Cloud Computing and IoT Fundamentals

Cloud Computing and IoT

• IoT deals with ubiquitous communication and connectivity.
• Old IoT definitions focus on connectivity and sensory requirements for entities involved in typical IoT environments.
• New IoT definitions give more value to the need for ubiquitous and autonomous networks of objects.
• Identification and service integration have an important and inevitable role.
• The Internet of Things (IoT) constitutes a system of physical objects.
• These objects can be discovered, monitored, controlled, or interacted with through electronic devices.
• The devices communicate over various networking interfaces and can eventually connect to the wider internet.

Context of Cloud Computing

• Context includes social integration of things with data in the world.
• Includes smart aspects: transport, living, health, energy electric grid, and planet green environment.
• There are also smart cities, communities, buildings, homes, and industry industrial environments.

Convergence Concept

• Convergence is the key concern in cloud computing.
• This involves network evolution, device convergence, web services, social networks, semantic web and internet of things.

IoT and Services

• Electronic devices can collect and exchange data to populate platforms.
• This leads to the "servitization" of the real world.
• Things as a Service involves a high number of components in single applications.
• It involves the Dynamic (re)configuration of applications.
• As an example; When a customer enters a shop holding a smartphone, they become part of an ecosystem.
• The ecosystem includes sensors in the shop, services accessing data from the retailer's Information System, and external internet services.

The Evolution of People's Roles

• Focus on how people are Spectaucthors & Prosumers in generating data and services.
• Territory-wide Data & Apps are provided for many applications.

Smart Networks as Communication Infrastructure

• Smart networks have standardization and openness of communication standards used.
• They interface with the physical world, tags and sensors.
• They connect communication layers between nodes and with the Internet.
• Object addressability (direct IP address) and multifunctionality functionalities.
• They can build a network for one application that would be available for other purposes, such as road-traffic monitoring.
• This would support environmental-pollution monitoring or traffic safety.

Service Oriented Computing (SOC)

• SOC is a change of perspective needed in systems design, deployment, and maintenance.
• Traditional (distributed) systems are single systems developed top down by decomposition.
• Contemporary distributed systems include third-party sub-systems.
• An example includes a banking system offering insurance contracts, event tickets, etc., to customers.
• Loose coupling is needed, where each component is maintained independently.
• Multifunctionality is needed where each component can serve different systems in different ways.

Software Ecosystem

• Software Ecosystem consists of software solutions that enable, support, and automate activities.
• These are performed by actors in social or business ecosystem.
• Should support organizations that provide these solutions, interaction, data exchange.
• Need to consider Non-functional aspects (QoS, business, legal,
• New metaphors are need to let humans understand and interact with new ecosystems of services.

Supporting Ecosystems

• Established protocols (HTTP) and media types (JSON, XML) simplify access/data processing.
• Components (Microservices) and containers (Docker, Kubernetes) simplify functionality/management

Semantic Annotations

• Semantic Web Services are too difficult to manage (mainly for the required skills and human effort)
• Simpler description format to annotate at semantic level for machine interpretation/composition is desired.
• Can be combined with contracts, defined as profiles
• A profile is defined not to alter the semantics of the resource representation to allow clients to learn about additional dynamics.

Semantic Information

• The semantic interpretation is achieved through constraints, conventions, and extensions.
• The most important is information those by media type and other mechanisms
• Current initiatives are Open API Initiative (OAI) based on JSON.
• Has Dublin Core Application Profile (DCAP) guidelines.

How to Compile Profiles.

• Get semantic information from the available resources.
• Can be formal descriptions such as text, table
• Can be informal description, such as information collected by monitoring.
• Can include semantic vocabularies ontologies, etc
• Semantic interoperation methods (entity linking, relation extraction) should be applied.
• This will disambiguate relevant topics or create enrich them if existing.

Profiles management

• Profiles need to become accessible as REST resources.
• Use HTTP OPTIONs.

Key Conclusions

• The approach to systems design and development must change.
• Business capabilities need to be embedded into independent components.
• Requires decentralized, event-driven coordination, simple principles, and models.
• The HTTP and Unix standards are examples.

