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Dr. Ionut Anghel
Senior researcher at Distributed Systems Research Laboratory; Associate professor at Computer Science Department, Faculty of Automation and Computer Science, Technical University of Cluj-Napoca, 400027, 26-28 Baritiu street, Cluj-Napoca, Romania

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0 Green IT
0 Smart Homes
0 ambient assisted living
0 social robots
0 Context aware systems

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Journal article
Published: 20 April 2021 in Sensors
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Data centers consume lots of energy to execute their computational workload and generate heat that is mostly wasted. In this paper, we address this problem by considering heat reuse in the case of a distributed data center that features IT equipment (i.e., servers) installed in residential homes to be used as a primary source of heat. We propose a workload scheduling solution for distributed data centers based on a constraint satisfaction model to optimally allocate workload on servers to reach and maintain the desired home temperature setpoint by reusing residual heat. We have defined two models to correlate the heat demand with the amount of workload to be executed by the servers: a mathematical model derived from thermodynamic laws calibrated with monitored data and a machine learning model able to predict the amount of workload to be executed by a server to reach a desired ambient temperature setpoint. The proposed solution was validated using the monitored data of an operational distributed data center. The server heat and power demand mathematical model achieve a correlation accuracy of 11.98% while in the case of machine learning models, the best correlation accuracy of 4.74% is obtained for a Gradient Boosting Regressor algorithm. Also, our solution manages to distribute the workload so that the temperature setpoint is met in a reasonable time, while the server power demand is accurately following the heat demand.

ACS Style

Marcel Antal; Andrei-Alexandru Cristea; Victor-Alexandru Pădurean; Tudor Cioara; Ionut Anghel; Claudia Antal (Pop); Ioan Salomie; Nicolas Saintherant. Heating Homes with Servers: Workload Scheduling for Heat Reuse in Distributed Data Centers. Sensors 2021, 21, 2879 .

AMA Style

Marcel Antal, Andrei-Alexandru Cristea, Victor-Alexandru Pădurean, Tudor Cioara, Ionut Anghel, Claudia Antal (Pop), Ioan Salomie, Nicolas Saintherant. Heating Homes with Servers: Workload Scheduling for Heat Reuse in Distributed Data Centers. Sensors. 2021; 21 (8):2879.

Chicago/Turabian Style

Marcel Antal; Andrei-Alexandru Cristea; Victor-Alexandru Pădurean; Tudor Cioara; Ionut Anghel; Claudia Antal (Pop); Ioan Salomie; Nicolas Saintherant. 2021. "Heating Homes with Servers: Workload Scheduling for Heat Reuse in Distributed Data Centers." Sensors 21, no. 8: 2879.

Review
Published: 27 February 2021 in Future Internet
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The Distributed Ledger Technology (DLT) provides an infrastructure for developing decentralized applications with no central authority for registering, sharing, and synchronizing transactions on digital assets. In the last years, it has drawn high interest from the academic community, technology developers, and startups mostly by the advent of its most popular type, blockchain technology. In this paper, we provide a comprehensive overview of DLT analyzing the challenges, provided solutions or alternatives, and their usage for developing decentralized applications. We define a three-tier based architecture for DLT applications to systematically classify the technology solutions described in over 100 papers and startup initiatives. Protocol and Network Tier contains solutions for digital assets registration, transactions, data structure, and privacy and business rules implementation and the creation of peer-to-peer networks, ledger replication, and consensus-based state validation. Scalability and Interoperability Tier solutions address the scalability and interoperability issues with a focus on blockchain technology, where they manifest most often, slowing down its large-scale adoption. The paper closes with a discussion on challenges and opportunities for developing decentralized applications by providing a multi-step guideline for decentralizing the design and implementation of traditional systems.

ACS Style

Claudia Antal; Tudor Cioara; Ionut Anghel; Marcel Antal; Ioan Salomie. Distributed Ledger Technology Review and Decentralized Applications Development Guidelines. Future Internet 2021, 13, 62 .

AMA Style

Claudia Antal, Tudor Cioara, Ionut Anghel, Marcel Antal, Ioan Salomie. Distributed Ledger Technology Review and Decentralized Applications Development Guidelines. Future Internet. 2021; 13 (3):62.

Chicago/Turabian Style

Claudia Antal; Tudor Cioara; Ionut Anghel; Marcel Antal; Ioan Salomie. 2021. "Distributed Ledger Technology Review and Decentralized Applications Development Guidelines." Future Internet 13, no. 3: 62.

Journal article
Published: 26 November 2020 in Sustainability
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In this paper, we address the management of Data Centers (DCs) by considering their optimal integration with the electrical, thermal, and IT (Information Technology) networks helping them to meet sustainability objectives and gain primary energy savings. Innovative scenarios are defined for exploiting the DCs electrical, thermal, and workload flexibility as a commodity and Information and Communication Technologies (ICT) are proposed and used as enablers for the scenarios’ implementation. The technology and scenarios were evaluated in the context of two operational DCs: a micro DC in Poznan which has on-site renewable sources and a DC in Point Saint Martin. The test cases’ results validate the possibility of using renewable energy sources (RES) for exploiting DCs’ energy flexibility and the potential of combining IT load migration with the availability of RES to increase the amount of energy flexibility by finding a trade-off between the flexibility level, IT load Quality of Service (QoS), and the RES production level. Moreover, the experiments conducted show that the DCs can successfully adapt their thermal energy profile for heat re-use as well as the combined electrical and thermal energy profiles to match specific flexibility requests.

