The 4th IEEE International Workshop on Distributed Intelligent Systems (DistInSys)

Abstract

The digital environment is, nowadays, populated by sensing devices that are ubiquitous, strongly interconnected, and heterogeneous. The vision of a large ecosystem of machines that can cooperate in solving articulated tasks is becoming realistic day by day. Teams of agents, sensors, and robots are ever more capable to sense the environment, process the gathered information, and act in structured and unstructured scenarios, even in space and harsh environments. To deal with complexity and a large amount of produced data, it is necessary to decompose systems into smaller, distributed, efficient, intelligent, and autonomous units responsible for local decision-making and control, let them explore knowledge stored locally and communicate among themselves only when needed. That solutions opens issues when discussing the systems design, data, and knowledge exchange, analysis of proper and optimal coupling of system parts as well as integration of subsystems,introducing a completely diverse nature into the overall framework. Given the depth of interests and applications, we invite all interested researchers, scientists and engineers to take part in DistInSys 2024 This workshop is in conjunction with the 29th IEEE Symposium on Computers and Communications (ISCC 2023).

Date
26 Jun 2024 09:00 — 13:00
Website
DistInSys 2024
Location
Paris, France
Submission Date
28th Apr, 2024
Notification Date
10th May, 2024
Camera-ready
20th May, 2024

Topics of interest

Papers are solicited in all areas of Distributed Intelligent Systems, including, but not restricted to:

  • Machine Learning Methods for Multi-Agent Systems
  • Distributed Architecture for Machine Learning
  • Middleware for Distributed Learning and their applications
  • Distributed Learning for Remote Sensing
  • Distributed Learning for Satellite and Space Applications
  • Distributed Learning for Autonomous Vehicles
  • Federated Learning methods and applications
  • Federated Reinforcement Learning
  • Deep Learning for Distributed Systems Applications
  • Deep Learning for Vision and Image Processing
  • Knowledge Representation Methods for Distributed Learning Systems
  • Knowledge Distillation and Quantization for Distributed Learning Systems
  • Remote Sensing for Environmental Monitoring
  • Internet of Autonomous Things
  • Distributed Cooperative Perception, Action and Planning
  • Distributed Decision Making
  • Multi-Agent and Swarm Robotics
  • Autonomous Systems, Vehicles, and Drones
  • Sensor and Actuator networks
  • Wireless and Robotic Sensor Networks
  • Cloud Multi-Robot Systems
  • Ambient Intelligence
  • Distributed Cyber-Physical Systems
  • Mobile, Pervasive, and Ubiquitous Computing
  • Hyperdistributed Applications in the Cloud Continuum
  • Trustworthy and verifiable distributed systems
  • Societal/economic/ethical/regulatory/educational considerations for distributed autonomous robotic systems

Submission

In order to download manuscript templates for IEEE conference proceedings, use the following link: https://www.ieee.org/conferences/publishing/templates.html. Papers can be submitted directly to EDAS: https://edas.info/newPaper.php?c=32200

Note that accepted papers up to 6 pages will be published with no additional charge. Exceeding pages will be charged an additional fee. Papers exceeding 7 pages will not be accepted. At least one author of each accepted paper is required to register to the conference and present the paper. Only registered and presented papers will be published in the conference proceedings. Accepted papers will be included in the ISCC 2024 proceedings and will be submitted for inclusion to IEEE Xplore. The ISCC proceedings have been indexed in the past by ISI, DBLP and Scopus. This makes the ISCC conference one of the publication venues with very high visibility and impact in both Computer and Communications areas.

Program Co-Chairs

Steering Committee

  • Lorenzo Carnevale, Università degli Studi di Messina, Messina, Italy
  • Antonino Galletta, Università degli Studi di Messina, Messina, Italy
  • Mario A.R. Dantas, Universidade Federal de Juiz de Fora, Juiz de Fora, Brazil
  • Massimo Villari, Università degli Studi di Messina, Messina, Italy

Technical Program Committee

tbd