SAVI-IoT: A Self-managing Containerized IoT Platform
•Als PPTX, PDF herunterladen•
0 gefällt mir•41 views
A paper presented in FiCloud 2017.
Empfohlen
Empfohlen
Weitere ähnliche Inhalte
Was ist angesagt?
Was ist angesagt? (20)
Ähnlich wie SAVI-IoT: A Self-managing Containerized IoT Platform
Ähnlich wie SAVI-IoT: A Self-managing Containerized IoT Platform (20)
Mehr von York University
Mehr von York University (7)
Kürzlich hochgeladen
Kürzlich hochgeladen (20)
SAVI-IoT: A Self-managing Containerized IoT Platform
- 1. The IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud17)August 22, 2017 SAVI-IoT: A Self-Managing Containerized IoT Platform Hamzeh Khazaei, Hadi Bannazadeh and Alberto Leon-Garcia Department of Electrical and Computer Engineering
- 2. The IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud17)August 22, 2017 2Agenda Introduction Objectives Features Architectural Views Autonomic Management System Experiment Conclusion & Future Research Demo
- 3. The IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud17)August 22, 2017 3Introduction • Layered architectures to leverage for IoT application and platforms • Hypervisor based virtualization (HVV) is quite mature • However, HVV is not flexible, portable, programmable and lightweight enough • Linux container Isolation (LCI) can bring the same revolutions to IoT that HVV brought to cloud • LCI allows us to instantiate, relocate, and optimize virtual IoT capabilities • SAVI-IoT is a platform for end-to-end management of IoT applications that leverages both
- 4. The IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud17)August 22, 2017 4Objectives • To enable the concept of Infrastructure as Code in the IoT context • To empower IoT operations with the flexibility and elasticity of cloud macro and micro services • To offer distributed and decentralized computation paradigm • To support systems where IoT-based and data intensive applications may pose specific requirements for • low latency • restricted bandwidth • data locality • elasticity, scalability • programmability • security and privacy.
- 5. The IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud17)August 22, 2017 5Features • SAVI-IoT is a fully programmable IoT platform • It is cloud and application agnostic • Combines SDI, SDN and SDT resulted in SDIoT platform • It is location-aware in both macroservice and microservice layers • Big data friendly; realtime and retrospective analysis; edge processing • Provides Autonomic Management System at runtime • Supports template-based deployment and configuration • Visualization & interactive monitoring • Implemented purely in Python
- 6. The IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud17)August 22, 2017 6Layered View
- 7. The IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud17)August 22, 2017 7Component View and Service Orchestration
- 8. The IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud17)August 22, 2017 8Sample IoT Application Deployed by SAVI-IoT
- 9. The IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud17)August 22, 2017 9Autonomic Management System Autonomic Manager: – Scale out/in & up/down all services autonomously – Scale out/in & up/down all layers accordingly – Cascade scalability – Workload management – Service inspection Interactive Monitoring: – Interval based – Event based
- 10. The IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud17)August 22, 2017 10 Smart Application on Virtual Infrastructure (SAVI) Cloud 1GE L2 Ethernet https://portal.savitestbed.ca https://www.savinetwork.ca
- 11. The IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud17)August 22, 2017 11Experiment – Auto-Scalability – Core Cloud UniversityofToronto,Ontario
- 12. The IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud17)August 22, 2017 12Experiment – Auto-Scalability – Edge Clouds Calgary, Alberta McGill, Quebec Waterloo, Ontario
- 13. The IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud17)August 22, 2017 13Conclusion & Future research Future Research – Smart Deployer for self-deployment and configuration • Benchmarking of the underlayer infrastructure • Tuning parameters by learning (RL) • Proposing a design pattern for a smart deployers Conclusion – We presented SAVI-IoT platform that provides: – End-to-End orchestration of IoT applications • decomposing the application into micro/macro services – Runtime management of highly distributed IoT applications • Brings about elasticity, reliability, scalability and fault tolerance – Fully programmable with location awareness – Visualization & Interactive monitoring
- 14. The IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud17)August 22, 2017 hamzeh.khazaei@ieee.org http://individual.utoronto.ca/hkh SAVI-IoT: A Self-Managing Containerized IoT Platform Demo: please download and play the file at: https://goo.gl/ZXGX6d
Hinweis der Redaktion
- Layered architectures are the right way to go for IoT application and platforms However, HVV is not flexible, portable, programmable and lightweight enough for edge and aggregators, in particular. LCI allows us to instantiate, relocate, and optimize virtual IoT capabilities in order to control in a more flexible and fine-grained fashion. SAVI-IoT is a platform for end-to-end management of IoT applications by leveraging both virtualization techniques.