API Economy Overview

• Web services mash-ups were first instance of services economy built on IT.
• Freely available Application Programming Interfaces (APIs) and open data were among early drivers.
• Shift driven by flexibly-managed services becoming mainstream - scalable service ecosystems composing business solutions.
• As-a-service economy now emerging. APIs are crucial. Cloud, mobile, social are fueling API-centric, business-as-a-service economies.
• Companies built on the web are co-creating value with others through APIs. Enterprises now exploring.
• Agile, scalable, consumable business-as-service model will shift business services like IT delivery through cloud.

SOA Service & API Contrast

• SOA Service intended for internal-maybe-partner developers, promotes reuse. API geared toward wider audience.
• SOA implements SOAP, has interoperability based on WSDL. API based on simplicity.
• SOA coarse-grained, has transactional options. API fine-grained, relaxed consistency, basic contracts.

API (application programming interface) Architecture

• API-centric enterprise architecture has evolved.
• Integrated Business Functions give way to business solutions and API-centric business services.
• Packaged applications, SOA, and long planning contrasted with composable web, short lifecycles delivery through cloud.

Traditional vs. Composable Business Models

• Traditional focused on distinct solution building and solutions integration. distinct design with sequential building, Distinct building testing.
• Engines foster engagement for long sales and integration
• Composable model has API composition with federated security and privacy.

Cloud Computing Involves Systems Of Systems

• Characterized by being composed of complementary parts.
• Has systems of Engagement & Records.

System Architecture

• It's the way a global system can be organized
• It is made out of system of insight, a enterprise innovations.
• Application location depends on delivery model, supports client needs, controls risk/regulation,
• Shifts away from traditional on-premises control.
• Moves toward a distributed computing model

Core Characteristics of "System of Systems"

• Systems of engagement are outside part, focus on processes with dynamic qualities.
• System of record is internal and invisible.

Systems of Record (SoR) Applications

• These are traditional applications handling business records/transactions (Financials, Order Processing, HR/CRM).
• SoR is designed to provide transactional functions to databases. It is OLTP with Business Intellignence is drives
• These drive the network functions with day 2 day operation
• Has compliance and reliability

Systems of Engagement (SoE) Applications

• Modern apps that facilitate business "engagement".
• Engagement happens through apps, in the 4th age of computing systems in cloud.
• Aim to improve engagement and interactions

Characteristics of SoE

• SoE must meet customer expectations, self-service & create new business models
• IT should interact like consumers/employees.
• Empower customers and enable actions based on context-rich experience.

Systems of Insight

• “Power the digital business of the future”
• A system of insight empowers you to discover what matters most to your users.
• System of Insight is equal part that consists people, processes, and machines

Technical Building Consideration of System of Insight

• Insight systems rely on diverse structured and unstructured data.
• Require insights team for data science and analysis.

Data Management Considerations

• Systems of Engagement must integrate new streams.
• Traditional Warehouses are limited
• There are audio, video, and data and new information on them.

Edge vs. Centralized Cloud Architectures

• Data needs to be closer to source devices
• The rise of edge computing and analytics.

Edge Computing Challenges

• Key challenges include increasing edge capacities, expensive data transfer.
• Security/privacy factors must be kept in consider.

Edge Architecture Objectives

• Edge devices need awareness "when/what" to analyze local.
• How devices connect to Cloud?
• Leverage edge to support constraints (QoS & Sec)

Global Architecture

• “Smart” systems combine device, edge, cloud & data center analytics.

Service Science

• A perspective that any phenomena breeds a science.
• Services create phenomena that may be subject to a formal science

Definition Building Blocks

• Services Science is multidisciplinary and depends on co-creation of value.
• Requires people to work together.
• Shared “information” must act as system.

Explore the convergence of Cloud Computing and IoT. Discover how IoT involves ubiquitous communication and autonomous networks of objects. Understand the context of cloud computing including smart transport, living, health, and environmental applications.