Evaluating virtualization for fog monitoring of real-time applications in mixed-criticality systems

Technological advances in embedded systems and the advent of fog computing led to improved quality of service of applications of cyber-physical systems. In fact, the deployment of such applications on powerful and heterogeneous embedded systems, such as multiprocessors system-on-chips (MPSoCs), allo...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Real-time systems 2023-12, Vol.59 (4), p.534-567
Hauptverfasser: Cinque, Marcello, De Simone, Luigi, Mazzocca, Nicola, Ottaviano, Daniele, Vitale, Francesco
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 567
container_issue 4
container_start_page 534
container_title Real-time systems
container_volume 59
creator Cinque, Marcello
De Simone, Luigi
Mazzocca, Nicola
Ottaviano, Daniele
Vitale, Francesco
description Technological advances in embedded systems and the advent of fog computing led to improved quality of service of applications of cyber-physical systems. In fact, the deployment of such applications on powerful and heterogeneous embedded systems, such as multiprocessors system-on-chips (MPSoCs), allows them to meet latency requirements and real-time operation. Highly relevant to the industry and our reference case-study, the challenging field of nuclear fusion deploys the aforementioned applications, involving high-frequency control with hard real-time and safety constraints. The use of fog computing and MPSoCs is promising to achieve safety, low latency, and timeliness of such control. Indeed, on one hand, applications designed according to fog computing distribute computation across hierarchically organized and geographically distributed edge devices, enabling timely anomaly detection during high-frequency sampling of time series, and, on the other hand, MPSoCs allow leveraging fog computing and integrating monitoring by deploying tasks on a flexible platform suited for mixed-criticality software, leading to so-called mixed criticality systems (MCSs). However, the integration of such software on the same MPSoC opens challenges related to predictability and reliability guarantees, as tasks interfering with each other when accessing the same shared MPSoC resources may introduce non-deterministic latency, possibly leading to failures on account of deadline overruns. Addressing the design, deployment, and evaluation of MCSs on MPSoCs, we propose a model-based system development process that facilitates the integration of real-time and monitoring software on the same platform by means of a formal notation for modeling the design and deployment of MPSoCs. The proposed notation allows developers to leverage embedded hypervisors for monitoring real-time applications and guaranteeing predictability by isolation of hardware resources. Providing evidence of the feasibility of our system development process and evaluating the industry-relevant class of nuclear fusion applications, we experiment with a safety-critical case-study in the context of the ITER nuclear fusion reactor. Our experimentation involves the design and evaluation of several prototypes deployed as MCSs on a virtualized MPSoC, showing that deployment choices linked to the monitor placement and virtualization configurations (e.g., resource allocation, partitioning, and scheduling policies) can signifi
doi_str_mv 10.1007/s11241-023-09410-4
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2899514614</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2899514614</sourcerecordid><originalsourceid>FETCH-LOGICAL-c363t-46adbefe99faa0822f056d7a85694fa34963d72b83b676103d9c59ee6331ce123</originalsourceid><addsrcrecordid>eNp9kE1LxDAQhoMouK7-AU8Bz9F8NW2OsqwfsOBFzyGbJkuWtqlJurj-etut4M3DMMzwvDPwAHBL8D3BuHxIhFBOEKYMYckJRvwMLEhRMkRYxc7BAktKkeCcXYKrlPYY44KUcgHM-qCbQWff7eDBxzzoxn-PY-igC3GsHWxD53OIExEcjFY3KPvWQt33jTcnNkHfwdZ_2RqZ6PO4bXw-wnRM2bbpGlw43SR789uX4ONp_b56QZu359fV4wYZJlhGXOh6a52V0mmNK0odLkRd6qoQkjvNuBSsLum2YltRCoJZLU0hrRWMEWMJZUtwN9_tY_gcbMpqH4bYjS8VraQsCBeEjxSdKRNDStE61Uff6nhUBKtJppplqlGmOslUU4jNodRPImz8O_1P6gfOLHkS</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2899514614</pqid></control><display><type>article</type><title>Evaluating virtualization for fog monitoring of real-time applications in mixed-criticality systems</title><source>Springer Nature - Complete Springer Journals</source><creator>Cinque, Marcello ; De Simone, Luigi ; Mazzocca, Nicola ; Ottaviano, Daniele ; Vitale, Francesco</creator><creatorcontrib>Cinque, Marcello ; De Simone, Luigi ; Mazzocca, Nicola ; Ottaviano, Daniele ; Vitale, Francesco</creatorcontrib><description>Technological advances in embedded systems and the advent of fog computing led to improved quality of service of applications of cyber-physical systems. In fact, the deployment of such applications on powerful and heterogeneous embedded systems, such as multiprocessors system-on-chips (MPSoCs), allows them to meet latency requirements and real-time operation. Highly relevant to the industry and our reference case-study, the challenging field of nuclear fusion deploys the aforementioned