Proposal ID: 957286
ICCS project ID: 63115400
Role: Partner
Acronym: ELEGANT
Topic: ICT-50-2020
Type of action: RIA
Call identifier: H2020-ICT-2018-20

ELEGANT: Secure and Seamless Edge-to-Cloud Analytics

Duration in months: 36
Fixed keyword 1: Software Architectures
Fixed keyword 2: Interoperability
Free keywords: IoT, Big Data, Software Programming paradigm, Performance, Energy Efficiency, Security, Reliability, Dependability, JVM

ELEGANT aims to solve the ever-increasing problem of software fragmentation in the IoT/Big Data interoperability domain. Software fragmentation prohibits the unification of these two ecosystems severely limiting the ability to regard them as a single system and tune the whole infrastructure towards defining its
a) Performance, b) Energy Efficiency, c) Security, d) Reliability, and d) Dependability (PESRD) requirements.
ELEGANT proposes a novel software programming paradigm, along with an associated set of methodologies and toolchains, to program IoT and Big Data frameworks using a unified programming framework.
Its key proposed innovations in the areas of: a) Light-weight application virtualization, b) Automatic code extraction compatible with both IoT and Big Data frameworks, c) AI-assisted Intelligent Orchestration, d) dynamic code motion, and e) advanced code verification and cybersecurity mechanisms, will enable the seamless operation of end-to-end IoT/Big Data complex systems.
This way, users employing the ELEGANT software stack and methodologies will be able to seamlessly define the paretooptimal point in the PESRD optimization space while the entire system will be able to dynamically adjust itself during execution.
To achieve its ambitious goals, ELEGANT assembles a consortium of experts across all domains ranging from low-level system software, IoT, Big Data, AI-assisted scheduling, and DevOps.
Finally, the proposed solutions will be evaluated against pre-defined KPIs across a wide range of operational use cases from four distinct domains: health, automotive, smart metering, and video surveillance.

Lab URL: