MAVIE: A mobile agents view synchronization system

Akaichi, Jalel; Oueslati, Wided

doi:10.1109/icadiwt.2008.4664334

Cited by 3 publications

(8 citation statements)

References 15 publications

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“…In the literature, the DW evolution can be classified into three different approaches namely schema evolution [1,2,3,4], schema versioning [5,6] and view maintenance [7,8,9,10,11,12,13,14,15].…”

Section: State Of the Artmentioning

confidence: 99%

“…The increase need to decrease the network saturation and to minimize communication costs, have led [14] to the EVE solution to become more adapted for dynamic and distributed environment by adopting new techniques like the mobile agents. In fact, authors of [14] propose to design a mobile agents view synchronization system based on EVE called MAVIE. This latter has to ensure data warehouse maintenance under schema changes.…”

Section: Drop View V'mentioning

confidence: 99%

“…The following figure describes the communication between mobile agents of MAVIE system. Figure 1: MAVIE agent communication [14] Mobile information sources can change their schema continuously. This fact makes the views of the data warehouse undefined.…”

Section: Drop View V'mentioning

confidence: 99%

“…Authors in [10], [11], [12], [13] and [14] focuses on structural view maintenance. In fact, they presented the problem of DW evolution when the data sources change their schema.…”

Section: Authormentioning

confidence: 99%

“…In fact, the DW technology is seen as the process of good decision making since it provides necessary tools for data analysis such as the On Line Analytical Processing (OLAP). In the literature the DW evolution can be classified into three different approaches namely schema evolution [1,2,3,4] and schema versioning [5,6] when the DW is defined as a multidimensional schema (fact and dimension tables) and view adaptation and synchronization [7,8,9,10,11,12,13,14,15] when the DW is defined as a set of materialized views. The goal of this paper is to present different works related to DW evolution, then to propose a comparative study between those works.…”

Section: Introductionmentioning

confidence: 99%

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A Survey on Data Warehouse Evolution

Oueslati¹,

Akaichi²

2010

IJDMS

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The data warehouse (DW) technology was developed to integrate heterogeneous information sources for analysis purposes. Information sources are more and more autonomous and they often change their content due to perpetual transactions (data changes) and may change their structure due to continual users' requirements evolving (schema changes). Handling properly all type of changes is a must. In fact, the DW which is considered as the core component of the modern decision support systems has to be update according to different type of evolution of information sources to reflect the real world subject to analysis. The goal of this paper is to propose an overview and a comparative study between different works related to the DW evolution problem.

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Section: State Of the Artmentioning

confidence: 99%

Section: Drop View V'mentioning

confidence: 99%

Section: Drop View V'mentioning

confidence: 99%

“…Authors in [10], [11], [12], [13] and [14] focuses on structural view maintenance. In fact, they presented the problem of DW evolution when the data sources change their schema.…”

Section: Authormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Survey on Data Warehouse Evolution

Oueslati¹,

Akaichi²

2010

IJDMS

Self Cite

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What is the Impact of Mobility Data Integration on Decision Support Systems' Modelling and Evolution?

Azaiez

Akaichi

2016

International Journal of Information Systems in the Service Sector

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Classic data seems unable to keep pace with the technology era. In fact, the incredible progress related to geographic information systems, pervasive computing, and positioning technologies have motivated classic data to evolve towards new data kind called mobility data. For decisional purposes, these later have to be analysed; therefore, their integration into a decision support system becomes a must. However, the data warehouse used to store classical data seems to be inadequate for mobility data storage and analysis. This gave the birth of a new central repository type called trajectory data warehouse which is able to support mobility data extraction, transformation, loading, and analysis and/or mining. As classic data warehouses, the trajectory one often changes its content as well as its structure for various reasons such as the organizational business processes progressing over time, the evolving needs of decision makers that lead to DW structure enrichment with additional analyses axes, or even the incompleteness of needs initially captured during the design phase of the DW . This work proposes a survey that gathers the research works that deal with the issue of trajectory data warehouse modelling and evolution; then the authors present comparative study of the proposed solutions.

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Handling Instance Changes in a Multiversion Trajectory Data Warehouse

Oueslati¹,

Akaichi²

2011

AISS

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MAVIE: A mobile agents view synchronization system

Cited by 3 publications

References 15 publications

A Survey on Data Warehouse Evolution

A Survey on Data Warehouse Evolution

What is the Impact of Mobility Data Integration on Decision Support Systems' Modelling and Evolution?

Handling Instance Changes in a Multiversion Trajectory Data Warehouse

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