ACS Style

Tudor Cioara; Marcel Antal; Claudia (Pop); Ionut Anghel; Massimo Bertoncini; Diego Arnone; Marilena Lazzaro; Marzia Mammina; Terpsichori-Helen Velivassaki; Artemis Voulkidis; Yoann Ricordel; Nicolas Sainthérant; Ariel Oleksiak; Wojciech Piatek. Data Centers Optimized Integration with Multi-Energy Grids: Test Cases and Results in Operational Environment. Sustainability 2020, 12, 9893 .

AMA Style

Tudor Cioara, Marcel Antal, Claudia (Pop), Ionut Anghel, Massimo Bertoncini, Diego Arnone, Marilena Lazzaro, Marzia Mammina, Terpsichori-Helen Velivassaki, Artemis Voulkidis, Yoann Ricordel, Nicolas Sainthérant, Ariel Oleksiak, Wojciech Piatek. Data Centers Optimized Integration with Multi-Energy Grids: Test Cases and Results in Operational Environment. Sustainability. 2020; 12 (23):9893.

Chicago/Turabian Style

Tudor Cioara; Marcel Antal; Claudia (Pop); Ionut Anghel; Massimo Bertoncini; Diego Arnone; Marilena Lazzaro; Marzia Mammina; Terpsichori-Helen Velivassaki; Artemis Voulkidis; Yoann Ricordel; Nicolas Sainthérant; Ariel Oleksiak; Wojciech Piatek. 2020. "Data Centers Optimized Integration with Multi-Energy Grids: Test Cases and Results in Operational Environment." Sustainability 12, no. 23: 9893.

Journal article
Published: 05 October 2020 in Sensors
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Nowadays, the adoption of demand response programs is still lagging due to the prosumers’ lack of awareness, fear of losing control and privacy of energy data, etc. Programs decentralization, by adopting promising technologies such as blockchain, may bring significant advantages in terms of transparency, openness, improved control, and increased active participation of prosumers. Nevertheless, even though in general the transparency of the public blockchain is a desirable feature in the energy domain, the prosumer energy data is sensitive and rather private, thus, a privacy-preserving solution is required. In this paper, we present a decentralized implementation of demand response programs on top of the public blockchain which deals with the privacy of the prosumer’s energy data using zero-knowledge proofs and validates on the blockchain the prosumer’s activity inside the program using smart contracts. Prosumer energy data is kept private, while on the blockchain it is stored a zero-knowledge proof that is generated by the prosumer itself allowing the implementation of functions to validate potential deviations from the request and settle prosumer’s activity. The solution evaluation results are promising in terms of ensuring the privacy of prosumer energy data stored in the public blockchain and detecting potential data inconsistencies.

ACS Style

Claudia Daniela Pop; Marcel Antal; Tudor Cioara; Ionut Anghel; Ioan Salomie. Blockchain and Demand Response: Zero-Knowledge Proofs for Energy Transactions Privacy. Sensors 2020, 20, 5678 .

AMA Style

Claudia Daniela Pop, Marcel Antal, Tudor Cioara, Ionut Anghel, Ioan Salomie. Blockchain and Demand Response: Zero-Knowledge Proofs for Energy Transactions Privacy. Sensors. 2020; 20 (19):5678.

Chicago/Turabian Style

Claudia Daniela Pop; Marcel Antal; Tudor Cioara; Ionut Anghel; Ioan Salomie. 2020. "Blockchain and Demand Response: Zero-Knowledge Proofs for Energy Transactions Privacy." Sensors 20, no. 19: 5678.

Journal article
Published: 27 May 2020 in International Journal of Environmental Research and Public Health
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The world is facing major societal challenges because of an aging population that is putting increasing pressure on the sustainability of care. While demand for care and social services is steadily increasing, the supply is constrained by the decreasing workforce. The development of smart, physical, social and age-friendly environments is identified by World Health Organization (WHO) as a key intervention point for enabling older adults, enabling them to remain as much possible in their residences, delay institutionalization, and ultimately, improve quality of life. In this study, we survey smart environments, machine learning and robot assistive technologies that can offer support for the independent living of older adults and provide age-friendly care services. We describe two examples of integrated care services that are using assistive technologies in innovative ways to assess and deliver of timely interventions for polypharmacy management and for social and cognitive activity support in older adults. We describe the architectural views of these services, focusing on details about technology usage, end-user interaction flows and data models that are developed or enhanced to achieve the envisioned objective of healthier, safer, more independent and socially connected older people.

ACS Style

Ionut Anghel; Tudor Cioara; Dorin Moldovan; Claudia Antal; Claudia Daniela Pop; Ioan Salomie; Cristina Bianca Pop; Viorica Rozina Chifu. Smart Environments and Social Robots for Age-Friendly Integrated Care Services. International Journal of Environmental Research and Public Health 2020, 17, 1 .

AMA Style

Ionut Anghel, Tudor Cioara, Dorin Moldovan, Claudia Antal, Claudia Daniela Pop, Ioan Salomie, Cristina Bianca Pop, Viorica Rozina Chifu. Smart Environments and Social Robots for Age-Friendly Integrated Care Services. International Journal of Environmental Research and Public Health. 2020; 17 (11):1.