- SAVI-IoT intends to enable the concept of Infrastructure as Code in the IoT context. The idea is to empower IoT operations with the flexibility and elasticity of cloud macro and micro services. It offers distributed and decentralized computation paradigm, as required by IoT technologies; bridging the gap between cloud computing and IoT things. (Fog, cloudlet and mobile edge) SAVI-IoT platform is designed to support systems where IoT-based and data intensive applications may pose specific requirements for low latency, restricted bandwidth, data locality, elasticity, scalability, programmability, security and privacy.
- Combines Software Defined Infrastructure (SDI), Software Defined Networking (SDN) and Software Defined Things (SDT) resulted in SDIoT platform Dynamically delivers any services to any layer or location Provides Autonomic Management System; elasticity, reliability, fault tolerance, scalability Visualization & interactive monitoring of the platform and applications
- This is the layered view comprising of the infrastructure, platform and applications that are contributing in realizing SAVI-IoT.
- This picture shows the SAVI-IoT components and the services that are deployed on each of them. In the bottom part we have sensors, i.e., the physical IoT plant. ----------------------------------------------------------------- IoT Gateway: is the closest node to the physical sensors; IoT Middleware: is responsible for managing underlayer sensors. These nodes will be part of the application cluster (i.e., a Cluster Worker) that can be managed from a single point of management. The Autonomic Manager component in this node is mainly monitoring agents to report the latest update of resource utilization at this layer. IoT Control Services: are services that will be used to control sensors; applying commands receiving from upper layer on connected sensors. Aggregator Microservices: these services are responsible for managing the sensor data at this layer. ----------------------------------------------------------------- Edge-Clouds: is the closest cloud resources to the IoT plant. Macroservices: includes all the services, VMs, networking, storage, etc, from the edge clouds. The rest of components have the same functionality as in the IoT Gateways but in a higher level. For example, Edge IoT Microservices deal with management of received data from all corresponding Gateways which is performing different data processing compared to Gateways. ----------------------------------------------------------------- Core-Cloud: the core data center that theoretically has unlimited resources and might be far from the IoT plant. Cluster-Master: is the master node of the IoT application cluster that will be deployed in the core cloud. Autonomic Manager: here all monitored data will be analyzed and then appropriate plans will be created to be executed across all layers. Current plans are mainly concerned with scaling services by providing them more/less resources according to the status of the application and/or the workload. Core IoT Microservices: here we deploy services that need to consume the whole IoT data or are supposed to have a global view of the whole IoT application.
- This diagram shows the sample IoT application that has been deployed and managed by SAVI-IoT. We leveraged virtual sensors that act as probes by sending the cpu, memory and network metrics obtained from their corresponding hosts. Kafka is the service deployed on IoT gateways. Spark as the edge cloud service. On core, we have Cassandra datastore, global Spark and visualization services. For this application we designed and deployed an autonomic management system to scale and monitor application continuously.
- SAVI is an OpenStack based academic multi-tire cloud computing center deployed in Canada. The SAVI-IoT platform inherits it’s name from SAVI cloud. SAVI has it’s core at the University of Toronto and seven edges at 7 universities across Canada.
- This figures show the auto-scalability feature of the SAVI IoT. The two top pictures show that services scale out and in according to the workload. The bottom picture shows the provisioning time for VMs and containers for different services.
- This pictures show the auto-scalability in Edge clouds located at Calgary, McGill and Waterloo. As can be seen both micro and macro services have been scaled out/in according to the workload.