Cockpits: Real-time Monitoring and Adaptation of Future Internet Applications

Transcription

1 paluno The Ruhr Institute for Software Technology Cockpits: Real-time Monitoring and Adaptation of Future Internet Applications Prof. Dr. Klaus Pohl CAiSE June, Agenda The Internet connects the world 1. The Future Internet 2. Use Cases & Cockpits 3. Pro-Active Responsiveness 4. Summary Focusing on infrastructure and communication, i.e., worldwide connectivity, bandwidth, speed, e.g., e mail, gopher, WWW, Access to contents and information from everywhere and by everyone e.g., Google, Yahoo, youtube, facebook, 1

2 The Internet in 2010 Internet of s NEW Globally accessible software functions (services) IT-mediated access to human-provided capabilities Servicification of products Internet of Content Internet of s NEW Cloud services Cross-organizational alignment of IT systems Value-add services through seamless composition and integration Internet of Things 6 Internet of s Growth Public Cloud Market Size 2020 $160 Billion Business Processes / Workflows as a Applications/ Software as a Internet of Things Network connected devices connecting the world to the Internet Digitization of real-world through connected sensors and actuators Uniquely identifiable objects 2011 $20 Billion Platforms as a Infrastructure as a : Compute, Storage, Network Source: S. Ried und H. Kisker, Sizing the Cloud, Forrester Research, Inc., Apr , p. 9 7 Sources: data-directions.com; xively; DHL 8 2

3 Internet of Things Growth The Future Internet Convergence of s and Things Internet-connected Devices Billion (50% of which mobile) Connected Things / Sensors / Actuators Logistics Internet of s Future Internet Smart Energy E Mobility Billion E Health Internet of Content Internet of Things (Smart-)Phones Sources: GSMA und Machina Research, The Connected Life: A USD4.5 9 trillion global impact in 2020, GSMA, Feb , p. 3 Enabler for novel types of software intensive systems: Future Internet Applications Future Internet Applications Example Future Internet Applications Example On-demand Garbage Transport [urbiotica.com] Smart Watering Energy reduction: 20% (estimated) Water reduction: 60% (estimated) Source: urbiotica 12 3

4 Future Internet FP7 paluno Agenda FP 7 NoE Secure Software s & Systems FP7 IP FI PPP Core Platform FP7 IP Operational Trustworthiness Enabling Technologies FP 7 NoE Software, s & Systems FP7 IP Platform for Heterogeneous Networked Cooperating Objects FP 7 NoE Cooperating Objects FP7 STREP Adaptive Middleware for Autonomous s 1. The Future Internet 2. Use Cases & Cockpits 3. Pro-Active Responsiveness 4. Summary FP7 IP Global Transport and Logistics (FI PPP Phase 1) FP7 IP AgriFood, Transport and Logistics (FI PPP Phase 2) FP7 STREP Smart Grid Key Neighborhood Indicator Cockpit FP7 STREP Electricity and Monitoring System FP7 STREP Pervasive Computing in Embedded Systems FP7 STREP Safe Wireless High Mobility Industrial Systems 13 The Future Internet FI-WARE Core Platform FI-WARE Generic Enablers > 30 s: Platform for cost-effective creation and delivery of services, providing high QoS and security Facts: Duration: 04/11 03/14 Total cost: 54 Million EUR Marketplace IoT Broker VM Cloud Proxy Internet of Things Trust and Security Interface to Network & Devices Apps & s Cloud Security & Trust Data & Context Functionality FI- CoDE (Tools) Identity BigData Analysis Online Testing 4

5 Future Internet Public Private Partnership INFINITY XIFI FINEST Technical Architect FP 7 IP FInest Use of Generic Enablers INSTANT MOBILITY Technical SMARTAGRIFOOD Coordinator FINSENY SAFECITY OUTSMART FI-CONTENT ENVIROFI FIspace FI-CONTENT 2 Finesce FI-STAR FITMAN Expansion of Use Cases Research Partner (1 of 5) FI-WARE TF Extension and Usage Phase 1 (Use Cases) Phase 2 (Trials) Phase 3 (Expansion) 17 4 s integrated into the proof-of-concepts (demos) 15 s considered for FInest technical specification 18 Future Internet Applications Logistic Use Cases Monitoring & Adapting Operational Processes Cockpits and Control Centres Farming in the Cloud Crop Protection Information Sharing 2. Greenhouse & Control Perishable Goods Logistics 3. Fish Distribution and (Re-)Planning 4. Fruit & Vegetables Quality Assurance 5. Flowers/Plants Supply Chain Monitoring Distribution & Consumption 6. Meat Information Provenance 7. Import & Export of Consumer Goods 8. Tailored Information for Consumers Robust Transport Chains Common solution for specific application areas, e.g., Emergency Disaster management Chemical plants Production automation Human-in-the-Loop Monitoring Analysis Decision-making Adaptation (execution of) 8. Parcel and package pre-run 9. Multi-modal container transport Sources: npc.org, parabolicarc 20 5

