Performance Evaluation of Binary Spray and Wait OppNet Protocol in the Context of Emergency Scenario

# Performance Evaluation of Binary Spray and Wait OppNet Protocol in the Context of Emergency Scenario

## Performance Evaluation of Binary Spray and Wait OppNet Protocol in the Context of Emergency Scenario

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1. Performance Evaluation of Binary Spray and Wait OppNet Protocol in the Context of Emergency Scenario Mazlan Abbas (MIMOS Berhad), Nur Husna Md Yusof (Universiti Teknologi Malaysia) and Norsheila Fisal (Universiti Teknologi Malaysia) Contact: mazlan.abbas@mimos.my @mazlan_abbas? h7ps://www.facebook.com/drmazlanabbas' PerNEM'2013,'San'Diego,'USA'

2. Outline •  Motivation •  Routing Challenges in Emergency Scenario •  Simulation Result •  Summary •  Future Work

3. Issues of Communications During Disasters and Emergency Lack'of' adequate' communic aLons' Terrorist'A7ack' Hurricane' Tsunami' Earthquake'

4. Opportunistic Networks (OppNets) To'enable'communicaLon'between'source'and'desLnaLon' without'the'support'of'a'fixed'network'infrastructure'

5. Smartphones – The Enabler GPS' Camera' Big'Storage' CPU'Power' WiFi'

6. History of Delay Tolerant Network •  Interplanetary'Internet'(IPN)'is'a'NASA'research'project'led'by'Vint'Cerf'in' 1998. •  The'basic'idea'is'to'try'to'make'data'communicaLons'in'space/'between' planets. •  IPN'became'the'most'fundamental'basis'for'DTN'architecture'and'protocol' suite.' •  The'Interplanetary'Internet'is'a'disconnected,'store\and'forward' ?network'of'Internets?'based'on'a'wireless'backbone'with'huge' delays'(The'delay'in'sending'or'receiving'data'from'Mars'takes' between'3.5'to'20'minutes'at'the'speed'of'light)'and'error'prone' links •  Failing'of'IP/TCP'in'space'missions –  End\to\end'path'exist –  Small'delays'

7. Delay Tolerant Networking (DTN) •  DTN'is'a'set'of'protocols'that' act'together'to'enable'a' standardized'method'of' performing'store\carry\and\ forward'communicaLons. Source' A' B' Store' Carry' •  CharacterisLcs'of'DTN: i.  Intermi7ent'connecLvity –  No'end\to\end'path'between'source' and'desLnaLon ii. Long'variable'delay –  Long'propagaLon'delays'between' nodes' B' Forward' C' Store' Carry' C' Forward' D' Delay'Tolerant'Network'(DTN)'='Mobile'OpportunisLc'Network'(OppNet)'

8. Public Safety 3G' WiFi' 3G' 3G' 3G'Base'' staLon' WiFi' WiFi' 8' OppNet'in'Emergency'Response'Scenario'

9. Public Safety Smartphones'(Nodes)'can'be' carried'by'?Pedestrians?'or' ?Vehicles?' X'X' 3G' WiFi' 3G' X' 3G' X' Base'' StaLon'down' WiFi' WiFi' WiFi' WiFi' Send'“SOS”'messages' Send'photos'of'vicLms'or'self' Can$we$send$videos?$ What$kind$of$file$size?$9' OppNet'in'Emergency'Response'Scenario' 10. Public Safety Internet' X'X' 3G' WiFi' 3G' X' 3G' X' Base'' StaLon'down' WiFi' WiFi' WiFi' WiFi' Ability'to'Connect'to'Internet'at' Remote'Ends' Ques7on:$Can$smartphones$help$us$ during$Emergency$Situa7on?$Internet' 10' 11. Internet' X'X' 3G' DTN'Gateway' WiFi' 3G' X' 3G' X' Base'' StaLon'down' WiFi' WiFi' WiFi' WiFi' DTN'Gateway' Internet' 11' 12. Routing Challenges C5' C3' Node'Mobility' C6' C3' C1' DesLnaLon' C4' C2' Source' Example:$Disaster'relief'efforts,'mining'operaLons,'health'campaigns' In'emergency'situaLons,'enLLes'with'any'sensing'capabiliLes''such'as'cellphones'with'GPS'or'desktops' equipped'with'surveillance'cameras,'can'be'especially'valuable'for'the'OppNet.'

13. Factors That Impact Performance Mobility'Pa7ern' RouLng'Mechanism' Size'of'Area' N1' Number'of'Nodes' Node'Speed' N2' Type'of'CommunicaLon' Transmission'Range' Buffer'Size' Message'Size' Time\to\Live' Ba7ery'Life'

14. Routing Protocols – Related Works (1) •  The Direct Delivery does not start any further transactions after exchanging the deliverable messages since it will send messages only if it is in contact with the final recipient. •  While in the First Contact routing, it sends as many messages to the other node as it has time; it removes the local copy of the message after a successful transfer. This results in only a single copy of every message in the network. •  Epidemic routing [Vahdat et al 2000] spreads an unlimited number of message copies by having nodes replicate them to all other nodes they connect. This includes the messages they create and the messages they have received from other nodes. 1 4 14'

15. Routing Protocols – Related Works (1) •  Predictive protocols such as PRoPHET [Lindgren et al 2004] use past encounters of nodes to predict their future suitability to deliver messages to a certain target. It uses a metric called delivery predictability that is based upon how often two nodes meet each other. The more frequently and the more recently these nodes have met, the better a forwarder one is for messages directed to the other. While PRoPHET checks if another node is more likely to meet the final recipient, MaxProp [Burgess et al 2006] uses Dijkstra?s algorithm to calculate whole paths from node to node using the meeting probabilities. The Spray and Wait [Spyropoulos et al 2005] works a bit like the Epidemic but it restricts the amount of copies that are spread in the network. Letting each created message to replicate only a certain amount of times. A node that has more than one copy of the message left, can give either a one copy to another node (the normal mode) or half of the copies (the binary mode). •  •  1 5 15'