Chicago/Turabian Style

Ionut Anghel; Tudor Cioara; Dorin Moldovan; Claudia Antal; Claudia Daniela Pop; Ioan Salomie; Cristina Bianca Pop; Viorica Rozina Chifu. 2020. "Smart Environments and Social Robots for Age-Friendly Integrated Care Services." International Journal of Environmental Research and Public Health 17, no. 11: 1.

Journal article
Published: 21 February 2020 in Applied Sciences
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Daily living activities (DLAs) classification using data collected from wearable monitoring sensors is very challenging due to the imbalance characteristics of the monitored data. A major research challenge is to determine the best combination of features that returns the best accuracy results using minimal computational resources, when the data is heterogeneous and not fitted for classical algorithms that are designed for balanced low-dimensional datasets. This research article: (1) presents a modification of the classical version of the binary particle swarm optimization (BPSO) algorithm that introduces a particular type of particles called sensor particles, (2) describes the adaptation of this algorithm for data generated by sensors that monitor DLAs to determine the best positions and features of the monitoring sensors that lead to the best classification results, and (3) evaluates and validates the proposed approach using a machine learning methodology that integrates the modified version of the algorithm. The methodology is tested and validated on the Daily Life Activities (DaLiAc) dataset.

ACS Style

Dorin Moldovan; Ionut Anghel; Tudor Cioara; Ioan Salomie. Adapted Binary Particle Swarm Optimization for Efficient Features Selection in the Case of Imbalanced Sensor Data. Applied Sciences 2020, 10, 1496 .

AMA Style

Dorin Moldovan, Ionut Anghel, Tudor Cioara, Ioan Salomie. Adapted Binary Particle Swarm Optimization for Efficient Features Selection in the Case of Imbalanced Sensor Data. Applied Sciences. 2020; 10 (4):1496.

Chicago/Turabian Style

Dorin Moldovan; Ionut Anghel; Tudor Cioara; Ioan Salomie. 2020. "Adapted Binary Particle Swarm Optimization for Efficient Features Selection in the Case of Imbalanced Sensor Data." Applied Sciences 10, no. 4: 1496.

Journal article
Published: 14 February 2020 in Sustainability
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In this paper, we address the problem of the efficient and sustainable operation of data centers (DCs) from the perspective of their optimal integration with the local energy grid through active participation in demand response (DR) programs. For DCs’ successful participation in such programs and for minimizing the risks for their core business processes, their energy demand and potential flexibility must be accurately forecasted in advance. Therefore, in this paper, we propose an energy prediction model that uses a genetic heuristic to determine the optimal ensemble of a set of neural network prediction models to minimize the prediction error and the uncertainty concerning DR participation. The model considers short term time horizons (i.e., day-ahead and 4-h-ahead refinements) and different aspects such as the energy demand and potential energy flexibility (the latter being defined in relation with the baseline energy consumption). The obtained results, considering the hardware characteristics as well as the historical energy consumption data of a medium scale DC, show that the genetic-based heuristic improves the energy demand prediction accuracy while the intra-day prediction refinements further reduce the day-ahead prediction error. In relation to flexibility, the prediction of both above and below baseline energy flexibility curves provides good results for the mean absolute percentage error (MAPE), which is just above 6%, allowing for safe DC participation in DR programs.

ACS Style

Andreea Valeria Vesa; Tudor Cioara; Ionut Anghel; Claudia Antal; Claudia Pop; Bogdan Iancu; Ioan Salomie; Vasile Teodor Dadarlat. Energy Flexibility Prediction for Data Center Engagement in Demand Response Programs. Sustainability 2020, 12, 1417 .

AMA Style

Andreea Valeria Vesa, Tudor Cioara, Ionut Anghel, Claudia Antal, Claudia Pop, Bogdan Iancu, Ioan Salomie, Vasile Teodor Dadarlat. Energy Flexibility Prediction for Data Center Engagement in Demand Response Programs. Sustainability. 2020; 12 (4):1417.

Chicago/Turabian Style

Andreea Valeria Vesa; Tudor Cioara; Ionut Anghel; Claudia Antal; Claudia Pop; Bogdan Iancu; Ioan Salomie; Vasile Teodor Dadarlat. 2020. "Energy Flexibility Prediction for Data Center Engagement in Demand Response Programs." Sustainability 12, no. 4: 1417.

Journal article
Published: 28 October 2019 in Sensors
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Nowadays, centralized energy grid systems are transitioning towards more decentralized systems driven by the need for efficient local integration of new deployed small scale renewable energy sources. The high limits for accessing the energy markets and also for the delivery of ancillary services act as a barrier for small scale prosumers participation forcing the implementation of new cooperative business models at the local level. This paper is proposing a fog computing infrastructure for the local management of energy systems and the creation of coalitions of prosumers able to provide ancillary services to the grid. It features an edge devices layer for energy monitoring of individual prosumers, a fog layer providing Information and Communication Technologies (ICT) techniques for managing local energy systems by implementing cooperative models, and a cloud layer where the service specific technical requirements are defined. On top, a model has been defined allowing the dynamical construction of coalitions of prosumers as Virtual Power Plants at the fog layer for the provisioning of frequency restoration reserve services while considering both the prosumers' local constraints and the service ones as well as the constituents’ profit maximization. Simulation results show our solution effectiveness in selecting the optimal coalition of prosumers to reliably deliver the service meeting the technical constraints while featuring a low time and computation overhead being feasible to be run closer to the edge.

