Research Lines

Research Lines

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Last Updated: Tuesday, 02 March 2021 12:41
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Telecommunications and Networking

2018-2021 Main Work Topics:

  • Unified communications in IoT (R. Sofia, D. Maniglia, H. Valente, L. I. Carvalho, J. Soares, J. Ardions). Aspects concerning protocolar transmission and unified abstraction models, as well as the relevancy of novel communication models (e.g., ICN) for both personal IoT (D. Maniglia) and Industrial IoT. This line of action involves cooperation with external entities.

  • Pervasive Wireless Communications (P. Mendes, H. Orrillo, A. Goodwin). This line of work concerns novel paradigms to orchestrate autonomic computational functions within a distributed networked system. Aspects being worked upon relate with Distributed Networks, Fog Computing and Cognitive Networking; For instance mobile edge computing in regards to optimizing distributed networked systems such as smart camera networks, as well as autonomous drones and cars.

  • Self-organization aspects in distributed sensing devices (S. Tomic, M. Beko). The work being developed concerns mechanisms to assist a system to react locally to the variations within sensing records (OSI Layer 1); hence, accurate determination of the sensor location where the deviations arise is key. By exploring the synergies between computational and physical components (J. Canto), one can form smart environments offering improved safety and efficiency in everyday life, e.g., smart parking; assistance for elderly or people with disabilities; monitoring of storage conditions and goods.

LONG-TERM PURPOSE:

We envision mobile systems to evolve to support a large set of data-centric networking services by including deeper awareness of mobile crowd behavior and context. We intend therefore to contribute to a broader notion of distributed cognitive networking, one that integrates the concept of programmable networks, allowing networked devices to perform customized computation closer to the end-user (user-centric networking). We envision that such generation of cognitive networks will rely on intelligence across all OSI Layers, raising the level of cognitive abilities (known as “Self-X” in the context of network management) via machine learning, e.g., to devise novel solutions related to adaptation and anticipation properties of the network elements across multiple OSI Layers.Since the Internet has evolved to be dominated by content sharing and retrieval, the opportunistic networking concept already under work in COPELABS is going to be exploited to handle data as a network primitive, decoupling data location from identity, security, and access, and allowing data to be shared directly among users.

This line of confluence shall also investigate open issues in the context of unified communication in IoT.

Another aspect of relevance for the success of IoT is its capability of setting up and controlling a communication layer among a set of distributed sensing devices. In such distributed communication systems, cooperation and localization is a crucial factor  since a system may be configured to react locally to the variations within sensing records; hence, accurate determination of the sensor location where the deviations arise is key. By exploring the synergies between computational and physical components one can form smart environments offering improved safety and efficiency in everyday life, e.g., smart parking; assistance for elderly or people with disabilities; monitoring of storage conditions and goods.

            

Computational Systems                              

2016-2019 Main Work Topics:

  • Personal cloud systems (J. Faísca, J. Rogado). Continuing the activity under development since 2012 (J. Faísca, J. Rogado), initially exploring identity management and data protection aspects, this line of work evolved into exploring Distributed Ledger Technology (DLT), commonly referred to as Blockchain, as a way to deal with some of the requirements implied by this sparse connectivity environments.

  • Fault-tolerance in cloud computing (P. Costa). Fault-tolerance is a major issue in the context of cloud computing, and it is expected to increase due to the development of cloudlets. As such, the challenge of building dependable and robust clouds and solutions remain a critical research problem. This topic focuses on analyzing the viability of combining the distributed consensus of Blockchain with MapReduce computation to sustain distributed cloudlet platforms in a way that they are tolerant to arbitrary faults, malicious faults and cloud outages, and still guarantee performance at an acceptable cost. During 2018 this area shall be explored via the development of a prototype that will combine the Blockchain paradigm with MapReduce computation to validate a real use case scenario.

