Periodic Reporting for period 1 - COMPRESS NETS (Compressed Sensing Techniques for Wireless Sensor Networks)
Reporting period: 2019-01-01 to 2020-12-31
"The Marie Skłodowska-Curie action (MSCA), entitled ""Compressed Sensing Techniques for Wireless Sensor Networks (COMPRESS NETS),"" addresses the problem of wireless sensing in future time-critical Internet of things (IoT) applications. The IoT concept aims at integrating the wireless node's sensing, computing, and communication capabilities, promising unprecedented opportunities to both industry and society. The advancement of smart devices with such capabilities makes it possible for our cities, transportation systems, factories and living environments to become more intelligent, sustainable, safe and secure. The IoT technology is also expected to revolutionize many industrial sectors, including utilities, automotive, transport, logistics, agriculture, manufacturing, healthcare, warehousing, mining and energy as well as to fundamentally change the way humans interact with other humans and/or machines.
The scientific goal of COMPRESS NETS project is to understand the fundamental design principles and investigate the ultimate capabilities of compressed sensing techniques in wireless sensor networks. To this end, we envision an optimization-based methodology which integrates compressed sensing and wireless data transport into a unified optimization framework which will serve as the mathematical basis for a systematic design and, ultimately, will reveal the performance limits. This work will provide: 1) mathematical characterizations of the optimal tradeoffs between different fundamental performance criteria, and 2) practical algorithms and hierarchically structured network protocols (i.e. key enablers for Internet of Things applications) able of handling large amount of data with lower energy and bandwidth consumption than in existing systems.
From the experienced researcher’s career development perspective, a major goal of the proposed project is to strengthen the researcher’s interdisciplinary competence and research-leadership skills for pursuing the next level of career: becoming an internationally recognized, top-tier research leader in ICT."
The scientific goal of COMPRESS NETS project is to understand the fundamental design principles and investigate the ultimate capabilities of compressed sensing techniques in wireless sensor networks. To this end, we envision an optimization-based methodology which integrates compressed sensing and wireless data transport into a unified optimization framework which will serve as the mathematical basis for a systematic design and, ultimately, will reveal the performance limits. This work will provide: 1) mathematical characterizations of the optimal tradeoffs between different fundamental performance criteria, and 2) practical algorithms and hierarchically structured network protocols (i.e. key enablers for Internet of Things applications) able of handling large amount of data with lower energy and bandwidth consumption than in existing systems.
From the experienced researcher’s career development perspective, a major goal of the proposed project is to strengthen the researcher’s interdisciplinary competence and research-leadership skills for pursuing the next level of career: becoming an internationally recognized, top-tier research leader in ICT."
The project is organized in three work-packages (WPs) as follows:
- WP1, entitled “Mathematical models, performance limits and tradeoffs” focuses on deriving mathematically tractable stochastic models for the wireless sensor networks and utilizing these models to characterize mathematically the fundamental performance limits and optimal tradeoffs,
- WP2, entitled “Algorithms and network protocols” focuses on deriving concrete signal reconstruction algorithms and network protocols for practical implementation, and
- WP3 focuses on researcher training and career development.
All tasks have been fully implemented and the project fully achieved its objectives and milestones. The research was carried out accordingly to the plan described in the MSCA application. The methodology included mathematical modeling and analysis, Monte Carlo computer simulations, and algorithm and architecture design. Queuing theory was used for mathematical modeling and performance analysis of time-critical wireless sensor networks. Stochastic optimization and machine learning techniques were used for deriving optimal dynamic control actions for the WSNs. Convex optimization methods were used for algorithms derivation. Most activity was based on the theoretical tools and concepts described above as they enabled appropriate abstraction of the WSN model to gain general and insightful answers to the considered research questions in Fellow's MSCA application. Validation of the derived theoretical results and performance evaluation of the devised methods and algorithms was performed via Monte Carlo computer simulations.
The scientific results of the MSCA are reported in 8 (eight) journal papers, one monograph and 14 (fourteen) international conference papers, which far exceeds the initial expectation stated in the Fellow's MSCA application (i.e. 4 journal papers and 6 conference papers). All publications were made available in open access repositories as well as on the project’s public website and all of them include acknowledgement to the EU funding.
For dissemination we selected the world-top scientific journals, book publishers, and conferences in the ICT field, including top-ranked IEEE journals (IEEE Transactions on Communications, IEEE Wireless Communications Letters, IEEE Open Journal of the Communications Society, IEEE Communications Letters), IET Image Processing, and Now Publishers' Foundations and Trends in Signal Processing.
To further increase the visibility, the project results were also presented in top-class ICT conferences, including IEEE International Symposium on Information Theory, IEEE INFOCOM, International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wire-less Networks, IEEE Information Theory Workshop, IEEE Wireless Communications and Networking Conference, Data Compression Conference, International Symposium on Wireless Communication Systems, 6G Wireless Summit, IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, and Asilomar Conference on Signals, Systems, and Computers.
The Fellow had meetings with the local industry to advertise project’s results and discuss possible collaboration and transfer of results to industry. Fellow also visited foreign universities, hosted visiting researchers, and organized seminars with foreign guest to establish academic collaboration and pursue joint research. Fellow organized special session on Compressed Sensing at the Nordic Workshop on System and Network Optimization for Wireless (SNOW 2019). Fellow also addressed to the undergraduate students to promote the projects results and benefits of MSCA.
