The Future of Real Time Services Delivery for IoT

Transcription

1 The Future of Real Time Services Delivery for IoT Schahram Dustdar Pacific Controls Systems, Advisory Board Member Professor of Computer Science, Vienna Univ. of Technology, Austria

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3 Future ICT Services Common Themes Innovation Shifts From Core Applications To The Edge Of The Enterprise and Analytics Ubiquitous, seamless open access becomes norm Internet of Things (IoT) drives the integration of the physical and digital worlds A new generation of supplier collaboration/integration emerges on cloud/saas platform Analytics, not business applications, improve business decisions and insights As-A-Service Becomes The Norm The per-use pricing model with the ability to scale up and down as the business requires More standardized offerings with lower management overhead for the customer Multitenant delivery to reduce costs; and The substitution of capex for opex outlays Nascent services today security, data management, and product development fully develop Usage Services Industry Structure Forces Shaping The Future Of ICT Services Access Shared Services & Data Brokerage Multi-Sided business models Integrates diverse needs Stages new services innovations Creates significant differentiation Barriers Between New Content And Services Providers And Traditional Network Providers Blur Demand And Growth Will Shift To New Services With Higher Margins De-coupling of network traffic and revenue New classes of offerings will emerge for services orchestration and services integration New services competitors will emerge as the lines between tech segments blur; old ones will fade Business Model Need For Advancements Within Network and Managed Services Infrastructure All environments (home, office, car) are context aware Market for ultra-low-cost devices grows New multi access wireless architectures are needed Radical new architectures and technologies are needed in order to cope with the massive exchange of data

4 Smart Evolution People, Services,Things Smart Energy Networks Smart egovernments & eadministrations Smart Homes DVC PC TV STB Game Machine Audio Elastic Systems Smart Transport Networks ehealth & Smart Health networks Telephone DVD

5 Autonomic Nervous System 5

6 Think Ecosystems: People, Services, Things Diverse users with complex networked dependencies and intrinsic adaptive behavior has: 1. Robustness mechanisms: achieving stability in the presence of disruption 2. Measures of health: diversity, population trends, other key indicators

7 Pacific Controls Connecting Cloud Computing to IoT From physically isolated verticals to virtual verticals Software-defined elastic data centers and IoT ecosystems SD units are described with well-defined API Provisioning units for customized gateways Dynamically composing units into runtime topologies Runtime controlling and optimization via configuration policies (DevOps principle)

8 Virtual verticals From physically isolated verticals to virtual verticals Shared common software services and computing resources Configurable IoT solutions Easy integration with heterogeneous IoT infrastructure Facilitate development and delivery of new services 8

9 IoT & Cloud Computing

10 Ultra Large-scale IoT Pacific Controls Command Control Center

11 Airports, ports and Critical Infrastructure Government Sector Hospitality Sector Healthcare Sector Utilities and Smart Grid Datacenters Industrial Sector Access control Environment Transport Sector Food Transfer Compliance Process Street Light Management Education Sector Lighting Control Power Quality Control Finance Sector Ubiquitous Managed Services Solution Across Business Verticals CCTV Monitoring FDD Storage policies Incidents manager Predictive Public Safety Chart modeling HealthCare builder Expert rule engine Operations manager Managed services Portfolio management Event management Analytics Algorithm Data engine Blackbox Event Facilities mining Industrial module Parking Open Waste mgmt Service Control process Control integration Management Mgmt GUI Resource platform Regression parameters Database builder mgmt. engine Portfolio Point manger Integration Mgmt Resource framework Analyics metering engine framework manager Numerous Forms Of Smart Services Provisioning Services SIM profile configuration Network configuration Controls Activation Deactivation Privacy Security Location awareness KIOSK Monitoring Transaction Mgmt. Visibility Billing Reporting IoT and Cloud Computing enable smart services ecosystem and collaboration opportunities Some 10 to 50 billion devices and sensors exist for M2M applications

12 Cloud Galaxy 2020 Real-Time Managed Services Platform Pacific Controls combines smart connected device management with complex IT systems & infrastructure to create unified real-time services delivery platform that addresses diverse challenges in a single, scalable solution Development Platform For Edge Devices Complex Event-based Processing Systems Real-time Situational Awareness Automated Real-time Analysis Mobile Devices and Workers Vertical Apps Vertical Apps 3 rd Party Vertical Apps Galaxy Core, Including Communications Governance, Database, Visualization, Integrity Rules, Metering, Billing, GBot Management & Deployment Comms Drivers Aggregation Device (OS) Software-Defined Machines Device Management Telco Connect Machine Sensor Instrument API Comms Drivers Aggregation Device (OS) Software-Defined Machines Machine Sensor Instrument 3 rd Party Vertical Apps Comms Drivers Vertical User Group Gbot-Enabled App Store GBot Gateways Galaxy Ready Need: GBot capable of processing: Time series data Structured data Un-structured data Monitoring Control

