Service-Oriented Computing

22nd International Conference, ICSOC 2024, Tunis, Tunisia, December 3-6, 2024, Proceedings, Part I
Herausgegeben:Gaaloul, Walid; Sheng, Michael; Yu, Qi; Yangui, Sami

• Broschiertes Buch

Produktbeschreibung

The two-volume set LNCS 15404 and 15405 constitutes the refereed proceedings of the 22nd International Conference on Service-Oriented Computing, ICSOC 2024, held in Tunis, Tunisia, during December 3-6, 2024.

The 38 full papers and 19 short papers presented in these proceedings were carefully reviewed and selected from 255 submissions. The papers are organized in the following topical sections:

Part I: Edge and IoT; Generative AI; Service Security and Privacy; and Processes and Workflows.

Part II: Cloud Computing; QoS and SLA; Microservice; Service Recommendation; Emerging Technologies and Approaches; Service Composition; Blockchain; and Industry Papers.

Produktdetails

• Lecture Notes in Computer Science 15404
• Verlag: Springer / Springer Nature Singapore / Springer, Berlin
• Artikelnr. des Verlages: 978-981-96-0804-1
• Seitenzahl: 420
• Erscheinungstermin: 7. Dezember 2024
• Englisch
• Abmessung: 235mm x 155mm x 23mm
• Gewicht: 634g
• ISBN-13: 9789819608041
• ISBN-10: 981960804X
• Artikelnr.: 72063282

Inhaltsangabe

.- Edge and IoT.
.- Efficient and Dependency-aware Placement of Serverless Functions on Edge Infrastructures.
.- POSEIDON: Efficient Function Placement at the Edge using Deep Reinforcement Learning.
.- ABBA-VSM: Time Series Classification using Symbolic Representation on the Edge.
.- An Energy-Efficient Partition and Offloading Method for Multi-DNN Applications in Edge-End Collaboration Environments.
.- Crowdsourcing Task Assignment with Category and Mobile Combined Preference Learning.
.- Federated Learning as a Service for Hierarchical Edge Networks with Heterogeneous Models.
.- Optimizing Traffic Allocation for Multi-Replica Microservice Deployments in Edge Cloud.
.- An Event-B Based Approach for Horizontally Scalable IoT Applications.
.- Efficient Provisioning of IoT Energy Services.
.- Attention-driven Conflict Management in Smart IoT-based Systems.
.- Benchmarking Deep Learning Models for Object Detection on Edge Computing Devices.
.- Generative AI.
.- LLM Enhanced Representation For Cold Start Service Recommendation.
.- Combining Generative AI and PPTalk Service Specification for Dynamic and Adaptive Task-Oriented Chatbots.
.- Automated Generation of BPMN Processes from Textual Requirements.
.- Plug-and-Play Performance Estimation for LLM Services without Relying on Labeled Data.
.- UELLM: A Unified and Efficient Approach for Large Language Model Inference Serving.
.- Service-Oriented Requirements Elicitation Through Systematic Questionnaire Design: A Problem-Driven GenAI Approach.
.- Assessing Large Language Models Effectiveness in Outdated Method Renaming.
.- Service Security and Privacy.
.- DynaEDI: Decentralized Integrity Verification for Dynamic Edge Data.
.- Heterogeneous Multi Relation Trust for SIoT Service Recommendation.
.- A Context-Aware Service Framework for Detecting Fake Images.
.- Bias Exposed: The BiaXposer Framework for NLP Fairness.
.- FlowShredder: Protocol-Independent In-Network Encryption for Rich Media Traffic.
.- Processes and workflows.
.- HiGPP: A History-informed Graph-based Process Predictor for Next Activity.
.- From Visual Choreographies to Flexible Information Protocols.
.- Architectural Elements of decentralized Process Management Systems.
.- LLM-based Business Process Documentation Generation.