applications, involving high-frequency control with hard real-time and safety constraints. The use of fog computing and MPSoCs is promising to achieve safety, low latency, and timeliness of such control. Indeed, on one hand, applications designed according to fog computing distribute computation across hierarchically organized and geographically distributed edge devices, enabling timely anomaly detection during high-frequency sampling of time series, and, on the other hand, MPSoCs allow leveraging fog computing and integrating monitoring by deploying tasks on a flexible platform suited for mixed-criticality software, leading to so-called mixed criticality systems (MCSs). However, the integration of such software on the same MPSoC opens challenges related to predictability and reliability guarantees, as tasks interfering with each other when accessing the same shared MPSoC resources may introduce non-deterministic latency, possibly leading to failures on account of deadline overruns. Addressing the design, deployment, and evaluation of MCSs on MPSoCs, we propose a model-based system development process that facilitates the integration of real-time and monitoring software on the same platform by means of a formal notation for modeling the design and deployment of MPSoCs. The proposed notation allows developers to leverage embedded hypervisors for monitoring real-time applications and guaranteeing predictability by isolation of hardware resources. Providing evidence of the feasibility of our system development process and evaluating the industry-relevant class of nuclear fusion applications, we experiment with a safety-critical case-study in the context of the ITER nuclear fusion reactor. Our experimentation involves the design and evaluation of several prototypes deployed as MCSs on a virtualized MPSoC, showing that deployment choices linked to the monitor placement and virtualization configurations (e.g., resource allocation, partitioning, and scheduling policies) can significantly impact the predictability of MCSs in terms of Worst-Case Execution Times and other related metrics.</description><identifier>ISSN: 0922-6443</identifier><identifier>EISSN: 1573-1383</identifier><identifier>DOI: 10.1007/s11241-023-09410-4</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Anomalies ; Chips (electronics) ; Communications Engineering ; Computer Science ; Computer Systems Organization and Communication Networks ; Control ; Cyber-physical systems ; Design analysis ; Edge computing ; Embedded systems ; Frequency control ; Fusion ; Fusion reactors ; Geographical distribution ; Mechatronics ; Model-based systems ; Monitoring ; Multiprocessing ; Networks ; Nuclear fusion ; Nuclear power plants ; Nuclear safety ; Performance and Reliability ; Real time operation ; Resource allocation ; Resource scheduling ; Robotics ; Safety critical ; Software ; Special Purpose and Application-Based Systems ; System on chip ; Systems development</subject><ispartof>Real-time systems, 2023-12, Vol.59 (4), p.534-567</ispartof><rights>The Author(s) 2023</rights><rights>The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c363t-46adbefe99faa0822f056d7a85694fa34963d72b83b676103d9c59ee6331ce123</citedby><cites>FETCH-LOGICAL-c363t-46adbefe99faa0822f056d7a85694fa34963d72b83b676103d9c59ee6331ce123</cites><orcidid>0000-0003-2325-0056</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11241-023-09410-4$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11241-023-09410-4$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,27915,27916,41479,42548,51310</link.rule.ids></links><search><creatorcontrib>Cinque, Marcello</creatorcontrib><creatorcontrib>De Simone, Luigi</creatorcontrib><creatorcontrib>Mazzocca, Nicola</creatorcontrib><creatorcontrib>Ottaviano, Daniele</creatorcontrib><creatorcontrib>Vitale, Francesco</creatorcontrib><title>Evaluating virtualization for fog monitoring of real-time applications in mixed-criticality systems</title><title>Real-time systems</title><addtitle>Real-Time Syst</addtitle><description>Technological advances in embedded systems and the advent of fog computing led to improved quality of service of applications of cyber-physical systems. In fact, the deployment of such applications on powerful and heterogeneous embedded systems, such as multiprocessors system-on-chips (MPSoCs), allows them to meet latency requirements and real-time operation. Highly relevant to the industry and our reference case-study, the challenging field of nuclear fusion deploys the aforementioned applications, involving high-frequency control with hard real-time and safety constraints. The use of fog computing and MPSoCs is promising to achieve safety, low latency, and timeliness of such control. Indeed, on one hand, applications designed according to fog computing distribute computation across hierarchically organized and geographically distributed edge devices, enabling timely anomaly detection during high-frequency sampling of time series, and, on the other hand, MPSoCs allow leveraging fog computing and integrating monitoring by deploying tasks on a flexible platform suited for