A database for publications published by researchers and students at SimulaMet.
Research area
Publication type
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- Journal articles (124)
- Books (6)
- Edited books (2)
- Proceedings, refereed (135)
- Book chapters (4)
- Talks, keynote (11)
- PhD theses (3)
- Proceedings, non-refereed (15)
- Posters (5)
- Technical reports (12)
- Talks, invited (145)
- Talks, contributed (14)
- Public outreach (48)
- Miscellaneous (11)
Journal articles
Towards a Lightweight Task Scheduling Framework for Cloud and Edge Platform
Internet of Things; Engineering Cyber Physical Human Systems (2023).Status: Accepted
Towards a Lightweight Task Scheduling Framework for Cloud and Edge Platform
Mobile devices are becoming ubiquitous in our daily lives, but they have limited computational capacity. Thanks to the advancement in the network infrastructure, task offloading from resource-constrained devices to the near edge and the cloud becomes possible and advantageous. Complete task offloading is now possible to almost limitless computing resources of public cloud platforms. Generally, the edge computing resources support latency-sensitive applications with limited computing resources, while the cloud supports latency-tolerant applications. This paper proposes one lightweight task-scheduling framework from cloud service provider perspective, for applications using both cloud and edge platforms. Here, the challenge is using edge and cloud resources efficiently when necessary. Such decisions have to be made quickly, with a small management overhead. Our framework aims at solving two research questions. They are: i) How to distribute tasks to the edge resource pools and multi-clouds? ii) How to manage these resource pools effectively with low overheads? To answer these two questions, we examine the performance of our proposed framework based on Reliable Server Pooling (RSerPool). We have shown via simulations that RSerPool, with the correct usage and configuration of pool member selection policies, can accomplish the cloud/edge setup resource selection task with a small overhead.
Afilliation | Communication Systems |
Project(s) | The Center for Resilient Networks and Applications, Simula Metropolitan Center for Digital Engineering, Simula Metropolitan Center for Digital Engineering, NorNet, SMIL: SimulaMet Interoperability Lab |
Publication Type | Journal Article |
Year of Publication | 2023 |
Journal | Internet of Things; Engineering Cyber Physical Human Systems |
Publisher | Elsevier |
Keywords | Cloud computing, Edge Computing, Reliable Server Pooling (RSerPool), Resource Pools, Task Scheduling |
Live Streaming Technology and Online Child Sexual Exploitation and Abuse - A Scoping Review
Trauma, Violence, & Abuse (2023).Status: Accepted
Live Streaming Technology and Online Child Sexual Exploitation and Abuse - A Scoping Review
Livestreaming of child sexual abuse is an established form of online child sexual exploitation
and abuse. However, only a limited body of research has examined this issue. The Covid-19
pandemic has accelerated internet use and user knowledge of livestreaming services
emphasising the importance of understanding this crime. In this scoping review, existing
literature was brought together through an iterative search of eight databases containing peer-
reviewed journal articles, as well as grey literature. Records were eligible for inclusion if the
primary focus was on livestream technology and online child sexual exploitation and abuse,
the child being defined as eighteen years or younger. Fourteen of the 2,218 records were
selected. The data were charted and divided into four categories: victims, offenders,
legislation, and technology. Limited research, differences in terminology, study design, and
population inclusion criteria present a challenge to drawing general conclusions on the
current state of livestreaming of child sexual abuse. The records show that victims are
predominantly female. The average livestream offender was found to be older than the
average online child sexual abuse offender. Therefore, it is unclear whether the findings are
representative of the global population of livestream offenders. Furthermore, there appears to
be a gap in what the records show on platforms and payment services used and current digital
trends. The lack of a legal definition and privacy considerations pose a challenge to
investigation, detection, and prosecution. The available data allow some insights into a
potentially much larger issue.
Afilliation | Communication Systems, Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Journal Article |
Year of Publication | 2023 |
Journal | Trauma, Violence, & Abuse |
Publisher | SAGE Publications |
Finding shortest and nearly shortest path nodes in large substantially incomplete networks by hyperbolic mapping
Nature Communications 14 (2023).Status: Published
Finding shortest and nearly shortest path nodes in large substantially incomplete networks by hyperbolic mapping
<p>Dynamic processes on networks, be it information transfer in the Internet, contagious spreading in a social network, or neural signaling, take place along shortest or nearly shortest paths. Computing shortest paths is a straightforward task when the network of interest is fully known, and there are a plethora of computational algorithms for this purpose. Unfortunately, our maps of most large networks are substantially incomplete due to either the highly dynamic nature of networks, or high cost of network measurements, or both, rendering traditional path finding methods inefficient. We find that shortest paths in large real networks, such as the network of protein-protein interactions and the Internet at the autonomous system level, are not random but are organized according to latent-geometric rules. If nodes of these networks are mapped to points in latent hyperbolic spaces, shortest paths in them align along geodesic curves connecting endpoint nodes. We find that this alignment is sufficiently strong to allow for the identification of shortest path nodes even in the case of substantially incomplete networks, where numbers of missing links exceed those of observable links. We demonstrate the utility of latent-geometric path finding in problems of cellular pathway reconstruction and communication security.</p>
Afilliation | Communication Systems |
Project(s) | The Center for Resilient Networks and Applications |
Publication Type | Journal Article |
Year of Publication | 2023 |
Journal | Nature Communications |
Volume | 14 |
Number | 186 |
Publisher | Nature |
Books
Simula SpringerBriefs on ComputingSmittestopp − A Case Study on Digital Contact Tracing
Vol. 11. Simula Springer Briefs: Springer International Publishing, 2022.Status: Published
Simula SpringerBriefs on ComputingSmittestopp − A Case Study on Digital Contact Tracing
Afilliation | Communication Systems |
Project(s) | The Center for Resilient Networks and Applications |
Publication Type | Book |
Year of Publication | 2022 |
Volume | 11 |
Publisher | Springer International Publishing |
Place Published | Simula Springer Briefs |
ISBN | 2512-1677 |
ISBN Number | 978-3-031-05465-5 |
URL | https://link.springer.com/10.1007/978-3-031-05466-2https://link.springer... |
DOI | 10.1007/978-3-031-05466-2 |
Book chapters
5G-sikkerhet: Norge mellom stormaktene
In Digitalisering og internasjonal politikk. Universitetsforlaget, 2022.Status: Published
5G-sikkerhet: Norge mellom stormaktene
Afilliation | Communication Systems |
Project(s) | The Center for Resilient Networks and Applications, GAIA |
Publication Type | Book Chapter |
Year of Publication | 2022 |
Book Title | Digitalisering og internasjonal politikk |
Chapter | 7 |
Date Published | 01/2022 |
Publisher | Universitetsforlaget |
ISBN Number | 9788215052557 |
Edited books
Smittestopp − A Case Study on Digital Contact Tracing
Vol. 11. Simula SpringerBriefs: SpringerNature, 2022.Status: Published
Smittestopp − A Case Study on Digital Contact Tracing
Afilliation | Communication Systems |
Project(s) | The Center for Resilient Networks and Applications |
Publication Type | Edited books |
Year of Publication | 2022 |
Volume | 11 |
Number of pages in book | 141 |
Date Published | 06/2022 |
Publisher | SpringerNature |
Place Published | Simula SpringerBriefs |
ISBN Number | 978-3-031-05466-2 |
URL | https://link.springer.com/book/10.1007/978-3-031-05466-2#bibliographic-i... |
DOI | 10.1007/978-3-031-05466-2 |
Journal articles
Secure Embedded Living: Towards a Self-contained User Data Preserving Framework
IEEE Communications Magazine 60, no. 11 (2022): 74-80.Status: Published
Secure Embedded Living: Towards a Self-contained User Data Preserving Framework
Smart living represents the hardware-software co-inhabiting with humans for better living standards and improved well-being. Here, hardware monitors human activities (by collecting data) specific to a context. Such data can be processed to offer context-specific valuable insights. Such insights can be used for optimising the well-being, living experience and energy cost of smart homes. This paper proposes a Secure Embedded Living Framework (SELF) that enforces a privacy-preserving data control mechanism by integrating multiple technologies, such as Internet-of-thing, cloud/fog platform, machine learning and blockchain. The primary aim of the SELF is to allow the user to retain more control of its data.
Afilliation | Communication Systems |
Project(s) | Simula Metropolitan Center for Digital Engineering, Simula Metropolitan Center for Digital Engineering, NorNet, SMIL: SimulaMet Interoperability Lab, GAIA, The Center for Resilient Networks and Applications |
Publication Type | Journal Article |
Year of Publication | 2022 |
Journal | IEEE Communications Magazine |
Volume | 60 |
Issue | 11 |
Pagination | 74–80 |
Date Published | 11/2022 |
Publisher | IEEE |
ISSN | 0163-6804 |
Keywords | blockchain, Cloud, Data, IoTs, Security, User |
DOI | 10.1109/MCOM.001.2200165 |
AI Anomaly Detection for Cloudified Mobile Core Architectures
Transactions on Network and Service Management (2022).Status: Published
AI Anomaly Detection for Cloudified Mobile Core Architectures
IT systems monitoring is a crucial process for managing and orchestrating network resources, allowing network providers to rapidly detect and react to most impediment causing network degradation. However, the high growth in size and complexity of current operational networks (2022) demands new solutions to process huge amounts of data (including alarms) reliably and swiftly. Further, as the network becomes progressively more virtualized, the hosting of nfv on cloud environments adds a magnitude of possible bottlenecks outside the control of the service owners. In this paper, we propose two deep learning anomaly detection solutions that leverage service exposure and apply it to automate the detection of service degradation and root cause discovery in a cloudified mobile network that is orchestrated by ETSI OSM. A testbed is built to validate these AI models. The testbed collects monitoring data from the OSM monitoring module, which is then exposed to the external AI anomaly detection modules, tuned to identify the anomalies and the network services causing them. The deep learning solutions are tested using various artificially induced bottlenecks. The AI solutions are shown to correctly detect anomalies and identify the network components involved in the bottlenecks, with certain limitations in a particular type of bottlenecks. A discussion of the right monitoring tools to identify concrete bottlenecks is provided.
Afilliation | Communication Systems |
Project(s) | 5G-VINNI: 5G Verticals INNovation Infrastructure , The Center for Resilient Networks and Applications, Simula Metropolitan Center for Digital Engineering, Simula Metropolitan Center for Digital Engineering, NorNet, SMIL: SimulaMet Interoperability Lab |
Publication Type | Journal Article |
Year of Publication | 2022 |
Journal | Transactions on Network and Service Management |
Date Published | 08/2022 |
Publisher | IEEE |
Place Published | Los Alamitos, California/U.S.A. |
ISSN | 1932-4537 |
Keywords | 5G, AI, Anomaly detection, Autoencoders, deep learning, Mobile networks, Smart Networks |
DOI | 10.1109/TNSM.2022.3203246 |
Modeling Variation in Mobile Download Speed in Presence of Missing Samples
IEEE Transactions on Mobile Computing (2022): 1-16.Status: Published
Modeling Variation in Mobile Download Speed in Presence of Missing Samples
Afilliation | Communication Systems, Machine Learning |
Project(s) | Department of Data Science and Knowledge Discovery |
Publication Type | Journal Article |
Year of Publication | 2022 |
Journal | IEEE Transactions on Mobile Computing |
Pagination | 1 - 16 |
Publisher | IEEE |
ISSN | 1536-1233 |
URL | https://ieeexplore.ieee.org/document/9999262/http://xplorestaging.ieee.o... |
DOI | 10.1109/TMC.2022.3231928 |
Sectors, Beams and Environmental Impact on the Performance of Commercial 5G mmWave Cells: An Empirical Study
IEEE Access 10 (2022): 133309-133323.Status: Published
Sectors, Beams and Environmental Impact on the Performance of Commercial 5G mmWave Cells: An Empirical Study
millimeter wave (mmWave) communication is one of the cornerstones of future generations of mobile networks. While the performance of mmWave links has been thoroughly investigated by simulations and testbeds, the behavior of this technology in real-world commercial setups has not yet been thoroughly documented. In this paper, we address this gap and present the results of an empirical study to determine the actual performance of a commercial 5G mmWave cell through on-field measurements. We evaluate the signal and beam coverage map of an operational network as well as the end-to-end communication performance of a 5G mmWave connection, considering various scenarios, including human body blockage effects, foliage-caused and rain-induced attenuation, and water surface effects. To the best of our knowledge, this paper is the first to report on a commercial deployment while not treating the radio as a black box. Measurement results are compared with 3GPP’s statistical channel models for mmWave to check the possible gaps between simulated and actual performance. This measurement analysis provides valuable information for researchers and 5G verticals to fully understand how a 5G mmWave commercial access network operates in the real-world.
Afilliation | Communication Systems |
Project(s) | The Center for Resilient Networks and Applications |
Publication Type | Journal Article |
Year of Publication | 2022 |
Journal | IEEE Access |
Volume | 10 |
Pagination | 133309-133323 |
Date Published | 12/2022 |
Publisher | IEEE |
ISSN | 2169-3536 |
Keywords | 5G, commercial 5G networks, coverage analysis, millimeter-wave, mmWave |
URL | https://ieeexplore.ieee.org/document/9987496 |
DOI | 10.1109/ACCESS.2022.3229588 |