ACS Style

Claudia Pop; Marcel Antal; Tudor Cioara; Ionut Anghel; Ioan Salomie; Massimo Bertoncini; Pop. A Fog Computing enabled Virtual Power Plant Model for Delivery of Frequency Restoration Reserve Services. Sensors 2019, 19, 4688 .

AMA Style

Claudia Pop, Marcel Antal, Tudor Cioara, Ionut Anghel, Ioan Salomie, Massimo Bertoncini, Pop. A Fog Computing enabled Virtual Power Plant Model for Delivery of Frequency Restoration Reserve Services. Sensors. 2019; 19 (21):4688.

Chicago/Turabian Style

Claudia Pop; Marcel Antal; Tudor Cioara; Ionut Anghel; Ioan Salomie; Massimo Bertoncini; Pop. 2019. "A Fog Computing enabled Virtual Power Plant Model for Delivery of Frequency Restoration Reserve Services." Sensors 19, no. 21: 4688.

Journal article
Published: 10 July 2019 in Sensors
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Nowadays, it has been recognized that blockchain can provide the technological infrastructure for developing decentralized, secure, and reliable smart energy grid management systems. However, an open issue that slows the adoption of blockchain technology in the energy sector is the low scalability and high processing overhead when dealing with the real-time energy data collected by smart energy meters. Thus, in this paper, we propose a scalable second tier solution which combines the blockchain ledger with distributed queuing systems and NoSQL (Not Only SQL database) databases to allow the registration of energy transactions less frequently on the chain without losing the tamper-evident benefits brought by the blockchain technology. At the same time, we propose a technique for tamper-evident registration of smart meters’ energy data and associated energy transactions using digital fingerprinting which allows the energy transaction to be linked hashed-back on-chain, while the sensors data is stored off-chain. A prototype was implemented using Ethereum and smart contracts for the on-chain components while for the off-chain components we used Cassandra database and RabbitMQ messaging broker. The prototype proved to be effective in managing a settlement of energy imbalances use-case and during the evaluation conducted in simulated environment shows promising results in terms of scalability, throughput, and tampering of energy data sampled by smart energy meters.

ACS Style

Claudia Pop; Claudia Antal; Tudor Cioara; Ionut Anghel; David Sera; Ioan Salomie; Giuseppe Raveduto; Denisa Ziu; Vincenzo Croce; Massimo Bertoncini. Blockchain-Based Scalable and Tamper-Evident Solution for Registering Energy Data. Sensors 2019, 19, 3033 .

AMA Style

Claudia Pop, Claudia Antal, Tudor Cioara, Ionut Anghel, David Sera, Ioan Salomie, Giuseppe Raveduto, Denisa Ziu, Vincenzo Croce, Massimo Bertoncini. Blockchain-Based Scalable and Tamper-Evident Solution for Registering Energy Data. Sensors. 2019; 19 (14):3033.

Chicago/Turabian Style

Claudia Pop; Claudia Antal; Tudor Cioara; Ionut Anghel; David Sera; Ioan Salomie; Giuseppe Raveduto; Denisa Ziu; Vincenzo Croce; Massimo Bertoncini. 2019. "Blockchain-Based Scalable and Tamper-Evident Solution for Registering Energy Data." Sensors 19, no. 14: 3033.

Journal article
Published: 01 March 2019 in Energies
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This paper addresses the problem of data centers’ cost efficiency considering the potential of reusing the generated heat in district heating networks. We started by analyzing the requirements and heat reuse potential of a high performance computing data center and then we had defined a heat reuse model which simulates the thermodynamic processes from the server room. This allows estimating by means of Computational Fluid Dynamics simulations the temperature of the hot air recovered by the heat pumps from the server room allowing them to operate more efficiently. To address the time and space complexity at run-time we have defined a Multi-Layer Perceptron neural network infrastructure to predict the hot air temperature distribution in the server room from the training data generated by means of simulations. For testing purposes, we have modeled a virtual server room having a volume of 48 m3 and two typical 42U racks. The results show that using our model the heat distribution in the server room can be predicted with an error less than 1 °C allowing data centers to accurately estimate in advance the amount of waste heat to be reused and the efficiency of heat pump operation.

ACS Style

Claudia Antal; Tudor Cioara; Ionut Anghel; Radoslaw Gorzenski; Radoslaw Januszewski; Ariel Oleksiak; Wojciech Piatek; Claudia Pop; Ioan Salomie; Wojciech Szeliga. Reuse of Data Center Waste Heat in Nearby Neighborhoods: A Neural Networks-Based Prediction Model. Energies 2019, 12, 814 .

AMA Style

Claudia Antal, Tudor Cioara, Ionut Anghel, Radoslaw Gorzenski, Radoslaw Januszewski, Ariel Oleksiak, Wojciech Piatek, Claudia Pop, Ioan Salomie, Wojciech Szeliga. Reuse of Data Center Waste Heat in Nearby Neighborhoods: A Neural Networks-Based Prediction Model. Energies. 2019; 12 (5):814.

Chicago/Turabian Style

Claudia Antal; Tudor Cioara; Ionut Anghel; Radoslaw Gorzenski; Radoslaw Januszewski; Ariel Oleksiak; Wojciech Piatek; Claudia Pop; Ioan Salomie; Wojciech Szeliga. 2019. "Reuse of Data Center Waste Heat in Nearby Neighborhoods: A Neural Networks-Based Prediction Model." Energies 12, no. 5: 814.

