UtilityChain: Dynamic Resource Allocation for Mining and Servicing in Blockchain System

In this research work, we propose – UtilityChain –, a method for efficient resource allocation of miners involved in both mining and service-related activities. The aim of this approach is to enhance the miner's utility ( overall efficiency) in response to the increasing need for real-time data processing generated by IoT devices. The security of the data is a crucial matter of concern, and the integration of blockchain technology for secure data storage and edge computing for real-time processing is deemed a suitable approach. However, the utilization of edge computing devices adds an extra cost burden. Additionally, fluctuations in resource prices and mining rewards frequently result in miner departures and underutilized resources. To tackle these challenges, UtilityChain employs the resources of miners for mining and providing services to the end-users, without the use of edge computing devices. This is achieved through the utilization of advanced deep reinforcement learning technique to dynamically allocate miner resources for both mining and service tasks. The experimental results demonstrate the efficacy of UtilityChain, with a resource allocation accuracy of 99.2% and a miner allocation accuracy of 98.8%. Additionally, UtilityChain exhibits a resource utilization rate of 8.2% for CPU and 78.2% for memory.