One document matched: draft-manner-roll-shm-requirements-00.txt




Network Working Group                                         J. Hollmen
Internet-Draft                                                 J. Manner
Intended status: Standards Track                                     TKK
Expires: January 8, 2009                                    July 7, 2008


  Sensor Network Routing Requirements of Structural Health Monitoring
                 draft-manner-roll-shm-requirements-00

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   Copyright (C) The IETF Trust (2008).

Abstract

   This document discusses monitoring the status of constructions,
   structural health monitoring, using sensor networks, and the
   requirements such a system puts on routing.








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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . . . 3
   2.  Structural Health Monitoring (SHM)  . . . . . . . . . . . . . . 3
   3.  Requirements on Sensor Network Routing  . . . . . . . . . . . . 5
     3.1.  Non-goals . . . . . . . . . . . . . . . . . . . . . . . . . 6
     3.2.  Requirements for the routing system . . . . . . . . . . . . 6
   4.  Security Considerations . . . . . . . . . . . . . . . . . . . . 7
   5.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . . . 8
   6.  Normative References  . . . . . . . . . . . . . . . . . . . . . 8
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . . . 8
   Intellectual Property and Copyright Statements  . . . . . . . . . . 9







































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1.  Introduction

   Structural health monitoring (SHM) aims at defining an abstract
   condition for a physical structure, such as a bridge, crane, tower or
   other physical object, even heavy machinery.  Measurement data is
   used to measure and monitor physical quantities and computer models
   are used to analyze the data and classify the current state of the
   structure to give alerts if necessary.  Structural health monitoring
   systems typically become a part of the structure for its entire
   lifetime, and the structure's condition will be inferred from the
   physical measurements.  Due to the lifetime requirements and physical
   size of the objects, wiring of the sensors recording physical
   quantities is not a preferred solution.  Wireless sensor networks are
   a solution that avoids costly and error-prone wiring within the
   structure.

   This draft presents the concept of structural health monitoring using
   sensor networks, and identifies requirements on the routing due to
   the task and the operating environment.


2.  Structural Health Monitoring (SHM)

   The challenge with monitoring the status and health of structures is
   that there does not exist a sensor that can tell directly the answer,
   e.g., is a bridge going to crash.  The only mechanism we have is to
   periodically measure physical quantities and then use various data
   mining techniques to analyze the data and find irregularities that
   could be a sign of an emerging problem.

   The structure's condition must be described by the physical
   quantities measured from the structure.  Typical physical quantities
   used are accelerations, strains, pressure, temperature, wind speed,
   flow, position, orientation, chemical quantities and wave propagation
   quantities.  Timely availability of the measurements have a large
   effect on the delay of detection and therefore typically close to
   real-time measurements are used.  This also sets requirements on the
   transmission bandwidths of the network.

   While measuring the structure, typically only the output measurements
   are availables, without the knowledge of the state (or condition) of
   the structure nor the input that caused, for instance, the structure
   to vibrate.  Usually, in the subsequent analysis phase, it is assumed
   that these measurements are representative for the normal condition
   of the structure.

   In civil engineering studies, a typical sampling frequency is often
   less than or equal to 100 Hz (Nyqvist theorem states that in order to



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   be able to detect signal frequencies up to a frequency f, the
   sampling frequency has to be double that frequency (2*f) ).  A
   typical SHM application includes vibration measurements
   (accelerometer), sampled at 100 Hz for 10 minutes at a time.  With
   some available hardware, it is possible to sample at up to 8 kHz, but
   then the memory constraints become an issue.  The data needs to be
   stored in an external flash memory.  With 100 Hz, it is possible to
   measure for 30 s, but to reach 10 minutes some further development
   needs to be done.  The node can not sample, process, transmit and
   receive simultaneously; rather, it can execute one of these functions
   at a time.

   For many applications of the measured data (e.g. data analysis), time
   synchronization is required.  The accuracy of timing after
   synchronization is in the scale of microseconds, but due to clock
   drifts, the synchronization needs to be done regularly (maybe every
   half a minute).  Due to local processing of data, the sampling is
   done in an asynchronous way (no continuous sampling), but at least
   the neighbor nodes should measure at same time instants.  This can be
   achieved by running a time synchronization algorithm in the network
   requiring communication from sensors/cluster heads to sensors.

