Intelligent Resource Allocation and Optimization for Industrial Robotics Using AI and Blockchain
- 29 December 2023
- book chapter
- Published by IGI Global Scientific Publishing
- p. 82-110
Abstract
This chapter focuses on the application of intelligent resource allocation and optimization techniques for industrial robotics systems using the synergistic integration of artificial intelligence (AI) and blockchain technologies. Efficient resource allocation is crucial for maximizing the performance and productivity of industrial robotics, and AI-based approaches offer the ability to dynamically allocate resources based on real-time data and system requirements. Additionally, blockchain technology provides a decentralized and secure platform for recording and verifying resource allocation transactions, ensuring transparency and trust in the allocation process. The chapter explores various AI algorithms and models that can be employed for resource allocation and optimization in industrial robotics, including machine learning, evolutionary algorithms, and reinforcement learning. Furthermore, the chapter investigates how blockchain technology can enhance resource allocation and optimization by providing a distributed ledger for recording and verifying resource transactions.Keywords
This publication has 12 references indexed in Scilit:
- I-HARF: Intelligent and Hierarchical Framework for Adaptive Resource Facilitation in Edge-IoT SystemsIEEE Internet of Things Journal, 2022
- Optimal and Privacy-Aware Resource Management in Artificial Intelligence of Things Using Osmotic ComputingIEEE Transactions on Industrial Informatics, 2021
- Resource Allocation and Consensus of Blockchains in Pervasive Edge Computing EnvironmentsIEEE Transactions on Mobile Computing, 2021
- Blockchain-Based Edge Computing Resource Allocation in IoT: A Deep Reinforcement Learning ApproachIEEE Internet of Things Journal, 2020
- BlockIoTIntelligence: A Blockchain-enabled Intelligent IoT Architecture with Artificial IntelligenceFuture Generation Computer Systems, 2020
- Blockchain-enabled resource management and sharing for 6G communicationsDigital Communications and Networks, 2020
- Machine Learning Methods for Reliable Resource Provisioning in Edge-Cloud ComputingACM Computing Surveys, 2019
- Deep Reinforcement Learning-Based Mode Selection and Resource Management for Green Fog Radio Access NetworksIEEE Internet of Things Journal, 2018
- Computation Offloading and Resource Allocation in Mixed Fog/Cloud Computing Systems With Min-Max Fairness GuaranteeIEEE Transactions on Communications, 2017
- Computing Resource Allocation in Three-Tier IoT Fog Networks: A Joint Optimization Approach Combining Stackelberg Game and MatchingIEEE Internet of Things Journal, 2017