DISA Workshop – EAI Chinacom 2021

Workshop on Intelligent Computing Empowered Data Intensive Services Application (DISA)

Service-oriented architecture (SOA) is a widely accepted and engaged paradigm for the realization of business processes that incorporate several distributed, loosely coupled partners. Today, Web services and the Business Process Execution Language for Web Services (BPEL4WS, BPEL for short) are the established technologies to implement such a service-oriented architecture. Generally, we define the notion of a data-intensive services based application as a collection of related structured activities or tasks (services) that produce a specific result; huge data sets have to be exchanged between several loosely coupled services in such a data-intensive application. In this case, the AI Empowered DISA has been applied in massive data successfully, such as data mining and analysis from mobile device data, population migration and virus contacts discovery form social media.

DISA focuses on the challenges imposed by data-intensive services based applications, and on the different state-of-the-art solutions proposed to overcome emerging challenges. The aim of DISA is to encourage academic researchers and industry practitioners to present and discuss all methods and technologies related to research and experiences in a broad spectrum of data-intensive services based applications.

Workshop Papers will be published in a dedicated section of the Chinacom Conference Proceedings.

All registered papers will be submitted for publishing by Springer and made available through SpringerLink Digital Library.

Proceedings will be submitted for inclusion in leading indexing services, such as Web of Science, EI Engineering Index (Compendex and Inspec databases), DBLP, EU Digital Library, Google Scholar, IO-Port, MathSciNet, Scopus, Zentralblatt MATH.

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The topics of the workshop include but not limited to:

1) Data intensive services representation

Modeling of data intensive services
Reference models for data intensive services
Semantic models for data intensive services
Logistics Ontology for data intensive services
Integrating data intensive services models with Web service models
Repositories and dictionaries for data intensive services
Data intensive service data integration

2) Data intensive services based application building, management and coordination

Data intensive service design and engineering
Data intensive service composition, orchestration and choreography
Data intensive service runtime management and monitoring
Services for managing decentralized data intensive services
Data intensive service quality aspects and their management
Negotiation protocols for data intensive services
Market-based coordination of data intensive services, i.e., auctions, exchanges
Modeling, simulation and optimization of data intensive services
Verification of data intensive services
Transactional safeguarding of data intensive services
Service-oriented architectures for the setup and enactment of data intensive services
Mashups and data intensive services
Agents for the lifecycle management of data intensive services
Performance aspects of data intensive application

3) SLA Management

Languages for describing SLAs for data intensive services along and across value chains
Semantic annotation of SLA for data intensive services
SLA negotiation for data intensive services
SLA monitoring for data intensive services
Integrating data intensive services into SLA management infrastructures

4) Case studies and demos