scholarly journals Agent Based Load Balancing in Grid Computing

2020 ◽  
Author(s):  
Wided Ali ◽  
Fatima Bouakkaz
Keyword(s):  
Load Balancing ◽  
Heterogeneous Systems ◽  
Agent Based ◽  
Selection Policy ◽  
Development Framework ◽  
Policy Selection ◽  
Proposed Model ◽  
Multi Agent ◽  
Location Policy ◽  
System Characteristics

Load-Balancing is an important problem in distributed heterogeneous systems. In this paper, an Agent-based load-balancing model is developed for implementation in a grid environment. Load balancing is realized via migration of worker agents from overloaded resources to underloaded ones. The proposed model purposes to take benefit of the multi-agent system characteristics to create an autonomous system. The Agent-based load balancing model is implemented using JADE (Java Agent Development Framework) and Alea 2 as a grid simulator. The use of MAS is discussed, concerning the solutions adopted for gathering information policy, location policy, selection policy, worker agents migration, and load balancing.

An Agent-Based Load Balancing Approach for RFID MiddleWares

2014 ◽  
Vol 541-542 ◽  
pp. 1458-1462
Author(s):  
Zhen Gang Wei ◽  
Xi Zhou Sun ◽  
Xiao Hua Wang
Keyword(s):  
Load Balancing ◽  
Mobile Agent ◽  
Load Transfer ◽  
Independent Set ◽  
Policy Transfer ◽  
Transfer Policy ◽  
Selection Policy ◽  
Policy Selection ◽  
Local Host ◽  
Location Policy

For company to extend their RFID applications ceaselessly, the fundamental challenge is how to satisfy enterprise applications more effectively, while avoids mainframe server purchased and existed servers leave unused. It needs to decentralize work by using several RFID middlewares. So load balancing method is required for preventing centralization work in certain RFID middleware. In this paper, as a solution of tackle the challenge, we proposed a new load balancing approach based on mobile agent for RFID middlewares, which includes: information gathering policy, transfer policy, selection policy and location policy, and three agents are developed: load-info monitoring agent (LIMA) compliant to monitoring local host workload status; load-info gathering agent (LIGA) compliant to gather local and global load information; load transfer mobile agent (LTMA) compliant to choose the independent set and the appropriate scheduling scheme and implement the relocation work.

Adaptive Ensemble Multi-Agent Based Intrusion Detection Model

2010 ◽  
pp. 36-48 ◽  
Author(s):  
Tarek Helmy
Keyword(s):  
Machine Learning ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Machine Learning Algorithms ◽  
Agent Based ◽  
Detection Model ◽  
Detection Analysis ◽  
Proposed Model ◽  
Multi Agent

The system that monitors the events occurring in a computer system or a network and analyzes the events for sign of intrusions is known as intrusion detection system. The performance of the intrusion detection system can be improved by combing anomaly and misuse analysis. This chapter proposes an ensemble multi-agent-based intrusion detection model. The proposed model combines anomaly, misuse, and host-based detection analysis. The agents in the proposed model use rules to check for intrusions, and adopt machine learning algorithms to recognize unknown actions, to update or create new rules automatically. Each agent in the proposed model encapsulates a specific classification technique, and gives its belief about any packet event in the network. These agents collaborate to determine the decision about any event, have the ability to generalize, and to detect novel attacks. Empirical results indicate that the proposed model is efficient, and outperforms other intrusion detection models.

The Use of Multi-Agent Systems in Managing Sustainable Supply Chain

2013 ◽  
Vol 315 ◽  
pp. 108-112
Author(s):  
Majid Aarabi ◽  
Muhamad Zameri Mat Saman ◽  
Kuan Yew Wong
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Supply Chains ◽  
Sustainable Supply Chain ◽  
Multi Agent Systems ◽  
Chain Management ◽  
Agent Based ◽  
Goods And Services ◽  
Proposed Model ◽  
Multi Agent

The main purposes and challenges in supply chain management are reducing cost and time. Significantly, factors such as the competition of markets in the globe, limitation of energy, raw and virgin materials, environmental protection crisis and increasing of global population dramatically are causing unprecedented issues for the worldwide supply chains for providing goods and services to customers efficiently and effectively. The sustainability approach for Supply Chain Management (SCM) considers the 6Rs principles in four main stages of the supply chains: Pre-manufacture, Manufacture, Use and Post-use. The use of Multi-Agent System (MAS) prepares the most important requirements of an effective sustainable supply chain. At the same time, this agent-based approach provides reliable and agile systems, which will enable enterprises to accommodate ever changing needs of their customers in the future. In this article, the use of MAS for optimal Sustainable Supply Chain Management (SSCM) is reviewed and the integrated functioning of certain agents resulting in information sharing is also demonstrated. With this idea, an attempt is made to provide a MAS model for the SSCM. In the proposed model, each agent performs a specific function of the organization and shares information with other agents. In order to describe this multi-agent based approach, a simple case study is given to illustrate the sustainable supply chain operations.

scholarly journals Multi-Agent Based Load Balancing Dispatch for Power Systems with Renewable Energy

2020 ◽  
Vol 2020 (0) ◽  
pp. 13-16
Author(s):  
Kenta Hanada ◽  
Takayuki Wada ◽  
Izumi Masubuchi ◽  
Toru Asai ◽  
Yasumasa Fujisaki
Keyword(s):  
Renewable Energy ◽  
Load Balancing ◽  
Power Systems ◽  
Agent Based ◽  
Multi Agent