6 Cockpits for Future Internet Applications Cockpits for Future Internet Applications Multi-modal Container Transport Software Software Monitoring Information Adaptation Guidance IoS Cockpits / Control Centre Sensor Effector IoT P D A Cockpits for Future Internet Applications Functional Building Blocks Suitable Abstractions to support Human Interactions MAPE LOOP Dynamically mapping of monitoring information to Application Models Alarm/ Info Analyze + Failure Prediction Observation Monitor + Fault Prediction Past Events Event Cockpit Front End Incl. Predictive Capabilities Adaptation Need Plans, Models, Knowledge Alternatives Changes IoT & IoS Gateway Future Internet Cockpit Plan Execute Decision Selection Action Human Operator IoT IoS Agenda 1. The Future Internet 2. Use Cases & Cockpits 3. Pro-Active Responsiveness 4. Summary 6

7 Future Internet Cockpits Proactive Responsiveness Fault Machine or environment (incl. third-party services) do not behave as expected Failure Experienced violation of requirement of service-based application Assume that a fault is observed e.g., violation of service contract Three possible cases All Requirements are still valid no adaptation needed Some Requirements violated + violation experienced in real world Failure detection reactive adaptation Some Requirements violated, but violation not experience yet Failure prediction proactive adaptation Future Internet Cockpits Proactive Adaptation Reactive Adaptation Repair/compensate failure already visible for end-user Proactive Adaptation (Case 1) A fault occurs and will lead to a failure? Repair/compensate fault to prevent failure Proactive Adaptation (Case 2) A fault is imminent, but did not yet occur Modify system before fault actually occurs Fault! Fault? Failure Failure Source: Carlo Ghezzi; Wace 2010, Ghent Future Internet Cockpits Pro-Active Failure Prediction Time Series Prediction: extrapolate future quality based on past observation Online Testing: complement monitoring data with testing data Machine Learning/Data Mining: prediction models trained using historic monitoring data Run-time Verification: formal analysis to ascertain predefined properties hold Static Analysis: infer properties of artifact Simulation: execute dynamic models Predictive Event-Processing: extends complex event processing with fault/failure prediction capabilities Failure Prediction Example: Predictive Complex Event Processing Extension of Complex Event Processing Monitoring Fault Prediction Failure Prediction Proactive Adaptation Y. Engel, O. Etzion, Towards proactive event driven computing, DEBS

8 Failure Prediction Example: Predictive Complex Event Processing Failure Prediction Example: Predictive Complex Event Processing Use Case - Airfreight Focus: High Shows / Low Shows Discrepancy between booked weight and actual weight delivered Can result in Over-loaded flights Under-loaded flights Empirical Validation IATA Cargo 2000 Monitoring Standard Shipper (Customer) BKD PUP REW Export Forwarder DEH FWB DOC BKD: Freight Booking by Shipper PUP: Pick up from Customer REW: Freight Received Forwarder RCS DEP ARR RCF Airline (Carrier) NFD AWD DLV DEH: Truck Departure to Airline FWB: Master Airway Bill Creation DOC: Truck Arrival at Departure Airline REH OFD POD Import Forwarder Consignee RCS: Freight Checked in at Airline Inefficient use of transport assets Transport delays, additional transports Cargo 2000 Monitoring data of a large forwarding company Five months of operational data Approximately 151,000 transport processes (80% for training; 20% test data) Failure Prediction Example: Predictive Complex Event Processing Agenda Results 586 over-loaded flights 532 under-loaded flights Predictive CEP fosters early warning 1. The Future Internet Mean Warning time: 58 hours (before departure) Accuracy over-load warnings: Precision: 99% Recall: 70% Accuracy under-load warnings: Precision: 80%, Recall: 95% 2. Use Cases & Cockpits 3. Pro-Active Responsiveness 4. Summary Z. Feldmann, F. Fournier, R. Franklin, and A. Metzger, Proactive event processing in action: A case study on the proactive management of transport processes, DEBS

9 Cockpits: Real-time Monitoring and Adaptation of Future Internet Applications Challenges for Future Internet Applications High Complexity Cockpit Front End Alarm/ Info Alternatives Decision Analyze + Failure Prediction Adaptation Need Plans, Models, Plan Observation Monitor + Fault Prediction Past Events Event Knowledge Changes Execute Selection Action IoT IoT & IoS Gateway Future Internet Cockpit IoS Source: L. Northrop, Keynote, ICSE Challenges for Future Internet Applications High Complexity Challenges for Future Internet Applications Servicification of Products Physical goods and products are Enhanced and extended by services Even fully turned into services, e.g., car sharing, washing-machine-as-aservice, drilling-as-a-service, Smart Grids Ultra Large Scale Systems Cyber Physical Systems Socio-technical Systems Multimodal Transport Smart Cities Immaterial products Business processes (BPaaS) Software (SaaS) Platforms (PaaS) Infrastructure (IaaS) Content/Data (CaaS, DaaS) 2011 $20 Billion 2020 $160 Billion Sources: umd.edu; Acatech; libelium Sources: NESSI; IFIP; Forester 9

10 Data Flood (Tsunami) Contents, Media, Documents Global Data Volume Exabyte Challenges for Future Internet Applications Fast-paced Technology and Societal Changes Million March 2013 # of Users 1.11 billion Exabyte 1 Exabyte = 1 million Terabyte = 12 stacks of books from earth to Sun Exabyte = 160 stacks of books from earth to Pluto 2004 Launch of Facebook Basically all this information has been produced in the last 20 years Source: IDC s Digital Universe Study, sponsored by EMC, December Sources: facebook, Ben Foster; dreamgrow.com 38 Challenges for Future Internet Applications Fast-paced Technology and Societal Changes Summary Radical Change / Revolution

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