitter using Taguchi Design of Experiments. At different network sizes with different lower mobility values, TTL is found as the most significant factor. We simulated the performance of STAR using QualNet simulator. According to the characteristics of a network routing protocol TTL plays a vital role. If TTL is too low, connection cannot be established and if it is too high energy consumption increases, which in turn affects the network life time. Our DOE experimental results revealed that, TTL is the most significant factor to enhance the performance of defacto STAR for MANETs to support real time communication. So, we conclude that our experimental results are strengthening the theoretical concept of the time-sensitive configurable parameters of the STAR routing protocol.

References

[1]. Attada, V., & Setty, S. P. (2015). Cross layer design approach to enhance the quality of service in mobile ad hoc networks. Wireless Personal Communications, 84(1), 305-319. https://doi.org/10.1007/s11277-015-2609-6

[2]. Cavin, D., Sasson, Y., & Schiper, A. (2002, October). On the accuracy of MANET simulators. In Proceedings of the Second ACM International Workshop on Principles of Mobile Computing (pp. 38-43). ACM. https://doi.org/10. 1145/584490.584499

[3]. Corson, S., & Macker, J. (1999). Mobile ad hoc networking (MANET): Routing protocol performance issues and evaluation considerations. RFC2501. https://doi.org/10.17487/RFC2501

[4]. Garcia-Luna-Aceves, J. J., & Spohn, M. (1999, October). Source-tree routing in wireless networks. In Proceedings. Seventh International Conference on Network Protocols (pp. 273-282). IEEE. https://doi.org/10. 1109/ICNP.1999.801950

[5]. Lee, M. H., Sarahintu, M., Mohamed, H., Sanugi, B., Olariu, S., & Zaharim, A. (2008, December). Performance evaluation of routing protocols for mobile ad hoc networks using statistical Taguchi's experimental design. In WSEAS International Conference. Proceedings. Mathematics and Computers in Science and Engineering (No. 13, pp. 220-226). WSEAS.

[6]. Manohar, M. P., & Setty, S. P. (2018a). Performance analysis of reactive routing protocols AODV, DYMO, DSR, LAR in MANETs. International Journal on Future Revolution in Computer Science & Communication Engineering (IJFRSCE), 4(3), 1-7.

[7]. Manohar, M. P., & Setty, S. P. (2018b). Taguchi design of experiments approach to find the most significant factor of DYMO routing protocol in mobile adhoc networks. imanager's Journal on Wireless Communication Networks, 7(1), 1-11. https://doi.org/10.26634/jwcn.7.1.1 4971

[8]. Mohamed, H., Lee, M. H., Sarahintu, M., Salleh, S., & Sanugi, B. (2008). The use of Taguchi method to determine factors affecting the performance of destination sequence distance vector routing protocol in mobile adhoc networks. Journal of Mathematics and Statistics, 4(4), 194-198. https://doi.org/10.3844/jmssp. 2008.194.198

[9]. Mohamed, H., & Lee, M. H. (2010). Taguchi approach for performance evaluation of routing protocols in mobile Adhoc networks. In Proceedings of the Regional Conference on Statistical Sciences (RCSS'10) (pp. 21-29).

[10]. Rawat, D., Gupta, N., & Shibu, S. (2015). Recognition of novel variance parameters using taguchi loss function in MANET. International Journal of Innovative Research in Computer and Communication Engineering, 3(1), 416- 426. https://doi.org/10.15680/ijircce.2015.0301063

[11]. Saxena, S., & Sinha, M. (2013). Single-response metric analysis of adaptive fault tolerant replication routing protocol for MANETs using Taguchi approach. International Journal of Computer Networking, Wireless and Mobile Communications (IJCNWMC), 3(3), 105-116.

[12]. Singh, C., Gupta, V., & Kaur, G. (2014). A Review paper on introduction to MANET. International Journal of Engineering Trends and Technology (IJETT), 11(1), 38-43. https://doi.org/10.14445/22315381/IJETT-V11P208

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Research Paper

Improving QoS for Voice Flow under Bursty Traffic in IEEE 802.11E

C. Ramakristanaiah* , P. Chenna Reddy , R. Praveen Sam *

* Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Kakinada, Andhra Pradesh, India.

Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Anantapur, India.

* Department of Computer Science and Engineering, G. Pulla Reddy Engineering College, Kurnool, Andhra Pradesh, India.