13 Integration Presentation Third Party Application Developers End Users Facilities Management Service Providers Measurement & Verification Continuous Commissioning Energy Analysis Fault Detection & Diagnostics Dashboards & Reports OEM Carbon Footprint Analysis & GHG Accounting Maintenance Management Asset Performance Management Alarm Management Database ICT Network Enterprise Application Security System Vehicle Tracking Device Temperature Sensor AHU Vehicle Tracking System Fire Alarms Cameras KW Meter KW Meter Power Meter SIM Smoke Detector Humidity Sensor Flow Meter Occupancy Sensor Pressure Sensor ATMs Chillers Boilers Signage FAHU UPS Pumps Generators HVTS

14 Remote Service Governance RETAIL VERTICAL LIFE & SAFETY VERTICAL INDUSTRIAL VERTICAL SECURITY & SURVEILLANCE BUILDINGS DATA CENTER VERTICAL TRANSPORT VERTICAL HOTELS VERTICAL HEALTH VERTICAL EDUCATIONAL VERTICAL AIRPORT VERTICAL ENERGY VERTICAL

15 HVAC (Heating, Ventilation, Air Conditioning) Ecosystem

16 Water Ecosystem

17 Air Ecosystem

18 Monitoring

19 Chiller Plant Analysis Tool

20 Galaxy 2020 Real-Time Managed Services Platform Dynamic business models Diverse ecosystem of stakeholders Wide range of cloud services Infrastructure as a Service Sensing as a Service Platform as a Service Data as a Service Software as a Service Virtual verticals Third-party applications 20

21 User Interface Galaxy 2020 Real-Time Managed Services Platform on the Cloud Customer [Cartridge] Tomcat [Cartridge] PHP Application Cartridges Galaxy SOA Application [Cartridge] ESB [Cartridge] AS [Cartridge] DSS [Cartridge] Cassandra [Cartridge] PostgreSQL Platform Cartridges Galaxy SOA Platform Platform provider Cloud Platform Messaging Logging Security Registry Cloud provider Foundation Services Apache Stratos Elastic Load Balancer Cloud Controller Deployment Synchronizer Stratos Manager Load Monitor PaaS Controller Infrastructure Provider Cloud API Cloud Infrastructure 21 Apache jclouds OpenStack Cloud

22 Galaxy 2020 Real-Time Managed Services Platform on the Cloud Facilitates: OpenStack and Apache Stratos Use PaaS framework to provide cloud-based environment to build a scalable and reliable Platform Offer several features for PaaS & Verticals/Applications: Elastic scaling, Multi-tenancy Automated resource management Platform-wide monitoring and billing Extensibility (e.g.: cartridge mechanism) Use robust, widely-adopted technologies for Cloud Infrastructure to facilitate underlying infrastructure more efficiently 22

23 Galaxy PaaS framework Using Enterprise Service Bus for customizing PaaS framework and developing further platform features and services Providing AppStore for developing and deploying customer-specific Applications Using API Management strategies to support consumer s Applications/Verticals Scalability, Extensibility, Reliability...

24 Software-defined IoT units Provide software-defined API for accessing, configuring and controlling units Provisioning API Support fine-grained internal configurations, e.g, adding functional capabilities like different communication protocols, at runtime. Can be composed at higher-level, via dependency units, creating virtual topologies (of multiple gateways) that can be (re)configured at runtime. Enable decoupled and managed configuration (via late-bound policies) to provision the units dynamically and on-demand. Functional API Functional aspects Runtime composition Dependency units Runtime mechanisms Utility cost-function Software-defined IoT Unit Late-bound policies Runtime controllers (e.g, elasticity) IoT resource and functionality binding Infrastructure capabilities Non-functional aspects Governance API Have utility cost-functions that enable pricing the IoT resources as utilities.

