Universitaet Innsbruck

Institut fuer Informatik


Seminar "Vertiefungsseminar" (SE 2.0)

Cloud, Edge und Fog Computing

Themensammlung

Die folgende Liste ist lediglich eine Sammlung der möglichen Themen für das Seminar. Themen in roter Farbe sind neue Themen. Seminarthemen können auch von Studierenden vorgeschlagen werden. Die genaue Festlegung der Themen und der Zeiten erfolgt in der Vorbesprechung!
 

Themenkatalog
Themen
Einführung Cloud Computing: Eine Einführung (IaaS, PaaS, SaaS)
 Introduction to Edge and IoT
From event streams to process models and back: challenges and opportunities, by Pnina Soffer et al.
Fog computing and its role in the IoT
Fogbus: a blockchain-based lightweight framework for edge and fog computing
Serverless Computing The Rise of Serverless Computing; What Serverless Computing is and should become: next phase of cloud computing
A decentralized framework for serverless edge cmputing in the IoT
On the FaaS Track: Buidling stateful distributed applications with serverless architectures
A practical declarative programming framework for serverless computing, by Shannon Joyner et al.
Serverless computing with  OpenWhisk and  AWS Lambda
Serverless computing with Google
Serverless computing with Microsoft Azure
lithops.cloud
FaaSm: Lightweight isolation for efficient stateful serverless computing
Backend as a Service (BaaS)
Google cloud dataflow
AWS glue 
google App Engine
PyWren and numpywren
ExCamera
FaaSM: lightweight isolation for efficient stateful serverless computing
notification services: AWS SNS, AWS SQS, etc.
Interoperabilität Interoperability in Internet of Things: Taxonomies and Open Challenges
Semantic Interoperability
Next generation service interface to achieve interoperability for distributed systems (NGSI)
FIWARE: The open source platform for our smart digital future
Formal foundations of serverless computing, by Abhinav Jangda et al.
Cloud Integration Hubs: integrate data through batch, real-time and events over the Cloud
Workflows allgemein
Sweep: accelerating scientific research through scalable serverless workflows
workflowpatterns.com
Node-RED von IBM
FAIR workflows: fair-workflows.github.io
Workflow provenance
The future of scientific workflows, by E. Deelman et al
Serverless Workflows RADICAL-Cybertools: Building blocks for middleware for workflow systems
Parsl: phython library for programming and executing data oriented workflows in parallel
Flux: the workflow of workflows
CRUCIAL: buillding stateful distributed applications with serverless architectures, by. Daniel Barcelona-Pons, et al.
Fogflow (NEC)
Azzure IoT Edge
Amazon Greengrass
Workflows with Microsoft LogicApps
Workflows with Azzure Durable Functions
Workflows with Amazon StepFunctions
Workflows with Google Cloud Composer
Workflows with IBM Composer
Workflows with Fission
Triggerflow: Trigger-based orchestration of serverless workflows
FaaS orchestration of parallel workflows, Gerard Paris, et al.
Heterogeneous hierarchical workflow composition (Rosa Badia et al)
Comparison of FaaS orchestration systems (by Pedro Garcia Lopez et al)
In search of fast and efficient serverless DAG engine, by Benjamin Carver, et al.
FunctionBench: A suite of workloads for serverless cloud function services
Scheduling Multiple workflow scheduling with offloading tasks to edge cloud
MCDS: AI augmented workflow scheduling in mobile edge cloud computing systems
Addressing application latency requirements through edge scheduling
Task offloading for mobile edge computing in software defined ultra-dense network
Microservices scheduling model over heterogeneous cloud-edge environments as support for IoT applications
Online job dispatching and scheduling in edge-clouds
A data-replica placement strategy for IoT workflows in collaborative edge and cloud environments
Dynamic scheduling for sotchastic edge-cloud computing environments using A3C learning and residual recurrent neural networks
A task scheduling strategy in edge-cloud collaborative scenario based on deadline
IoT-Edge without the cloud Picasso: A lightweight edge computing platform
Incremental deployment and migration of geo-distributed situation awareness applications in the fog
Tasklets: better than best-effort computing
Resource management Resource managemeent in fog/edge computing: a survey on architectures, infrastructure, and algorithms
HUNTER:  AI based holistic resource management for sustainable cloud computing
Disaggregated datacenters
LegoOS: a disseminated, distributed OS for Hardware Resource Disaggregration
EdgeOS: an edge operating system
Resource management approaches in fog computing: a comprehensive review
ENORM: a framework for edge node resource management
Resource management at the network edge: a deep reinforcement learning approach
Connecting and managing a large number of of IoT devices: Azure IoT Hub
Holistic resource managment for sustainable and reliable cloud computing
Automated fine-grained cpu cap control in serverless computing platform
Deadline-based dynmaic resource allocation and provisioning algorithms in fog-cloud environment
A dynamic resource controller for a lambda architecture
Amoeba: Qos-awareness and reduced resource usage of microservices with serverless computing
Distributed and Local Storage IBM cloud object storage project
Faasm: lightweight isolation for efficient stateful serverless computing
Plasma object storage from apache arrow: local per-node cache
Infinispan: cluster based caching
RUCIO: scientific data management
CRUCIAL distributed shared objects: https://github.com/danielBCN/crucial-dso
Cassandra: a decentralized structured storage system
dataClay: distributed data storage system
Verschiedenes Galaxy: open, web-based platform for accessible, reproducible, and transparent computational research (galaxyproject.org)
Software, tools, and respositories for code mining (D3.1 from the Morphemic EU project)
New Directions in Cloud programming, A. Cheung et al
Consistency analysis in Bloom: ca CALM and collected approach
CAMEL: Cloud application modellling and execution language
PLEDGER: benchmarking for the cloud
Riotbench: an IoT benchmark for distributed stream processing systems.
Unikraft OS toolki8t for lightweight OS images

 

T. Fahringer, Institut für Informatik, Universität Innsbruck