Journal article
Published: 18 December 2018 in Simulation Modelling Practice and Theory
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This paper proposes a methodology for modeling and simulation the operation of Complex Systems considering the energy perspective which may feature both discrete and continuous as well as linear and nonlinear sub-systems. The methodology integrates in a unified view, sub-systems with behavioral or phenomenological models, each of them featuring a set of inputs, outputs and control variables with their associated actions. A proactive optimization process is defined in terms of system level flexibility as well as operation self-adaption, and is leveraging on model simulations to calculate over a time window the system outputs for a set of given inputs and actions. We aim to determine the optimal plan of actions over a set of predicted inputs that will minimize the distance between the system outputs and a given target. To prove its effectiveness, we model and simulate the thermal-electrical processes inside a Data Center, aiming to optimize its operation by exploiting the thermal energy flexibility to re-use the otherwise wasted heat in nearby neighborhoods.

ACS Style

Marcel Antal; Claudia Pop; Teodor Petrican; Andreea Valeria Vesa; Tudor Cioara; Ionut Anghel; Ioan Salomie; Ewa Niewiadomska-Szynkiewicz. MoSiCS: Modeling, simulation and optimization of complex systems–A case study on energy efficient datacenters. Simulation Modelling Practice and Theory 2018, 93, 21 -41.

AMA Style

Marcel Antal, Claudia Pop, Teodor Petrican, Andreea Valeria Vesa, Tudor Cioara, Ionut Anghel, Ioan Salomie, Ewa Niewiadomska-Szynkiewicz. MoSiCS: Modeling, simulation and optimization of complex systems–A case study on energy efficient datacenters. Simulation Modelling Practice and Theory. 2018; 93 ():21-41.

Chicago/Turabian Style

Marcel Antal; Claudia Pop; Teodor Petrican; Andreea Valeria Vesa; Tudor Cioara; Ionut Anghel; Ioan Salomie; Ewa Niewiadomska-Szynkiewicz. 2018. "MoSiCS: Modeling, simulation and optimization of complex systems–A case study on energy efficient datacenters." Simulation Modelling Practice and Theory 93, no. : 21-41.

Conference paper
Published: 27 May 2018 in Advances in Intelligent Systems and Computing
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Dementia is an incurable disease that affects a large part of the population of elders and more than 21% of the elders suffering from dementia are exposed to polypharmacy. Moreover, dementia is very correlated with diabetes and high blood pressure. The medication adherence becomes a big challenge that can be approached by analyzing the daily activities of the patients and taking preventive or corrective measures. The weakest link in the pharmacy chain tends to be the patients, especially the patients with cognitive impairments. In this paper we analyze the feasibility of four classification algorithms from the machine learning library of Apache Spark for the prediction of the daily behavior pattern of the patients that suffer from dementia. The algorithms are tested on two datasets from literature that contain data collected from sensors. The best results are obtained when the Random Forest classification algorithm is applied.

ACS Style

Dorin Moldovan; Marcel Antal; Claudia Pop; Adrian Olosutean; Tudor Cioara; Ionut Anghel; Ioan Salomie. Spark-Based Classification Algorithms for Daily Living Activities. Advances in Intelligent Systems and Computing 2018, 69 -78.

AMA Style

Dorin Moldovan, Marcel Antal, Claudia Pop, Adrian Olosutean, Tudor Cioara, Ionut Anghel, Ioan Salomie. Spark-Based Classification Algorithms for Daily Living Activities. Advances in Intelligent Systems and Computing. 2018; ():69-78.

Chicago/Turabian Style

Dorin Moldovan; Marcel Antal; Claudia Pop; Adrian Olosutean; Tudor Cioara; Ionut Anghel; Ioan Salomie. 2018. "Spark-Based Classification Algorithms for Daily Living Activities." Advances in Intelligent Systems and Computing , no. : 69-78.

Journal article
Published: 23 March 2018 in Sustainability
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In this paper, we see the Data Centers (DCs) as producers of waste heat integrated with smart energy infrastructures, heat which can be re-used for nearby neighborhoods. We provide a model of the thermo-electric processes within DCs equipped with heat reuse technology, allowing them to adapt their thermal response profile to meet various levels of hot water demand. On top of the model, we have implemented computational fluid dynamics-based simulations to determine the cooling system operational parameters settings, which allow the heat to build up without endangering the servers’ safety operation as well as the distribution of the workload on the servers to avoid hot spots. This will allow for setting higher temperature set points for short periods of time and using pre-cooling and post-cooling as flexibility mechanisms for DC thermal profile adaptation. To reduce the computational time complexity, we have used neural networks, which are trained using the simulation results. Experiments have been conducted considering a small operational DC featuring a server room of 24 square meters and 60 servers organized in four racks. The results show the DCs’ potential to meet different levels of thermal energy demand by re-using their waste heat in nearby neighborhoods.

ACS Style

Claudia Antal; Tudor Cioara; Ionut Anghel; Claudia Pop; Ioan Salomie. Transforming Data Centers in Active Thermal Energy Players in Nearby Neighborhoods. Sustainability 2018, 10, 939 .

AMA Style

Claudia Antal, Tudor Cioara, Ionut Anghel, Claudia Pop, Ioan Salomie. Transforming Data Centers in Active Thermal Energy Players in Nearby Neighborhoods. Sustainability. 2018; 10 (4):939.

