Ontology-Based Semantic Priority Scheduling for Multi-domain Active Measurements
Abstract Network control and management techniques (e.g., dynamic path switching and on-demand bandwidth provisioning) rely on active measurements of the end-to-end network status. The measurements are needed to meet network monitoring objectives such as network weather forecasting, anomaly detectio...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Calyam, Prasad [verfasserIn] Kumarasamy, Lakshmi [verfasserIn] Lee, Chang-Gun [verfasserIn] Ozguner, Fusun [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2013 |
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| Schlagwörter: |
Multi-domain network performance monitoring Policy-based active measurements scheduling |
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| Übergeordnetes Werk: |
Enthalten in: Journal of network and systems management - Dordrecht [u.a.] : Springer Science + Business Media, 1993, 22(2013), 3 vom: 24. Nov., Seite 331-365 |
|---|---|
| Übergeordnetes Werk: |
volume:22 ; year:2013 ; number:3 ; day:24 ; month:11 ; pages:331-365 |
| Links: |
|---|
| DOI / URN: |
10.1007/s10922-013-9297-x |
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| Katalog-ID: |
SPR014662957 |
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| 520 | |a Abstract Network control and management techniques (e.g., dynamic path switching and on-demand bandwidth provisioning) rely on active measurements of the end-to-end network status. The measurements are needed to meet network monitoring objectives such as network weather forecasting, anomaly detection, and fault-diagnosis. Recent widespread deployment of openly accessible multi-domain active measurement frameworks, such as perfSONAR, has resulted in users competing for system and network measurement resources. Hence, there is a need to prioritize measurement requests of users before they are scheduled on measurement resources. In this paper, we present a novel ontology-based semantic priority scheduling algorithm (SPS) that handles resource contention while servicing measurement requests for meeting network monitoring objectives. We adopt ontologies to formalize semantic definitions and develop an inference engine to dynamically prioritize measurement requests. The prioritization is based upon user roles, user sampling preferences, resource policies, and oversampling mitigation factors. Performance evaluation results demonstrate that our SPS algorithm outperforms existing deterministic and heuristic algorithms in terms of user ‘satisfaction ratio’ and ‘average stretch’ among serviced measurement requests. Further, by sampling experiments on real-network perfSONAR measurement data sets, we show that our SPS algorithm successfully mitigates oversampling and further improves the satisfaction ratio. Our SPS scheme and evaluation results are vital to manage large-scale measurement infrastructures used for meeting monitoring objectives in the next-generation applications and networks. | ||
| 650 | 4 | |a Multi-domain network performance monitoring |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Policy-based active measurements scheduling |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Network measurement federations |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Semantic measurement policy handling |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Kumarasamy, Lakshmi |e verfasserin |4 aut | |
| 700 | 1 | |a Lee, Chang-Gun |e verfasserin |4 aut | |
| 700 | 1 | |a Ozguner, Fusun |e verfasserin |4 aut | |
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10.1007/s10922-013-9297-x doi (DE-627)SPR014662957 (SPR)s10922-013-9297-x-e DE-627 ger DE-627 rakwb eng 004 ASE 54.32 bkl 54.54 bkl Calyam, Prasad verfasserin aut Ontology-Based Semantic Priority Scheduling for Multi-domain Active Measurements 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Network control and management techniques (e.g., dynamic path switching and on-demand bandwidth provisioning) rely on active measurements of the end-to-end network status. The measurements are needed to meet network monitoring objectives such as network weather forecasting, anomaly detection, and fault-diagnosis. Recent widespread deployment of openly accessible multi-domain active measurement frameworks, such as perfSONAR, has resulted in users competing for system and network measurement resources. Hence, there is a need to prioritize measurement requests of users before they are scheduled on measurement resources. In this paper, we present a novel ontology-based semantic priority scheduling algorithm (SPS) that handles resource contention while servicing measurement requests for meeting network monitoring objectives. We adopt ontologies to formalize semantic definitions and develop an inference engine to dynamically prioritize measurement requests. The prioritization is based upon user roles, user sampling preferences, resource policies, and oversampling mitigation factors. Performance evaluation results demonstrate that our SPS algorithm outperforms existing deterministic and heuristic algorithms in terms of user ‘satisfaction ratio’ and ‘average stretch’ among serviced measurement requests. Further, by sampling experiments on real-network perfSONAR measurement data sets, we show that our SPS algorithm successfully mitigates oversampling and further improves the satisfaction ratio. Our SPS scheme and evaluation results are vital