Ramakristanaiah , C., Reddy, P., S., & Sam, R., P. (2019). Improving QoS for Voice Flow under Bursty Traffic in IEEE 802.11E.i-manager’s Journal on Wireless Communication Networks , 8(1),17-23. https://doi.org/10.26634/jwcn.8.1.16253

Abstract

In Saturated conditions burst data can be generated for voice queue. IEEE 802.11e is not supported a large amount of burst transmission for any AC. IEEE 802.11e EDCA parameter set enables the Voice traffic to send several packets per one transmission opportunity (TXOP). If the network is saturated with all type of flows, it takes several TXOPs to complete transmission of all generated packets and this takes more time. Voice flow access the channel more times but to serve all generated packets, voice Access category (AC) needs more TXOPs. It indirectly affects the channel winning probability of other Queues. In this paper, a channel accessing method for Voice queue is proposed. If more voice packets has been generated for voice AC, the queue length will be increased. This length reaches ideal queue length, then adaptive channel access mechanism invoked. This method suspends the backoff procedure and take the channel unconditionally. So that bakoff time will be reused as TXOP instead of waiting. This method enables the voice access category to transmit more packets with in single TXOP. The simulations are conducted and results are analyzed. The results show that 91% of voice flow even at 512 Kbps has been sent over the network.

References

[1]. AlAlawi, K., & Al-Aqrabi, H. (2015, February). Quality of service evaluation of VoIP over wireless networks. In 2015 IEEE 8^th GCC Conference & Exhibition (pp. 1-6). IEEE. https://doi.org/10.1109/IEEEGCC.2015.7060070

[2]. Ansel, P., Ni, Q., & Turletti, T. (2004, March). An efficient scheduling scheme for IEEE 802.11e. In Proceedings. Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (pp. 24-26).

[3]. Dong, P., Wang, J., Huang, J., Wang, H., & Pan, Y. (2015). Improving performance of QoS applications for wireless networks. International Journal of Distributed Sensor Networks, 11(10), 385935. https://doi.org/10.1 155%2F2015%2F385935

[4]. Dong, P., Wang, J., Wang, H., & Pan, Y. (2015). Boosting VoIP capacity via service differentiation in IEEE 802.11 e EDCA networks. International Journal of Distributed Sensor Networks, 11 (3), 235-648. https://doi.org/10.1155% 2F2015%2F235648

[5]. IEEE 802.11e. (n.d.). Draft-2005. In Wikipedia, Retrieved from https://en.wikipedia.org/w/index. php?title=Special:ElectronPdf&page=IEEE+802.11& action=show-download-screen

[6]. Miraz, M. H., Molvi, S. A., Ganie, M. A., Ali, M., & Hussein, A. H. (2017). Simulation and analysis of quality of service (QoS) parameters of voice over IP (VoIP) traffic through heterogeneous networks. International Journal of Advanced Computer Science and Applications, 8(7), 242-248.

[7]. Moraes, R., Portugal, P., Vasques, F., & Custódio, R. (2010). Assessment of the IEEE 802.11e EDCA protocol limitations when dealing with real-time communication. EURASIP Journal on Wireless Communications and Networking, 2010(1), 351480. https://doi.org/10.1155/ 2010/351480

[8]. Prasetya, S., Rahmat, B., & Susanto, E. (2015, December). Quality of service improvement with 802.11e EDCA scheme using enhanced adaptive contention window algorithm. In 2015 IEEE International Conference on Communication, Networks and Satellite (COMNESTAT) (pp. 80-85). IEEE. https://doi.org/10.1109/COMNETSAT. 2015.7434292

[9]. Rashwand, S., & Misic, J. (2011). IEEE 802.11 e EDCA under bursty traffic-How much TXOP can improve performance. IEEE Transactions on Vehicular Technology, 60(3), 1099-1115. https://doi.org/10.1109/TVT.2011. 2107928

[10]. Rodrigues, D., Cerqueira, E., & Monteiro, E. (2009, October). QoE assessment of VoIP in next generation networks. In IFIP/IEEE International Conference on Management of Multimedia Networks and Services (pp. 94-105). Berlin, Heidelberg: Springer. https://doi.org/ 10.1007/978-3-642-04994-1_8

[11]. Taher, N. C., Doudane, Y. G., El Hassan, B., & Agoulmine, N. (2014). Towards voice/video application support in 802.11e WLANs: A model-based admission control algorithm. Computer Communications, 39, 41- 53. https://doi.org/10.1016/j.comcom.2013.10.006

