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Full-Text Articles in Engineering
Decentralized Resource Allocation And Scheduling Via Walrasian Auctions With Negotiable Agents, Huaxing Chen, Hoong Chuin Lau
Decentralized Resource Allocation And Scheduling Via Walrasian Auctions With Negotiable Agents, Huaxing Chen, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
This paper is concerned with solving decentralized resource allocation and scheduling problems via auctions with negotiable agents by allowing agents to switch their bid generation strategies within the auction process, such that a better system wide performance is achieved on average as compared to the conventional walrasian auction running with agents of fixed bid generation strategy. We propose a negotiation mechanism embedded in auctioneer to solicit bidders’ change of strategies in the process of auction. Finally we benchmark our approach against conventional auctions subject to the real-time large-scale dynamic resource coordination problem to demonstrate the effectiveness of our approach.
Case Study Of Finite Resource Optimization In Fpga Using Genetic Algorithm, Jingxia Wang, Sin Ming Loo
Case Study Of Finite Resource Optimization In Fpga Using Genetic Algorithm, Jingxia Wang, Sin Ming Loo
Electrical and Computer Engineering Faculty Publications and Presentations
Modem Field-Programmable Gate Arrays (FPGAs) are becoming very popular in embedded systems and high performance applications. FPGA has benefited from the shrinking of transistor feature size, which allows more on-chip reconfigurable (e.g., memories and look-up tables) and routing resources available. Unfortunately, the amount of reconfigurable resources in a FPGA is fixed and limited. This paper investigates the mapping scheme of the applications in a FPGA by utilizing sequential processing (e.g., Altera Nios II or Xilinx Microblaze, using C programming language) and task specific hardware (using hardware description language). Genetic Algorithm is used in this study. We found that placing sequential …
Optimizing Reconfigurable Hardware Resource Usage In System-On-A-Programmable-Chip With Location-Aware Genetic Algorithm, Sin Ming Loo, Jingxia Wang
Optimizing Reconfigurable Hardware Resource Usage In System-On-A-Programmable-Chip With Location-Aware Genetic Algorithm, Sin Ming Loo, Jingxia Wang
Electrical and Computer Engineering Faculty Publications and Presentations
This paper presents static task scheduling using location-aware genetic algorithm techniques to schedule task systems to finite amounts of reconfigurable hardware. This research optimizes the use of limited reconfigurable resources. This scheduling algorithm is built upon our previous work [12- 14]. In this paper, the genetic algorithm has been expanded to include a feature to assign selected tasks to specific functional units. In this reconfigurable hardware environment, multiple sequential processing elements (soft core processors such as Xilinx MicroBlaze [22] or Altera Nios-II [1]), task-specific core (application specific hardware), and communication network within the reconfigurable hardware can be used (such a …