The rapid expansion of the Internet of Things (IoT) has driven the need for advanced computational frameworks capable of handling the complex data processing and security challenges that modern IoT applications demand. However, traditional cloud computing frameworks face significant latency, scalability, and security issues. Quantum-Edge Cloud Computing (QECC) offers an innovative solution by integrating the computational power of quantum computing with the low-latency advantages of edge computing and the scalability of cloud computing resources. This study is grounded in an extensive literature review, performance improvements, and metrics data from Bangladesh, focusing on smart city infrastructure, healthcare monitoring, and the industrial IoT sector. The discussion covers vital elements, including integrating quantum cryptography to enhance data security, the critical role of edge computing in reducing response times, and cloud computing's ability to support large-scale IoT networks with its extensive resources. Through case studies such as the application of quantum sensors in autonomous vehicles, the practical impact of QECC is demonstrated. Additionally, the paper outlines future research opportunities, including developing quantum-resistant encryption techniques and optimizing quantum algorithms for edge computing. The convergence of these technologies in QECC has the potential to overcome the current limitations of IoT frameworks, setting a new standard for future IoT applications.
The rapid expansion of the Internet of Things (IoT) has driven the need for advanced computational frameworks capable of handling the complex data processing and security challenges that modern IoT applications demand. However, traditional cloud computing frameworks face significant latency, scalability, and security issues. Quantum-Edge Cloud Computing (QECC) offers an innovative solution by integrating the computational power of quantum computing with the low-latency advantages of edge computing and the scalability of cloud computing resources. This study is grounded in an extensive literature review, performance improvements, and metrics data from Bangladesh, focusing on smart city infrastructure, healthcare monitoring, and the industrial IoT sector. The discussion covers vital elements, including integrating quantum cryptography to enhance data security, the critical role of edge computing in reducing response times, and cloud computing's ability to support large-scale IoT networks with its extensive resources. Through case studies such as the application of quantum sensors in autonomous vehicles, the practical impact of QECC is demonstrated. Additionally, the paper outlines future research opportunities, including developing quantum-resistant encryption techniques and optimizing quantum algorithms for edge computing. The convergence of these technologies in QECC has the potential to overcome the current limitations of IoT frameworks, setting a new standard for future IoT applications.
The Internet of Things (IoT) is expanding rapidly, which has created a need for sophisticated computational frameworks that can handle the data and security requirements inherent in modern IoT applications. However, traditional cloud computing frameworks have struggled with latency, scalability, and security vulnerabilities. Quantum-Edge Cloud Computing (QECC) is a new paradigm that effectively addresses these challenges by combining the computational power of quantum computing, the low-latency benefits of edge computing, and the scalable resources of cloud computing. This study has been conducted based on a published literature review, performance improvements, and metrics data from Bangladesh on smart city infrastructure, healthcare monitoring, and the industrial IoT sector. We have discussed the integration of quantum cryptography to enhance data integrity, the role of edge computing in reducing response times, and how cloud computing's resource abundance can support large IoT networks. We examine case studies, such as the use of quantum sensors in self-driving vehicles, to illustrate the real-world impact of QECC. Furthermore, the paper identifies future research directions, including developing quantum-resistant encryption and optimizing quantum algorithms for edge computing. The convergence of these technologies in QECC promises to overcome the existing limitations of IoT frameworks and set a new standard for the future of IoT applications.
The Internet of Things (IoT) has rapidly transformed industries by enabling the interconnectivity of devices and the real-time exchange of data. However, as IoT networks continue to scale, the limitations of traditional edge and cloud computing architectures—such as latency, security concerns, and scalability challenges—become more pronounced. This article explores the emerging role of quantum computing in addressing these challenges and advancing the evolution of edge and cloud solutions for IoT systems. By leveraging the unique capabilities of quantum computing, including superposition, entanglement, and quantum parallelism, IoT systems can achieve enhanced data processing speeds, improved security, and more efficient resource management. This article discusses the potential benefits of integrating quantum computing with edge and cloud infrastructures, focusing on use cases in real-time analytics, secure communication, and advanced machine learning for IoT applications. Additionally, it examines the technical, ethical, and regulatory challenges that need to be addressed for the successful deployment of quantum-edge cloud solutions. Finally, the article highlights the importance of collaboration between academia, industry, and policymakers to drive the development of quantum-enabled IoT systems. The findings suggest that quantum computing will play a pivotal role in the next generation of IoT infrastructure, unlocking new possibilities for smarter, more responsive, and secure IoT ecosystems.
