Sensing as a Service

Mobile Sensing MiddlewareThe OpenIoT Approach

Ali S. Bilal (bilal@ut.ac.ir)University of Tehran

Spring 2015

We already have televisions, cars, homes, industrial equipment and other things connected to the Internet.

They can automate systems for us, allow us to communicate easier, and collect data for us.

So whether we’ve known it or not, the Internet of Things is already here.

But the amount of Internet of Things (IoT) connections is about

to explode

Take a look…

While American technology companies are making lots of IoT progress, Asia currently has the most connections.

Asia Europe North America

Latin America

Africa Oceania0%5%

10%15%20%25%30%35%40%45%50%

Percentage of Machine-to-Machine Con-

nections

That’s because China’s government has committed to spend $603 billion by 2020 for machine-to-machine connections.

So what’s the worth of all of these connected things?

Probably much more than you think!

2013 20200

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Internet of Things Market Size(in trillions of dollars)

But not everyone has the same predictions.

Cisco believes the market size will be $19 trillion by 2025.

The potential market size is so big because the IoT is about increasing efficiency, as well as creating new profits.

And those efficiencies will touch nearly every part of our lives: healthcare, transportation, utilities, etc.

General Electric says that a 1% increase in efficiencies from the Industrial Internet (part of the IoT) will have huge savings.

Rail Aviation Healthcare Power Oil & Gas0

102030405060708090

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Savings from Industrial In-ternet Efficiencies

(in billions of dollars)

There’s still a lot of room for varying Internet of Things predictions.

But even if we look at the low estimates, the Internet of Things will still have a huge impact on our lives.

And we’ve only just begun!

Sensing as a Service (SaaS)

Mobile phones have evolved as key electronic devices for communications, computing and

entertainment, and have become an important part of people’s daily life

Most current mobile phones (such as iPhone, Samsung’s Android phones, etc.) are equipped with

a rich set of embedded sensors such as camera, GPS, WiFi/3G/4G radios, accelerometer, digital compass, gyroscope, microphone and so on

Moreover, external sensors (such heartbeat sensor, air pollution sensor, etc) can also be connected to a

mobile phone via its Bluetooth interface

These sensors can enable attractive sensing applications in various domains such as

environmental monitoring, social networking, healthcare, transportation, etc.

SaaS Model

• Cloud user initiates a sensing request through a web front-end

• the request will be forwarded to a sensing server

• Sensing server will then push the request to a subset of mobile phones that happen to be in the area of interest

• The corresponding sensing task will be fulfilled by these mobile phones

• The sensed data will then be collected by a sensing server and stored in the database and returned to the cloud user who requests the service

SaaS Requirements

• The system must be general enough such that it can support various applications over different mobile phone platforms

• The system can be easily and quickly reconfigured to replace old inefficient algorithms or policies with new ones

• Sensing energy consumption should be minimized such that mobile phones can undertake sensing tasks, and in the meanwhile, can still fulfill its regular duties

• The system must have effective incentive mechanisms to attract mobile phone users to participate in sensing activities

Mobile Broker (publish/subscribe

middleware) is used for the

integration of mobile sensors

X-GSN collects, filters and

combines data streams from

virtual sensors or physical

devices

Acts as a cloud database which enables storage of data streams

stemming from the sensor middleware and metadata

required for the operation of OpenIoT

OpenIoT

Open Source Internet-of-Things in the CloudCUPUS Middleware

CUPUS

CloUd-based Publish/Subscribe middleware for the IoT

• CPSP is responsible for acquiring data from external data sources

• Processing the data to see if it matches any active subscriptions

• Disseminating the data to external data consumers

• Mobile Broker (MB) is a data stream processing component running on mobile devices

• It is responsible for filtering and aggregating locally produced sensor data

• The QoS Manager monitors subscriptions and publications to make smart decisions regarding mobile ICO activation/deactivation

• Serves as a hub for pushing the data received by the CPSP Engine to LSM via X-GSN for permanent storage

Cloud-Based Publish/Subscribe Middleware (CUPUS)

• CUPUS has a Hierarchical three-tier architectureo CPSP Engine at the top layero MBs running on mobile devices at the middle layero Publishers and Subscribers at the bottom layer

• Implements the standard publish-subscribe-notify communication pattern

• Introduce Announce message to advertise the data types associated with mobile sensors and sensor locations

Cloud-Based Publish/Subscribe Middleware (CUPUS)

• An MB running on the device announce the type of data it is able to contribute based on sensors attached to it and its current location

• This information is transmitted to the CPSP Engine which thus knows the locations and characteristics of all available data publishers

• The CPSP Engine answers to announce messages with subscriptions matching the defined data types which become data filters and prevent potential data overload within the CPSP Engine

Mobile Broker (MB)

• An MB is a special processing engine running on mobile devices

• It saves batteries of both sensors and end-user devices by filtering sensor data and suppressing redundant sensing

• The filtering is achieved by matching of locally generated publications with active subscriptions received from the CPSP engine so that only matching publications are forwarded to the CPSP engine

Quality of Service Manager

• The QoS Manager component adds support for intelligent QoS-based monitoring and management

• Ensure that the sensed data received by an end user meets his/her sensor data demands (accuracy and frequency of sensor readings)

• It does so by acquiring a sufficient number of sensor readings to satisfy the data quality requirements for all active end-user subscriptions in that area (global data requirements)

• Based on reported mobile ICO battery levels, the QoS Manager decides about activation/deactivation of available data sources

Interactions Within the CUPUS Middleware (Publish)

Interactions Within the CUPUS Middleware (Announce)

Interactions with the LSM Sending Data Through Virtual Sensors

Interactions with the LSM Interaction with LSM-Light

Urban Air Quality Crowdsensing Use Case

References

• Interoperability and Open-Source Solutions for the Internet of Things

• Sensing as a Service, Challenges, Solutions and Future Directions

• Sensing as a Service Model for Smart Cities Supported by Internet of Things