 

 LONG-TERM PURPOSE:

 The computational systems research line intends to continue the focus on exploring decentralization technologies, in the context of next generation networks, i.e., cloudlet based mobile approaches. In addition to mobile storage and caching issues, decentralized solutions require mobile devices to be connected to their peers or to their cloud service providers, usually via cellular technology often with intermittent connectivity, which can be extremely limiting both in terms of cost, latency, as well as in terms of energy consumption. Continuing the activity under development since 2012 initially exploring identity management and data protection aspects, this line of work evolved into exploring Distributed Ledger Technology (DLT), commonly referred to as Blockchain, as a way to deal with some of the requirements implied by this sparse connectivity environments. Blockchain, a concept initially associated to the support of a digital currency (i.e.: Bitcoin), is currently generalized to many areas of activity. Its decentralized mode of operation, the immutable characteristics of its storage and the secure nature of its transactions, fit into several scenarios where the primary challenge relies on a secure and immutable transactional infrastructure connecting entities (humans or machines). These entities can exchange values, services, but also negotiate the controlled disclosure of personal data, such as identity claims or personal sensor information. The promising results obtained in recent academic work, which applied DLT to Semantic Identity Management and leveraged Ethereum smart contracts to negotiate sensor data pave the way for a future sustained line of research activity in the context of these emerging areas.

Information and Data Sciences                                                                                 

2018-2021 Main Work Topics:

  • Network mining (R. Sofia, L. Carvalho, F. Melo Pereira). A relevant aspect to address in the context of a next generation internet concerns data mining and analytics applied locally (e.g. in decentralized systems, or in cloudlets. In this context, eager classification models such as neural networks have been the preferential choice for pattern detection in wireless and mobile environments. Inference of behavior can, however, be simplified (S. Dattagupta and R. Sofia) and some activities can be performed locally, in mobile devices. Firstly, because it allows considering extraction of data in a more secure way, keeping user anonymity. Secondly, this approach reduces the cost associated with data transmission to a cloud. Therefore, the allocation of local computational tasks for the classification of sensed data is of key importance for mobile sensing systems.
  • Supervised and unsupervised modeling. Still in this context we envision contributions in the context of supervised and unsupervised modelling techniques and statistical techniques (F. Costigliola, T. Almada, A. Fonseca, F. Duarte), e.g., for improving feedback (e.g. text analytics in sensing middleware, or a better adaptation of interfaces).

 

LONG-TERM PURPOSE:

A relevant aspect to address in the context of a next generation internet concerns data mining and analytics applied locally (e.g. in decentralized systems, or in cloudlets - rf. to the BEING project, ). In this context, eager classification models such as neural networks have been the preferential choice for pattern detection in wireless and mobile environments. Inference of behavior can, however, be simplified and some activities can be performed locally, in mobile devices. Firstly, because it allows to consider extraction of data in a more secure way, keeping user anonymity. Secondly, this approach reduces the cost associated with data transmission to a cloud. Therefore, the allocation of local computational tasks for the classification of sensed data is of key importance for mobile sensing systems.

Contributions in this area of confluence concern the assumption that contextual and behavior inference as well as predictive analytics shall most likely be residing on the fringes of the internet (cloudlets, mobile devices). Research on almost-reliable protocols, as well as on neural networks to assist linear programming is expected as follow-up of work already under development by several researchers in the unit. Still in this context we envision contributions in the context of supervised and unsupervised modeling techniques and statistical techniques, e.g., for improving feedback (e.g. text analytics in sensing middleware, or a better adaptation of interfaces).

 

 

  

Knowledge and Management Information Systems

2018-2021 Main Work Topics:

  • Entrepreunerial culture (R. Ribeiro ). Contributions derived from this area of confluence concern models for a systematic analysis of ideas and relevancy in the context of business (e.g., to increase the success of pitching ideas to potential investors); alignment of information systems management with the business strategies; technology adoption modeling; models for technology transfer derived from COPELABS activities.

 
 
LONG-TERM PURPOSE:

This area of confluence integrates the know-how of members that teach executive and middle-management courses in the context of LISS (Lusofona Information Systems School, ULHT). This confluence area shall therefore support COPELABS scientific activities in the context of transfer, entrepreneurial culture, IPR strategy as well as in assisting researchers to pursue on their own projects (pet projects) derived from technology created within the research context of COPELABS. Contributions derived from this area of confluence concern models for a systematic analysis of ideas and relevancy in the context of business (e.g., to increase the success of pitching ideas to potential investors); alignment of information systems management with the business strategies; technology adoption modeling; models for technology transfer derived from COPELABS activities.

