A Secured Agent-Based Framework for Data Warehouse Management

A Multi-Agent based transmission fault diagnosis system is researched in this paper. Many data digging analysis methods are employed, combined with data warehouse, OLAP and Multi-Agent technology. An intelligent decision supporting system for monitoring transmission network data is built. Data digging method is used to intelligently analyze and process fault data in the data warehouse, and Agent technology is used to realize data collection, pretreatment, inquiry, knowledge Automatic extraction, mining and other functions, which makes the whole mining process intellectual and intelligent. It aids transmission management with decision-making, thus to make the monitoring and repair of power grid fault more timely and accurate.

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AGENT BASED DATA STORAGE AND DISTRIBUTION IN DATA WAREHOUSES

International Journal of Software Engineering and Knowledge Engineering ◽

10.1142/s0218194008003842 ◽

2008 ◽

Vol 18 (05) ◽

pp. 597-617 ◽

Cited By ~ 1

Author(s):

NADER KOLSI ◽

ABDELAZIZ ABDELLATIF ◽

KHALED GHEDIRA

Keyword(s):

Data Warehouse ◽

Data Storage ◽

Data Distribution ◽

Distributed Data ◽

Agent Based ◽

Agent Model ◽

Capacity Limit ◽

Processing Resources ◽

Multi Agent ◽

Distributed Data Warehouse

The data warehouse (DWH) is usually presented as a centralized database. In this paper, we propose a new approach to manage data storage and distribution in a data warehouse environment. This approach deals with the dynamic data distribution of the DWH on a set of servers. The data distribution that we consider is different from the "classical" one which depends on the data use. The distribution in our approach consists in distributing data when the server reaches its storage capacity limit. This distribution assures the scalability and exploits the storage and processing resources available in the organization using the data warehouse. It is worth noting that our approach is based on a multi-agent model mixed with the scalability distribution proposed by the Scalable Distributed Data Structures. The proposed multi-agent model is composed of stationary agent classes: Client, Dispatcher, Domain and Server, and a mobile agent class called Messenger. These agents collaborate and interact to achieve automatically the storage, the splitting (distribution), the redirection and the access operations on the distributed data warehouse. In this paper, we demonstrate the improvements obtained when we have used the multi-agent system and the Messenger agents in the data storage operation.

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DMBVA - A Compression-Based Distributed Data Warehouse Management In Parallel Environment

Malaysian Journal of Computer Science ◽

10.22452/mjcs.vol20no1.6 ◽

2007 ◽

Vol 20 (1) ◽

pp. 63-76 ◽

Cited By ~ 2

Author(s):

Fazlul Hasan Siddiqui ◽

Abu Sayed Md. Latiful Hoque

Keyword(s):

Data Warehouse ◽

Distributed Data ◽

Warehouse Management ◽

Parallel Environment ◽

Distributed Data Warehouse

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Intelligent agent based framework to augment warehouse management systems for dynamic demand environments

Australasian Journal of Information Systems ◽

10.3127/ajis.v25i0.2845 ◽

2021 ◽

Vol 25 ◽

Author(s):

Tania Binos ◽

Vince Bruno ◽

Arthur Adamopoulos

Keyword(s):

Real Time ◽

Intelligent Agent ◽

Golden Rule ◽

Development Stage ◽

Management Systems ◽

Warehouse Management ◽

Agent Based ◽

Operational Issues ◽

Operational Constraints ◽

The Impact

Warehouses are being impacted by increasing e-commerce and omni-channel commerce. The design of current WMSs (Warehouse Management Systems) may not be suitable to this mode of operation. The golden rule of material handling is smooth product flow, but there are day-to-day operational issues that occur in the warehouse that can impact this and order fulfilment, resulting in disruptions. Standard operational process is paramount to warehouse operational control but may preclude a dynamic response to real-time operational constraints. The growth of IoT (Internet of Things) sensor and data analytics technology provide new opportunities for designing warehouse management systems that detect and reorganise around real-time constraints to mitigate the impact of day-to-day warehouse operational issues. This paper presents the design and development stage of a design science methodology of an intelligent agent framework for basic warehouse management systems. This framework is distributed, is structured around operational constraints and includes the human operator at operational and decision support levels. An agent based simulation was built to demonstrate the viability of the framework.

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