band aide a tool for cyber physical oriented analysis and design of body area networks and devices n.
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Authors: Ayan Banerjee, Sailesh Kandula , Tridib Mukherjee and Sandeep K. S. Gupta PowerPoint Presentation
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Authors: Ayan Banerjee, Sailesh Kandula , Tridib Mukherjee and Sandeep K. S. Gupta

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

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

  2. Introduction • 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 Model Based Engineering (MBE) approach

  3. Challenges & Requirements • 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)

  4. 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

  5. Goal and Contributions • 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

  6. Related Works • 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 These approaches are application-specific

  7. Modeling Requirements for BANs

  8. 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.

  9. Model Based Engineering (MBE) MBE is the method of developing behavioral models of real systems and analyzing the models for requirement verification.

  10. Modeling Framework • Inputs to the framework: • BAN Requirements • BAN System • Analysis Parameters

  11. Modeling Framework

  12. Modeling of BANs as CPSs • Global CPS (GCPS): A BAN is considered as a GCPS

  13. 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)

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

  15. Modeling of BANs as CPSs • 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.

  16. 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.

  17. Modeling of BANs as CPSs

  18. BAND-AiDe Analyzer • Model Parser: • Requirements parser • BAN-CPS parser • Analysis parameter parser

  19. BAND-AiDe Analyzer

  20. BAND-AiDe Analyzer

  21. Implementation • 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

  22. Implementation

  23. Case studies • Worker nodes • Sensing temperature, humidity, sound and physiological signals • Data communication through wireless radio • Communication security through Physiological values based Key Agreement (PKA)

  24. Case studies

  25. Single Wearable Medical Device • TelosB mote • Smith fingertip pulse oximeter (PPG) • Deployed on the index finger • Ayushuman workload

  26. Single Wearable Medical Device

  27. 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

  28. Single Wearable Medical Device

  29. Single Wearable Medical Device

  30. Network of Devices • 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

  31. Network of Devices

  32. Network of Devices • BAND-AiDe model

  33. Network of Devices

  34. Network of Devices

  35. Discussion • 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