[12]. Trad, A., Ni, Q., & Afifi, H. (2004, November). Adaptive VoIP transmission over heterogeneous wired/wireless networks. In International Workshop on Multimedia Interactive Protocols and Systems (pp. 25- 36). Springer, Berlin, Heidelberg. https://doi.org/10.1007/ 978-3-540-30493-7_3

[13]. Yu, J., Choi, M., Qiao, D., & Choi, S. (2009). Supporting VoIP services in IEEE 802.11e WLANs. International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642- 10625-5_31

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Research Paper

Performance Evaluation of CoAP Congestion Control Mechanisms in Global Event Traffic Scenario

Tejeswar Eluri*

Computer Science and Engineering, JNTUK, Kakinada, Andhra Pradesh, India.

Eluri, T. (2019). Performance Evaluation of CoAP Congestion Control Mechanisms in Global Event Traffic Scenario. i-manager’s Journal on Wireless Communication Networks, 8(1), 24-33. https://doi.org/10.26634/jwcn.8.1.16187

Abstract

The Internet Engineering Task Force (IETF) designed the Constrained Application Protocol (CoAP) for Internet of Things (IoT) gadgets. The IoT devices with restricted radio channel limits and equipment assets are called constrained devices. Network communications in constrained devices face congestion because of their limited resources. To face the congestion CoAP uses a basic (CC) congestion control mechanism for solid transmission. Alternative CoAP CC mechanisms CoCoA and CoCoA+ are introduced by the IETF Constrained RESTful Environments (CoRE) Working Group. However, there had been limited evaluations have done on CoAP CC mechanisms. In this paper, we focus on this crucial study and perform evaluations that show how the default and alternative CC mechanisms contrast with one another. We utilize the Cooja simulation condition, which is one of the Contiki advancement toolset for simulating CoAP CC mechanisms in different network topologies and varying in different link delivery ratios in global event traffic scenario. By evaluating the generated results CoCoA+ shows better performance compare to Default CoAP and CoCoA.

References

[1]. Balandina, E., Koucheryavy, Y., & Gurtov, A. (2013). Computing the retransmission timeout in CoAP. In Internet of Things, Smart Spaces, and Next Generation Networking (pp. 352-362). Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-40316-3_31

[2]. Betzler, A., Gomez, C., Demirkol, I., & Paradells, J. (2013, November). Congestion control in reliable CoAP communication. In Proceedings of the 16^th ACM International Conference on Modeling, Analysis & Simulation of Wireless and Mobile Systems (pp. 365-372). https://doi.org/10.1145/2507924.2507954

[3]. Betzler, A., Gomez, C., Demirkol, I., & Paradells, J. (2015). CoCoA+: An advanced congestion control mechanism for CoAP. Ad Hoc Networks, 33, 126-139. https://doi.org/10.1016/j.adhoc.2015.04.007

[4]. Dunkels, B. Gronvall, & T. Voigt. (2004). Contiki - a lightweight and flexible operating system for tiny networked sensors. In 29^th Annual IEEE International Conference on Local Computer Networks (pp. 455-462). IEEE. https://doi.org/10.1109/LCN.2004.38

[5]. Fielding, R. T. (2000). Architectural styles and the design of network-based software architectures (Doctoral dissertation) University of California, Irvine, 162.

[6]. Gomez, C., Demirkol, I., Bormann, C., & Betzler, A. (2014). CoAP Simple Congestion Control/Advanced. Internet Engineering Task Force (IETF) draft.

[7]. Hartke, K. (2015). Observing resources in the constrained application protocol (CoAP), Internet Engineering Task Force (IETF). RFC7641. https://doi.org/10. 17487/RFC7641

[8]. Kovatsch, M., Duquennoy, S., & Dunkels, A. (2011). A low-power CoAP for Contiki, In Proceedings of the 8^th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (pp. 885-860). https://doi.org/10.1109/MASS. 2011.100

[9]. Osterlind, F., Dunkels, A., Eriksson, J., Finne, N., & Voigt, T. (2006, November). Cross-Level Sensor Network Simulation with COOJA. In Proceedings. 2006 31^st IEEE Conference on Local Computer Networks (pp. 641-648). IEEE. https://doi.org/10.1109/LCN.2006.322172

[10]. Shelby, Z., & Bormann, C. (2016). Block-wise transfers in the constrained application protocol (CoAP), Internet Engineering Task Force (IETF). RFC7959. https://doi.org/ 10.17487/RFC7959

