IDC 2018 - 12th International Symposium on Intelligent Distributed Computing

The 12th International Symposium on Intelligent Distributed Computing (IDC 2018) will be held in October 2018 in Bilbao, Spain. The main goal of these series of symposiums 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. The IDC 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 and techniques ranging from classical artificial intelligence, information sciences or computational intelligence to more recent trends such as swarm intelligence, bio-inspired computation, cloud computing or machine learning. Distributed Computing develops technologies and methods to build complex computational systems composed of collaborating software components spread over different computational elements. Recent trends on this field are Ephemeral Computing, Federated Learning or Swarm Robotics. 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 2018 welcomes research works centered on all aspects of intelligent distributed computing, with an intention to balance between theoretical research ideas and their practicability as well as industrial applicability. To this end, scholars and practitioners from academia and industrial fields are invited to submit high-quality original contributions to IDC 2018. 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 focused on multi-disciplinary and cutting-edge topics.
IDC 2018 has a special interest in novel architectures, systems and methods that facilitate distributed / parallel / multi-agent biocomputing for solving complex computational and real-life problems. The scope of this edition spans further to embrace recent paradigms in Distributed Computation. Symposium topics include, but are not limited to:
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
Distributed frameworks and middleware for the Internet of Things
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
Ehemeral 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
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