   The are two distinct methods for analyzing the sensor data, online
   and offline applications, where the data is either processed at the
   scene or offline (later on).  The choice of mode greatly affects the
   networking solutions.  There is also an obvious trade-off in local
   data processing vs. data transmission.  A rule of thumb is that
   energy-wise transmitting one byte is as expensive as running 8000 CPU
   cycles.  This means that computation should be done as close as
   possible to the measurement point, i.e. locally on the nodes.  Only
   the fused information should be transmitted to those nodes that need
   the information (e.g. certain covariance information might be needed
   in another node to be able to perform Kalman-filtering etc.).  The
   computing capabilities of the nodes are very constrained.  The
   microprocessor in many sensor products is TI MSP430 with 10 kB of RAM
   and 256 KB flash memory running at 8 MHz.  The node also has a 4 Mbit
   serial data flash memory.  The nodes are typically equiped with a
   6LowPAN protocol stack.

   Often the positions of sensors need to be known.  Sometimes these
   need to be very accurately fixed in advance, and sometimes the
   sensors need to be installed exactly on the same locations as in the
   previous time.  Location is not only important for data analysis, but
   also for networking.  Hence there might be needs for localization
   support, meaning that the nodes would have to be equipped with GPS or
   ultrasound sensors, because the radio signal strength based
   localization results in low accuracy.




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   The sensors used to measure the physical quantities are located in
   different physical locations in the structure.  In order to have a
   holistic view on the entire structure, the detector must have access
   to all of the data.  Two alternative architectures are possible:
   centralized architecture, where the data is mediated through the
   wireless sensor network to a central node, where the detector
   analyzes the data and assesses the structure's condition.  In a de-
   centralized architecture, there is more analysis local to the
   sensors.

   Two modes of measurement can be differentiated: in a periodic batch
   type of a measurement, a fixed period of time (for instance, 10
   minutes) is dedicated to the measurements, after which the data is
   mediated and analyzed without little real-time constraints on these
   activities.  In a continuous measurement mode, the condition of the
   structure is continually measured, parallel to the data mediation and
   its analysis.  This sets stringent requirements on the throughput of
   the network and well as the response time for the detector.

   Two modes of analysis can be used.  The data based mode uses
   measurement data in order to estimate a model of the normal behavior
   and use it in assessing the condition of the structure.  Statistical
   time-series models are well suited for this task.  Model-based
   approach relies on a computer-based model of the physical structure
   and finite element method derived results on the behavior of the
   structure.


3.  Requirements on Sensor Network Routing

   Based on the previous description of the functionality of a system to
   monitor the health of structures, this section highlights functional
   requirements of a sensor network and how the routing should perform.
   The terminology used follows [RFC2119].

   There are two fundamental properties of the SHM that put pressure on
   how the routing should function.  First, sensor networks for SHM
   produce large amounts of data at various intervals.  Typical
   applications do not, e.g., produce some small amount of continuous
   data, or frequent small bursts.  Rather, e.g., every 8 hours a
   relatively big chunk of data must be transfered from the sources to
   one or more sinks.  This does not happen all over the network at one
   time, but rather a certain section of the network needs to transfer
   the data at a given time.  Secondly, SHM is used in many areas where
   lives could be lost.  Thus, once a section of the sensor network
   starts to transfer data, the data must get to its destination with a
   high reliability.




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   A SHM sensor network is not only about periodic one-way transmission
   of measurement data.  If the data mining reveals a possible problem
   in the structure, advanced applications would control the sensors to
   continue measuring the structure at a redefined frequency and data
   delivery interval.  Additional functionality of an SHM sensor network
   include service discovery, sensors need to find sinks, or nodes
   performing data fusion, and the sinks must be able to find the
   sensors.

   Furthermore, as discussed in the previous section, we have two types
   of modes for the data mining, offline and online.  In the following
   discussion on requirements, we mainly focus on the offline mode.
   Online mode makes similar requirements on the data routing, i.e.,
   large amounts of data must be periodically sent to an entity, either
   a sink and gateway to external networks, or a place for data fusion
   and online data mining.

