E-raamat: Service-Oriented Computing: 18th International Conference, ICSOC 2020, Dubai, United Arab Emirates, December 14-17, 2020, Proceedings

Microservices.- Optimal Evolution Planning and Execution for
Multi-Version Coexisting Microservice Systems.- Topology-aware Continuous
Experimentation in Microservice-based Applications.- Charting Microservices
to Support Services Developers: the Anaximander Approach.- Fast Replica of
Polyglot Persistence in Microservice Architectures for Fog Computing.- On
Discovering Data Preparation Modules Using Examples.- Internet of Things.-
Accelerate Personalized IoT Service Provision by Cloud-Aided Edge
Reinforcement Learning: A Case Study on Smart Lighting.- A game-based secure
trading of big data and IoT services: Blockchain as a two-sided market.- A
Dynamic Cost Model to Minimize Energy Consumption and Processing Time for IoT
Tasks in Mobile Edge Computing Environment.- Automated SLA Negotiation in the
IoT Environment A Metaheuristic Approach.- PATRIoT: A data sharing platform
for IoT using a service-oriented approach based on blockchain.- Services at
the Edge.- Energy Minimization for Cloud Services with Stochastic Requests.-
Scalable Joint Optimization of Placement and Parallelism of Data Stream
Processing Applications on Cloud-Edge Infrastructure.- Impact of Service-
and Cloud-Based Dynamic Routing Architectures on System Reliability.- Pricing
in the Competing Auction-based Cloud Market: A Multi-Agent Deep Deterministic
Policy Gradient Approach.- Dynamic Edge User Allocation with User specified
QoS preferences.- Fault-tolerating Edge Computing with Server Redundancy
based on a Variant of Group Degree Centrality.- TD-EUA: Task-decomposable
Edge User Allocation with QoE Optimization.- A Decentralized Reactive
Approach to Online Task Offloading in Mobile Edge Computing Environments.-
Mobility-Aware Service Placement for Vehicular Users in Edge-Cloud
Environment.- Machine Learning for Service Oriented Computing.-
Feature-Model-Guided Online Reinforcement Learning for Self-Adaptive
Services Metzger.- FAST: A Fairness Assured Service Recommendation Strategy
Considering Service Capacity Constraint.- Real-time Automatic Configuration
Tuning for Smart Manufacturing with Federated Deep Learning.- A Trust and
Energy-Aware Double Deep Reinforcement Learning Scheduling Strategy for
Federated Learning on IoT Devices.- Smart Data and Smart Services.- A
Spectrum of Entropy-Based Precision and Recall Measurements Between
Partially Matching Designed and Observed Processes.- A Knowledge Graph based
Approach for Mobile Application Recommendation.- ICS-Assist: Intelligent
Customer Inquiry Resolution Recommendation in Online Customer Service for
Large E-Commerce Businesses.- Detecting User Significant Intention via
Sentiment-Preference Correlation Analysis for Continues App Improvement.-
Fine-Grained Task Distribution for Mobile Sensor Networks with Agent
Cooperation Relationship.- Allocation Priority Policies for Serverless
Function-execution Scheduling Optimisation.- Adaptive Recollected RNN for
Workload Forecasting in Database-as-a-Service.- Exploring Interpretability
for Predictive Process Analytics.- Designing Optimal Robotic Process
Automation Architectures.- Service Oriented Technology Trends.- RESTest:
Black-Box Constraint-Based Testing of RESTful Web APIs.- A Type-Sensitive
Service Identification Approach for Legacy-to-SOA Migration.- Automated
Quality Assessment of Incident Tickets for Smart Service Continuity.-
API-Prefer: An API Package Recommender System based on Composition Feature
Learning.- Tail-Latency-Aware Fog Application Replica Placement.- Two-Sided
Matching Scheduling using Multi-Level Look-Ahead Queue of Supply and Demand.-
A Practice-Oriented, Control-Flow-Based Anomaly Detection Approach for
Internal Process Audits.- Industry papers.- Latest Image Recommendation
Method for Automatic Base Image Update in Dockerfile.- Online Topic Modeling
for Short Texts.- Metrics for Assessing Architecture Conformance to
Microservice Architecture Patterns and Practices.