Resource Allocation Problem in Manufacturing Grid Based on JADE

2010 ◽  
Vol 26-28 ◽  
pp. 710-713
Author(s):  
Fu Qing Zhao ◽  
Ya Hong Yang
Keyword(s):  
Interaction Mechanism ◽  
Scheduling Problem ◽  
Manufacturing Grid ◽  
Grid Resource ◽  
Contract Net ◽  
Forward Contract ◽  
Scheduling Method ◽  
Multi Agent ◽  
Grid Resources ◽  
Grid Based

The grid resources scheduling problem is one of the key problem in manufacturing grid. After studying on manufacturing grid resource property and requirement on scheduling, the scheduling method based on multi-agent and genetic algorithm is put forward. Contract Net Protocol is adopted to the multi-agent cooperation and negotiation system. The communication and interaction mechanism are guarantee on the JADE and JGAP platform. Simulation result shows that the method is effective to the negotiation and scheduling problem in manufacturing grid.

Time-Efficient Ensemble Learning with Sample Exchange for Edge Computing

2021 ◽  
Vol 21 (3) ◽  
pp. 1-17
Author(s):  
Wu Chen ◽  
Yong Yu ◽  
Keke Gai ◽  
Jiamou Liu ◽  
Kim-Kwang Raymond Choo
Keyword(s):  
Ensemble Learning ◽  
Real World ◽  
Interaction Mechanism ◽  
Training Model ◽  
Edge Computing ◽  
Learning Techniques ◽  
Multi Agent ◽  
Real World Datasets ◽  
Entire Dataset ◽  
Exchange Data

In existing ensemble learning algorithms (e.g., random forest), each base learner’s model needs the entire dataset for sampling and training. However, this may not be practical in many real-world applications, and it incurs additional computational costs. To achieve better efficiency, we propose a decentralized framework: Multi-Agent Ensemble. The framework leverages edge computing to facilitate ensemble learning techniques by focusing on the balancing of access restrictions (small sub-dataset) and accuracy enhancement. Specifically, network edge nodes (learners) are utilized to model classifications and predictions in our framework. Data is then distributed to multiple base learners who exchange data via an interaction mechanism to achieve improved prediction. The proposed approach relies on a training model rather than conventional centralized learning. Findings from the experimental evaluations using 20 real-world datasets suggest that Multi-Agent Ensemble outperforms other ensemble approaches in terms of accuracy even though the base learners require fewer samples (i.e., significant reduction in computation costs).

scholarly journals Ant Colony Intelligence in Flexible Manufacturing Scheduling Using Contract-Net Model

2011 ◽  
Vol 2-3 ◽  
pp. 608-613
Author(s):  
Ying Zi Wei ◽  
Yi Jun Feng ◽  
Kan Feng Gu
Keyword(s):  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Ant Colony ◽  
Contract Net Protocol ◽  
Agent Based ◽  
Contract Net ◽  
Multi Agent ◽  
Bidding Mechanism ◽  
Alternative Processes ◽  
Alternative Machines

This paper builds an efficient agent-based flexible scheduling for real-world manufacturing systems. Considering the alternative processes and alternative machines, the allocation of manufacturing resources is achieved through negotiation among the job and machine agents in a multi-agent system (MAS). Ant Colony Intelligence (ACI) is proposed to be combined with Contract Net Protocol (CNP) so as to make agents adaptive to changing circumstances. ACI is integrated into both machine agents and job agents to solve the task allocation and sequencing problem. CNP is introduced to allow the agents to cooperate and coordinate their local schedules in order to find globally near-optimal robust schedules. The negotiation protocol is an interactive bidding mechanism based on the hybrid contract net protocol. The implementation of the issues using CNP model is discussed. Experimental results verify the effectiveness and efficiency of the proposed algorithm integrated with ant-inspired coordination.