3.1.  Non-goals

   Designing a routing protocol is ultimately about choices, one
   performance aspect rules out another one, all functional design
   decisions affect performance in some way.  SHM is about rather static
   deployments and use cases.  Thus, support for highly dynamic networks
   is not needed.  We can expect the network to bootstrap itself in
   matter of hours or even days, rather than seconds.  Also, once the
   network routing has been put in place, the only changes are that some
   nodes may just die out, and some are replaced, at a very modest
   frequency.

   SHM applications do not require extremely large sensor networks.  One
   network might consist of tens up to couple hundred nodes.  If larger
   structures need to be monitored, multiple independent sensor networks
   could be used.

3.2.  Requirements for the routing system

   This section highlights some aspects that the SHM application would
   need from the underlying routing system.

   o Autoconfiguration: the network MUST be able to automatically
   configure itself and the routing paths.  Yet, this does not have
   strict requirements on timeliness.  In order to make accurate
   measurements from multiple sensors at the exact same instance in
   time, we need time synchronization with an accuracy in the order of
   milliseconds, possibly over multiple hops.

   o Multicast support: in order to make the bootstrapping function, and
   also save energy, the routing SHOULD support multicast.  This is



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   needed especially for the service/node discovery.

   o Multiple routing paths: since SHM produces large amounts of data at
   one time, the routing system SHOULD be able to support more than one
   routing path between a data producer and the consumers.  This
   requirement is not fully mandatory (MUST), since the use of multiple
   paths can be simulated on a higher layer, by a sensor sending its
   data to multiple sinks.

   o Reliability: when a group of sensors provide their data for further
   processing (data mining), this data MUST be routed/transported in a
   reliable way.  If one part of the whole data is lost, the entire
   sampled data may be useless.  This requirement is more important than
   real-time operation.  Also, bandwidth problems can be partly solved
   by using multiple data sinks.

   o Energy-awareness: obviously the routing protocol SHOULD be aware of
   the energy levels of the sensor nodes and seek to balance the energy
   consumption of the whole network.

   o Route repair: the routing protocol MUST be able to repair routes as
   nodes die out and news ones are put in place.  New nodes may also be
   installed just to increase the reliability and performance of the
   network.  The change SHOULD be localized, and not visible all around
   the sensor network.  The time interval for repairing the network may
   be relatively long, as in the bootstrapping phase.

   o Coupling with RRM: since the sensor nodes need to save power, they
   will sleep most of their lifetime.  Also, since the hardware
   typically only supports one function at a time (measuring or data
   transmission/reception), nodes are not always able to receive data.
   Thus, the routing protocol SHOULD consider the node availability with
   regard to the radio interface, and each nodes ability to further
   forward, route, packets.  It is of little use to send data on a
   certain path if that path will be truncated as hops down the path
   will be sleeping.


4.  Security Considerations

   Moniroting the health of structures enables saving lives, but also
   allows timely response to emerging problems.  The data provided by
   sensors is thus of utmost importance.  The whole transport and
   routing infrastructure must support a high level of reliability and
   the ability to verify the data source.  When we get measurement data
   of a structure, we must be able to trust the data.  Thus, data origin
   authentication is the primary security feature that must be
   available.  Encryption of the transmitted data and eavesdropping is



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   not a primary concern.  The sensor data is mostly public information.


5.  Acknowledgements

   This work is part of an ongoing project Intelligent Structural Health
   Monitoring System (ISMO) funded by the Multidisciplinary Institute of
   Digitalisation and Energy (MIDE), a technology initiative by the
   Helsinki University of Technology (TKK).  More information at:
   http://mide.tkk.fi/en/


6.  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119, March 1997.


Authors' Addresses

   Jaakko Hollmen
   Helsinki University of Technology (TKK)
   P.O. Box 5400
   Espoo  FI-02015 TKK
   Finland

   Phone: +358 9 451 5290
   Email: jaakko.hollmen@tkk.fi


   Jukka Manner
   Helsinki University of Technology (TKK)
   P.O. Box 3000
   Espoo  FI-02015 TKK
   Finland

   Phone: +358 9 451 2481
   Email: jukka.manner@tkk.fi













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