[11]. Shelby, Z., Hartke, K., & Bormann, C. (2014). The Constrained Application Protocol (CoAP). Internet Engineering Task Force (IETF) RFC7252. https://doi.org/ 10.17487/RFC7252

[12]. Winter, T., Thubert, P., Brandt, A., Hui, J., Kelsey, R., Levis, P., & RPL, A., R. (2012). IPv6 routing protocol for lowpower and lossy networks. RFC 6550. https://doi.org/10. 17487/RFC6550

[13]. Youssef, M. F., Elsayed, K. M., & Zahran, A. H. (2014, March). Adaptive radio duty cycling in ContikiMAC: Proposal and analysis. In 2014 IEEE World Forum on Internet of Things (WF-IoT) (pp. 491-495). IEEE. https://doi.org/10.1109/WF-IoT.2014.6803216

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Research Paper

Development of IoT Based Remote Monitoring System for Air And Water Pollutants in Industrial Environment

Anupamashree S. * , Eirini Nari, Muhammad Ismail Durrani, Keerthishree K. V., Puneeth S.

*-*****Department of Electronics and Communication Engineering, KS School of Engineering and Management, Bengaluru, Karnataka, India.

Anupamashree, S., Priya,G., A., C., Harshitha, P., Keerthishree, K., V., & Puneeth, S. (2019). Development of IoT Based Remote Monitoring System for Air And Water Pollutants in Industrial Environment.i-manager’s Journal on Wireless Communication Networks , 8(1), 34-40. https://doi.org/10.26634/jwcn.8.1.16211

Abstract

To keep the authoritative officials aware about issue of pollution and pollutant in industrial area system is developed to keep track of these pollutant information which are harmful to living species. The system uses sensors to detect the pollutants which are input to the system using IoT platform when these pollutant in air and water crosses the limit. The change in pollutant level can be remotely monitored by officials to take necessary actions. This paper presents the design of a system that can efficiently measure the level of SO₂, NO₂, CO in Air and temperature, transparency and pH in water around industrial area and send alert message about atmospheric condition to the respective authority in real time. This remote monitoring system is developed using Arduino ATMega328P, NodeMCU and sensors to monitor the environment of industries. The methodology used finds more efficient when compared to the existing technologies. The remote monitoring system uses BLYNK App and GSM module to monitor the environmental conditions without human intervention. The system was successfully able to monitor the some compound elements of Air and Water Quality indoor and outdoor environments of industries. The system finds to be accurate and efficient compared to existing monitoring system without human intervention and also gives an idea to implement the system in other scenario.

References

[1]. Annual Report on River Water Quality “Hot Spots” in Rivers of India. (2015-2016). Central Water Commission, New Delhi.

[2]. Annual Report on River Water Quality “Hot Spots” in Rivers of India. (2014-2015). Central Water Commission, New Delhi.

[3]. Bhatt, J., & Patoliya, J. (2016). IoT based water quality monitoring system. International Journal of Industrial Electronics and Electrical Engineering, 4(4), 44-48.

[4]. Daigavane, V. V., & Gaikwad, M. A. (2017). Water Quality Monitoring System based on IoT. Department Electronics & Telecommunication Engineering, Advances in Wireless and Mobile Communications, 10(5), 1107-1116.

[5]. Doni, A., Murthy, C., & Kurian, M. Z. (2018). Survey on multi sensor based air and water quality monitoring using IoT. Indian Journal of Scientific Research, 17(2), 147-153.

[6]. Kamble,R., Kakade, S., Mahajan, A., & Bhosale, A. (2017). Automatic water quality monitoring system using Arduino. International Journal of Recent Innovation in Engineering and Research (IJRIER), 2(2).

[7]. Kumar, P., & Kumar, S. P. (2018). Air and water quality monitoring through IoT by using aquatic surface drone, International Journal of Pure and Applied Mathematics, 118(22), 51-55.

[8]. Nirosha, K., Durgasree, B., & Shirisha, N. (2017). IoT based air pollution monitoring system. International Journal of Current Engineering and Scientific Research, 4(6), 40-42.

[9]. Pal, P., Gupta, R., Tiwari, S., & Sharma, A. (2017). IoT based air pollution monitoring system using Arduino. International Research Journal of Engineering and Technology (IRJET), 4(10), 1137-1140.

