SWITCH EU H2020- ICT So)ware Workbench for Interac5ve, Time Cri5cal and Highly self- adap5ve Cloud applica5ons

Transcription

1 EU H2020- ICT SWITCH So)ware Workbench for Interac5ve, Time Cri5cal and Highly self- adap5ve Cloud applica5ons Dr. Zhiming Zhao System and network engineering University of Amsterdam

2 Outline Time cridcal applicadons and Cloud The SWITCH approach Use cases Current status Summary

3 Background me cri(cal Applica(ons: have very high business potendal or social impacts, e.g., live event broadcasdng, disaster early warning, and real- Dme business collaboradon; have very cri(cal quality requirements for services, e.g., video quality, system interacdon, or data delivery; But are very expensive in implementadon and operadon. 3

4 Background Clouds can provide: ElasDc resources Quality on demand services Programmability on the infrastructure SoRware defined networking etc. A potendal environment for Dme cridcal applicadons 4

5 Background Applica(on logic Time cri(cal qualit constraints, Virtualised infrastruc So>ware defined networking Sensors and mobi 5 devices.

6 Requirements System level performance requirements must be sadsfied to deliver acceptable performance; Verifiability for proving that the applicadon will actually achieve the desired QoS; Integra(on complexity of the applicadons require specialized knowledge on modeling and controlling sorware and infrastructure parameters; Use of virtualized resources require profound Cloud knowledge on selecdon of appropriate cloud plavorms and programming models; Configura(on of the infrastructure requires a common, reusable interface for programming the infrastructure and must be tailored to achieve the required response Dmes; Data intensive communica(on in the applicadon require virtualized storage and communicadon configuradons based on funcdonal descripdons and to characterize data throughput and latency amongst applicadon components; Adaptability for quality- on- demand: applicadons increasingly need to be configured to cope with quality- on- demand in the run- Dme environment; Adaptability for infrastructure in order to maintain the system level of performance; SLA nego(a(on is required when adapdng infrastructure to enforce explicit SLA with (federated) Cloud providers dynamically.

7 State of the art 7

8 State of the art 8

9 Requirements System level performance requirements must be sadsfied to deliver acceptable performance; Verifiability for proving that the applicadon will actually achieve the desired QoS; Integra(on complexity of the applicadons require specialized knowledge on modeling and controlling sorware and infrastructure parameters; Challenges: Use of virtualized resources require profound Cloud knowledge on selecdon of appropriate cloud plavorms 1. The and engineering programming models; method and sorware tools for developing, deploying Configura(on and execudng of the infrastructure classical requires Dme cridcal a common, applicadons reusable interface do not for yet programming include the infrastructure and must be tailored to achieve the required response Dmes; the programmability and controllability provided by the Clouds; Data intensive communica(on in the applicadon require virtualized storage and communicadon configuradons 2. The Dme based cridcal on funcdonal applicadons descripdons cannot and to yet characterize get the full data potendal throughput benefits and latency amongst which applicadon Cloud components; technologies could provide. Adaptability for quality- on- demand: applicadons increasingly need to be configured to cope with quality- on- demand in the run- Dme environment; Adaptability for infrastructure in order to maintain the system level of performance; SLA nego(a(on is required when adapdng infrastructure to enforce explicit SLA with (federated) Cloud providers dynamically.

10 H2020 SWITCH project Total budget: 3M euro DuraDon: Feb/2015- Jan/2018 Coordinator: University of Amsterdam ScienDfic coordinator: Zhiming Zhao ConsorDum: 10

11 About SWITCH ITCH addresses the entire lifele of time-critical, self-adaptive ud applications by developing middleware and front-end ls to enable users to specify ir time-critical requirements for application interactively using a ct manipulation user interface, loy their applications and adapt infrastructure to changing uirements at runtime either omatically (using the specified uirements) or by human rvention if desired.

12 SWITCH Integrated Development Environment (SIDE) Developer begins by composing the pplica(on logic and defining QoS/ oe constraints (step 1). (S)he can also give an abstract etwork overlay and other frastructure requirements (step 2). These acdvides are supported a rmal reasoning component (step ). This informadon is passed from IDE to DRIP, along with equirements such as resource roviders to be used and total pplicadon execudon cost budget tep 4).

13 Dynamic Real- Time Infrastructure Planner (DRIP) DRIP plans concrete virtual run(me nvironment (compudng, storage, etwork), reasoning with pplicadon- level QoS/QoE onstraints (step 5). DRIP generates Service Level greements (SLAs) with resource rovider(s) (step 6). The virtual environment is rovisioned (step 7). DRIP then customizes the virtual environment and deploys necessary services for the applicadon (step 8), and unbundles and executes the applicadon (step 9) onto the virtual infrastructures.

14 Autonomous System Adap5ve PlaPorm (ASAP) At run- Dme, SIDE allows user to: query & visualise applicadon, run- Dme environment status and real- Dme monitoring informadon (step 10); receive no(fica(on of important system status changes (step 11), and directly manipulate system execudon (step 12). ASAP also diagnoses system erformance and, where possible, utonomously makes decisions on ontrol acdons to restore erformance (step 10 again).

15 ApplicaDon logic programming User nodficadon for interacdon Query and visualizadon of system status Interact with the system Program infrastructure SWITCH interacdve development Environment (SIDE) Distributed Real Time Infrastructure Planner (DRIP) Applica(on- infrastructure Co- programming and control model Autonomous System AdaptaDon PlaVorm (ASAP) Execute applicadon Real- Dme monitoring Planning /provision virtual rundme environment Cloud provider(s)

16 Use cases Real (me business communica(on a^orm (Wellness telecom, Spain) 3. Cloud studio for direc(ng and broadcas(ng live events (MOG, Portugal) 2. The Elas(c Disaster Earlier warning system (BEIA, Romania) 16

17 So)ware development Use case (long term) Phase 5 SWITCH (Version 4) Phase 6 Use case (medium term) Use case (short term) SWITCH (Version 1) Phase 4 Phase 5 Phase 6 SWITCH (Version 2) SWITCH (Version 3) Phase 1-3 Phase 4 Phase 5 Phase 6 Single Private/ community Cloud test bed Federated Private/ community Cloud test bed Single public Cloud test bed Federated public Cloud test bed

18 Summary The SWITCH project (SoRware Workbench for InteracDve, Time CriDcal and Highly self- adapdve Cloud applicadons) addresses the urgent industrial need for developing and execudng Dme cridcal applicadons in Clouds. SWITCH addresses these problems by providing an interacdve and flexible sorware workbench that can Bring the necessary tools to control the lifecycle for rapid development, deployment, management and dynamic reconfiguradon of complex distributed Dme- cridcal Cloud applicadons. Bring infrastructure in the loop when designing and controlling Dme cridcal applicadons SoRware Workbench for InteracDve, Time CriDcal and Highly self- adapdve Cloud applicadons 18

19 Reference b: project.eu radon: , Funding: 3M Euro. e SWITCH InnovaDon and exploitadon Commifee. himing Zhao cien&fic Coordinator) Francisco Jesus Hidalgo Andrew Jones Vlado Stankovski George Surciu Pedro Ferre ees de Laat Ian Taylor Alexandre