After the invention of new IoT devices the new connection has been added in the network and bulk of data flow in the system. AI is very famous algorithum and software-defined networking (SDN) is new fast network controlling method both can be integrate for fast and secure network-related scenarios and finding great experience and growing interest in the research community. The present network connected to many number of objects over the Internet and present a complex scenario. To ensure security, privacy, confidentiality, and programmability, the architecture of AI and blockchain for SDN network is proposed in this paper. For network service provider this is ample time to apply artificial intelligence (AI) and blockchain (BC) in a software-defined network controller to ensure a secure network control, traffic management and system optimimum performnce. Also for shortest path to reduce delay in the network, the best routing algorithum must be apply in the network. The AI (artificial intelligence) algorithum can help SDN controller to fastdecision to reduced delay and can provide security in the network. In this paper routing algorithm also will be investigate faster Network.

The sixth-generation (6G) wireless networks aim to revolutionize connectivity, offering unprecedented performance in terms of speed, latency, reliability, and scalability. Beyond the capabilities of 5G, 6G envisions integrating advanced technologies such as terahertz communication, artificial intelligence, and quantum computing to support a hyperconnected and intelligent world. This paper explores the key innovations driving 6G development, including advanced spectrum utilization, ultra-massive MIMO, and edge intelligence. Furthermore, it addresses the emerging challenges associated with 6G network traffic management, including spectrum scarcity, energy efficiency, and security vulnerabilities. We examine the anticipated rise in data traffic fueled by applications such as holographic communications, immersive virtual reality, and the Internet of Everything (IoE), emphasizing the need for adaptive traffic engineering strategies. By analyzing these innovations and challenges, the study provides insights into the architectural, technical, and policy requirements for enabling efficient and sustainable 6G networks. The findings aim to guide researchers, engineers, and policymakers in shaping the future of wireless communication.

The new data processing systems required reliable. Fast and low latency data services for smart cities operations and unmanned vehicle systems for quick and fast decisions. At present the low latency and speed data for video decoding for real time are required for intelligent decisions. In this research work we present video decoding model based on for decoding data in real time. This proposed model is based on hybrid Edge-Fog-Cloud orchestration layer that perform decoding task in real time according to the network congestion and this technique ensure data integrity, traceable task distribution and protect the data from tempering by using IoT backbone secured by blockchain technology. To reduce the risk of end-to-end latency and packet loss in worst conditions a novel Temporal-Spatial Predictive Decoding (TSPD) method is used. The AI model deep reinforcement learning is used for fast decisions. After analyzing it can be concluded that a 47.8% improvement in decoding throughput, a 62% reduction in jitter and 38% improvement QoE. This shows satisfactory performance from proposed model. By optimizing energy-latency and combining decentralized system with IoT-driven communication for autonomous aerial system can be used in future 6G network.

In the contemporary digital landscape, Software-Defined Networking (SDN) has emerged as a transformative approach that decouples network control from hardware, enabling greater flexibility and centralized management. However, this innovation has also introduced new vulnerabilities, making SDN networks susceptible to cyber-attacks. To reduce the risk of cyber-attack blockchain can play vital role. In paper we propose a novel framework that leverages blockchain technology to enhance the security and resilience of SDN environments against potential threats. By integrating blockchain’s decentralized and immutable characteristics, our approach facilitates secure data transactions, enhances network visibility, and fosters trust among network participants. We present a comprehensive analysis of the vulnerabilities inherent in traditional SDN architectures and outline method, how blockchain can mitigate these risks through secure authentication, data integrity, and enhanced access controls.Furthermore, we conduct a series of experiments to evaluate the performance impact and security benefits of our proposed solution. The results demonstrate a significant reduction in the likelihood of cyber-attacks, showcasing the viability of blockchain as a potent tool for safeguarding SDN networks. Our findings underscore the importance of interdisciplinary approaches in addressing the evolving challenges of network security, paving the way for more resilient and secure SDN infrastructures in the future.

With the growing population in the entire world, especially in under develop countries, the traffic problems are arising with high ratio. The people are using cars, bikes, trains and buses to research at destination. The rush on the roads has been increased rapidly and traffic controlling issues are at worst condition. In year 2030, the traffic will be double and the resources will be almost same. The major issue is to control traffic and conjunction in future automatically. One way is to construct new roads overhead and underground bridges but it is not possible in under developing countries like Pakistan, India and Bangladesh, etc. The other solution is to implement automatic system with the combination of IoT and blockchain and sensors to address this issue. The automatic system must be intelligent to detect changes in traffic conditions and automatically change the traffic signal timings to control congestion. For this purpose, videos cameras and IoT network sensors can be used to sense the condition, position of vehicles at a traffic signal and send information to control room or change signaling time automatically for optimum performance. In this research compare different methods to resolve above issue and matrix method will be analyze to address the issue. For simulation, the matlab simulation tool will be use.

The environment pollution is one of the biggest issues in the world and with the passage of time this issue becoming more severe. The researchers are focusing on this issue from many years but there is still no control and it’s creating bad impacts on weather and health. The impact of issue can be seen in form of changes occurs in global temperature, weather and health. There are many factors that contribute to raise pollution such as CO2, and main sources are smog, smoke and heat generated with energy resources. The pollution must be control for clean and healthy environment. The energy generate from the coal, diesel and by burning fuel must be stop and clean energy resources must be used such as hydroelectricity, solar and wind energy in future. In this research paper, the main issues related to energy and its environmental impact and solution will be proposed. The Microgrid is new approach and reliable and decentralized control system, which can address many technical and non-technical issues related to present power system by using the blockchain. A Simulink model of microgrid will be used for analyzing the result graphically.