 

 

 

 

 

 

Highlights

News

06.2023. Mikovic, A. & Vojinovic, M. (2023) State-Sum Models of Piecewise Linear Quantum Gravity, https://doi.org/10.1142/13233

05.2023. Fachada, N., de Andrade, D., Serra, P., Códices, N., Luz, F., Lopes, P., Fonseca, M. & Neves, P. (2023). Improving the CS Curriculum of a Top-Down Videogames BA. In Proc. of the 11th Computer Science Education Research Conference, CSERC '22 (pp. 62-63), Leiden, Netherlands. ACM. https://doi.org/10.1145/3569173.3569183

04.2023. Petukhova, A. & Fachada, N. (2023). MN-DS: A Multilabeled News Dataset for News Article Hierarchical Classification. Data, 8(5), 74. https://doi.org/10.3390/data8050074

04.2023. de Andrade, D. & Fachada, N. (2023). Automated Generation of Map Pieces for Snappable Meshes. In Proceedings of the 18th International Conference on the Foundations of Digital Games, FDG '23  (pp. 2:1-2:10), Lisbon, Portugal. https://doi.org/10.1145/3582437.3582483

03.2023. dos Santos, R.P., Fachada, N., Beko, M. & Leithardt, V.R.Q. (2023). A Rapid Review on the Use of Free and Open Source Technologies and Software Applied to Precision Agriculture Practices. Journal of Sensor and Actuator Networks, 12(3), 28. https://doi.org/10.3390/jsan12020028

01.2023. Ferreira, D. J., Mateus-Coelho, N. & Mamede, H. S. (2023). Methodology for Predictive Cyber Security Risk Assessment (PCSRA). Procedia Computer Science, 219, 1555-1563. https://doi.org/10.1016/j.procs.2023.01.447

11.2022. Ramos, G., Silvestre D., A. & Aguiar, A. P. (2022). A resilient continuous-time consensus method using a switching topology. Systems & Control Letters, 169, 105381. https://doi.org/10.1016/j.sysconle.2022.105381

11.2022. Figueiredo, E., Moldovan, I., Alves, P., Rebelo, H. & Souza, L. (2022). Smartphone Application for Structural Health Monitoring of Bridges. Sensors, 2022, 22(21), 8483. https://doi.org/10.3390/s22218483

10.2022. Lima, B., Fachada, N., Dinis, R., da Costa, D.B. & Beko, M. (2022). uavnoma: a UAV-NOMA network model under non-ideal conditions. Journal of Open Research Software, 10(1), 9. https://doi.org/10.5334/jors.397

09.2022. Saraiva, M., Mateus-Coelho, N. (2022). CyberSoc Framework a Systematic Review of the State-of-Art. Procedia Computer Science, 204, 961-972. https://doi.org/10.1016/j.procs.2022.08.117

07.2022. Fachada, N., e Silva, R.C., de Andrade, D. & Códices, N. (2022). Unity Snappable Meshes. Software Impacts, 13, 100363. https://doi.org/10.1016/j.simpa.2022.100363

06.2022. Petukhova, A. & Fachada, N. (2022). TextCL: a Python package for NLP preprocessing tasks. SoftwareX, 19. 101122. https://doi.org/10.1016/j.softx.2022.101122

06.2022. A. Sharma, V. Sharma, M. Jaiswal, Hwang-Cheng Wang, Dushantha Nalin Jayakody*, C. Basnayaka, A. Muthanna. (2022). "Recent Trends in AI-based Intelligent Sensing", Electronics 2022, 11, 1661. https://doi.org/10.3390/electronics11101661

05.2022. M. F. Ali, Dushantha Nalin K. Jayakody, S. Garg, G. Kaddoum, and M. Shamim Hossain. (2022). "Dual-Hop Mixed FSO-VLC Underwater WirelessCommunication Link, IEEE Transactions on Network and Service Management, June 2022,  https://doi.org/10.1109/TNSM.2022.3181169

05.2022  Petukhova, A. & Fachada, N. (2022). Retail System Scenario Modeling Using Fuzzy Cognitive Maps. Information, 13(5), 251. https://doi.org/10.3390/info13050251

05.2022. Magaia, N., Ferreira, P., Pereira, P. R., Muhammad, K., Del Ser, J., & de Albuquerque, V. H. C. (2022). Group'n Route: An Edge Learning-based Clustering and Efficient Routing Scheme Leveraging Social Strength for the Internet of Vehicles. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/TITS.2022.3171978

04.2022. Fachada, N. (2022). A computational pipeline for modeling and predicting wildfire behavior. In Proceedings of the 7th International Conference on Complexity, Future Information Systems and Risk, COMPLEXIS 2022 (pp. 79-84), Virtual Event. SciTePress/INSTICC. DOI: https://doi.org/10.5220/0011073900003197

04.2022. Hu, Q., Gois, F. N. B., Costa, R., Zhang, L., Yin, L., Magaia, N., & de Albuquerque, V. H. C. (2022). Explainable artificial intelligence-based edge fuzzy images for COVID-19 detection and identification. Applied Soft Computing, 108966. https://doi.org/10.1016/j.asoc.2022.108966