16. Spray & Wait - A Better Choice Spray'&'Wait'–'High'delivery'probability' Spray'&'Wait'–'Low'overhead'(First'contact'don’t'have' good'delivery'probability)' ! Shortest$Path$MapDBased$Movement$Model\$–'Assuming'in' most'emergency'situaLon,'people'and'vehicle'will'move' along'the'roads.'' Spray'&'Wait'–'Low'latency' [Source:'“performance'of'Challenged'Internet'of'Things'in'Emergency'Response”,'M.'Abbas'and'N.H.Md.'Yusuf,'Technical'Report,'2012]' 1 6 16'

17. Spray and Wait Routing Protocol •  In Spray and Wait, message is delivered in two phases; the spray phase and the wait phase. •  In the spray phase, source node spread a small number of copies to only a few relays. A node that has more than one copy of the message left can give either a copy to another node (the normal mode) or half of the copies (the binary mode) and keeps the rest to itself. •  In the wait phase, if the node has only a single copy of the message left, it is directly transmitted only to the destination. •  We use Spray-and-Wait in binary mode: a node carrying k copies of a message forwards k/2 of them to the next nodes it meets until the k =1. Then, a node waits till it meets the destination. 17'

18. Performance Metrics •  Delivery probability: It is a ratio between the number of messages arrives at destination and the number of messages sent. •  Message dropped: It is the number of messages dropped from nodes' buffers during transmission. Messages are dropped once the buffer is full. •  Latency average: The latency average is an average time taken for a message to reach destination. •  Hop count average: It is an average number of hops between source and destination nodes. 18'

19. Assumptions SimulaLon'tool:'ONE'(OpportunisLc'Networking'Environment)' Helsinki'Downtown'Map'(4.5km'x'3.4'km)' 1 9 19'

20. Main Simulation Parameters Parameter' SimulaLon'Time'(s)' SimulaLon'Area'(sq.m)' RouLng'Protocol' Number'of'Copies' Mobility'Model' Transmission'Range'(m)' Transmit'Speed'(Mb/s)' TTL'(minutes)' Value' 43200' 4500x3400' Binary'Spray'and'Wait' 6' Shortest'Path'Map'Based'Movement' 10' 10' 300' 20'

21. Experiments – Varying Buffer Size Experiment' Group' Number'of'Nodes' Speed'(m/s)' 1' Pedestrians' 20' 0.5\1.5'' 2' Cars' 20' 2.7'–'13.9' 3' Pedestrians' 100' 0.5'–'1.5' 4' Cars' 100' 2.7'–'13.9'' Parameter' Buffer'size'(MB)' Message'size'(B)' Message'generaLon' Value' 5\100' 500k'–'1M' Every'30'seconds' 21'

22. Varying the Buffer Size Speed'of'nodes'does'not' ma7er'with'buffer'size'but' number'of'nodes'does' ma7er' Impact'on'Delivery'Probability' Delivery'Probability'vs.'Buffer'Size'' Higher'loss'of'messages'when'buffer'size' is'too'small.'OpLmum'at'30'MB.' Messages'eventually'have'to'be'dropped' if'it'exceeded'the'TTL.' 22'

23. Varying the Buffer Size Impact'on'Number'of'Messages'Dropped' Number'of'Messages'Dropped'vs.'Buffer'Size'' Beyond'30'MB'buffer'size,'the'number'of'messages'being'dropped'remained'the'same.' 23'

24. Varying the Buffer Size Smaller'number'of' nodes'has'higher' latency.' Impact'on'Latency'Average' Latency'Average'vs.'Buffer'Size'' 24'

25. Varying the Buffer Size Impact'on'Average'Hop'Count' Hop'Count'vs.'Buffer'Size'' 25'

26. Experiments – Varying Message Size Experiment' Group' Number'of'Nodes' Speed'(m/s)' 1' Pedestrians' 20' 0.5\1.5'' 2' Cars' 20' 2.7'–'13.9' 3' Pedestrians' 100' 0.5'–'1.5' 4' Cars' 100' 2.7'–'13.9'' Parameter' Message'size'' Buffer'size' Value' 500'kB''to''5'MB' 30'MB' 26'

27. Varying the Message Size Impact'on'Delivery'Probability' Slower'nodes'able'to'carry'bigger'message'sizes' Delivery'Probability'vs'Message'Size' 27'

28. Varying the Message Size Impact'on'Average'Latency' Average'Latency'vs'Message'Size' 28'

29. Summary •  Opportunistic Networks (OppNets) are very useful in the context of emergency scenarios •  Binary Spray and Wait Protocol is one good option for routing •  Smartphones seems to be a good potential candidate communications tool in emergency scenarios •  Speedier nodes (cars) require smaller Message size (images rather than videos). 29'

30. Future Work •  Requires actual datasets (emergency scenarios) for mobility model •  Mixed mobility scenarios (pedestrians plus vehicles) •  Find better battery efficient methods •  Further refinements to Spray & Wait Protocol with other parameters such as Contact Time etc. •  Implementation on smartphones – e.g. WiFi Direct 802.11ac or Bluetooth

31. THANK YOU Contact: mazlan.abbas@mimos.my @mazlan_abbas? h7ps://www.facebook.com/drmazlanabbas'