Chicago/Turabian Style

Claudia Antal; Tudor Cioara; Ionut Anghel; Claudia Pop; Ioan Salomie. 2018. "Transforming Data Centers in Active Thermal Energy Players in Nearby Neighborhoods." Sustainability 10, no. 4: 939.

Journal article
Published: 01 March 2018 in Future Generation Computer Systems
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ACS Style

Tudor Cioara; Ionut Anghel; Ioan Salomie; Lina Barakat; Simon Miles; Dianne Reidlinger; Adel Taweel; Ciprian Dobre; Florin Pop. Expert system for nutrition care process of older adults. Future Generation Computer Systems 2018, 80, 368 -383.

AMA Style

Tudor Cioara, Ionut Anghel, Ioan Salomie, Lina Barakat, Simon Miles, Dianne Reidlinger, Adel Taweel, Ciprian Dobre, Florin Pop. Expert system for nutrition care process of older adults. Future Generation Computer Systems. 2018; 80 ():368-383.

Chicago/Turabian Style

Tudor Cioara; Ionut Anghel; Ioan Salomie; Lina Barakat; Simon Miles; Dianne Reidlinger; Adel Taweel; Ciprian Dobre; Florin Pop. 2018. "Expert system for nutrition care process of older adults." Future Generation Computer Systems 80, no. : 368-383.

Communication
Published: 09 January 2018 in Sensors
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In this paper, we investigate the use of decentralized blockchain mechanisms for delivering transparent, secure, reliable, and timely energy flexibility, under the form of adaptation of energy demand profiles of Distributed Energy Prosumers, to all the stakeholders involved in the flexibility markets (Distribution System Operators primarily, retailers, aggregators, etc.). In our approach, a blockchain based distributed ledger stores in a tamper proof manner the energy prosumption information collected from Internet of Things smart metering devices, while self-enforcing smart contracts programmatically define the expected energy flexibility at the level of each prosumer, the associated rewards or penalties, and the rules for balancing the energy demand with the energy production at grid level. Consensus based validation will be used for demand response programs validation and to activate the appropriate financial settlement for the flexibility providers. The approach was validated using a prototype implemented in an Ethereum platform using energy consumption and production traces of several buildings from literature data sets. The results show that our blockchain based distributed demand side management can be used for matching energy demand and production at smart grid level, the demand response signal being followed with high accuracy, while the amount of energy flexibility needed for convergence is reduced.

ACS Style

Claudia Pop; Tudor Cioara; Claudia Antal; Ionut Anghel; Ioan Salomie; Massimo Bertoncini. Blockchain Based Decentralized Management of Demand Response Programs in Smart Energy Grids. Sensors 2018, 18, 162 .

AMA Style

Claudia Pop, Tudor Cioara, Claudia Antal, Ionut Anghel, Ioan Salomie, Massimo Bertoncini. Blockchain Based Decentralized Management of Demand Response Programs in Smart Energy Grids. Sensors. 2018; 18 (2):162.

Chicago/Turabian Style

Claudia Pop; Tudor Cioara; Claudia Antal; Ionut Anghel; Ioan Salomie; Massimo Bertoncini. 2018. "Blockchain Based Decentralized Management of Demand Response Programs in Smart Energy Grids." Sensors 18, no. 2: 162.

Journal article
Published: 01 January 2018 in Future Generation Computer Systems
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Highlights•Scheduling and optimizing Data Centres operation.•Data Centre participation in Smart Demand Response programs.•Data Centre flexible energy resources.•Electronic marketplace for trading energy flexibility and ancillary services. AbstractIn this paper we address the problem of Data Centres (DCs) integration into the Smart Grid scenario by proposing a technique for scheduling and optimizing their operation allowing them to participate in Smart Demand Response programs. The technique is leveraging on DCs available flexible energy resources, on mechanisms for eliciting this latent flexibility and on an innovative electronic marketplace designed for trading energy flexibility and ancillary services. This will enact DCs to shape their energy demand to buy additional energy when prices are low and sell energy surplus when prices are high. At the same time DCs will be able to provide increased energy demand due to a large un-forecasted renewable energy production in their local grid, shed or shift energy demand over time to avoid a coincidental peak load, provide fast ramping power by turning on their backup fossil fuelled generators and injecting the energy surplus in the grid and finally provide reactive power regulation by changing their power factor. Numerical simulations results considering traces of an operational DC indicate the great potential of the proposed technique for supporting DCs participation in Smart Demand Response programs.

ACS Style

Tudor Cioara; Ionut Anghel; Massimo Bertoncini; Ioan Salomie; Diego Arnone; Marzia Mammina; Terpsichori-Helen Velivassaki; Marcel Antal. Optimized flexibility management enacting Data Centres participation in Smart Demand Response programs. Future Generation Computer Systems 2018, 78, 330 -342.

AMA Style

Tudor Cioara, Ionut Anghel, Massimo Bertoncini, Ioan Salomie, Diego Arnone, Marzia Mammina, Terpsichori-Helen Velivassaki, Marcel Antal. Optimized flexibility management enacting Data Centres participation in Smart Demand Response programs. Future Generation Computer Systems. 2018; 78 ():330-342.

Chicago/Turabian Style

Tudor Cioara; Ionut Anghel; Massimo Bertoncini; Ioan Salomie; Diego Arnone; Marzia Mammina; Terpsichori-Helen Velivassaki; Marcel Antal. 2018. "Optimized flexibility management enacting Data Centres participation in Smart Demand Response programs." Future Generation Computer Systems 78, no. : 330-342.

