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An Integrated Secure Scalable Blockchain Framework for IoT Communications
The Internet of Things (IoT) has shown great promise in the years since its invention and widespread acceptance by demonstrating its ability to adapt and improve manual processes while bringing them into the digital age. IoT's capacity to do so has elevated it to the ranks of the most promising technologies of our time. Despite the fact that IPv4 and IPv6 are being utilized to serve a growing number of devices in IoT connectivity, there are still issues with address space allocation and other security concerns, including scalability and poor access control methods. It is necessary to go through these difficulties and worries. Both of these organizations have spent a considerable amount of time in the vanguard of advancement in the study of IoT and Blockchain technology. Since IoT devices are capable of efficient two-way communication, integrating Blockchain technology is challenging. However, scalability is the biggest obstacle. The IoT Blockchain Framework discussed in the research article has the potential to be a game-changing solution to the issues that IoTs currently face, provided that it is used properly. Data access control and data interchange, transparency, and scalability without compromising privacy or dependability are all issues with the IoT paradigm that Blockchain technology may be able to efficiently address. Creating a local index that is scalable and does not interfere with either the local or global peer validation procedures is one way to limit the number of transactions that contact the global Blockchain. According to the findings, the blocks are significantly lighter and smaller than those seen in other parts of the world.
Keywords
Internet of Things, Large Scale IoT Framework, Lpeer, Scalability.
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- Xu R, Chen Y, Li X & Blasch E, A secure dynamic edge resource federation architecture for cross-domain IoT systems, Int Conf Comput Commun Netw (ICCCN) (Manchester Metropolitan University, United Kingdom) 2022, 1–7, doi: 10.1109/ICCCN54977.2022.9868843.
- Mallick S R & Sharma S, EMRI: A scalable and secure Blockchain-based IoMT framework for healthcare data transaction, 19th OITS Int Conf Inf Technol (OCIT) (IEEE) 2021, 261–266, doi: 10.1109/OCIT53463.2021.00060.
- Al Nuaimi K & Kamel H, A survey of indoor positioning systems and algorithms, Proc Int Conf Innov Inf Technol (IEEE) 2011, 185–190.
- Misra P & Enge P, Global positioning system: signals, measurements & Performance, IEEE Aerosp Electron Syst Mag, 17(10) (2002) 36−37.
- Zhen F, Zhan Z, Peng Q & Yuguo Z, Analysis based on RSSI ranging, Chin J Sens Actuators, 20(11) (2007) 2526−2530.
- Jeon K E, She J, Soonsawad P & Ng P C, BLE, beacons for internet of things applications: Survey, challenges, and opportunities, IEEE Internet Things J, 5(2) (2018) 811–828.
- Qiu Y, Zhao C C, Dai G L & Hu C J, Research on localization technology for wireless sensor networks, Comput Sci, 35(5) (2008) 47−50.
- Akyildiz I F, Su W, Sankarasubramaniam Y & Cayirci E, A survey on sensor networks, IEEE Commun Mag, 40(8) (2002) 102–114.
- Li Y, Meng M Q H, Li S, Chen W & Liang H, Particle filtering for range-based localization in wireless sensor networks, Proc 7th World Congress on Intelligent Control and Automation (IEEE) 2008, 1629–1634.
- Sahinoglu Z & Gezici S, Ranging in the IEEE 802.15.4a standard, Proc Microw Technol Conf (WAMICON) (IEEE) (2006), 1−5.
- Chen W, LiW, Shou H & Yuan B, Weighted centroid localization algorithm based on RSSI for wireless sensor networks, J Wuhan Univ Technol, 30(2) (2006) 256–268.
- Iyengar R & Sikdar B, Scalable and distributed GPS free positioning for sensor networks, Proc Int Conf Commun (ICC'03) (IEEE) 2003, 338–342.
- Chen Y, Li X, Ding Y, Xu J & Liu Z, An improved DV-Hop localization algorithm for wireless sensor networks, Proc 13th IEEE Conf Ind Electron Appl (ICIEA) (IEEE) 2018, 1831–1836.
- Wang Z M & Zheng Y, The study of the weighted centroid localization algorithm based on RSSI, Proc IEEE Int Conf Wirel Commun Sens Netw (IEEE) 2014, 276–279.
- Chapre Y, Mohapatra P, Jha S & Seneviratne A, Received signal strength indicator and its analysis in a typical WLAN system (short paper), Proc IEEE LCN annu Conf Local Comput Netw (IEEE) 2013, 304–307.
- Al Nuaimi K & Kamel H, A survey of indoor positioning systems and algorithm, Proc IEEE Int Conf Innov Inf Technol (IEEE) 2011, 185−190.
- Misra P & Enge P, Global positioning system: signals measurements & performance, IEEE Aerosp Electron, 17(10) (2002) 36–37.
- Zhen F, Zhan Z, Peng Q & Yuguo Z, Analysis based on RSSI ranging, Chin J Sens Actuators, 20(11) (2007) 2526–2530.
- Jeon K E, She J, Soonsawad P & Ng P C, BLE beacons for internet of things applications: Survey, challenges, and opportunities, IEEE Internet Things J, 5(2) (2018) 811–828.
- Qiu Y, Zhao C C, Dai G L & Hu, C J, Research on localization technology for wireless sensor networks, Comput Sci, 35(5) (2008) 47–50.
- Akyildiz I F, Su W, Sankarasubramaniam Y & Cayirci E, A survey on sensor networks, IEEE Commun Mag, 40(8) (2002) 102–114.
- Li Y, Meng M Q H, Li S, Chen W & Liang H, Particle filtering for range-based localization in wireless sensor networks, Proc IEEE 7th World Congress on Intell Control Autom (IEEE) 2008, 1629–1634.
- Sahinoglu Z & Gezici S, Ranging in the IEEE 802.15. 4astandard, Proc IEEE Microw Technol Conf (WAMICON) (2006), 1–5.
- Chen W, Li W, Shou H & Yuan B, Weighted centroid localization algorithm based on RSSI for wireless sensor networks, J Wuhan Univ Technol, 30(2) (2006) 256–268.
- Chen Y, Li, X, Ding Y, Xu J & Liu Z, An improved DV-Hop localization algorithm for wireless sensor networks, Proc13th IEEE Conf Ind Electron Appl (ICIEA) (IEEE) 2018, 1831–1836.
- Iyengar R & Sikdar B, Scalable and distributed GPS free positioning for sensor networks, Proc IEEE Int Conf Commun (ICC'03) (IEEE) 2003, 338–342.
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