m2m and iot

M2M Definition

Solutions allowing communication between devices of the same type and a specific application via wired or wireless networks

Three drivers of M2M and IoT growth

Understanding physical environment, improved technology/networking, and reduced component costs

Main goal of M2M deployment

To achieve productivity gains, reduce costs, and increase safety or security

Key difference between M2M and IoT data sharing

M2M generally does not allow broad data sharing; IoT connects systems to the broader Internet

IoT blending of information sources

Combines sensor data with GIS (road databases), weather systems, and other real

M2M vs IoT: Application Focus

M2M is Single application

M2M vs IoT: Business Model

M2M is Business objective driven (B2B); IoT is Participatory community driven (B2B, B2C)

M2M vs IoT: System Approach

M2M is a Vertical system solution; IoT is a Horizontal enabler approach

M2M vs IoT: Standards

M2M is often De facto and proprietary; IoT uses Standards and open source

SENSEI Project Goal

To enable "Real World integration in a future Internet"

SENSEI Service Infrastructure requirement

Separated from underlying communication networks and based on Internet Protocol (IP)

SENSEI Resource Separation

Separation of sensing/actuation from devices, entity

ETSI M2M TC Architecture type

A horizontal system with separation of devices, gateways, and common service core

IoT

A ARM meaning

IoT

A Main Aim

IoT Design Objective: Horizontal System

Target a system of real

IoT Design Objective: Reuse

Design for the reuse of deployed IoT resources across different application domains

IoT Design Objective: Abstraction

Design different levels to hide underlying complexities and heterogeneities

IoT Design Objective: Trust

Design for ensuring trust, security, and privacy

Basic IoT Device Properties

Microcontroller (8/16/32

IoT Device Operating Systems

Main

Device Management (DM) definition

Efficient means to perform management tasks like provisioning and configuration

Execution Environment (EE)

Manages application lifecycle and provides Application Programming Interfaces (APIs)

Basic Device Type

Provides basic sensor/actuator services and requires a gateway for WAN connection

Advanced Device Type

Hosts application logic and WAN connections; often functions as a gateway

DM Task: Provisioning

Initialization or activation of devices regarding configuration and enabled features

DM Task: Fault Management

Enables error reporting and access to device status

Gateway role as a Mediator

Operates between the DM server and devices when direct communication is not optimal

Gateway as a Proxy

Gateway acts as a DM server to the device and a DM client to the server

Gateway as a Translator

Gateway represents devices and translates between different protocols like TR

Network Definition

Created when two or more computing devices exchange data or information

Network Nodes and Links

Computing devices are "nodes" and they communicate over "links"

M2M Big Data characteristic

Huge amounts of data generated capturing detailed aspects of device

M2M Heterogeneous Data

Data produced by a variety of devices differing in sampling rate and quality

M2M Temporal Data

Data that measures the environment over time

M2M Spatial Data

Data coupled to interactions in specific locations

M2M Polymorphic Data

Data that obtains different meanings depending on the semantics and process applied

M2M Data Security Risk

High risk of leaking private information and usage patterns due to detailed capturing

Data Acquisition

Collection of data from devices via wired or wireless links (continuous, interval, or event

Data Validation

Checking acquired data for correctness and meaningfulness within an operating context

Cloud On

Demand Self

Cloud Broad Network Access

Capabilities accessed through standard mechanisms for thin or thick client platforms

Cloud Resource Pooling

Provider resources are dynamically assigned to multiple consumers via a multi

Cloud Rapid Elasticity

Capabilities can scale rapidly outward and inward commensurate with demand

Cloud Measured Service

Automatic control and optimization of resource use leveraging metering capabilities

Public Cloud

Services owned/operated by third parties with costs borne by the provider

Hybrid Cloud

Combines public cloud and on

Private Cloud

Cloud infrastructure used exclusively by one organization

Infrastructure

as

Platform

as

Software

as

IaaS Target User

Network Architects

PaaS Target User

Developers

SaaS Target User

End Users

Descriptive Analytics

Uses statistics (means, frequencies) to create KPIs for system performance

Predictive Analytics

Uses historical facts to forecast demand or perform predictive maintenance

Clustering Analytics

Identification of groups with similar characteristics for customer segmentation

Anomaly Detection

Identifying fraud or failures by checking for anomalous consumption patterns