A5043809260- Distributed and Parallel Computing Systems
- Cellular Automata and Applications
- Evolutionary Algorithms and Applications
- IoT and Edge/Fog Computing
- Metaheuristic Optimization Algorithms Research
- Context-Aware Activity Recognition Systems
- Peer-to-Peer Network Technologies
- Parallel Computing and Optimization Techniques
- Advanced Data Storage Technologies
- Modular Robots and Swarm Intelligence
- Algorithms and Data Compression
- Mobile Crowdsensing and Crowdsourcing
- Data Management and Algorithms
- Advanced Clustering Algorithms Research
- Distributed systems and fault tolerance
- Smart Grid Energy Management
- Data Stream Mining Techniques
- Air Quality Monitoring and Forecasting
- Building Energy and Comfort Optimization
- Interconnection Networks and Systems
- Embedded Systems Design Techniques
- Smart Cities and Technologies
- Data Mining Algorithms and Applications
- Scientific Computing and Data Management
- Complex Network Analysis Techniques
Institute for High Performance Computing and Networking
2015-2024
National Research Council
2015-2024
Indian Council of Agricultural Research
2003-2018
National Academies of Sciences, Engineering, and Medicine
2006-2015
University of Calabria
1997-2008
Interactions, Corpus, Apprentissages, Représentations
2007
Vrije Universiteit Amsterdam
2005
Naturalis Biodiversity Center
2005
University of Lausanne
2005
Leiden University
2005
Large-scale smart environments (LSEs) are open and dynamic systems typically extending over a wide area including huge number of interacting devices with heterogeneous nature. Thus, during their deployment scalability interoperability key requirements to be definitely taken into account. To these, discovery reputation assessment services objects have added, given that new functionalities continuously join LSEs. In spite the increasing interest in this topic, effective approaches develop LSEs...
Enterprise Resource Planning (ERP) system is a collection of collaborative software programs. It handles transactions through enterprise-wide business processes using shared databases, standard methodologies, and data exchange across within functional domains. Setting up an enterprise complex activity costly dangerous investment. Further, ERP potentially affects core supporting processes, especially in cyber-physical domains such as Industrial Internet Things (IIoT) Smart Factory. Cloud...
The increasing data produced by IoT devices and the need to harness intelligence in our environments impose shift of computing at edge, leading a novel paradigm called Edge Intelligence/Edge AI. This combines Artificial Intelligence Computing, enables deployment machine learning algorithms where is generated, able overcome drawbacks centralized approach based on cloud (e.g., performance bottleneck, poor scalability, single point failure). AI supports distributed Federated Learning (FL) model...
In today's world, a significant amount of global energy is used in buildings. Unfortunately, lot this wasted, because electrical appliances are not properly or efficiently. One way to reduce waste by detecting, learning, and predicting when people present To do this, buildings need become "smart" "cognitive" use modern technologies sense how occupying the By leveraging information, can make smart decisions based on recently developed methods. paper, we provide comprehensive overview recent...
Future buildings are complex systems that aim at improving the quality of life their inhabitants and increasing safeness, security, efficiency. In order to reach these goals, they require own self-management self-adaptation capabilities, thus becoming cognitive entities. However, developing exploit advanced Artificial Intelligence (AI) techniques in a distributed fashion is still challenge. Indeed, need continuously collect process variety environmental parameters, learn predict users’ needs...
The real-time control (RTC) system is a valid and cost-effective solution for urban stormwater management. This paper aims to evaluate the beneficial effect on flooding risk mitigation produced by applying RTC techniques an drainage network considering different configuration scenarios. To achieve aim, distributed system, validated in previous studies, was considered. approach uses smart moveable gates controlled software agents, managed swarm intelligence algorithm. By running scenarios...
The paper discusses Camel, an interactive parallel programming environment based on cellular automata. With Camel users can develop high-performance applications in science and engineering. Examples geology, traffic planning, image processing, genetic algorithms show its usefulness.
An extension of cellular genetic programming for data classification (CGPC) to induce an ensemble predictors is presented. Two algorithms implementing the bagging and boosting techniques are described compared with CGPC. The approach able deal large sets that do not fit in main memory since each classifier trained on a subset overall training data. then combined classify new tuples. Experiments several show that, by using set reduced size, better accuracy can be obtained, but at much lower...
A new parallel implementation of genetic programming (GP) based on the cellular model is presented and compared with both canonical GP island approach. The method adopts a load-balancing policy that avoids unequal utilization processors. Experimental results benchmark problems different complexity show superiority approach respect to sequential model. theoretical performance analysis reveals high scalability realized allows predict size population when number processors their efficiency are fixed.