to manage large-scale measurement infrastructures used for meeting monitoring objectives in the next-generation applications and networks. Multi-domain network performance monitoring (dpeaa)DE-He213 Policy-based active measurements scheduling (dpeaa)DE-He213 Network measurement federations (dpeaa)DE-He213 Semantic measurement policy handling (dpeaa)DE-He213 Kumarasamy, Lakshmi verfasserin aut Lee, Chang-Gun verfasserin aut Ozguner, Fusun verfasserin aut Enthalten in Journal of network and systems management Dordrecht [u.a.] : Springer Science + Business Media, 1993 22(2013), 3 vom: 24. Nov., Seite 331-365 (DE-627)320575756 (DE-600)2017028-2 1573-7705 nnns volume:22 year:2013 number:3 day:24 month:11 pages:331-365 https://dx.doi.org/10.1007/s10922-013-9297-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_1200 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.32 ASE 54.54 ASE AR 22 2013 3 24 11 331-365 |
| spelling |
10.1007/s10922-013-9297-x doi (DE-627)SPR014662957 (SPR)s10922-013-9297-x-e DE-627 ger DE-627 rakwb eng 004 ASE 54.32 bkl 54.54 bkl Calyam, Prasad verfasserin aut Ontology-Based Semantic Priority Scheduling for Multi-domain Active Measurements 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Network control and management techniques (e.g., dynamic path switching and on-demand bandwidth provisioning) rely on active measurements of the end-to-end network status. The measurements are needed to meet network monitoring objectives such as network weather forecasting, anomaly detection, and fault-diagnosis. Recent widespread deployment of openly accessible multi-domain active measurement frameworks, such as perfSONAR, has resulted in users competing for system and network measurement resources. Hence, there is a need to prioritize measurement requests of users before they are scheduled on measurement resources. In this paper, we present a novel ontology-based semantic priority scheduling algorithm (SPS) that handles resource contention while servicing measurement requests for meeting network monitoring objectives. We adopt ontologies to formalize semantic definitions and develop an inference engine to dynamically prioritize measurement requests. The prioritization is based upon user roles, user sampling preferences, resource policies, and oversampling mitigation factors. Performance evaluation results demonstrate that our SPS algorithm outperforms existing deterministic and heuristic algorithms in terms of user ‘satisfaction ratio’ and ‘average stretch’ among serviced measurement requests. Further, by sampling experiments on real-network perfSONAR measurement data sets, we show that our SPS algorithm successfully mitigates oversampling and further improves the satisfaction ratio. Our SPS scheme and evaluation results are vital to manage large-scale measurement infrastructures used for meeting monitoring objectives in the next-generation applications and networks. Multi-domain network performance monitoring (dpeaa)DE-He213 Policy-based active measurements scheduling (dpeaa)DE-He213 Network measurement federations (dpeaa)DE-He213 Semantic measurement policy handling (dpeaa)DE-He213 Kumarasamy, Lakshmi verfasserin aut Lee, Chang-Gun verfasserin aut Ozguner, Fusun verfasserin aut Enthalten in Journal of network and systems management Dordrecht [u.a.] : Springer Science + Business Media, 1993 22(2013), 3 vom: 24. Nov., Seite 331-365 (DE-627)320575756 (DE-600)2017028-2 1573-7705 nnns volume:22 year:2013 number:3 day:24 month:11 pages:331-365 https://dx.doi.org/10.1007/s10922-013-9297-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_1200 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.32 ASE 54.54 ASE AR 22 2013 3 24 11 331-365 |
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10.1007/s10922-013-9297-x doi (DE-627)SPR014662957 (SPR)s10922-013-9297-x-e DE-627 ger DE-627 rakwb eng 004 ASE 54.32 bkl 54.54 bkl Calyam, Prasad verfasserin aut Ontology-Based Semantic Priority Scheduling for Multi-domain Active Measurements 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Network control and management techniques (e.g., dynamic path switching and on-demand bandwidth provisioning) rely on active measurements of the end-to-end network status. The measurements are needed to meet network monitoring objectives such as network weather forecasting, anomaly detection, and fault-diagnosis. Recent widespread deployment of openly accessible multi-domain active measurement frameworks, such as perfSONAR, has resulted in users competing for system and network measurement resources. Hence, there is a need to prioritize measurement requests of users before they are scheduled on measurement resources. In this paper, we present a novel ontology-based semantic priority scheduling algorithm (SPS) that handles resource contention while servicing measurement requests for meeting network monitoring objectives. We adopt ontologies to formalize semantic definitions and develop an inference engine to dynamically prioritize measurement requests. The prioritization is based upon user roles, user sampling preferences, resource policies, and oversampling mitigation factors. Performance evaluation results demonstrate that our SPS algorithm outperforms existing deterministic and heuristic algorithms in terms of user ‘satisfaction ratio’ and ‘average stretch’ among serviced measurement requests. Further, by sampling experiments on real-network perfSONAR measurement data sets, we show that