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

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

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

TelosB mote Smith fingertip pulse oximeter (PPG) Deployed on the index finger Ayushuman workload 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

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

BAND-AiDe model 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