04.2022. Cipriano, B.P., Fachada, N. & Alves, P. (2022). Drop Project: An automatic assessment tool for programming assignments. SoftwareX, 18. 101079. https://doi.org/10.1016/j.softx.2022.101079

04.2022. e Silva, R. C., Fachada, N., de Andrade, D., & Códices, N. (2022). Procedural Generation of 3D Maps with Snappable Meshes. IEEE Access, 10. https://doi.org/10.1109/ACCESS.2022.3168832

02.2022. Fachada, V., Rahkila, P., Fachada, N., Turpeinen, T., Kujala, U. & Kainulainen, H. (2022). Enlarged PLIN5-uncoated lipid droplets in inner regions of skeletal muscle type II fibers associate with type 2 diabetes. Acta Histochemica, 124(3), 100014. https://doi.org/10.1016/j.acthis.2022.151869

01.2022. Accepted paper, S. Tomić, M. Beko (2022). Detecting Distance-spoofing Attacks in Arbitrarily-deployed Wireless Networks, IEEE Transactions on Vehicular Technology, DOI: 10.1109/TVT.2022.3148199

01.2022. Fernandes, P.A., Inácio, P.A., Feliciano, H. & Fachada, N. (2022). SimpAI: Evolutionary Heuristics for the ColorShapeLinks Board Game Competition. Videogame Sciences and Arts, VJ 2020, Revised Selected Papers. CCIS, vol 1531 (pp. 113-126). Springer Nature. https://doi.org/10.1007/978-3-030-95305-8_9

01.2022. Valderi R.Q. Leithardt, et al., 2022. "An Empirical Comparison of Portuguese and Multilingual BERT Models for Auto-Classification of NCM Codes in International Trade" Big Data and Cognitive Computing 6, no. 1: 8. https://doi.org/10.3390/bdcc6010008 - Quartil SJR: Q1

01.2022. Valderi R.Q. Leithardt, et al., 2022. "Towards ubiquitous requirements engineering through recommendations based on context histories." PeerJ Computer Science 8:e794 https://doi.org/10.7717/peerj-cs.794 Quartil SJR: Q2

12.2021. Valderi R.Q. Leithardt, et al., 2021. "Application of Machine Learning Techniques to Predict a Patient’s No-Show in the Healthcare Sector" Future Internet 14, no. 1: 3. https://doi.org/10.3390/fi14010003 Quartil SJR: Q2

12.2021. Accepted paper, M. Beko, S. Tomić, Toward Secure Localization in Randomly Deployed Wireless Networks, IEEE Internet of Things Journal, DOI: 10.1109/JIOT.2021.3078216

11.2021. de Andrade, D. & Fachada, N. (2021). PyXYZ: an educational 3D wireframe engine in Python. In Proceedings of the 26th Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE '21 (pp. 519-525), Virtual Event, Germany. https://doi.org/10.1145/3430665.3456345

11.2021. Daniel Silvestre (2021). Constrained Convex Generators: A Tool Suitable for Set-Based Estimation With Range and Bearing Measurements . In:
IEEE Control Systems Letters 6, pp. 1610 1615. doi: 10.1109/LCSYS.2021.3129729

11.2021. Accepted paper, G. Asaamoning, P Mendes, and N. Magaia. .A Dynamic Clustering Mechanism with Load-Balancing for Flying Ad Hoc Networks, IEEE Access, DOI: 10.1109/ACCESS.2021.3130417

09.2021. Accepted paper, F Neves, AC Finamore, SC Madeira, R Henriques. (2021).Mining Actionable Patterns of Road Mobility From Heterogeneous Traffic Data Using Biclustering, IEEE Transactions on Intelligent Transportation Systems,   https://ieeexplore.ieee.org/iel7/6979/4358928/09357483.pdf

07.2021. Accepted paper: S. Tomic, M. Beko, “A New Perspective on Range and Directional Localization Problem’’, to appear in IEEE Open Journal of Vehicular Technology, https://doi.org/10.1109/OJVT.2021.3094180

06.2021. Fachada, N. (2021). ColorShapeLinks: A Board Game AI Competition Framework for Educators and Students. Computers & Education: Artificial Intelligence, 2. 100014. https://doi.org/10.1016/j.caeai.2021.100014

