A Novel Bio-Inspired Approach for High-Performance Management in Service-Oriented Networks
Service-continuity in distributed computing can be enhanced by designing self-organized systems, with a non-fixed structure, able to modify their structure and organization, as well as adaptively react to internal and external environment changes. In this paper, an architecture exploiting a bio-insp...
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Veröffentlicht in: | IEEE transactions on emerging topics in computing 2021-10, Vol.9 (4), p.1709-1722 |
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creator | Conti, Vincenzo Militello, Carmelo Rundo, Leonardo Vitabile, Salvatore |
description | Service-continuity in distributed computing can be enhanced by designing self-organized systems, with a non-fixed structure, able to modify their structure and organization, as well as adaptively react to internal and external environment changes. In this paper, an architecture exploiting a bio-inspired management approach, i.e., the functioning of cell metabolism, for specialized computing environments in Service-Oriented Networks (SONs) is proposed. Similar to the processes acting in metabolic networks, the nodes communicate to each other by means of stimulation or suppression chains giving rise to emergent behaviors to defend against foreign invaders, attacks, and malfunctioning. The main contribution of this work is a novel bio-inspired methodology for SON analysis to improve the network reliability and robustness for maintaining service-continuity. To show the effectiveness of the proposed computational framework, an embedded Field-Programmable Gate Array (FPGA) prototyped SON for a relevant healthcare imaging application is also outlined. In particular, our case study extracts and analyzes the Cerebral Vascular Tree from Magnetic Resonance Angiography series via a Maximum Intensity Projection algorithm; the proposed solution addresses and implements some basic issues of an interesting diagnosis tool for cerebral aneurysm detection. The prototyped system was tested and evaluated in terms of execution time and used resource analysis, by achieving a 4× speed-up factor compared to the software counterpart. |
doi_str_mv | 10.1109/TETC.2020.3018312 |
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In this paper, an architecture exploiting a bio-inspired management approach, i.e., the functioning of cell metabolism, for specialized computing environments in Service-Oriented Networks (SONs) is proposed. Similar to the processes acting in metabolic networks, the nodes communicate to each other by means of stimulation or suppression chains giving rise to emergent behaviors to defend against foreign invaders, attacks, and malfunctioning. The main contribution of this work is a novel bio-inspired methodology for SON analysis to improve the network reliability and robustness for maintaining service-continuity. To show the effectiveness of the proposed computational framework, an embedded Field-Programmable Gate Array (FPGA) prototyped SON for a relevant healthcare imaging application is also outlined. In particular, our case study extracts and analyzes the Cerebral Vascular Tree from Magnetic Resonance Angiography series via a Maximum Intensity Projection algorithm; the proposed solution addresses and implements some basic issues of an interesting diagnosis tool for cerebral aneurysm detection. The prototyped system was tested and evaluated in terms of execution time and used resource analysis, by achieving a 4× speed-up factor compared to the software counterpart.</description><identifier>ISSN: 2168-6750</identifier><identifier>EISSN: 2168-6750</identifier><identifier>DOI: 10.1109/TETC.2020.3018312</identifier><identifier>CODEN: ITETBT</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Angiography ; Bio-inspired computing ; bio-inspired networks ; Biomedical imaging ; Blood vessels ; cerebral vascular tree reconstruction ; Computer architecture ; Computer networks ; Continuity ; Distributed processing ; Field programmable gate arrays ; FPGA technology ; High performance computing ; high-performance management ; Magnetic resonance ; magnetic resonance angiography ; maximum intensity projection ; Network reliability ; Performance management ; Reliability analysis ; Robustness (mathematics) ; Self organizing systems ; Service-oriented architecture ; Service-oriented networks</subject><ispartof>IEEE transactions on emerging topics in computing, 2021-10, Vol.9 (4), p.1709-1722</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c359t-a801198e93c660b44f8f27073913580efb49410675d6de589132004105bb2ee53</citedby><cites>FETCH-LOGICAL-c359t-a801198e93c660b44f8f27073913580efb49410675d6de589132004105bb2ee53</cites><orcidid>0000-0003-3341-5483 ; 0000-0002-2673-8551 ; 0000-0002-8718-111X ; 0000-0003-2249-9538</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9172042$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27631,27922,27923,54756,54931</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9172042$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Conti, Vincenzo</creatorcontrib><creatorcontrib>Militello, Carmelo</creatorcontrib><creatorcontrib>Rundo, Leonardo</creatorcontrib><creatorcontrib>Vitabile, Salvatore</creatorcontrib><title>A Novel Bio-Inspired Approach for High-Performance Management in Service-Oriented Networks</title><title>IEEE transactions on emerging topics in computing</title><addtitle>TETC</addtitle><description>Service-continuity in distributed computing can be enhanced by designing self-organized systems, with a non-fixed