A Multi-Agent-Based Data Collection and Aggregation Model for Fog-Enabled Cloud Monitoring

2021 ◽  
Vol 11 (1) ◽  
pp. 73-92
Author(s):  
Chetan M. Bulla ◽  
Mahantesh N. Birje
Keyword(s):  
Data Collection ◽  
Fog Computing ◽  
Communication Overhead ◽  
Aggregation Model ◽  
Agent Based ◽  
Redundant Data ◽  
Monitoring Process ◽  
Proposed Model ◽  
Cloud Monitoring ◽  
Multi Agent

The fog-enabled cloud computing has received considerable attention as the fog nodes are deployed at the network edge to provide low latency. It involves various activities, such as configuration management, security management, and data management. Monitoring these activities is essential to improve performance and QoS of fog computing infrastructure. Data collection and aggregation are the basic tasks in the monitoring process, and these phases consume more communicational power as the IoT nodes generate a huge amount of redundant data frequently. In this paper, a multi-agent-based data collection and aggregation model is proposed for monitoring fog infrastructure. The data collection model adopts a hybrid push-pull algorithm that updates the data when a certain change in new data compared to old data. A tree-based data aggregation model is developed to reduce communication overhead between fog node and cloud. The experimental results show that the proposed model improves data coherency and reduces communication overhead compared to existing data collection and aggregation models.

Multi-Agent Based Dynamic E-Learning Environment

2011 ◽  
pp. 142-158 ◽  
Author(s):  
Saleh AlZahrani ◽  
Aladdin Ayesh ◽  
Hussein Zedan
Keyword(s):  
Learning Environment ◽  
Learning Objects ◽  
Agent Based ◽  
Development Framework ◽  
The World ◽  
E Learning ◽  
Multi Agent ◽  
The Subject ◽  
And Training ◽  
Agent Development

Grids are increasingly being used in applications, one of which is e-learning. As most of business and academic institutions (universities) and training centres around the world have adopted this technology in order to create, deliver and manage their learning materials through the Web, the subject has become the focus of investigate. Still, collaboration between these institutions and centres is limited. Existing technologies such as grid, Web services and agents are promising better results. In this article the authors support building our architecture Regionally Distributed Architecture for Dynamic e-Learning Environment (RDADeLE) by combining those technologies via Java Agent DEvelopment Framework (JADE). By describing these agents in details, they prove that agents can be implemented to work well to extend the autonomy and interoperability for learning objects as data grid.

Multi-Agent Simulation of Emergency Evacuation on the Sidewalk

2012 ◽  
Vol 253-255 ◽  
pp. 2005-2008
Author(s):  
Peng Chen ◽  
Shun Ying Zhu ◽  
Liang Jie Xu ◽  
Xiao Feng Ma ◽  
Zhi Gang Du
Keyword(s):  
Emergency Evacuation ◽  
Agent Based ◽  
Proposed Model ◽  
Agent Simulation ◽  
Multi Agent ◽  
Bus Station ◽  
Evacuee Behavior ◽  
Walking Time ◽  
Statistical Area

Transportation evacuation study has become a research focus in recent years. This paper deals with emergency evacuation on the sidewalk using agent-based simulation. The current study develops a traffic simulator within NetLogo, an agent-based environment. Two sub-models are proposed including facility sub-model to describe global path planning of evacuee and evacuee sub-model to describe the evacuee behavior. We conducted simulations to investigate the effect of generation position of evacuees and the proportion of choosing bus on evacuation through a case study. Simulation results indicate that the proposed model can well address the interaction among evacuees with different evacuation modes, and if evacuees choosing bus evacuate near bus station and evacuees choosing walk evacuate away from bus station, then average walking time of evacuees and maximum density in statistical area are relatively small.

A Multi-Agent Based Load Balancing Architecture to Support INPE Satellite Control Software

2006 ◽  
Author(s):  
Andreia Carniello de Aquino ◽  
Adriana Carniello Biancho ◽  
Mauricio Gonçalves Vieira Ferreira ◽  
José Demisio Simões da Silva
Keyword(s):  
Load Balancing ◽  
Control Software ◽  
Agent Based ◽  
Multi Agent ◽  
Satellite Control

Adaptive Ensemble Multi-Agent Based Intrusion Detection Model

2012 ◽  
pp. 647-659
Author(s):  
Tarek Helmy
Keyword(s):  
Machine Learning ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Machine Learning Algorithms ◽  
Agent Based ◽  
Detection Model ◽  
Detection Analysis ◽  
Proposed Model ◽  
Multi Agent

The system that monitors the events occurring in a computer system or a network and analyzes the events for sign of intrusions is known as intrusion detection system. The performance of the intrusion detection system can be improved by combing anomaly and misuse analysis. This chapter proposes an ensemble multi-agent-based intrusion detection model. The proposed model combines anomaly, misuse, and host-based detection analysis. The agents in the proposed model use rules to check for intrusions, and adopt machine learning algorithms to recognize unknown actions, to update or create new rules automatically. Each agent in the proposed model encapsulates a specific classification technique, and gives its belief about any packet event in the network. These agents collaborate to determine the decision about any event, have the ability to generalize, and to detect novel attacks. Empirical results indicate that the proposed model is efficient, and outperforms other intrusion detection models.

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