The Distributed Systems Research Laboratory, part of the Technical University of Cluj-Napoca, has extensive experience in many fields of the distributed systems related research areas:

ENERGY EFFICIENCY IN LARGE SCALE DISTRIBUTED SYSTEMS
Data center energy usage assessment using our Greenness Level Assessment tool and various Green Performance Indicators and metrics (PUE, DH-UR, etc.) Nonlinear programming optimization for increasing energy efficiency of IT systems. Workload consolidation for energy consumption reduction using our Green Cloud Scheduling Technology for open clouds. Delay tolerant workload scheduling for minimizing energy costs. Optimization of IT resources energy consumption through Dynamic Power Management

BIG DATA ANALYTICS
Technological support for creating and storing, and managing the use of big data streams. Integration of new big data technologies into existing data platform and improve data life-cycle management functions. - Service delivery of customized insights and information through advanced analytics out of big data sets to drive business growth. Building and deploying big data applications and advanced analytics to improve business results. Data disambiguation, noise elimination and predictive analytics based on time series analysis and clustering techniques. Implementation of decision making support tools tailored to various organizational and system goals based on reinforcement learning, deep learning, decision trees, neural networks, and genetic algorithms.

IOT AND BLOCKCHAIN TECHNOLOGY
Distributed shared ledger implementation, smart contracts, Ethereum technology, distributed peer to peer control, distribute consensus (proof of work and prof of stake). Applicability in domains such as management of smart grids and demand-response programs, ecosystem management and payment of ecosystem services trading, circular economy and smart manufacturing.

AMBIENT ASSISTED LIVING (AAL)
Study and develop techniques and methods to enhance the quality of life of older people through the use of Information and Communication Technologies (ICT).

MODELLING AND SIMULATION
Mathematical modeling of complex systems and system behavioral analysis. Modelling of complex systems and environments so that the effect of changes can be predicted. Engineering and software integration of domain ontology. Rule-based reasoning over semantic representations for knowledge extraction and decision making. What-if model simulation to evaluate the performance of a system, existing or proposed, under different configurations of interest and over time.

MULTIDISCIPLINARY OPTIMIZATION
Mathematical modeling and simulation of complex hybrid systems that exhibits both continuous and discrete behaviors. DC components energy flexibility aggregation and DR signal matching Recommend optimal configurations are tailored to specific organizational goals and industry best practices. Identify and quantify plant performance improvements that can be expected from enhanced automation. Analysis and optimization of processes based on event logs using process mining. Industrial process real time control and costs optimization. Multi-objective and multi-criteria problems solving using mathematical models

BIO-INSPIRED OPTIMIZATION
Study and develop bio-inspired hybrid meta-heuristics applicable in multi-objective optimization problems such as (i) selecting the optimal solution in semantic web service composition, (ii) data clustering, (iii) business process mining, (iv) generating personalized healthy diet recommendations, (v) ensuring energy efficiency at the server/data center level

Distributed Systems Research Laboratory

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