mixed-criticality software, leading to so-called mixed criticality systems (MCSs). However, the integration of such software on the same MPSoC opens challenges related to predictability and reliability guarantees, as tasks interfering with each other when accessing the same shared MPSoC resources may introduce non-deterministic latency, possibly leading to failures on account of deadline overruns. Addressing the design, deployment, and evaluation of MCSs on MPSoCs, we propose a model-based system development process that facilitates the integration of real-time and monitoring software on the same platform by means of a formal notation for modeling the design and deployment of MPSoCs. The proposed notation allows developers to leverage embedded hypervisors for monitoring real-time applications and guaranteeing predictability by isolation of hardware resources. Providing evidence of the feasibility of our system development process and evaluating the industry-relevant class of nuclear fusion applications, we experiment with a safety-critical case-study in the context of the ITER nuclear fusion reactor. Our experimentation involves the design and evaluation of several prototypes deployed as MCSs on a virtualized MPSoC, showing that deployment choices linked to the monitor placement and virtualization configurations (e.g., resource allocation, partitioning, and scheduling policies) can significantly impact the predictability of MCSs in terms of Worst-Case Execution Times and other related metrics.</description><subject>Anomalies</subject><subject>Chips (electronics)</subject><subject>Communications Engineering</subject><subject>Computer Science</subject><subject>Computer Systems Organization and Communication Networks</subject><subject>Control</subject><subject>Cyber-physical systems</subject><subject>Design analysis</subject><subject>Edge computing</subject><subject>Embedded systems</subject><subject>Frequency control</subject><subject>Fusion</subject><subject>Fusion reactors</subject><subject>Geographical distribution</subject><subject>Mechatronics</subject><subject>Model-based systems</subject><subject>Monitoring</subject><subject>Multiprocessing</subject><subject>Networks</subject><subject>Nuclear fusion</subject><subject>Nuclear power plants</subject><subject>Nuclear safety</subject><subject>Performance and Reliability</subject><subject>Real time operation</subject><subject>Resource allocation</subject><subject>Resource scheduling</subject><subject>Robotics</subject><subject>Safety critical</subject><subject>Software</subject><subject>Special Purpose and Application-Based Systems</subject><subject>System on chip</subject><subject>Systems development</subject><issn>0922-6443</issn><issn>1573-1383</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp9kE1LxDAQhoMouK7-AU8Bz9F8NW2OsqwfsOBFzyGbJkuWtqlJurj-etut4M3DMMzwvDPwAHBL8D3BuHxIhFBOEKYMYckJRvwMLEhRMkRYxc7BAktKkeCcXYKrlPYY44KUcgHM-qCbQWff7eDBxzzoxn-PY-igC3GsHWxD53OIExEcjFY3KPvWQt33jTcnNkHfwdZ_2RqZ6PO4bXw-wnRM2bbpGlw43SR789uX4ONp_b56QZu359fV4wYZJlhGXOh6a52V0mmNK0odLkRd6qoQkjvNuBSsLum2YltRCoJZLU0hrRWMEWMJZUtwN9_tY_gcbMpqH4bYjS8VraQsCBeEjxSdKRNDStE61Uff6nhUBKtJppplqlGmOslUU4jNodRPImz8O_1P6gfOLHkS</recordid><startdate>20231201</startdate><enddate>20231201</enddate><creator>Cinque, Marcello</creator><creator>De Simone, Luigi</creator><creator>Mazzocca, Nicola</creator><creator>Ottaviano, Daniele</creator><creator>Vitale, Francesco</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><orcidid>https://orcid.org/0000-0003-2325-0056</orcidid></search><sort><creationdate>20231201</creationdate><title>Evaluating virtualization for fog monitoring of real-time applications in mixed-criticality systems</title><author>Cinque, Marcello ; De Simone, Luigi ; Mazzocca, Nicola ; Ottaviano, Daniele ; Vitale, Francesco</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c363t-46adbefe99faa0822f056d7a85694fa34963d72b83b676103d9c59ee6331ce123</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Anomalies</topic><topic>Chips (electronics)</topic><topic>Communications Engineering</topic><topic>Computer Science</topic><topic>Computer Systems Organization and Communication Networks</topic><topic>Control</topic><topic>Cyber-physical systems</topic><topic>Design analysis</topic><topic>Edge computing</topic><topic>Embedded systems</topic><topic>Frequency control</topic><topic>Fusion</topic><topic>Fusion reactors</topic><topic>Geographical distribution</topic><topic>Mechatronics</topic><topic>Model-based systems</topic><topic>Monitoring</topic><topic>Multiprocessing</topic><topic>Networks</topic><topic>Nuclear fusion</topic><topic>Nuclear power plants</topic><topic>Nuclear safety</topic><topic>Performance and Reliability</topic><topic>Real time operation</topic><topic>Resource allocation</topic><topic>Resource scheduling</topic><topic>Robotics</topic><topic>Safety critical</topic><topic>Software</topic><topic>Special Purpose and Application-Based Systems</topic><topic>System on chip</topic><topic>Systems development</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cinque, Marcello</creatorcontrib><creatorcontrib>De