[10]. Pradeep, V., & Ilaiyaraja, V. (2018). Analysis and control the air quality using NodeMCU. International Journal of Advance Research, Ideas and Innovations in Technology, 4(2), 2591-2593.

[11]. Revathy, V. S., Ganesan, K., Rohini, K., Chindhu, S. T., & Boobalan, T. (2016). Air pollution monitoring system. IOSR Journal of Electronics and Communication Engineering, 11(2), 27-40.

[12]. Saikumar, V., Reji, M., & Kishoreraja, P., C.(2017). IoT based air quality monitoring system. International Journal of Pure and Applied Mathematics, 117 (9), 53-57.

[13]. Shah, H., N., Khan, Z., Merchant, A., A., Moghal, M., Shaikh, A., & Rane, P. (2018). IoT based air pollution monitoring system. International Journal of Scientific

i-manager's Journal on Wireless Communication Networks (JWCN)

Current Issue Vol. 13 Issue 1

Most Read

Most Cited

Volume 8 Issue 1 April - June 2019

Wireless Scada Using Raspberry Pi 3 and Arduino Nano V3

Ch. Venkateswara Rao* , Jamin Santiago**

* Department of Electrical and Electronics Engineering, Salalah College of Technology, Salalah, Sultanate of Oman. ** Department of Electrical Engineering, Salalah College of Technology, Salalah, Sultanate of Oman.

Rao, V., & Santiago, J.(2019). Wireless Scada Using Raspberry Pi 3 and Arduino Nano V3.i-manager’s Journal on Wireless Communication Networks, 8(1), 1-8. https://doi.org/10.26634/jwcn.8.1.16515

Abstract

References

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DOE to Identify the Most Significant Factor to Enhance the Performance of Defacto Star for Manets to Support Real Time Communication

C. P. V. N. J. Mohan Rao* , S. Pallam Setty **

*Department of Computer Science and Engineering, Avanthi Institute of Engineering and Technology, Narsipatnam, Andhra Pradesh, India. **Department of Computer Science and Systems Engineering, AUCE (A), Andhra University, Visakhapatnam, Andhra Pradesh, India.

Rao, C., P., V., N., J., M., & Setty , S., P. (2019). DOE to Identify the Most Significant Factor to Enhance the Performance of Defacto Star for Manets to Support Real Time Communication. i-manager’s Journal on Wireless Communication Networks , 8(1),9-16. https://doi.org/10.26634/jwcn.8.1.16554

Abstract

References

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Improving QoS for Voice Flow under Bursty Traffic in IEEE 802.11E

C. Ramakristanaiah* , P. Chenna Reddy **, R. Praveen Sam ***

Ramakristanaiah , C., Reddy, P., S., & Sam, R., P. (2019). Improving QoS for Voice Flow under Bursty Traffic in IEEE 802.11E.i-manager’s Journal on Wireless Communication Networks , 8(1),17-23. https://doi.org/10.26634/jwcn.8.1.16253

Abstract

References

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Performance Evaluation of CoAP Congestion Control Mechanisms in Global Event Traffic Scenario

Tejeswar Eluri*

Computer Science and Engineering, JNTUK, Kakinada, Andhra Pradesh, India.

Eluri, T. (2019). Performance Evaluation of CoAP Congestion Control Mechanisms in Global Event Traffic Scenario. i-manager’s Journal on Wireless Communication Networks, 8(1), 24-33. https://doi.org/10.26634/jwcn.8.1.16187

Abstract

References

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Development of IoT Based Remote Monitoring System for Air And Water Pollutants in Industrial Environment

Anupamashree S. * , Eirini Nari**, Muhammad Ismail Durrani***, Keerthishree K. V.****, Puneeth S.*****

*-*****Department of Electronics and Communication Engineering, KS School of Engineering and Management, Bengaluru, Karnataka, India.

Abstract

References

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* Department of Electrical and Electronics Engineering, Salalah College of Technology, Salalah, Sultanate of Oman.

** Department of Electrical Engineering, Salalah College of Technology, Salalah, Sultanate of Oman.

*Department of Computer Science and Engineering, Avanthi Institute of Engineering and Technology, Narsipatnam, Andhra Pradesh, India.

**Department of Computer Science and Systems Engineering, AUCE (A), Andhra University, Visakhapatnam, Andhra Pradesh, India.

C. Ramakristanaiah* , P. Chenna Reddy , R. Praveen Sam *

Anupamashree S. * , Eirini Nari, Muhammad Ismail Durrani, Keerthishree K. V., Puneeth S.