06.2021. Accepted paper: Rodrigo Cortesão, Daniel Fernandes, Gabriela Soares, Diogo Clemente, Pedro Sebastião and Lúcio S. Ferreira, "Cloud-based Implementation of a SON Radio Resources Planning System for Mobile Networks and Integration in SaaS Metric", to appear in IEEE Access 10.1109/ACCESS.2021.3087398

05.2021. Tiago Simas and Rion Brattig Correia and Luis M. Rocha, "The distance backbone of complex networks", Journal of Complex Networks, Oxford University Press,

https://doi.org/10.1093/comnet/cnab021

03.2021. Accepted paper:  FG Encinas, LA Silva, AS Mendes, GV González, VRQ Leithardt, ..., "Singular Spectrum Analysis for Source Separation in Drone-Based Audio Recording" In IEEE Access.https://doi.org/10.1109/ACCESS.2021.3065775 

02.2021. Accepted Paper, M. S. Stankovic, M. Beko, S. S. Stankovic, “Distributed Value Function Approximation for Collaborative Multi-Agent Reinforcement Learning’’, in IEEE Transactions on Control of Network Systems, https://doi.org/10.1109/TCNS.2021.3061909

11.2020. Accepted Paper, B. Lima, D. Costa, et.al "Adaptive Power Factor Allocation for Cooperative Full-Duplex NOMA Systems With Imperfect SIC and Rate Fairness", in IEEE Transactions on Vehicular technology, https://doi.org/10.1109/TVT.2020.3029791

11.2020. Accepted Paper, IEEE Open Journal of the Communications Society, M. Barahman, L. Correia, L. S. Ferreira, "A QoS-Demand-Aware Computing Resource Management Scheme in Cloud-RAN", in IEEE OJ-COMS. https://doi.org/10.1109/OJCOMS.2020.3034297

10.2020. Accepted Paper, IEEE Access, Daniel Silva, Rute Sofia. "A Discussion on Context-awareness to Better Support the IoT Cloud/Edge Continuum", in IEEE Access. DOI 10.1109/ACCESS.2020.3032388.

09.2020. Accepted paper, Electronics, Sales Mendes, André, Diego M. Jiménez-Bravo, María Navarro-Cáceres, Valderi Reis Quietinho Leithardt, and Gabriel Villarrubia González. "Multi-Agent Approach Using LoRaWAN Devices: An Airport Case Study." Electronics 9, no. 9 (2020): 1430.

https://doi.org/10.3390/electronics9091430

08.2020. Accepted paper, IEEE Access, J. C. S. Anjos and Valderi Leithardt et al., "Data Processing Model to Perform Big Data Analytics in Hybrid Infrastructures," in IEEE Access, doi: 10.1109/ACCESS.2020.3023344.

07.2020. Accepted Paper, IEEE Access, Fernandes,D., Raimundo,A., Cercas,F., Sebastiao,P., Rinis,R., Ferreira,L.S.. "Comparison of Artificial Intelligence and Semi-Empirical Methodologies for Estimation of Coverage in Mobile Networks", in IEEE Access, Vol. 8, July 2020, pp 139803-139812, 10.1109/ACCESS.2020.3013036

04.2020. Accepted Paper, IEEE Access , Fernandes,D., Clemente,D., Soares,G., Sebastiao,P., Cercas,F., Dinis,R, Ferreira,L.S., “Cloud-Based Implementation of an Automatic Coverage Estimation Methodology for Self-Organising Network”, in IEEE Access, Vol 8, Apr. 2020, pp 66456-66474, 10.1109/ACCESS.2020.2986437

01.2020. The most recently hired researcher Nuno Ricardo Garcia had a paper accepted in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). TPAMI is the journal with the highest impact factor in the area of computer science (IF=17.73 for 2018). Congratulations.

11.2019. Accepted Paper, IEEE Transactions on Vehicular Technology,
S. Tomic, M. Beko, “A Geometric Approach for Distributed Multi-hop Target Localization in Cooperative Networks’’, to appear in IEEE Transactions on Vehicular Technology. https://doi.org/10.1109/TVT.2019.2952715

07.2019: Accepted Paper, IEEE Transactions on Antennas and Propagation,
K Turbic, L. Correia, M. Beko. A Channel Model for Polarised Off-Body Communications with Dynamic Users’’, IEEE Transactions on Antennas and Propagation, vol. 67, no. 11, pp. 7001-7013, November 2019. https://doi.org/10.1109/TAP.2019.2925157

