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	    2017</a> | <a href="http://www.inria.fr/en/teams/aoste2">Presentation of the Team AOSTE2</a></small>
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        <h2>Section: 
      Overall Objectives</h2>
        <h3 class="titre3">Overall Objectives</h3>
        <p>The recent advances in merging different technologies and engineering domains
has led to the emergence of Cyber-Physical Systems (CPS). In such systems,
embedded computers interact with, and control physical processes. These
embedded computers (cyber) may communicate from a tightly coupled way, for
example through a serial CAN bus in the automotive domain or through an AFDX
bus in the avionics domain to control engine(s) or brakes (physics), to a
loosely coupled way for example through the internet network to offer
multimedia services or data-base accesses. Because of the heterogeneity of the
involved components (multi-physics, sensors, actuators, embedded computers),
CPS may feature very complex design and implementation phases as well as
complex computer platforms (multi/manycore, multiprocessor, distributed and
parallel computers), ever raising the need for effective approaches in order to
build reliable systems.</p>
        <p>Most of these CPS are time sensitive, i.e. time is a crucial issue which must
be carefully mastered, that yet increases their complexity. Mastering time in
such CPS is the major objective of the team. Due to their heterogeneous nature,
the different components may have different levels of criticality, e.g. engine
and brakes have a higher criticality level than multimedia services, which
increase the difficulty in the design and implementation phases since lower
criticality parts must not interfere with higher criticality parts. In the team
we mainly address mixed-criticality issues in term of software safety. However,
we started to take into account, in addition, security issues (cyber attacks).</p>
        <p>The members of the team beeing involved for a long time in <i>synchronous
languages</i>, we address the design of CPS with models compliant with the
semantics of these languages. Theses models are basicaly graphs and more
specifically “clocked graphs” that model data dependences beetween the
functions of the functional specification as well as “logical clocks” that
are attached to every function. These logical clocks may be related to physical
clocks which correspond to periods of functions. These periods are defined by
automatic control engineers and are not dependent of the platform. Such
approach allows verifications on the functional specification, guaranteeing
that the output events of the control system obtained “in reaction” to some
input events, are consistent with the input events that triggered
them. Verifying functional specifications very early in the design phase,
prevents a lot of classic errors found usually later on during the
implementation phase. This approach is an important step for providing
“correct by construction” implementations. However, non functional
specifications must also be taken into consideration. Indeed, to perform
real-time schedulability analyses used to guarantee that the implementation is
correct in terms of time, we need for every function its worst case execution
times (WCET) and for every dependence its worst case communication times
(WCCT). Both worst case execution and communication times are dependent of the
platform. Using these worst case times, schedulability analyses are able to
compute worst case response times and end-to-end worst case execution times in
order to verify if real-time constraints, e.g. deadline, imposed by automatic
control engineers, are met. Note that, unfortunately, automatic control
engineers define these constraints whereas they usually do not know the
platform that will be used later on in the developpement process.</p>
        <p>This is the reason why, in the non functionnal specifications we need precise
models that encompass important features found at different levels of the
platform architecture, e.g. at a high level the number of cores, their means of
communication, at a low level the structure of the caches, pipelines, etc.
Depending on the complexity of the platform the problem of estimating these
worst case times may be more or less difficult. In the case of simple
predictable processors and buses, both used presently in the industry for
critical railways and avionics applications, the estimation of worst case times
is relatively easy. For this purpose we use static analyses or techniques based
on measurements for the WCETs for example. However, due to the ever increasing
smartphone market, the microprocessor industry provides more and more general
purpose platforms based on multicore and, in a near future, based on
manycore. These platform have complex architectures that are not predictable
due to, e.g. multiple levels of cache and pipeline, speculative branching,
communicating through shared memory or/and through a network on chip,
etc. Therefore, nowadays the CPS industry has to face the great challenge of
using such off the shelf platforms and consequently to estimate the
corresponding worst case times of the programs (tasks) that they will execute.</p>
        <p>From functional and non functional specifications of the design phase we intend
to synthesize, as automatically as possible, based on the real-time
schedulability theory, an implementation that is correct by construction. This
synthesizing process is close to the process used in language compilation but,
in addition, it must take into account more complex non functional
specifications. On the other hand, when platforms are not predictable an
alternative to the classic estimation of worst case times mentioned
previously, consists in reformulating the different problems in a probabilistic
framework.</p>
        <p>The overall objectives given above lead to three main research programs that
are detailed below.</p>
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