Journal article
Published: 24 May 2017 in Future Generation Computer Systems
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This paper addresses the problem of proactive planning and optimizing the operation of a Systems of Systems (SoS) over a time horizon while considering the characteristics of each constituent system and complex interactions among them. We define a mathematical formalism for modeling complex systems composed of a mesh of sub-systems with linear and non-linear behaviors and abstractions like discrete time, atomic systems and interconnection of atomic system. The proposed modeling approach is simple enough to allow fast computations and simulations, and at the same time complex enough to capture the essential features of the real system thus allowing the mapping of proactive optimization problems to Mixed-Integer Optimal Control Problems. The proactive planning uses hierarchical optimization processes that compute predictions and optimization plans at various time granularities, each finer layer plan adjusting and refining the ones with higher granularity. To show case our approach we model a Data Center which is a well-known case of a large scale complex system aiming to plan and optimize its operation to use as much as possible the locally produced renewable energy and optimize its integration in smart grid advanced context. Simulation based results show a reduction of 5% of the carbon footprint and at the same time an increase in profit of more than 14% due to flexible energy shifting.

ACS Style

Marcel Antal; Claudia Pop; Tudor Cioara; Ionut Anghel; Ioan Salomie; Florin Pop. A System of Systems approach for data centers optimization and integration into smart energy grids. Future Generation Computer Systems 2017, 105, 948 -963.

AMA Style

Marcel Antal, Claudia Pop, Tudor Cioara, Ionut Anghel, Ioan Salomie, Florin Pop. A System of Systems approach for data centers optimization and integration into smart energy grids. Future Generation Computer Systems. 2017; 105 ():948-963.

Chicago/Turabian Style

Marcel Antal; Claudia Pop; Tudor Cioara; Ionut Anghel; Ioan Salomie; Florin Pop. 2017. "A System of Systems approach for data centers optimization and integration into smart energy grids." Future Generation Computer Systems 105, no. : 948-963.

Book chapter
Published: 01 January 2017 in Ambient Assisted Living and Enhanced Living Environments
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This paper proposes an adaptive workspace interface customized to the elders' specific needs to bring their valuable experience to start-ups and small companies, addressing intergenerational knowledge transfer of skills and competencies. The approach is based on monitoring elders' interaction with the workspace to adapt the interface layout and contents to their cognitive conditions by applying the necessary changes for providing increased usability as well as to engage and motivate them in optimal collaboration for a prolonged period of time. Collected data is represented in a semantic manner aiming at inferring information about the cognitive abilities and engagement levels such as potential impairments that decrease the interaction quality, problems with screen focus, screen reading difficulties, problems to manage the keyboard or the items on the screen, etc. A genetic algorithm is used to automatically decide and select the best configuration (both layout and content) for presenting the information to the elders.

ACS Style

Tudor Cioara; Ionut Anghel; Dan Valea; Ioan Salomie; Victor Sanchez Martin; Alejandro García Marchena; Elisa Jimeno; Martijn Vastenburg. Adaptive Workspace Interface for Facilitating the Knowledge Transfer from Retired Elders to Start-up Companies. Ambient Assisted Living and Enhanced Living Environments 2017, 287 -309.

AMA Style

Tudor Cioara, Ionut Anghel, Dan Valea, Ioan Salomie, Victor Sanchez Martin, Alejandro García Marchena, Elisa Jimeno, Martijn Vastenburg. Adaptive Workspace Interface for Facilitating the Knowledge Transfer from Retired Elders to Start-up Companies. Ambient Assisted Living and Enhanced Living Environments. 2017; ():287-309.

Chicago/Turabian Style

Tudor Cioara; Ionut Anghel; Dan Valea; Ioan Salomie; Victor Sanchez Martin; Alejandro García Marchena; Elisa Jimeno; Martijn Vastenburg. 2017. "Adaptive Workspace Interface for Facilitating the Knowledge Transfer from Retired Elders to Start-up Companies." Ambient Assisted Living and Enhanced Living Environments , no. : 287-309.

Book chapter
Published: 01 January 2017 in Ambient Assisted Living and Enhanced Living Environments
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ACS Style

Ghufran Ahmed; Raluca Maria Aileni; Ionut Anghel; Nauman Aslam; Abdullah Balcı; Liviu Breniuc; Ivan Chorbev; Chandreyee Chowdhury; Tudor Cioara; Valeriu David; Antonio Del Campo; Ciprian Dobre; Elisa Felici; Ennio Gambi; Nuno M. Garcia; Alejandro García Marchena; Rossitza I. Goleva; Sérgio Guerreiro; Cristian-Gyozo Haba; Vasos Hadjioannou; Najmul Hassan; Hilal Jan; Elisa Jimeno; Helmut Leopold; Maria Lindén; Javier Malagón Hernández; María Luisa Martín Ruiz; George Mastorakis; Constandinos X. Mavromoustakis; Laura Montanini; Davide Perla; Laura Raffaeli; Muhammad Riaz; Lorena Rossi; Ioan Salomie; Victor Sanchez Martin; Maham Shahid; Azfar Shakeel; Radosveta I. Sokullu; Susanna Spinsante; Rumen Stainov; Vera Stara; Rodica Strungaru; Loizos Toumbas; Vladimir Trajkovik; Saif Ul Islam; Laura Vadillo Moreno; Alberto Carlos Valderrama; Dan Valea; Miguel Ángel Valero Duboy; Martijn Vastenburg; Florian Wamser; Irene Yu-Hua Gu; Yixiao Yun; Thomas Zinner; Abdullah Balci. Contributors. Ambient Assisted Living and Enhanced Living Environments 2017, 1 .