06.2019: Accepted Paper, IEEE Access
D. Pedro, S. Tomic, L. Bernardo, M. Beko, P. Pinto, “Algorithms for Estimating the Location of Remote Nodes using Smartphones’’, IEEE Access, vol. 7, pp. 33713-33727, December 2019. https://doi.org/10.1109/ACCESS.2019.2904241

05.2019: Accepted Paper, MDPI Future Internet, Special Issue on Information-centric Networking

R. C. Sofia, Guidelines Towards Information-driven Mobility Management, Future Internet 2019, 11(5), 111; https://doi.org/10.3390/fi11050111

04.2019: Accepted Paper, MDPI Future Internet, Special Issue on Information-centric Networking

R. C. Sofia, P. Mendes, An Overview on Push-Based Communication Models for Information-centric Networking. MDPI Future Internet, 2019, 11(3), 74; https://doi.org/10.3390/fi11030074.

03.2019: Accepted Paper, European Control Conference 2019

Henry, D.; Cieslak, J.; Colmenarejo, P.; Branco, J.; Santos, N.; Serra, P.; Telaard, J.; Strauch, H.; Giordano, A. M.; De Stefano, M.; Ott, C.; Reiner, M.; Jaworski, J.; Papadopoulos, E.; Visentin, G.; Ankersen, F.; Fernandez, J.G.Model-based fault diagnosis and tolerant control: the ESA’s e.Deorbit mission

03.2019: Accepted paper, MDPI Future Internet 2019, Special issue on ICN

Sofia, Rute C.; Mendes, Paulo. An Overview on Push-based Communication Models for Information-Centric Networking

02.2019: New IRTF ICNRG draft

Mendes, Paulo; Sofia, Rute C.; Tsaoussidis, Vassilis; Diamantopoulos, Sotiris; Borrego, Carlos; Borrel, Joan; Sarros, Christos-Alessandros. nformation-centric Routing for Opportunistic Wireless Networks.

01.2019: Accepted paper, Sensors 2019, Special Issue on Wireless Location Tracking

Stankovic, S. S.; Stankovic, Milos; Johansson, Karl H.; Beko, Marko. On Consensus-based Distribution Blind Calibration of Sensor Networks

11.2018: Rute C. Sofia becomes Associate Editor of IEEE Access

11.2018: Accepted paper MDPI Sensors 2018, Special Issue on Wireless Location Tracking

Correia, Sergio; Beko, Marko; Cruz, Luis A. da Silva; Tomic, Slavisa. Elephant Herding Optimization for Energy-Based Localization

11.2018: Accepted paper Sensors 2018, Special Issue on Wireless Location Tracking

Tomic, Slavisa; Beko, Marko. Target Localization via Integrated and Segregated Ranging Based on RSS and TOA Measurements

11.2018: Results of the CEEC/COPELABS/JUNIOR2018: Prof. Dr. Pedro Sá Costa admitted.

10.2018: Rute C. Sofia becomes an IEEE Senior member

10.2018: Invited Talk: Cooperative wireless networking: Research challenges, P. Mendes, @LakesideLabs, University of Klagenfurt, Austria

09.2018: Accepted paper, ACM ICN 2018

P. Mendes, R. Sofia, V. Tsaoussidis, S. Diamantopoulos, J. Soares,Information-centric routing for opportunistic wireless networks. InProc. ACM ICN 2018, Sep. 2018.

09:2018: Accepted paper, IEEE WiMob

G. Asaamoning, P. Mendes, A Study for a Name-based Coordination of Autonomic IoT Functions. inProc. IEEE WiMob/MobiEdge 2018, Sep. 2018.

09.2018:C-BRAINs 2018/2019

C-BRAINS for 2018/2019 are out!

07.2018: Ciencia 2018

People-to-people Communication in Emergency Scenarios, P. Mendes, R. Sofia, M. Tavares, O. Aponte

06.2018: UMOBILE project

POC2 - information-centric communication in opportunistic scenarios, P. Mendes, M. Tavares, O. Aponte, R. Sofia, J. Soares

05.2018

UMOBILE Demo in Italy, Umbria

04.2018 Accepted Book Chapter

 Rute C. Sofia, Liliana I. Carvalho., Francisco de Melo Pereira, Samrat Dattagupta.The Role of Smart Data in Inference of Human Behavior and Interaction. Book chapter. "Smart Data: State-of-the-Art and Perspectives in Computing and Applications".

03.2018 IRTF draft DABBER

Information-centric Routing for Opportunistic Wireless Networks

 

 

 

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