Controlled Load (CL) Service using distributed measurement-based admission control (D-MBAC)
Challenges and Design Issues in a Distributed Measurement scenario
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Transcript of Challenges and Design Issues in a Distributed Measurement scenario
Challenges and Design Issues in a Distributed Measurement scenario
Special session in Distributed Measurement Systems
PADOVA UNIVERSITYDept. of Information Engineering PadovaItaly
INGRID/2008
Luigino BenetazzoMatteo Bertocco Giovanni GambaAlessandro Sona
summary
introduction topology issues design issues
Introduction
why communication & measurements
should meet?
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An historical note ...
from analog (only) instrumentation...
How have instruments evolved in recent years?
digital instrumentation
to...
where A/D and D/A converters, and signal processing
provided considerable improvements
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from analog (only) instrumentation
How have instruments evolved in recent years?
digital instrumentation
to...
virtual instruments
where digital instrumentation, interfaces, andmeasurement software
provide a new “virtual instrument”, having added functionalities with respect to the actually available physical instruments
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from analog (only) instrumentation
How have instruments evolved in recent years?
digital instrumentation
to...
virtual instruments
where a set of virtual instruments, and
computersthrough some communication links
provide a way for remote interaction with instrumentation
networked instruments
internet
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from analog (only) instrumentation
How have instruments evolved in recent years?
digital instrumentation
to...
virtual instruments
where a measuring devices are distributed
in some geographical areas, while many (hardware & software) componentscooperates in order to provide some useful final results
networked instruments
network
distributed instruments
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from analog (only) instrumentation
How have instruments evolved in recent years?
digital instrumentation
to...
virtual instruments
networked instruments
wirelessnetwork
distributed instruments
wireless distributed instruments
where “wireless”
has a number of interesting consequences,from mobility, to ad-hoc architectures ...
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communication engineer
instrumentation & measurement engineer (metrologist)
computer science engineer
often have a different point o view
wirelessnetwork
in the above (wireless distributed measurement system) scenario
some key issues are considered, in order to stimulate joint work & research
topology issues
a snapshot, as seen from the measurement point of view...
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a DMS, for what ?
Distributed Measurement Systems (DMS), can be designed having in mind different applications
some examplespower quality, land surveillance, pollution monitoring, ...
hence, bandwidth, connectivity reliability, time synchronization, etc.may have very different numerical specifications ...
this does not mean that any topology can be adopted as far as bandwidth constraints, for instance, are satisfied,
becausethis is a measurement system ...
so, let us see what does it means for some topologies...
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Ad-hoc topology
AD-HOC (P2P)
consensus-based algorithms greatly simplified (fast convergence)
advantages
prevents “single point of failure” (redundancy), hence prevents data loss when information flows toward a “master” node
data loss means loss of accuracy!
scalable, hence the number of nodes may considerably grow
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Ad-hoc topology
AD-HOC (P2P)
the nodes must be sufficiently “clever”this implies sufficient processing power, energy consumption, and raises costs
disadvantages
management of the system is not so easy
yes, it is scalable, but since management is somewhat complicated, is this topology really the best choice for a large DMS (possibly with low-cost sensors) ?
in practice, a (hopefully) good choice for not too-low-cost sensors, and not too far away located, and not for a large number of nodes
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Star topology STAR
the node can be rather “stupid”, (low computing power, low communication energy, low cost)
advantages
real-time constraints can be satisfied in an easier manner (with resp. to ad-hoc)
disadvantages
“static” topology: less flexible, less scalable (round-robin time increases with the number of nodes), ...
a good choice for many “industrial applications”, where measurements meets automatic control
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Cluster-tree topology CLUSTER
CLUSTER
CLUSTER TREE
an improved version of cluster topology
inherits advantages, and mitigates drawbacks
balances an increased complexity with scalability, even though the hierarchy that it implies can be exploited in order to simplify the management of the network itself
still exposed to single point failures, and hence its usage may be questionable when a loss of measured data is a detrimental fact
advantages
disadvantages
a compromise solution choice with respect to ad-hoc and star topologies
design issues
please, add a dimension to your “usual” perspective...