The augmented growth of the Internet of things (IoT) has brought an enormous surge in data generation requiring highly efficient, secure and scalable computational architectures. While conventional cloud computing is a widely used solution, it struggles with various issues like bandwidth constraints, latency and security vulnerabilities. Edge computing alleviates some of these concerns by processing the data closer to its source but time and again it is limited by restricted computational power. Quantum Edge Cloud Computing (QECC) presents a groundbreaking approach by assimilating the power of quantum computing with edge and cloud infrastructure to improve IoT performance. This study caverns the synergy between quantum computing, cloud computing and edge computing, foregrounding how this synergy can strengthen the IoT ecosystems. It examines the advantage of quantum assisted edge-cloud frameworks, investigates the advancements in cyber security through cryptographic methods and discusses plausible real-world applications. Additionally, the paper also features existing technological challenges, traces future research directions and suggests strategies required to realize a truly secure, intelligent and adaptive computing framework for IoT.
Abstract The amount and difficulty of data have both grown a lot since the number of Internet of Things (IoT) devices in the medical and industrial sectors has grown a lot. These situations with a lot of data have needs that go beyond what most cloud and edge computing frameworks can do when it comes to processing in real time, energy efficiency, and security. The inclusion of quantum computing, which can handle a lot of processing at once and execute more sophisticated tasks at once, could transform the way things are done in a big manner. When it comes to handling sensitive and different IoT, the current Edge-Cloud designs have a few big problems: they don't scale effectively, they have a lot of latency, and they do not have enough capacity. In order for predictive maintenance and automation to perform well in industrial Internet of Things (IIoT) contexts, they need to be able to address problems and act promptly. On the other hand, late diagnoses and data breaches are very dangerous for medical settings. All of these key factors; the computing burden, the reaction speed, and the security are handled by one unified design. The Quantum-Enhanced Edge-Cloud Computing Framework (QEECF) is proposed to speed up essential operations including encryption, finding anomalies, and making decisions in real time. With this technology, the quantum processing units (QPUs) are added to both the cloud servers and the edge nodes at the same time. The framework uses a hybrid quantum-classical scheduling strategy that combines quantum annealing with variational circuits to give the best possible job offloading. The objective of a federated quantum learning system is to keep sensitive data safe. This data is stored in databases all around the world, like those used in business and healthcare. We evaluate the technology by running simulations of things like smart manufacturing and keeping an eye on healthcare. These simulations are easier using IBM Qiskit and edge simulators. When compared to standard Edge-Cloud arrangements, QEECF might increase data throughput by 36%, cut job delays by 43%, and improve the accuracy of finding anomalies by 48%.
The Internet of Things (IoT) has emerged as an innovative framework, connecting physical devices into intricate networks that monitor and control various aspects of daily life. While traditional technologies such as big data analytics and cloud computing have driven the growth of IoT, the emergence of quantum technologies, spanning quantum computing, quantum communication, and quantum sensing, presents unprecedented opportunities to enhance IoT systems. This paper explores the realistic potential and challenges of integrating quantum technologies into IoT, emphasizing the need for a nuanced understanding of what quantum technologies can achieve to bridge the gap between promise and practical application. By fostering collaboration between disciplines, quantum technologies can shape the future of IoT, improving its security, efficiency, and precision.
The Internet of Things (IoT) has grown rapidly, transforming various aspects of daily life into intelligent systems capable of collecting and exchanging data in real time. At the same time, advances in quantum computing have given rise to powerful quantum computers capable of processing complex tasks at unprecedented speed. This disparity between the limited resources of IoT devices and the capabilities of quantum computers poses significant security challenges. Quantum computers introduce new vulnerabilities that threaten IoT systems, particularly in critical applications such as connected healthcare, industrial networks, smart infrastructure, and secure embedded systems. This study reviews the existing literature on post-quantum cryptography (PQC) applied to IoT devices. It analyzes the characteristics and security requirements of IoT environments, current security technologies, and unresolved issues. It highlights the growing threat of post-quantum attacks and the need to adapt security strategies. Finally, the study explores post-quantum code-based cryptosystems as solutions to enhance the security of resource-constrained IoT applications and ensure their resilience against future challenges.