BAND-AiDe: A Tool for Cyber-Physical Oriented Analysis and Design of Body Area Networks and Devices...

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BAND-AiDe: A Tool for Cyber- Physical Oriented Analysis and Design of Body Area Networks and Devices Authors: Ayan Banerjee, Sailesh Kandula, Tridib Mukherjee and Sandeep K. S. Gupta Presented by: Raquel Guerreiro Machado

Transcript of BAND-AiDe: A Tool for Cyber-Physical Oriented Analysis and Design of Body Area Networks and Devices...

BAND-AiDe: A Tool for Cyber-Physical Oriented Analysis and

Design of Body Area Networks and Devices

Authors: Ayan Banerjee, Sailesh Kandula, Tridib Mukherjee and Sandeep K. S. Gupta

Presented by: Raquel Guerreiro Machado

• Body Area Networks (BANs)– Wireless networks– Devices capable of sensing, actuation, computation and

communication– Wearable or implanted– Can be used in various applications

• Problems– Real deployment may harm human body– Needs automated design and verification without real

deployment

Introduction

Model Based Engineering (MBE) approach

• Cyber-Physical in nature

– Cyber entities (medical devices)– Physical environment (human body)

• Interactions between devices and human body

– Intentional interactions – required for the BAN functionalities– Un-intentional interactions – undesirable side-effects of the

BAN operations on the human body and vice-versa (i.e. temperature rise)

Challenges & Requirements

• Design requirements– Safety: Non-intentional interactions has to be within a limit

– Sustainability: BAN operations can be sustained without any re-deployment using human body power sources

– Security: Information exchange should maintain privacy, authenticity, and integrity of personal health data

– Accuracy and Low latency: • Should guarantee correctness of BAN functionalities • Low delay is necessary given the applications time-critical nature

Challenges & Requirements

• Goal: Perform MBE to design and analyze BANs in terms of the safety of human body during the BAN operations and sustainability of these operations

• Contributions:

– Abstract model of BANs as CPSs that captures both intentional and un-intentional interactions

– Body Area Networks and Devices – Analysis and Design (BAND-AiDe)

– Case studies

Goal and Contributions

• Wireless Health Systems (WHSs)– Small individual wireless medical devices (pulse oximeters or

camera capsules)– Networks of medical devices [Milenkovic et al. 2006;

Venkatasibramanian et al. 2005]

• Safe and sustainable BANs– Multi-hop cluster-based communication scheduling algorithms

that ensure thermal safety of the human body– Analyzing the sustainability of sensing and data dissemination– Designing sustainable information security protocols for

communication

Related Works

These approaches are application-specific

Modeling Requirements for BANs

Body Area Networks (BAN)

A Body Area Network is a heterogeneous set of medical devices that can sense, actuate, compute and communicate with each other through a wireless channel.

Model Based Engineering (MBE)

MBE is the method of developing behavioral models of real systems and analyzing the models for requirement verification.

Modeling Framework

• Inputs to the framework:– BAN Requirements

– BAN System

– Analysis Parameters

Modeling Framework

• Global CPS (GCPS): A BAN is considered as a GCPS

Modeling of BANs as CPSs

• Local CPS (LCPS): Each individual subsystem is a GCPS is referred to as an LCPS.

• Computing unit: Corresponds to the worker nodes capable of sensing, computation, and communication

– Computing property: Characterizes computing behavior (processor speed)

– Physical property: Characterizes physical behavior (power dissipation of computing unit)

Modeling of BANs as CPSs

• Physical unit: Models the portion of the physical environment which the computing unit interacts to.

– Region-Of-Interest (ROIn): Models the intentional interactions• Monitored parameter: Models the system parameters that are affected by

intentional interactions• Region boundary: Represents the limits of the bounded region

– Region-Of-Impact (ROIm): Models the un-intentional interactions

• Physical Property: Characterizes the physiological parameters (tissue temperature)

• Physical Dynamics: Models the physical processes. (equations)• Region boundary: The region boundary depends on the physical properties

and dynamics

Modeling of BANs as CPSs

Any interaction of the computing unit with the physical world will take place within a bounded region

• Local Interactions: Cyber-Physical interactions between the computing unit and the physical unit within an LCPS

– Intended interactions: Modeled as transfer of information between the computing unit and the ROIn.

– Unintended interactions: Modeled as transfer of energy between the computing units and the ROIm.

Modeling of BANs as CPSs

• Interactions among the LCPSs– Models the interconnections between the LCPSs.– These interconnections are called global interactions.– Occurs when there is an overlap in the ROIn or the ROIm of 2

LSCPs.

• Analysis Parameter Modeling: Involves specific methodology to solve equations that govern the physical dynamics.

Modeling of BANs as CPSs

Modeling of BANs as CPSs

• Model Parser:– Requirements parser– BAN-CPS parser– Analysis parameter parser

BAND-AiDe Analyzer

BAND-AiDe Analyzer

BAND-AiDe Analyzer

• Uses Abstract Architecture Description Language (AADL)

– AADL specifications are hierarchical in nature

– AADL has dedicated construct to model hardware and software of embedded computing devices

– AADL has been used to model wireless sensor networks

– AADL provides language extension

Implementation

Implementation

• Worker nodes– Sensing temperature, humidity, sound and physiological

signals– Data communication through wireless radio– Communication security through Physiological values based

Key Agreement (PKA)

Case studies

Case studies

• TelosB mote

• Smith fingertip pulse oximeter (PPG)

• Deployed on the index finger

• Ayushuman workload

Single Wearable Medical Device

Single Wearable Medical Device

• BAND-AiDe Model

– Skin temperature threshold

– Available power from scavenging sources

– Scavenging duration

– Time steps and gird sizes

• Thermodynamics of human skin

Single Wearable Medical Device

Single Wearable Medical Device

Single Wearable Medical Device

• Low-power devices– EKG sensors– TelosB motes

• Cluster based multi-hop communication protocol– Worker nodes form cluster– Nodes nominate a leader– Leader forwards information to base station

Network of Devices

Network of Devices

• BAND-AiDe model

Network of Devices

Network of Devices

Network of Devices

• Physical processes in the ROIm can affect the monitored parameters in the ROIn

• Operation in the ROIn may also affect the ROIm parameters in a BAN

• It is possible that one BAN affect the others

Discussion