Research of Flexible Dynamic Scheduling Problem Based on Genetic Algorithm

2009 ◽  
Vol 16-19 ◽  
pp. 743-747
Author(s):  
Yu Wu ◽  
Xin Cun Zhuang ◽  
Cong Xin Li
Keyword(s):  
Genetic Algorithm ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Dynamic Scheduling ◽  
Scheduling Problem ◽  
Static Scheduling ◽  
Coding Method ◽  
Scheduling Method ◽  
Distribution Principle ◽  
Working Procedure

Solve the flexible dynamic scheduling problem by using “dynamic management & static scheduling” method. Aim at the property of flexible Manufacturing systems, the dynamic scheduling methods are analyzed and a coding method based on working procedure is improved in this paper. Thus it can be efficiently solve the problem of multiple working routes selection under the active distribution principle. On the other hand, the self-adaptive gene is provided and the parameters of the genetic algorithm are defined. In such a solution, the scheduling is confirmed to be simple and efficient.

Grid Resource Allocation with Genetic Algorithm Using Population Based on Multisets

2017 ◽  
Vol 26 (1) ◽  
pp. 169-184 ◽  
Author(s):  
Absalom E. Ezugwu ◽  
Nneoma A. Okoroafor ◽  
Seyed M. Buhari ◽  
Marc E. Frincu ◽  
Sahalu B. Junaidu
Keyword(s):  
Genetic Algorithm ◽  
Resource Allocation ◽  
Grid Computing ◽  
Resource Selection ◽  
Computing System ◽  
Population Based ◽  
Fine Tuning ◽  
Grid Resource ◽  
Performance Results ◽  
Grid Resources

AbstractThe operational efficacy of the grid computing system depends mainly on the proper management of grid resources to carry out the various jobs that users send to the grid. The paper explores an alternative way of efficiently searching, matching, and allocating distributed grid resources to jobs in such a way that the resource demand of each grid user job is met. A proposal of resource selection method that is based on the concept of genetic algorithm (GA) using populations based on multisets is made. Furthermore, the paper presents a hybrid GA-based scheduling framework that efficiently searches for the best available resources for user jobs in a typical grid computing environment. For the proposed resource allocation method, additional mechanisms (populations based on multiset and adaptive matching) are introduced into the GA components to enhance their search capability in a large problem space. Empirical study is presented in order to demonstrate the importance of operator improvement on traditional GA. The preliminary performance results show that the proposed introduction of an additional operator fine-tuning is efficient in both speed and accuracy and can keep up with high job arrival rates.

scholarly journals A Weight-based Query Forwarding Technique for Super-peer-based Grid Resource Discovery

2017 ◽  
Vol 7 (1) ◽  
pp. 1398-1404
Author(s):  
M. Mollamotalebi ◽  
R. Maghami ◽  
A. S. Ismail
Keyword(s):  
Response Time ◽  
Resource Discovery ◽  
Search Process ◽  
Grid Resource ◽  
Grid Environment ◽  
Grid Applications ◽  
Computing Environments ◽  
Grid Resources ◽  
Grid Resource Discovery ◽  
Super Peer

Grid computing environments include heterogeneous resources shared by a large number of computers to handle data and process intensive applications. The required resources must be accessible for the grid applications on demand, which makes resource discovery a critical service. In recent years, different techniques are provided to index and discover grid resources. Response time and message load during the search process highly affect the efficiency of resource discovery. This paper proposes a technique to forward the queries based on the resource types accessible through each neighbor in super-peer-based grid resource discovery approaches. The proposed technique is simulated in GridSim and the experimental results indicated that it is able to reduce the response time and message load during the search process especially when the grid environment contains a large number of nodes.

Application of Fuzzy Labeled Transition System to Contract Net Protocol

2015 ◽  
Vol 6 (3) ◽  
pp. 27-46 ◽  
Author(s):  
Sofia Kouah ◽  
Djamel Eddine Saïdouni
Keyword(s):  
Dynamic Systems ◽  
Transition System ◽  
Multi Agent Systems ◽  
Contract Net Protocol ◽  
Agent Systems ◽  
Contract Net ◽  
Multi Agent ◽  
Refinement Process ◽  
Labeled Transition System

For developing large dynamic systems in a rigorous manner, fuzzy labeled transition refinement tree (FLTRT for short) has been defined. This model provides a formal specification framework for designing such systems. In fact, it supports abstraction and enables fuzziness which allows a rigorous formal refinement process. The purpose of this paper is to illustrate the applicability of FLTRT for designing multi agent systems (MAS for short), among others collective and internal agent's behaviors. Therefore, Contract Net Protocol (CNP for short) is chosen as case study.

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