The researcher training activities (WP3) included attending (and passing) two pedagogic courses required for the Linköping University (LiU) tenure track progression. The Fellow has also been involved in the following joint activities targeting “acquiring knowledge and skills by experience”: 1) writing two national research proposals, 2) involvement in preparation of two Horizon 2020 FET proposal applications, 3) joint advising of PhD students and a postdoctoral researcher, and 4) management training through the participation in the scientific administration of research projects at LiU.
- WP1, entitled “Mathematical models, performance limits and tradeoffs” focuses on deriving mathematically tractable stochastic models for the wireless sensor networks and utilizing these models to characterize mathematically the fundamental performance limits and optimal tradeoffs,
- WP2, entitled “Algorithms and network protocols” focuses on deriving concrete signal reconstruction algorithms and network protocols for practical implementation, and
- WP3 focuses on researcher training and career development.
All tasks have been fully implemented and the project fully achieved its objectives and milestones. The research was carried out accordingly to the plan described in the MSCA application. The methodology included mathematical modeling and analysis, Monte Carlo computer simulations, and algorithm and architecture design. Queuing theory was used for mathematical modeling and performance analysis of time-critical wireless sensor networks. Stochastic optimization and machine learning techniques were used for deriving optimal dynamic control actions for the WSNs. Convex optimization methods were used for algorithms derivation. Most activity was based on the theoretical tools and concepts described above as they enabled appropriate abstraction of the WSN model to gain general and insightful answers to the considered research questions in Fellow's MSCA application. Validation of the derived theoretical results and performance evaluation of the devised methods and algorithms was performed via Monte Carlo computer simulations.
The scientific results of the MSCA are reported in 8 (eight) journal papers, one monograph and 14 (fourteen) international conference papers, which far exceeds the initial expectation stated in the Fellow's MSCA application (i.e. 4 journal papers and 6 conference papers). All publications were made available in open access repositories as well as on the project’s public website and all of them include acknowledgement to the EU funding.
For dissemination we selected the world-top scientific journals, book publishers, and conferences in the ICT field, including top-ranked IEEE journals (IEEE Transactions on Communications, IEEE Wireless Communications Letters, IEEE Open Journal of the Communications Society, IEEE Communications Letters), IET Image Processing, and Now Publishers' Foundations and Trends in Signal Processing.
To further increase the visibility, the project results were also presented in top-class ICT conferences, including IEEE International Symposium on Information Theory, IEEE INFOCOM, International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wire-less Networks, IEEE Information Theory Workshop, IEEE Wireless Communications and Networking Conference, Data Compression Conference, International Symposium on Wireless Communication Systems, 6G Wireless Summit, IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, and Asilomar Conference on Signals, Systems, and Computers.
The Fellow had meetings with the local industry to advertise project’s results and discuss possible collaboration and transfer of results to industry. Fellow also visited foreign universities, hosted visiting researchers, and organized seminars with foreign guest to establish academic collaboration and pursue joint research. Fellow organized special session on Compressed Sensing at the Nordic Workshop on System and Network Optimization for Wireless (SNOW 2019). Fellow also addressed to the undergraduate students to promote the projects results and benefits of MSCA.
The researcher training activities (WP3) included attending (and passing) two pedagogic courses required for the Linköping University (LiU) tenure track progression. The Fellow has also been involved in the following joint activities targeting “acquiring knowledge and skills by experience”: 1) writing two national research proposals, 2) involvement in preparation of two Horizon 2020 FET proposal applications, 3) joint advising of PhD students and a postdoctoral researcher, and 4) management training through the participation in the scientific administration of research projects at LiU.
Impacts anticipated from the MSCA are increased and improved theoretical basis for efficient and automated sensing over wireless connectivity. This will allow inventing and designing new time critical IoT applications and services with profound implications for future smart and sustainable industry and society.
From the Fellow’s career perspective, the MSCA helped him to quickly acquire a unique combination of complementary competences including a solid understanding of advanced queuing theory methods and machine learning techniques. This allowed the Fellow to make important scientific contributions, publish them in the most prestigious academic journals, and establish academic collaboration with world-leading research groups. Thus, the Fellow increased his visibility and become internationally recognized as a top contributor to the areas of sparse signal processing and information aging. The newly acquired skills created a high potential for real research breakthroughs (rather than common incremental steps) and, therefore, they will also continue to have a strong positive impact on the Fellow's career after the MSCA action ends.
From the Fellow’s career perspective, the MSCA helped him to quickly acquire a unique combination of complementary competences including a solid understanding of advanced queuing theory methods and machine learning techniques. This allowed the Fellow to make important scientific contributions, publish them in the most prestigious academic journals, and establish academic collaboration with world-leading research groups. Thus, the Fellow increased his visibility and become internationally recognized as a top contributor to the areas of sparse signal processing and information aging. The newly acquired skills created a high potential for real research breakthroughs (rather than common incremental steps) and, therefore, they will also continue to have a strong positive impact on the Fellow's career after the MSCA action ends.