BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Canada/Eastern BEGIN:DAYLIGHT DTSTART:20170312T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20171105T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20170602T194845Z UID:7D19E147-47CC-11E7-8752-0050568D2FB3 DTSTART;TZID=Canada/Eastern:20170613T150000 DTEND;TZID=Canada/Eastern:20170613T160000 DESCRIPTION:The IEEE Toronto Section and University of Toronto – ECE are inviting all interested IEEE members and other engineers\, technologists a nd students to our Distinguished Lecture:\n\nTopology Preserving Maps: A L ocalization-Free Approach for\n\n2-D and 3-D IoT Subnets\n\nProf. Anura Ja yasumana\n\nDept. of Electrical & Computer Engineering\n\nColorado State U niversity\, Ft. Collins\, CO 80523 USA\n\nWeb: http://www.engr.colostate.e du/~anura\n\nDate: Tuesday June 13th\, 2017.\n\nTime: Refreshments 2:3—3 :00pm. Lecture: 3:00-4:00pm.\n\nLocation: University of Toronto\, Bahen Ce ntre for Information Technology\, 40 St George St\, Toronto\, ON M5S 2E4\n \nRoom:BA 2135\n\nContact:Eman Hammad\, eman.hammad.ca@ieee.org\n\nTalk Ab stract:\n\nDriven by higher potency and lower cost/size of devices capable of sensing\, actuating\, processing and communicating\, the Internet of T hings and of Everything promises to dramatically increase our ability to e mbed intelligence in the surroundings. Subnets of simple devices such as R FIDs and tiny sensors/actuators deployed in massive numbers in 2D and comp lex 3D spaces will be a key aspect of this emerging infrastructure. Most t echniques for self-organization\, routing and tracking in such networks re ly on distances and localization in the physical domain. While geographic coordinates fit well with our intuitions into physical spaces\, their use is not feasible in complex environments. Protocols based on geographical c oordinates do not scale well to 3D either. We present a novel localization -free coordinate system\, the Topology Coordinates (TC). Interestingly\, g eographic features such as voids and shapes are preserved in the resulting Topology-Preserving Maps (TPMs) of 2-D and 3-D networks. Ability to speci fy virtual cardinal directions and angles in networks is a radical change from the traditional approaches. A novel self-learning algorithm is presen ted to provide network awareness to individual nodes\, a step toward large -scale evolving sensor networks. Application of TCs to social networking w ill be illustrated.\n\nSpeaker(s): Prof. Anura Jayasumana\, \, Prof. Anura Jayasumana\, \n\nRoom: BA 2135\, Bldg: Bahen Centre for Information Techn ology\, University of Toronto\, 40 St George St\, Toronto\, Ontario\, Cana da\, M5S 2E4 LOCATION:Room: BA 2135\, Bldg: Bahen Centre for Information Technology\, Un iversity of Toronto\, 40 St George St\, Toronto\, Ontario\, Canada\, M5S 2 E4 ORGANIZER:eman.hammad.ca@ieee.org SEQUENCE:0 SUMMARY:IEEE ComSoc Distinguished Lecture: Topology Preserving Maps: A Loca lization-Free Approach for 2-D and 3-D IoT Subnets URL;VALUE=URI:https://events.vtools.ieee.org/m/45777 X-ALT-DESC:Description: <br /><p>The IEEE Toronto Section and University of Toronto &ndash\; ECE are inviting all interested IEEE members and other e ngineers\, technologists and students to our <strong>Distinguished Lecture </strong>:</p>\n<p><strong>Topology Preserving Maps: A Localization-Free A pproach for </strong></p>\n<p><strong>2-D and 3-D IoT Subnets&nbsp\;&nbsp\ ; </strong></p>\n<p><strong>&nbsp\;</strong></p>\n<p><strong>Prof. Anura J ayasumana</strong></p>\n<p><strong>Dept. of Electrical &amp\; Computer Eng ineering</strong></p>\n<p><strong>Colorado State University\, Ft. Collins\ , CO 80523 USA</strong></p>\n<p><strong>Web:&nbsp\;&nbsp\;&nbsp\;&nbsp\;&n bsp\; </strong><strong><a href="http://www.engr.colostate.edu/~anura">http ://www.engr.colostate.edu/~anura</a></strong></p>\n<p><strong>&nbsp\;</str ong></p>\n<p><strong>Date: </strong>Tuesday June 13<sup>th</sup>\, 2017.</ p>\n<p><strong>Time:</strong> Refreshments 2:3&mdash\;3:00pm. Lecture: 3:0 0-4:00pm.</p>\n<p><strong>Location:</strong> University of Toronto\, Bahen Centre for Information Technology\, 40 St George St\, Toronto\, ON M5S 2E 4</p>\n<p><strong>Room:</strong><strong>BA 2135</strong></p>\n<p><strong>C ontact:</strong>Eman Hammad\, <a href="mailto:eman.hammad.ca@ieee.org">ema n.hammad.ca@ieee.org</a></p>\n<p><strong>Talk Abstract:</strong></p>\n<p>D riven by higher potency and lower cost/size of devices capable of sensing\ , actuating\, processing and communicating\, the Internet of Things and of Everything promises to dramatically increase our ability to embed intelli gence in the surroundings. Subnets of simple devices such as RFIDs and tin y sensors/actuators deployed in massive numbers in 2D and complex 3D space s will be a key aspect of this emerging infrastructure. Most techniques fo r self-organization\, routing and tracking in such networks rely on distan ces and localization in the physical domain. While geographic coordinates fit well with our intuitions into physical spaces\, their use is not feasi ble in complex environments. Protocols based on geographical coordinates d o not scale well to 3D either. We present a novel localization-free coordi nate system\, the Topology Coordinates (TC). &nbsp\;Interestingly\, geogra phic features such as voids and shapes are preserved in the resulting Topo logy-Preserving Maps (TPMs) of 2-D and 3-D networks. Ability to specify vi rtual cardinal directions and angles in networks is a radical change from the traditional approaches.&nbsp\; &nbsp\;A novel self-learning algorithm is presented to provide network awareness to individual nodes\, a step tow ard large-scale evolving sensor networks. &nbsp\;Application of TCs to soc ial networking will be illustrated.&nbsp\;</p> END:VEVENT END:VCALENDAR