structure, able to modify their structure and organization, as well as adaptively react to internal and external environment changes. In this paper, an architecture exploiting a bio-inspired management approach, i.e., the functioning of cell metabolism, for specialized computing environments in Service-Oriented Networks (SONs) is proposed. Similar to the processes acting in metabolic networks, the nodes communicate to each other by means of stimulation or suppression chains giving rise to emergent behaviors to defend against foreign invaders, attacks, and malfunctioning. The main contribution of this work is a novel bio-inspired methodology for SON analysis to improve the network reliability and robustness for maintaining service-continuity. To show the effectiveness of the proposed computational framework, an embedded Field-Programmable Gate Array (FPGA) prototyped SON for a relevant healthcare imaging application is also outlined. In particular, our case study extracts and analyzes the Cerebral Vascular Tree from Magnetic Resonance Angiography series via a Maximum Intensity Projection algorithm; the proposed solution addresses and implements some basic issues of an interesting diagnosis tool for cerebral aneurysm detection. The prototyped system was tested and evaluated in terms of execution time and used resource analysis, by achieving a 4× speed-up factor compared to the software counterpart.</description><subject>Algorithms</subject><subject>Angiography</subject><subject>Bio-inspired computing</subject><subject>bio-inspired networks</subject><subject>Biomedical imaging</subject><subject>Blood vessels</subject><subject>cerebral vascular tree reconstruction</subject><subject>Computer architecture</subject><subject>Computer networks</subject><subject>Continuity</subject><subject>Distributed processing</subject><subject>Field programmable gate arrays</subject><subject>FPGA technology</subject><subject>High performance computing</subject><subject>high-performance management</subject><subject>Magnetic resonance</subject><subject>magnetic resonance angiography</subject><subject>maximum intensity projection</subject><subject>Network reliability</subject><subject>Performance management</subject><subject>Reliability analysis</subject><subject>Robustness (mathematics)</subject><subject>Self organizing systems</subject><subject>Service-oriented architecture</subject><subject>Service-oriented networks</subject><issn>2168-6750</issn><issn>2168-6750</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNUNFKwzAUDaLgmPsA8SXgc-dN0qbJ4xzqBtMJzhdfQtvdbplbW5Nu4t-bsiHel3s4nHPv4RByzWDIGOi7xcNiPOTAYSiAKcH4GelxJlUk0wTO_-FLMvB-A2EUk1qmPfIxoi_1Abf03tbRtPKNdbiko6ZxdVasaVk7OrGrdfSKLuBdVhVIn7MqW-EOq5bair6hO9gCo7mzgQnmF2y_a_fpr8hFmW09Dk67T94fQ9BJNJs_TcejWVSIRLdRpoAxrVCLQkrI47hUJU8hFZqJRAGWeaxjBiH-Ui4xUYHmAIFJ8pwjJqJPbo93Q-avPfrWbOq9q8JLwyUkKSihOxU7qgpXe--wNI2zu8z9GAama9F0LZquRXNqMXhujh6LiH96zVIOMRe_R7hriw</recordid><startdate>20211001</startdate><enddate>20211001</enddate><creator>Conti, Vincenzo</creator><creator>Militello, Carmelo</creator><creator>Rundo, Leonardo</creator><creator>Vitabile, Salvatore</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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In this paper, an architecture exploiting a bio-inspired management approach, i.e., the functioning of cell metabolism, for specialized computing environments in Service-Oriented Networks (SONs) is proposed. Similar to the processes acting in metabolic networks, the nodes communicate to each other by means of stimulation or suppression chains giving rise to emergent behaviors to defend against foreign invaders, attacks, and malfunctioning. The main contribution of this work is a novel bio-inspired methodology for SON analysis to improve the network reliability and robustness for maintaining service-continuity. To show the effectiveness of the proposed computational framework, an embedded Field-Programmable Gate Array (FPGA) prototyped SON for a relevant healthcare imaging application is also outlined. In particular, our case study extracts and analyzes the Cerebral Vascular Tree from Magnetic Resonance Angiography series via a Maximum Intensity Projection algorithm; the proposed solution addresses and implements some basic issues of an interesting diagnosis tool for cerebral aneurysm detection. The prototyped system was tested and evaluated in terms of execution time and used resource analysis, by achieving a 4× speed-up factor compared to the software counterpart.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TETC.2020.3018312</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0003-3341-5483</orcidid><orcidid>https://orcid.org/0000-0002-2673-8551</orcidid><orcidid>https://orcid.org/0000-0002-8718-111X</orcidid><orcidid>https://orcid.org/0000-0003-2249-9538</orcidid></addata></record> |
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subjects | Algorithms Angiography Bio-inspired computing bio-inspired networks Biomedical imaging Blood vessels cerebral vascular tree reconstruction Computer architecture Computer networks Continuity Distributed processing Field programmable gate arrays FPGA technology High performance computing high-performance management Magnetic resonance magnetic resonance angiography maximum intensity projection Network reliability Performance management Reliability analysis Robustness (mathematics) Self organizing systems Service-oriented architecture Service-oriented networks |
title | A Novel Bio-Inspired Approach for High-Performance Management in Service-Oriented Networks |
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