IDC 2021

14th International Symposium on Intelligent Distributed Computing
Scilla, Reggio Calabria, Italy, 16/09/2021–18/09/2021

The 14th International Symposium on Intelligent Distributed Computing (IDC 2021) will be held September 16-18, 2021 in Scilla (Reggio Calabria), Italy. The main goal of the IDC symposium is to gather researchers and practitioners to foster and ease rich discussions around the latest findings, research achievements and ideas in the area of Intelligent Distributed Computing. Specifically, The IDC 2021 provides an open forum for enhancing the collaboration between researchers, lecturers, and students from Intelligent Computing and Distributing Computing communities. Intelligent Computing covers a hybrid palette of methods, techniques and their applications ranging from classical artificial intelligence, information and data sciences, multi-agent technologies or computational intelligence to more recent trends such as swarm intelligence, bio-inspired computation, cloud computing, machine learning or social-cyber-physical trust and security. Distributed Computing develops methods and technology to build complex computational systems composed of collaborating software components scattered across diverse computational elements. Recent trends on this field present ephemeral computing, federated learning, swarm Intelligence, fog computing, semantic data science, Internet of Things, Robotics and others. Thus, the field of Intelligent Distributed Computing seeks for the design and implementation of new generation of intelligent distributed systems, adapting or hybridizing researches in both Intelligent Computing and Distributed Computing. IDC 2021 welcomes research works centered on all aspects of intelligent distributed computing, with an intention to balance between theoretical research ideas and their application to great variety of industrial cases. To this end, scholars and practitioners from academia and industrial fields are invited to submit high-quality original contributions to IDC 2021. The structure of the symposium consists of regular sessions with technical contributions reviewed and selected by an international program committee, as well as of special sessions and workshops targeted on multi-disciplinary and cutting-edge topics. IDC 2021 is particularly interested in novel models, approaches, architectures, systems and methods for the Internet of Things (IoT) domain, for solving complex computational and communication problems as well as social challenges in agent cooperation and/or competition, including formation of groups and teams, coordination strategies, recent paradigms and frameworks in trust-based computation, recommendation techniques and efficient and effective communication among smart objects. 

topics of interest
  • Intelligent Distributed and High-Performance Architectures
    • Hybrid distributed systems involving software agents and human actors
    • Intelligent grid and cloud infrastructures
    • Agent-based wireless sensor networks
    • GPU, multicore, and many-core intelligent computing
    • Intelligent high-performance architectures
    • Context-aware intelligent computing
    • Virtualization infrastructures for intelligent computing
    • Bio-inspired and nature-inspired distributed computing
  • Organization and Management
    • Autonomic and adaptive distributed computing
    • Intelligent service composition and orchestration
    • Self-organizing and adaptive distributed systems
    • Emerging behaviors in complex distributed systems
    • Intelligent integration of heterogeneous data and processes
    • Methodologies for development of intelligent distributed systems and applications
    • Trust-based Computation
  • Ephemeral and Unreliable computing
    • Theory and applications of complex ephemeral or unreliable environments
    • Design and deployment of ephemeral computing systems
    • Application of Soft Computing methods on computational environments featuring ephemeral behavior (unreliability, dynamicity, and/or heterogeneity)
    • Meta-heuristics for modeling and analyzing systems with ephemeral properties, such as social network dynamics, ephemeral clustering and pattern mining, ephemeral computational creativity or content generation.
  • Intelligent Distributed Knowledge Representation and Processing
    • Information extraction and retrieval in distributed environments
    • Knowledge integration and fusion from distributed sources
    • Data mining and knowledge discovery in distributed environments
    • Semantic and knowledge grids
    • Ontologies and meta-data for describing heterogeneous resources and services
    • Distributed fusion of sensor data streams
    • Big Data Processing
  • Networked Intelligence
    • E-service and web intelligence
    • Intelligence in mobile, ubiquitous and wearable computing
    • Intelligence in peer-to-peer systems
    • Intelligence in distributed and networked multimedia systems
    • Security, privacy, trust and reputation
  • Parallel metaheuristics for optimization
    • Global single-population master-slave, panmictic population GAs
    • Single-population fine-grained GAs
    • Multiple-population, multiple-deme, distributed, island based, coarse grained, GAs
    • Evolutionary simulated annealing, Distributed Tabu Search
    • Parallel Variable Neighborhood Search
    • Swarm intelligence methods based on distributed knowledge sharing: bat algorithm, firefly algorithm, imperialist competitive algorithm, particle swarm optimization, ant colony optimization, artificial bee colony, golden ball, coral reefs optimization, water cycle algorithm, cuckoo search, harmony search
    • Hybridization of Swarm Intelligence techniques, Memetic Computing, Adaptive Swarm Intelligence methods
    • Distributed Evolutionary Techniques, Cellular Evolutionary Algorithm, Hyper Heuristics
    • Applications of swarm intelligence techniques for distributed or cooperative environments
  • Distributed swarm robotics systems
    • Recent advances on Soft Computing methods for Robotics
    • Novel applications of Swarm Robotics, with a priority on real-world scenarios
    • New synergies between Swarm Intelligence and Swarm Robotics
    • Coordination and control of Swarm Robotic Systems
    • Applications of Swarm Intelligence for collaborative positioning and route optimization in robotic swarms
    • Distributed inference in Swarm Robotics
    • Self-organization in robotics enabled by Swarm Intelligence
  • Nature inspired methods for data science and machine learning
    • Recent advances on nature inspired methods for data science
    • Novel applications of bio-inspired methods to data mining, with priority on real-world scenarios
    • Nature-inspired methods for supervised and unsupervised data mining
    • Hybridizing bio-inspired methods with machine learning and data mining techniques
      • Nature-inspired methods for feature selection and/or instance generation/selection
    • Implementation of bio-inspired methods using Big Data technologies
    • Federated learning: theory and applications
    • Recent advances on nature inspired methods for data science
    • Novel applications of bio-inspired methods to data mining, with priority on real-world scenarios
    • Nature-inspired methods for supervised and unsupervised data mining
  • Internet of Things
    • Agriculture and Ocean of Things
    • Commercial and Manufacturing IoT
    • Distributed frameworks and middleware for IoT
    • Cloud of Things
    • Energy and environmental management and monitoring IoT
    • H2M and M2M IoT interacions
    • IoT group formation
    • Medical and healthcare IoT
    • Mobile IoT
    • Pervasive IoT
    • Trust and reputation systems for IoT
    • Smart home and smart cities
  • Intelligent Distributed Applications
    • Distributed problem solving and decision making
    • Intelligent applications in e-business/e-commerce, e-learning, e-health, e-science, e-government, crisis management, smart grid
    • Modeling, simulation and development of intelligent distributed systems
    • Simulation of groups and crowds
    • Intelligent data processing
    • Intelligent robots
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