our SPS algorithm successfully mitigates oversampling and further improves the satisfaction ratio. Our SPS scheme and evaluation results are vital to manage large-scale measurement infrastructures used for meeting monitoring objectives in the next-generation applications and networks. Multi-domain network performance monitoring (dpeaa)DE-He213 Policy-based active measurements scheduling (dpeaa)DE-He213 Network measurement federations (dpeaa)DE-He213 Semantic measurement policy handling (dpeaa)DE-He213 Kumarasamy, Lakshmi verfasserin aut Lee, Chang-Gun verfasserin aut Ozguner, Fusun verfasserin aut Enthalten in Journal of network and systems management Dordrecht [u.a.] : Springer Science + Business Media, 1993 22(2013), 3 vom: 24. Nov., Seite 331-365 (DE-627)320575756 (DE-600)2017028-2 1573-7705 nnns volume:22 year:2013 number:3 day:24 month:11 pages:331-365 https://dx.doi.org/10.1007/s10922-013-9297-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_1200 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.32 ASE 54.54 ASE AR 22 2013 3 24 11 331-365 |
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Calyam, Prasad @@aut@@ Kumarasamy, Lakshmi @@aut@@ Lee, Chang-Gun @@aut@@ Ozguner, Fusun @@aut@@ |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR014662957</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220111011914.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201006s2013 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10922-013-9297-x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR014662957</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s10922-013-9297-x-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">54.32</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">54.54</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Calyam, Prasad</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Ontology-Based Semantic Priority Scheduling for Multi-domain Active Measurements</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2013</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Network control and management techniques (e.g., dynamic path switching and on-demand bandwidth provisioning) rely on active measurements of the end-to-end network status. The measurements are needed to meet network monitoring objectives such as network weather forecasting, anomaly detection, and fault-diagnosis. Recent widespread deployment of openly accessible multi-domain active measurement frameworks, such as perfSONAR, has resulted in users competing for system and network measurement resources. Hence, there is a need to prioritize measurement requests of users before they are scheduled on measurement resources. In this paper, we present a novel ontology-based semantic priority scheduling algorithm (SPS) that handles resource contention while servicing measurement requests for meeting network monitoring objectives. We adopt ontologies to formalize semantic definitions and develop an inference engine to dynamically prioritize measurement requests. The prioritization is based upon user roles, user sampling preferences, resource policies, and oversampling mitigation factors. Performance evaluation results demonstrate that our SPS algorithm outperforms existing deterministic and heuristic algorithms in terms of user ‘satisfaction ratio’ and ‘average stretch’ among serviced measurement requests. Further, by sampling experiments on real-network perfSONAR measurement data sets, we show that our SPS algorithm successfully mitigates oversampling and further improves the satisfaction ratio. Our SPS scheme and evaluation results are vital to manage large-scale measurement infrastructures used for meeting monitoring objectives in the next-generation applications and networks.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Multi-domain network performance monitoring</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Policy-based active measurements scheduling</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Network measurement federations</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Semantic measurement policy handling</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kumarasamy, Lakshmi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lee, Chang-Gun</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ozguner, Fusun</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of network and systems management</subfield><subfield code="d">Dordrecht [u.a.] : Springer Science + Business Media, 1993</subfield><subfield code="g">22(2013), 3 vom: 24. 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004 ASE 54.32 bkl 54.54 bkl Ontology-Based Semantic Priority Scheduling for Multi-domain Active Measurements Multi-domain network performance monitoring (dpeaa)DE-He213 Policy-based active measurements scheduling (dpeaa)DE-He213 Network measurement federations (dpeaa)DE-He213 Semantic measurement policy handling (dpeaa)DE-He213 |
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ontology-based semantic priority scheduling for multi-domain active measurements |
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Ontology-Based Semantic Priority Scheduling for Multi-domain Active Measurements |
| abstract |
