BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Canada/Eastern BEGIN:DAYLIGHT DTSTART:20210314T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20211107T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20211014T005030Z UID:958B2B29-7FBB-4824-9D7F-DF949B0057F4 DTSTART;TZID=Canada/Eastern:20210810T180000 DTEND;TZID=Canada/Eastern:20210810T190000 DESCRIPTION:This talk will present the first\, novel\, dynamic\, resilient\ , and consistent Blockchain COngestion ContrOL (BCOOL) system for vehicula r networks that fills the gap of trustworthy Blockchain congestion predict ion systems. BCOOL relies on the heterogeneity of Machine Learning\, Softw are-Defined Networks and Network Function Virtualization that is customize d in three hybrid cloud/edge-based On/Offchain smart contract modules and ruled by an efficient and reliable communication protocol. BCOOL's first n ovel module aims at managing message and vehicle trustworthiness using a n ovel\, dynamic and hybrid Blockchain Fog-based Distributed Trust Contract Strategy (FDTCS). The second novel module accurately and proactively predi cts the occurrence of congestion\, ahead of time\, using a novel Hybrid On /Off-Chain Multiple Linear Regression Software-defined Contract Strategy ( HOMLRCS). This module presents a virtualization facility layer to the thir d novel K-means/Random Forest-based On/Off-Chain Dynamic Service Function Chaining Contract Strategy (KRF-ODSFCS) that dynamically\, securely and pr oactively predicts VNF placements and their chaining order in the context of SFCs w.r.t users' dynamic QoS priority demands. This talk will demonstr ate how BCOOL exhibits a linear complexity and a strong resilience to fail ures. Using simulation results I will show that BCOOL outperforms the next best comparable strategies by 80% and 100% reliability and efficiency gai ns in challenging data congestion environments. I will also show how BCOOL performance yields to fast\, reliable and accurate congestion prediction decisions\, ahead of time\, and how it optimizes transaction validation pr ocessing time. Globally\, the Byzantine resilience\, complexity and attack mitigation strategies along with simulation results proved that BCOOL sec urely predicts the congestion and provides real-time monitoring\, fast and accurate SFC deployment decisions while lowering both capital and operati onal expenditures (CAPEX/OPEX) costs.\n\nSpeaker(s): Dr. Saida Maaroufi\, \n\nMontreal\, Quebec\, Canada\, Virtual: https://events.vtools.ieee.org/m /277907 LOCATION:Montreal\, Quebec\, Canada\, Virtual: https://events.vtools.ieee.o rg/m/277907 ORGANIZER:saidamaaroufi@ieee.org SEQUENCE:4 SUMMARY:BCOOL: A Novel Blockchain Congestion Control Architecture Using Dyn amic Service Function Chaining and Machine Learning for Next Generation Ve hicular Networks URL;VALUE=URI:https://events.vtools.ieee.org/m/277907 X-ALT-DESC:Description: <br /><p><span style="font-family: verdana\, geneva \, sans-serif\;">This talk will present the first\, novel\, dynamic\, resi lient\, and consistent Blockchain COngestion ContrOL (BCOOL) system for ve hicular networks that fills the gap of trustworthy Blockchain congestion p rediction systems. BCOOL relies on the heterogeneity of Machine Learning\, Software-Defined Networks and Network Function Virtualization that is cus tomized in three hybrid cloud/edge-based On/Offchain smart contract module s and ruled by an efficient and reliable communication protocol. BCOOL's f irst novel module aims at managing message and vehicle trustworthiness usi ng a novel\, dynamic and hybrid Blockchain Fog-based Distributed Trust Con tract Strategy (FDTCS). The second novel module accurately and proactively predicts the occurrence of congestion\, ahead of time\, using a novel Hyb rid On/Off-Chain Multiple Linear Regression Software-defined Contract Stra tegy (HOMLRCS). This module presents a virtualization facility layer to th e third novel K-means/Random Forest-based On/Off-Chain Dynamic Service Fun ction Chaining Contract Strategy (KRF-ODSFCS) that dynamically\, securely and proactively predicts VNF placements and their chaining order in the co ntext of SFCs w.r.t users' dynamic QoS priority demands. This talk will de monstrate how BCOOL exhibits a linear complexity and a strong resilience t o failures.&nbsp\; Using simulation results I will show that BCOOL outperf orms the next best comparable strategies by 80% and 100% reliability and e fficiency gains in challenging data congestion environments. I will also s how how BCOOL performance yields to fast\, reliable and accurate congestio n prediction decisions\, ahead of time\, and how it optimizes transaction validation processing time. Globally\, the Byzantine resilience\, complexi ty and attack mitigation strategies along with simulation results proved t hat BCOOL securely predicts the congestion and provides real-time monitori ng\, fast and accurate SFC deployment decisions while lowering both capita l and operational expenditures (CAPEX/OPEX) costs.</span></p>\n<p>&nbsp\;< /p> END:VEVENT END:VCALENDAR