Workshop on Service Oriented Edge-side Computing and Application (SOECA)

With the increasing adoption of the Internet of Things (IoT), an abundance of geographically dispersed IoT devices have been deployed at the edge of the network. Edge/Fog computing is a new type of computing paradigm in which substantial computing and storage resources are placed at the edge of the Internet. Edge-side computing is ideal for some latency sensitive and network bandwidth demanding applications and systems, since they can fully utilize the resources near the edge of the network instead of communicate with cloud servers.

Service-oriented computing (SOC) is a key enabler for the development of robust and high-quality intelligent Internet-scale distributed applications. Many standards and technologies have been proposed and implemented in the SOA area and can be used to guide new Edge-based architectures and applications.

This workshop is to bring together researchers working on service oriented edge-side computing and applications. Specific topics of interest include but are not limited to:
Service Oriented Edge-side Engineering:
  • Design of lightweight edge-side architecture
  • Lightweight edge services
  • Edge service orchestration
  • Edge Qos Management
  • Security, privacy, and trust of edge services
  • Variety of network connections
  • Heterogeneity of edge devices
  • Edge service fault tolerance
  • Energy management
  • Workflows in edge services
Edge Services:
  • Service mining
  • Device discovery service
  • Data monitoring service
  • Service based workload sharing
  • Services for IoT applications
  • Edge service interaction
  • Service for mobile devices
  • Service change management
  • Microservices deployment and management
Edge Storage Service:
  • From cloud to edge device
  • From edge device to cloud
  • Resource scheduling
  • Resource management
  • Security and anomaly detection
  • Privacy-enhanced services
Edge Service applications:
  • Artificial Intelligence
  • Virtual Reality
  • Image Processing
  • Natural Language Processing
  • Machine Learning
  • Big Data Analysis
  • Data Mining
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