Abstract Network control and management techniques (e.g., dynamic path switching and on-demand bandwidth provisioning) rely on active measurements of the end-to-end network status. The measurements are needed to meet network monitoring objectives such as network weather forecasting, anomaly detection, and fault-diagnosis. Recent widespread deployment of openly accessible multi-domain active measurement frameworks, such as perfSONAR, has resulted in users competing for system and network measurement resources. Hence, there is a need to prioritize measurement requests of users before they are scheduled on measurement resources. In this paper, we present a novel ontology-based semantic priority scheduling algorithm (SPS) that handles resource contention while servicing measurement requests for meeting network monitoring objectives. We adopt ontologies to formalize semantic definitions and develop an inference engine to dynamically prioritize measurement requests. The prioritization is based upon user roles, user sampling preferences, resource policies, and oversampling mitigation factors. Performance evaluation results demonstrate that our SPS algorithm outperforms existing deterministic and heuristic algorithms in terms of user ‘satisfaction ratio’ and ‘average stretch’ among serviced measurement requests. Further, by sampling experiments on real-network perfSONAR measurement data sets, we show that our SPS algorithm successfully mitigates oversampling and further improves the satisfaction ratio. Our SPS scheme and evaluation results are vital to manage large-scale measurement infrastructures used for meeting monitoring objectives in the next-generation applications and networks. |
| abstractGer |
Abstract Network control and management techniques (e.g., dynamic path switching and on-demand bandwidth provisioning) rely on active measurements of the end-to-end network status. The measurements are needed to meet network monitoring objectives such as network weather forecasting, anomaly detection, and fault-diagnosis. Recent widespread deployment of openly accessible multi-domain active measurement frameworks, such as perfSONAR, has resulted in users competing for system and network measurement resources. Hence, there is a need to prioritize measurement requests of users before they are scheduled on measurement resources. In this paper, we present a novel ontology-based semantic priority scheduling algorithm (SPS) that handles resource contention while servicing measurement requests for meeting network monitoring objectives. We adopt ontologies to formalize semantic definitions and develop an inference engine to dynamically prioritize measurement requests. The prioritization is based upon user roles, user sampling preferences, resource policies, and oversampling mitigation factors. Performance evaluation results demonstrate that our SPS algorithm outperforms existing deterministic and heuristic algorithms in terms of user ‘satisfaction ratio’ and ‘average stretch’ among serviced measurement requests. Further, by sampling experiments on real-network perfSONAR measurement data sets, we show that our SPS algorithm successfully mitigates oversampling and further improves the satisfaction ratio. Our SPS scheme and evaluation results are vital to manage large-scale measurement infrastructures used for meeting monitoring objectives in the next-generation applications and networks. |
| abstract_unstemmed |
Abstract Network control and management techniques (e.g., dynamic path switching and on-demand bandwidth provisioning) rely on active measurements of the end-to-end network status. The measurements are needed to meet network monitoring objectives such as network weather forecasting, anomaly detection, and fault-diagnosis. Recent widespread deployment of openly accessible multi-domain active measurement frameworks, such as perfSONAR, has resulted in users competing for system and network measurement resources. Hence, there is a need to prioritize measurement requests of users before they are scheduled on measurement resources. In this paper, we present a novel ontology-based semantic priority scheduling algorithm (SPS) that handles resource contention while servicing measurement requests for meeting network monitoring objectives. We adopt ontologies to formalize semantic definitions and develop an inference engine to dynamically prioritize measurement requests. The prioritization is based upon user roles, user sampling preferences, resource policies, and oversampling mitigation factors. Performance evaluation results demonstrate that our SPS algorithm outperforms existing deterministic and heuristic algorithms in terms of user ‘satisfaction ratio’ and ‘average stretch’ among serviced measurement requests. Further, by sampling experiments on real-network perfSONAR measurement data sets, we show that our SPS algorithm successfully mitigates oversampling and further improves the satisfaction ratio. Our SPS scheme and evaluation results are vital to manage large-scale measurement infrastructures used for meeting monitoring objectives in the next-generation applications and networks. |
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| title_short |
Ontology-Based Semantic Priority Scheduling for Multi-domain Active Measurements |
| url |
https://dx.doi.org/10.1007/s10922-013-9297-x |
| remote_bool |
true |
| author2 |
Kumarasamy, Lakshmi Lee, Chang-Gun Ozguner, Fusun |
| author2Str |
Kumarasamy, Lakshmi Lee, Chang-Gun Ozguner, Fusun |
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| doi_str |
10.1007/s10922-013-9297-x |
| up_date |
2024-07-04T02:37:31.109Z |
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| score |
7.400321 |