25 Ecosystem for software-defined IoT systems Create an ecosystem of software-defined IoT units for the creation of software-defined IoT systems. Distributing IoT units in a market-like fashion, e.g., via IoT AppStore.... IoT compute In-memory image Atomic software-defined IoT units IoT data storage GW Data point runtime controller Custom Volatile History proc. logic Monitor. Component -model CEP Functional capabilities Key/Value store Communication Non-functional capabilities... Elasticity Data quality Network overlay Protocol Auto scaling group controller VPN Messaging Outliers filter Config. Security Sand box

26 Software Defined Elastic Data Center

27 Elasticity Scaleability Resource elasticity Software / human-based computing elements, multiple clouds Quality elasticity Non-functional parameters e.g., performance, quality of data, service availability, human trust Elasticity Costs & Benefit elasticity rewards, incentives

28 Some diverse types of elasticity requirements Application user: If the cost is greater than 800 USD, there should be a scale-in action for keeping costs in acceptable limits Software provider: Response time should be less than amount X varying with the number of users. Developer: The result from the data analytics algorithm must reach a certain data accuracy under a cost constraint. I don t care about how many resources should be used for executing this code. Cloud provider: When availability is higher than 99% for a period of time, and the cost is the same as for availability 80%, the cost should increase with 10%.

29 Software Defined Elastic Cloud Services Service Developer Easy to program elasticity requirements Service Owner Reduced time to market + Infrastructure Provider Native cloud service engineering Designing and programming software-defined elastic services Automatic service deployment Elasticity Control Elasticity monitoring and analysis Service Owner + Maintains service s performance while reducing cost Infrastructure Provider Reduces resources overprovisioning Service Developer + Service Owner Easy to understand service s elasticity boundaries 29

30 High Level Description of Elasticity Requirements SYBL (Simple Yet Beautiful Language) for specifying elasticity requirements SYBL-supported requirement levels 1. Cloud Service Level 2. Service Topology Level 3. Service Unit Level 4. Relationship Level 5. Programming/Code Level #SYBL.CloudServiceLevel Cons1: CONSTRAINT responsetime < 5 ms Cons2: CONSTRAINT responsetime < 10 ms WHEN nbofusers > Str1: STRATEGY CASE fulfilled(cons1) OR fulfilled(cons2): minimize(cost) #SYBL.ServiceUnitLevel Str2: STRATEGY CASE iocost < 3 USD: maximize( datafreshness ) #SYBL.CodeRegionLevel Cons4: CONSTRAINT dataaccuracy>90% AND cost<4 USD Georgiana Copil, Daniel Moldovan, Hong-Linh Truong, Schahram Dustdar, "SYBL: an Extensible Language for Controlling Elasticity in Cloud Applications", 13th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), May 14-16, 2013, Delft, Netherlands

31 Mapping Services Structures to Elasticity Analytics

32 Elasticity Model for Cloud Services Analytics Moldovan D., G. Copil, Truong H.-L., Dustdar S. (2013). MELA: Monitoring and Analyzing Elasticity of Cloud Service. CloudCom 2013 Elasticity Pathway functions: to characterize the elasticity behavior from a general/particular view Elasticity Space Elasticity space functions: to determine if a service unit/service has the intended elasticity behavior

33 Multi-Level Elasticity Space Analytics Service requirement COST<= $/client/h 2.5$ monthly subscription for each service client (sensor) Determined Elasticity Space Boundaries Clients/h > ms ResponseTime 1100 ms Elasticity Space Clients/h Dimension Elasticity Space Response Time Dimension

34 Human augmentation Engineering Techniques

35 Specifying and controling elasticity of human-based services What if we need to invoke a human? #Predictive Maintenance for chiller measurements #SYBL.ServiceUnitLevel Mon1 MONITORING accuracy = Quality.Accuracy Cons1 CONSTRAINT accuracy < 0.7 Str1 STRATEGY CASE Violated(Cons1): Notify(Incident.DEFAULT, ServiceUnitType.HBS)

36 Elasticity for Teams (Social Compute Units) and APIs SCU execution model and lifecycle management Software-defined APIs allow controlling the elasticity of SCU Algorithms to deal with elasticity capabilities programming Mirela Riveni, Hong-Linh Truong, and Schahram Dustdar, On the Elasticity of Social Compute Units, CAISE 2014

37 Conclusions Complex ecosystems of People, IoT, and Systems Elastic Computing as a key enabler Galaxy 2020: Cloud based service ecosystem PaaS for real time services delivery

38 Thank You Schahram Dustdar Pacific Controls Cloud Computing Research Lab Distributed Systems Group - TU Vienna, Austria See us at booths 236 & 238