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Deployment
A DMS is physically created by inserting new measurement nodes, controllers (management items), clients, etc.
one aspect
plug&play features are “a must”
in telecom apps. often the nodes are very similar each other
in a measurement context, instead, the nodes can significantly differ
and hence
for an efficient management of the nodes a “middleware” may be required, that allows dealing with nodes in a unified manner
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Mobility
in a measurement context, mobility means in practicemobility of the Equipment Under Test (EUT), rather than mobility of people performing tests (with some exceptions!)
sometimes, mobility is not really required: a wireless connection is adopted just in order to simplifying deployment (cabling, connections, ...)
some interesting “exceptions”: - rotating machines - sensors “inside” a product along a production plant
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Mobility
coverage area for telecom apps. means “almost worldwide”, for measurements coverage area means “reach the EUT”
in many cases, the area is sufficiently limited so that cell handover is an issue almost out of scope
when multiple cells are actually needed, the possible data loss associated to handover implies:
in a telecom scenario: degradation of speech/video, delays
in a measurement context: loss of measures - more critical, since it implies a worse accuracy
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rese
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Hetereogeneity
research works tend to standardize as far as possible the nodes, so that they can be considered almost equal
... but in many practical applications, measurements node significantly differs
development of a “middleware layer” that standardize the way nodes are seen from other system components
many solutions (de facto, standards, proprietary s/w drivers,...) promise interoperability, in practice this is still a hard task
instead of letting proprietary applications do the job, why not to rethink a “compatibility” network layer in a similar manner to the one offered by the widely-known HTTP protocol for the data exchange of web contents?
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Energy
Energy-constrained networks is a large research topic
different points of view (a meaningful example):
signal processing optimize distributed detection and estimation network task while minimizing use of communications
communications support network specific goals while minimizing idle listening, network setup and network maintenance
systems exploit low power hardware and external assets, to the greatest possible extent
metrology how to optimize energy-hungry calibration tasks?
...
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Energy
Energy-constrained networks is a large research topic
different point of view (example):
metrology how to optimize energy-hungry calibration tasks?
calibration means accuracy!
energy optimization can be viewed as the search for compromise solutions that optimize overall accuracy rather than signal processing, communication, or system parameters re
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Synchronization
another large research topic
the degree of synchronization can greatly vary:
coarse synchronization
many nodes detect the same event
ADC sample time accuracy
two ADC sample data with a timing accuracy comparably better than the sampling rate
1s
1ns
10-6W
0.1W
accuracy energy
many good reasons to provide synchronization: from MAC scheduling, to intrinsic nature of the observed phenomenon
many side-effects to be considered: from component's aging to temperature drifts ...
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Synchronization
distributed algorithm measurement
synchronization is a key aspect
timing requirements may considerably vary, i.e. simultaneous means ensure a “skew” no larger than a given amount, and with a a priori defined accuracy
interesting research area:
extend the concepts of “trigger” to a “distributed trigger”
LXI is an interesting proposal, but a wireless, mobile scenario needs further study re
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Localization
many aspects, technologies, proposals...
... and a new requests are daily arising
interesting practical applications could benefit from low-cost radio localization technologies, accurate (<1m) but non GPS-based (low-cost, indoor)
security (machine-workers interaction) people/devices localization
an open question is calibration of a whole localization system
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Routing & Medium access control
distributed measurement systems are
- data-centric,- data may have a redundancy nature different from a “video content”- often a preferred flow of information can be stated (eg. towad a host)
routing schemes are designed having in mind a general context as far as possible,
but is this the right choice, when
- timing constraints are rather severe- data flows a “known” (hierarchical) scheme - a “cooperation model” among nodes is stated- nodes are moving
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?
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Reliability
a lost packet in a multimedia communications context means quality worsening (psychological or economic aspect)
a lost packet in a distributed measurement context means accuracy worsening
the concept of reliability needs some investigation
how accuracy depends on reliability?
which is the relationship between the accuracy loss and well-known network parameters?
...
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Testing
in electronics, “design for testability” concepts are well-known
in short, complicated equipments are provided with additional functionalities (hardware, software), so that system testing could be performed in a reasonably easy way
a distributed measurement system is complicated in a number of ways: hardware challenges, interference, protocol stacks, software agents,...
but testing
needs understanding the interaction between the above quite different aspects
why not to embed (e.g. in a “protocol stack”) mechanisms that simplify testing, i.e. add a “design for testability” perspective to the already known (or new) architectures?
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many other issues:
e.g.: cross-layer design, bandwidth, role of signal processing,...
design of IC in “fast motion”big research groups are hard working
but from above discussion, one need should be (at least) clear:
researchers on
telecommunication
instrumentation and measurement
computer science
... and “comfort noise”:
should more deeply interact, this will definitely provide an improved value to results!
final remarks