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Design Considerations for a Wireless Sensor Network Architecture Attached to a Cognitive Training System for the Elderly

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Academic year: 2021

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Design

 

Considerations

 

for

 

a

 

Wireless

 

Sensor

 

Network

 

Architecture

 

Attached

 

to

 

a

 

Cognitive

 

Training

 

System

 

for

 

the

 

Elderly

 

Bruno Salgues, Jorge A. Pardiñas‐Mir Télécom TIC et Santé, Institut Mines‐Télécom, France

THE INTERNATIONAL eHEALTH,

TELEMEDICINE AND HEALTH ICT FORUM For Education, Networking and Business

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This work is part of a e‐Health system project 

dedicated to the training and therapeutic 

cognitive care of the elderly people. 

The project is conducted in partnership with:

• ALTERA‐GROUP (Project manager,  Paris‐Montpellier) • LIRMM (CNRS ‐ Laboratoire d'Informatique, de 

Robotique et de Microélectronique de Montpellier) • INSTITUT TELECOM ‐ TIC & SANTÉ (Montpellier)

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3

We are working on a e-health system that offers a set of available home services for active seniors or elderly people affected or threatened by neuro-degenerative diseases as the Alzheimer’s disease, promoting improved quality of older people’s life through preventive and therapeutic actions.

It provides a set of specially designed activities to exercise the cognitive capacities of patients.

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At the base of the system there’s a touch computing device connected to the Internet (a tablet), easy to use, through which all activities are carried out and the patient’s information and progress is remotely managed at the system’s site.

Some activities:

• Reading newspapers.

• Watching videos

• Playing educational and therapeutic games

(serious games).

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5

System’s

 

Usage

 

Scenarios

The system can be used by the patient himself, at home, or with the assistance of others like friends or family. The patient may even benefit from the remote assistance of a tutor.

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Cloud

 

Architecture

 

Benefits

The use of a cloud architecture allows the system to start small and increase software and hardware resources only when needed, specifically:

• The resources and users’ capacities can be increased without limitation and according to the real demand.

• Applications hosted in the Cloud can be run in the Cloud itself from a low-level client computing device.

• Centralized storage of patient’s health information that can be accessed from anywhere by the authorized personal.

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The addition of a wireless sensor network

could bring valuable data related to the

patient’s health and his environment and it

can evolve according to particular needs.

7

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Added Network’s Main Features

• Start with basic variables such as room

temperature and vital signs, but easily

allowing the addition of other parameters.

• Growing capacity in a compatible way,

both in physical and management

aspects.

• Able to distinguish data from different

users from the same network.

• Able to joint other wireless networks in

the same physical building.

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9

General

 

Sensor

 

Networks

 

Characteristics

• Communication in wireless sensor networks occurs at low rate.

• Energy consumption must be guaranteed to rest at a low level.

• Support of nodes mobility and resulting topology changes.

• Necessity to deal with the unreliability characterizing wireless links.

While problems are deep-rooted in the classical Wireless Sensor Network architecture, where all nodes possesses all sensor and networking functionalities, Software Defined Networking can bring a good level of abstraction, allowing the programmability of the network and its evolution and management, taking into account that:

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Wireless

 

Sensor

 

Networks

 

Problems

• Resource underutilization. One single and versatile network could be used instead of multiple networks deployed for different applications in the same terrain.

• Counter-productivity. Prototyping and production is delayed because of lack of reusing common functionalities that could be shared between different vendors.

• Rigidity to policy changes.

• Management difficulty. Being the development of a global network management system for distributed WSN a demanding task.

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11

OpenFlow

 

Software

 

Definition

 

Networking

We propose to adopt the OpenFlow based SDN implementation in the WSN architecture:

• The Data Plane consists of sensors that also perform flow-based packet forwarding.

• The Control Plane centralizes the network control. • The sensor application lies at the applications

layer without taking care of the physical

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Wireless

 

Sensors

 

Networks

 

Transformation

OpenFlow based SDN implementation helps

transform Wireless Sensors Networks into networks that are:

• Versatile. They can support multiple applications in a plug-and-play way; sensors are no longer

application-dependent but

application-customizable.

• Flexible. Easy to enforce policy changes

throughout the entire network.

• Easy to manage. Building an network

management system is no different from adding another application on top of the control plane, using open programming interfaces (APIs).

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13

SDN

 

in

 

Wireless

 

Sensors

 

Networks

Many proposals promoting the use of open architecture for WSN based on Software Defined Networking:

• Software-Defined WSN (SD-WSN): featuring a clear separation between a data and a control plane. It defines Sensor OpenFlow (SOF) as a communication protocol between the two planes.

• SDWN: Software Defined Wireless Networking.

Differentiating generic nodes, with limited

computing/energy capabilities, from sink nodes, who executes the network controller, with much more computing/communication capabilities.

• OpenFlow in Wireless Mesh Networks: OpenFlow enabled mesh routers and mesh gateways, and the use of NOX (Open-Flow based Network Operative System) as the network controller.

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Conclusions

• The addition of a wireless sensor network to the cognitive training system must guarantee a future easy scalability and manageability of the network.

• This can be achieved by the application of the Software-defined Networking paradigm to Wireless Sensor Networks but in such a way that it considers the special features of this kind of network in order to obtain an efficient performance.

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15

Conclusions

• The adaptation must primarily take into account the low-rate data and low energy consumption characteristics of Wireless Sensor Networks.

• There are already some Wireless Sensor Networks proposals that show that it is convenient and possible to adapt the SDN paradigm to WSNs.

• This is an efficient architecture to be used in the design of a wireless sensor network for the cognitive training system.

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Design

 

Considerations

 

for

 

a

 

Wireless

 

Sensor

 

Network

 

Architecture

 

Attached

 

to

 

a

 

Cognitive

 

Training

 

System

 

for

 

the

 

Elderly

 

Bruno Salgues, Jorge A. Pardiñas‐Mir

Télécom TIC et Santé, Institut Mines‐Télécom, France / Iteso University, Mexico

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