Resource Management Final Year Projects for BE, BTech, ME, MSc, MCA and MTech final year engineering students. These Resource Management projects give practical experience and help complete final-year submissions. All projects follow IEEE standards and each project includes source code, project thesis report, presentation, project execution and explanation.

Resource Management Final Year Projects

A Novel Resource-Saving and Traceable Tea Production and Supply Chain Based on Blockchain and IoT

This project focuses on improving the tea production and supply chain using blockchain and IoT technologies. It creates a system called DeTea that tracks tea products, prevents counterfeiting, and automates plantation management. The system encourages honest behavior among participants and monitors the environment to optimize resources like water and equipment use. Overall, it makes tea production safer, more efficient, and fully traceable from planting to sale.
High-Efficiency Resource Allocation Scheme Introducing the Concept of Resource Sharing Paths in Industrial IoT

This project focuses on improving industrial wireless networks used in smart factories. It addresses the problem of resource wastage when many devices send data along overlapping routes. The researchers propose a method that shares communication resources on common paths and considers network conditions like congestion. Their simulations show this approach uses resources more efficiently and handles more devices than traditional methods.
TMaLB A Tolerable Many-Objective Load Balancing Technique for IoT Workflows Allocation

This project studies how to balance heavy and uneven data loads in Internet of Things systems. It looks at what factors matter most for good service, such as cost, speed, and energy use. The method uses an intelligent search algorithm to choose the best way to share work across devices. It improves both performance and the number of tasks the system can handle.
A Blockchain System for TDMA-Based Tactical Wireless Networks With Constrained Resources

This project develops a blockchain system for wireless networks that have limited communication resources. It ensures all devices can share the same data reliably, even when the network is unstable. The system uses an efficient method to decide which device can send data at a given time, saving energy and avoiding unnecessary competition. The design was tested using simulations and numerical analysis to show it works in different situations.
A Survey of Resource Management in D2D Communication for B5G Networks

This project studies a new type of wireless communication called Device-to-Device (D2D) for future networks beyond 5G. D2D allows nearby devices to connect directly without relying on a base station. The goal is to increase data speed, network coverage, and energy efficiency while reducing delays. The study reviews current challenges, like interference and security, and suggests ways to improve D2D communication in upcoming networks.
Congestion Control in Autonomous Resource Selection of Cellular-V2X

This project focuses on improving communication between vehicles in intelligent transportation systems. It addresses network congestion and communication problems when cellular coverage is absent. The researchers propose a method that controls vehicle transmission power and channel usage to reduce traffic on the network. Their solution improves performance and makes vehicle communication more reliable and flexible.
Dispersal Foraging Strategy With Cuckoo Search Optimization Based Path Planning in Unmanned Aerial Vehicle Networks

This project focuses on improving how drones (UAVs) move and communicate in complex environments like oceans. It proposes a new method that helps drones find the best paths while avoiding obstacles and efficiently sharing data. The approach also manages resources better and avoids getting stuck in poor solutions. Simulations show that this method performs better than existing techniques.
Handover Reduction in 5G High-Speed Network Using ML-Assisted User-Centric Channel Allocation

This project focuses on improving 5G network performance for high-speed road users like connected autonomous vehicles. It introduces a new channel allocation method called Vehicular Frequency Reuse (VFR) to reduce frequent handovers and improve connection reliability. A mobility management function separates high-speed and low-speed users using a simple velocity-based metric. Simulations show that this approach can reduce handovers by over 99% compared to traditional methods.
Machine Learning Empowered Emerging Wireless Networks in 6G Recent Advancements Challenges and Future Trends

This project explains how future 6G networks will use machine learning to make communication faster, smarter, and more reliable. It shows how ML helps the network manage resources on its own and solve problems like energy use, delays, and smooth connections. The paper reviews different ML methods and how they improve new types of networks, such as device-to-device and vehicular systems. It also discusses open challenges and future research directions for building intelligent 6G networks.

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Resource Management Project Synopsis & Presentation

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Resource Management Final Year Projects with Source Code