AMA Style

Ghufran Ahmed, Raluca Maria Aileni, Ionut Anghel, Nauman Aslam, Abdullah Balcı, Liviu Breniuc, Ivan Chorbev, Chandreyee Chowdhury, Tudor Cioara, Valeriu David, Antonio Del Campo, Ciprian Dobre, Elisa Felici, Ennio Gambi, Nuno M. Garcia, Alejandro García Marchena, Rossitza I. Goleva, Sérgio Guerreiro, Cristian-Gyozo Haba, Vasos Hadjioannou, Najmul Hassan, Hilal Jan, Elisa Jimeno, Helmut Leopold, Maria Lindén, Javier Malagón Hernández, María Luisa Martín Ruiz, George Mastorakis, Constandinos X. Mavromoustakis, Laura Montanini, Davide Perla, Laura Raffaeli, Muhammad Riaz, Lorena Rossi, Ioan Salomie, Victor Sanchez Martin, Maham Shahid, Azfar Shakeel, Radosveta I. Sokullu, Susanna Spinsante, Rumen Stainov, Vera Stara, Rodica Strungaru, Loizos Toumbas, Vladimir Trajkovik, Saif Ul Islam, Laura Vadillo Moreno, Alberto Carlos Valderrama, Dan Valea, Miguel Ángel Valero Duboy, Martijn Vastenburg, Florian Wamser, Irene Yu-Hua Gu, Yixiao Yun, Thomas Zinner, Abdullah Balci. Contributors. Ambient Assisted Living and Enhanced Living Environments. 2017; ():1.

Chicago/Turabian Style

Ghufran Ahmed; Raluca Maria Aileni; Ionut Anghel; Nauman Aslam; Abdullah Balcı; Liviu Breniuc; Ivan Chorbev; Chandreyee Chowdhury; Tudor Cioara; Valeriu David; Antonio Del Campo; Ciprian Dobre; Elisa Felici; Ennio Gambi; Nuno M. Garcia; Alejandro García Marchena; Rossitza I. Goleva; Sérgio Guerreiro; Cristian-Gyozo Haba; Vasos Hadjioannou; Najmul Hassan; Hilal Jan; Elisa Jimeno; Helmut Leopold; Maria Lindén; Javier Malagón Hernández; María Luisa Martín Ruiz; George Mastorakis; Constandinos X. Mavromoustakis; Laura Montanini; Davide Perla; Laura Raffaeli; Muhammad Riaz; Lorena Rossi; Ioan Salomie; Victor Sanchez Martin; Maham Shahid; Azfar Shakeel; Radosveta I. Sokullu; Susanna Spinsante; Rumen Stainov; Vera Stara; Rodica Strungaru; Loizos Toumbas; Vladimir Trajkovik; Saif Ul Islam; Laura Vadillo Moreno; Alberto Carlos Valderrama; Dan Valea; Miguel Ángel Valero Duboy; Martijn Vastenburg; Florian Wamser; Irene Yu-Hua Gu; Yixiao Yun; Thomas Zinner; Abdullah Balci. 2017. "Contributors." Ambient Assisted Living and Enhanced Living Environments , no. : 1.

Journal article
Published: 01 November 2016 in Computer Standards & Interfaces
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Malnutrition is considered one of the root causes for the occurrence of other diseases. It is particularly common in the ageing population, where it requires more efficient handling and management to enable longer home independent living. However, to achieve this, a number of related challenges need to be overcome, especially those related to management of health and disease let alone other social and logistical barriers. This paper presents the design of a distributed system that enables homecare management in the context of self-feeding and malnutrition prevention through balanced nutritional intake. The design employs a service-based system that incorporates a number of services including monitoring of activities, nutritional reasoning for assessing feeding habits, diet recommendation for food planning, and marketplace invocation for automating food shopping to meet dietary requirements. The solution is deployed in a small pilot in 12 elder adult houses that, in early results, demonstrates its holistic user-centred scalable approach for malnutrition self-management. A Service-based System holistic approach to enable malnutrition selfmanagement, through identification and monitoring.Nutrition-aware services to enable short and long-term reasoning of nutrition to work within an nonintrusive older adults environment.Semantic knowledge driven services approach to achieve reasoning over complex set of diet related QoS factors for (food) service selection

ACS Style

Adel Taweel; Lina Barakat; Simon Miles; Tudor Cioara; Ionut Anghel; Abdel-Rahman H. Tawil; Ioan Salomie. A service-based system for malnutrition prevention and self-management. Computer Standards & Interfaces 2016, 48, 225 -233.

AMA Style

Adel Taweel, Lina Barakat, Simon Miles, Tudor Cioara, Ionut Anghel, Abdel-Rahman H. Tawil, Ioan Salomie. A service-based system for malnutrition prevention and self-management. Computer Standards & Interfaces. 2016; 48 ():225-233.

Chicago/Turabian Style

Adel Taweel; Lina Barakat; Simon Miles; Tudor Cioara; Ionut Anghel; Abdel-Rahman H. Tawil; Ioan Salomie. 2016. "A service-based system for malnutrition prevention and self-management." Computer Standards & Interfaces 48, no. : 225-233.