Energy-aware Actor-based Distributed Programming

**Energy-aware actor-based distributed programming**:

- Réf **ABG-129018**
- Sujet de Thèse
- 03/03/2025
- Contrat doctoral
- IMT Atlantique (Nantes)
- Lieu de travail- Nantes - Pays de la Loire - France
- Intitulé du sujet- Energy-aware actor-based distributed programming
- Champs scientifiques- Informatique
- Ecologie, environnement
- Sciences de l’ingénieur
- Mots clés- Distributed systems, frugal computing, energy quotas, actor programming

**Description du sujet**:
**Domain and scientific/technical context**
- mains of the Cloud-Edge-IoT (CEI) continuum and AI-intensive software systems is a major challenge for today’s societies. Controlling the energy consumption is notably crucial in two different contexts: (i) the management/optimization of the overall energy consumption of large-scale software systems among with AI-intensive software systems now occupy a place of choice and (ii) the integration of massive numbers and large varieties of small, battery powered IoT devices in large-scale distributed systems.

Currently, energy consumption is typically handled by runtime monitoring of compo
- nents of the software systems running on distributed systems, e.g., data centers, grid ar
- chitectures, sensor networks and other distributed cyber-physical infrastructures. Based on measured energy consumption and (configured) available energy quotas, some scheduling component then dynamically enables computations based on energy policies. [SDU+23, HCW+21, CKC+21]

**Scientific/technical challenges**

Current distributed software/hardware systems almost never provide guarantees that future computations (that are typically encapsulated in some software component) can be executed given the currently available energy. Furthermore, energy-related information is currently almost always expressed at the API and systems-level [RWS+24]: energy-related properties therefore cannot be expressed at the programming level. Such guarantees require a precise link between energy-consuming computations, i.e., distributed programs, energy sources (available electricity networks, batteries) and available energy quotas determined based through dynamic monitoring.

Such a link has been proposed for non-distributed programs (through program language extensions or transformations [CY17, ZLL15, YVS17] as well as static analysis [MSP+21, KKK16]) but is lacking for distributed systems. Currently, software systems for distributed systems are typically structured in terms of separate programs that are deployed on different machines, often using containers [SDU+23], and cooperate at runtime. More precise energy policies and energy-aware schedulers can thus be defined only in terms of specifications that are difficult to link to the set of executing programs.

**Considered methods, targeted results and impacts**

The main goal of this PhD is the precise definition and efficient enforcement of energy contracts over distributed programs. We are targeting a distributed pro
- gramming language extension that allows required and available energy quotas of programs to be partially defined by the programmer and partially provided dynamically by the dis
- tributed environment in which the program is executed. Required energy quotas are then checked using static analysis or dynamic tests against the energy available from the execu
- tion environment. Energy quotas are managed and enforced through contexts that energy
- aware programs use to store energy-related environmental information. Contexts are also harnessed in order to actively manage energy-consuming computations using placement of computations, optimization of communication, rate limiting, scaling etc.

Distributed computations are represented and energy contexts maintained in the envi
- sioned programming method by means of software actors [MSD18, HSF16], components that encapsulate computations and data that can be flexibly deployed and executed in distributed systems.

**Environment (partners, places, specific tools and hardware)**

At IMT Atlantique, the PhD student will be part of the STACK team, a leading team on research on distributed programming and infrastructures, notably in the Cloud-Edge-IoT continuum.

At the VUB, the PhD student will be part of the Soft laboratory, a leading lab in the domain of programming languages.

**Interdisciplinarity aspects**

The topic straddles the domains of software engineering, energy efficiency and frugal com

analyses) and the Industry of the Future (e.g., the optimization of monolithic batch pro
- cesses that are currently used frequently). These interdisciplinary aspects will be explored, in particular, together with the non academic partners of this topic.

**Supervisors and study periods**

2.2

2.2.1

**Supervisors and study periods**
- IMT Atlantique: Prof. Mario Südholt, IMT Atlantique, Nantes, France
The PhD student will stay 2 years at IMT Atlantique.
- International partner: Prof. Coen De Roover and Prof. Wolfgang De Meuter, Vrije Un