Simone, Luigi</creatorcontrib><creatorcontrib>Mazzocca, Nicola</creatorcontrib><creatorcontrib>Ottaviano, Daniele</creatorcontrib><creatorcontrib>Vitale, Francesco</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Real-time systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cinque, Marcello</au><au>De Simone, Luigi</au><au>Mazzocca, Nicola</au><au>Ottaviano, Daniele</au><au>Vitale, Francesco</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluating virtualization for fog monitoring of real-time applications in mixed-criticality systems</atitle><jtitle>Real-time systems</jtitle><stitle>Real-Time Syst</stitle><date>2023-12-01</date><risdate>2023</risdate><volume>59</volume><issue>4</issue><spage>534</spage><epage>567</epage><pages>534-567</pages><issn>0922-6443</issn><eissn>1573-1383</eissn><abstract>Technological advances in embedded systems and the advent of fog computing led to improved quality of service of applications of cyber-physical systems. In fact, the deployment of such applications on powerful and heterogeneous embedded systems, such as multiprocessors system-on-chips (MPSoCs), allows them to meet latency requirements and real-time operation. Highly relevant to the industry and our reference case-study, the challenging field of nuclear fusion deploys the aforementioned applications, involving high-frequency control with hard real-time and safety constraints. The use of fog computing and MPSoCs is promising to achieve safety, low latency, and timeliness of such control. Indeed, on one hand, applications designed according to fog computing distribute computation across hierarchically organized and geographically distributed edge devices, enabling timely anomaly detection during high-frequency sampling of time series, and, on the other hand, MPSoCs allow leveraging fog computing and integrating monitoring by deploying tasks on a flexible platform suited for mixed-criticality software, leading to so-called mixed criticality systems (MCSs). However, the integration of such software on the same MPSoC opens challenges related to predictability and reliability guarantees, as tasks interfering with each other when accessing the same shared MPSoC resources may introduce non-deterministic latency, possibly leading to failures on account of deadline overruns. Addressing the design, deployment, and evaluation of MCSs on MPSoCs, we propose a model-based system development process that facilitates the integration of real-time and monitoring software on the same platform by means of a formal notation for modeling the design and deployment of MPSoCs. The proposed notation allows developers to leverage embedded hypervisors for monitoring real-time applications and guaranteeing predictability by isolation of hardware resources. Providing evidence of the feasibility of our system development process and evaluating the industry-relevant class of nuclear fusion applications, we experiment with a safety-critical case-study in the context of the ITER nuclear fusion reactor. Our experimentation involves the design and evaluation of several prototypes deployed as MCSs on a virtualized MPSoC, showing that deployment choices linked to the monitor placement and virtualization configurations (e.g., resource allocation, partitioning, and scheduling policies) can significantly impact the predictability of MCSs in terms of Worst-Case Execution Times and other related metrics.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s11241-023-09410-4</doi><tpages>34</tpages><orcidid>https://orcid.org/0000-0003-2325-0056</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0922-6443
ispartof Real-time systems, 2023-12, Vol.59 (4), p.534-567
issn 0922-6443
1573-1383
language eng
recordid cdi_proquest_journals_2899514614
source Springer Nature - Complete Springer Journals
subjects Anomalies
Chips (electronics)
Communications Engineering
Computer Science
Computer Systems Organization and Communication Networks
Control
Cyber-physical systems
Design analysis
Edge computing
Embedded systems
Frequency control
Fusion
Fusion reactors
Geographical distribution
Mechatronics
Model-based systems
Monitoring
Multiprocessing
Networks
Nuclear fusion
Nuclear power plants
Nuclear safety
Performance and Reliability
Real time operation
Resource allocation
Resource scheduling
Robotics
Safety critical
Software
Special Purpose and Application-Based Systems
System on chip
Systems development
title Evaluating virtualization for fog monitoring of real-time applications in mixed-criticality systems
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-15T05%3A37%3A49IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Evaluating%20virtualization%20for%20fog%20monitoring%20of%20real-time%20applications%20in%20mixed-criticality%20systems&rft.jtitle=Real-time%20systems&rft.au=Cinque,%20Marcello&rft.date=2023-12-01&rft.volume=59&rft.issue=4&rft.spage=534&rft.epage=567&rft.pages=534-567&rft.issn=0922-6443&rft.eissn=1573-1383&rft_id=info:doi/10.1007/s11241-023-09410-4&rft_dat=%3Cproquest_cross%3E2899514614%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2899514614&rft_id=info:pmid/&rfr_iscdi=true