Edge Computing and IIoT

Chapter 16

Edge Computing and IIoT

16.1 Introduction

Although the cloud approach has many advantages, it does have the disadvantage of introducing higher network latency because a data center is remote from the customers it serves.

Note: Latency is the time it takes for data to pass from one point on a network to another.

Cloud providers attempt to minimize network latency in two ways: 

• The use of multiple, geographically diverse sites 
• Low-latency network connections

16.2 Situations Where Latency Matters 

• In the financial industry, for example, a small delay in making stock trades can result in a huge loss.
• In the health care industry, a small delay in receiving data from a patient monitor can delay activation of an implanted medical treatment device.
• Industries that employ real-time control systems — sensors and actuators that monitor and control processing — rely on low delay.

The following table lists some of the industries for which low latency can be important.

16.3 Moving Computing To The Edge

To meet the requirements for low latency in cloud computing, edge computing architecture is introduced.

Edge computing

• Place some of the computing facilities near each source of information, and perform initial processing locally. 
• Computation performed near devices (smartphone) occurs near the edge instead of sending the data to a centralized cloud data center for processing.

Simultaneously run applications in a cloud data center, and use the cloud applications to handle computational-intensive tasks.

The following illustrates how edge computing works:

Lets assume the sensor monitors users heart ECG.

1. The data from the sensor is sent to the mobile phone to which the sensor is connected through an app.
2. The health care app running in the smartphone checks for any abnormality in the ECG signals.
3. If any abnormality is found, immediately a notification is sent to the doctor and the patients relatives for immediate action.
4. 
   

The edge computing approach places small, auxiliary data centers near locations that require low latency responses. 

Software in the edge data center handles low-latency computations locally and runs other computations in a cloud data center. 

16. 4 Extending Edge computing to Fog hierarchy

• The locations and sizes of the edge data centers depend on the applications being supported and the latency requirements. 
• To achieve the lowest possible latency, an edge facility must be as close to each user as possible (e.g., in each cell tower). 
• For applications with less stringent requirements, an edge computing facility might serve a neighborhood of multiple cell towers or a geographic region with many neighborhoods. 
• To serve all applications, edge facilities can be organized into a hierarchy

Industry sometimes uses the term fog data center to refer to an intermediate data center that serves a larger geographic area.

16.5 Edge computing and IIoT

The term Industrial Internet of Things (IIoT) refers to an enhanced, larger-scale version of the Internet of Things. 

The primary difference between consumer IoT systems and Industrial IoT systems lies in the importance: a company depends on an IIoT system as part of a critical business function.

Characteristics found in IIoT applications

• Specific latency requirements
• Geo-spatial knowledge
• Large volumes of data with various QoS requirements
• A need for data filtering
• High availability requirements
• Security requirements

Specific latency requirements.

IIoT applications have specific requirements (e.g., if a specific assembly line robot malfunctions, it must be shut down within 150 milliseconds after a problem is detected).

Geo-spatial knowledge. 

An IIoT system must be aware of locations and spatial relationships.

Large volumes of data with various QoS requirements.

• IIoT applications often employ many sensors and video cameras that each generate data continuously, resulting in large volumes of data;
• Each type of data may have specific Quality of Service (QoS) requirements, such as data rates and bounds on latency.

A need for data filtering.

Applications running in the cloud only need data that allows them to analyze long-term trends. Hence it is not necessary to send all the raw data from sensors to the cloud.

High availability requirements

Since a company depends on IIoT systems to sustain their business, the systems must be reliable. Thus, IIoT may need to employ redundancy (duplication).

Security requirements. 

IIoT systems must be secure from attack, and it must be possible to keep the data they gather confidential.

An IIoT system may transfer multiple types of data, each with its own requirements for performance, availability, and security.

16.6 Communications for IIoT

In an IIoT application data collected from sensors are transferred to different locations like cloud data center, edge devices or fog centers. How to make all these data points communicate effectively?

Solution - Given by OMG (Object Management Group)

An OMG standard known as the Distributed Data Service (DDS) defines a mechanism that allows data from sensors to flow upward through a hierarchy of edge and fog centers to applications using the data. 

The DDS approach has the following characteristics: 

• Completely decentralized 
• Suitable for industrial use
• Publish-Subscribe interactions
• Flexible data handling capabilities 
• Support for an edge hierarchy 

Completely decentralized

DDS avoids a single point of failure while minimizing latency by using direct communication

Suitable for industrial use. 

DDS offers the high reliability needed for IIoT applications

It can be configured to meet performance requirements.

DDS offers the ability to authenticate control messages and encrypt data traffic.

Publish-Subscribe interactions. 

DDS offers a publish-subscribe communication mechanism

Allows each application to choose the data the application will receive.

The applications can subscribe to only the data that is required.

Flexible data handling capabilities.

One subscriber may choose to receive all data while another chooses to receive only values beyond a specified threshold.

Support for an edge hierarchy.

    DDS can be configured to form a distributed system.

It can have a hierarchy of cloud centers followed by fog centers and then to edge     data center.

Databus

• Databus provides interconnections among publishers and subscribers.
• Databus is a communication abstraction implemented by software. 
• Software modules arrange to send messages between publishers and subscribers to meet requirements and optimize communication. 
• Databus technology includes a mechanism known as a gateway that allows a single Databus to span multiple levels of the hierarchy.
• Rather than blindly sending a copy of every message, gateways perform a filtering function, and only forward a message to another level if one or more applications have subscribed to receive the message.

The following figure illustrates the functioning of DDS databus.