Sociological Orbit aware Location Approximation and Routing (SOLAR) in MANET

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Sociological Orbit aware Location Approximation
and Routing (SOLAR) in MANET

• Joy Ghosh, Sumesh J. Philip, Chunming Qiao

Laboratory for Advanced Network Design,
Evaluation and Research (LANDER)
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Outline

• Sociological orbital movement
• Random orbit model
• Social acquaintance based query
• SOLAR protocol concept
• Performance Comparison
• Summary
• Current work

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What is a Sociological Orbit?

• List of special places (hubs) for most users
• Periodic visits in any sequence
• Substantial stay time
• E.g., Places with Internet Access Points,
  Academic buildings, Libraries, Residential
  Complex, Coffee shops, etc.
• Fair and economical assumption
• User nodes have GPS ( 80) or equivalent
  localization techniques to record the hubs
  visited
• Broader context of pervasive/ubiquitous computing

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Time and Space based hierarchy (e.g., life of a
graduate student!!)
City 2 Friends
Level 3 Orbit
Level 2 Orbit
Home Town
City 3 Relatives
Outdoors
Level 1 Orbit
Home
School
Potential DTN
Cafeteria
Cubicle
Kitchen
Porch/Yard
Conference Room
Living Room
Potential MANET
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Example mobility in Conference Scenario
Conference Track 2
Conference Track 1
Exhibits
Lounge
Conference Track 3
Registration
Posters
Conference Track 4
Cafeteria
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Random Orbit model and parameters
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Sociological acquaintance based query

• Acquaintance Based Soft Location Management
  (ABSoLoM)
• Our prior work (WCNC 2004) on formation and
  maintenance of acquaintances
• Use of acquaintances to query for unknown
  destination
• Inspired by the 1967 small world experiment by
  Stanley Milgram
• Random US citizens were seen to be connected by
  an average of six acquaintances six degrees
  of separation
• Sharing/caching location information via Hello
  packets
• Build a distributed database of acquaintances
  Hub lists
• Unlike acquaintanceship in ABSoLoM, in SOLAR we
  find
• No formal acquaintanceship request/response ? its
  not mutual
• Hub lists are valid longer than exact locations ?
  lesser updates
• No limit on number of acquaintances ? more
  flexible
• For unknown destination, query acquaintances for
  destinations Hub list, instead of destinations
  location
• Query hop threshold limits the process of query
  propagation

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Sociological Orbit aware Location Approximation
and Routing (SOLAR) protocol - Concept

• Subset of acquaintances to query
• Challenge Lots of acquaintances ? lot of query
  overhead
• Formulation Query a subset such that all the
  Hubs that a node learns of from its acquaintances
  are covered
• Packet Transmission to a Hub List
• All packets (query, response, data, update) are
  sent to nodes Hub list
• To send a packet to a Hub, geographically forward
  to Hubs center
• If current Hub is known unicast packet to
  current Hub
• Default simulcast separate copies to each Hub
  in list
• On reaching Hub, do Hub local flooding if
  necessary
• Improved Data Accessibility Cache data packets
  within Hub
• Data Connection Maintenance
• Two ends of active session keep each other
  informed
• Such location updates generate current Hub
  information

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SOLAR Protocol Illustration
Hub E
Hub A
Hub H
Hub D
Hub B
Hub G
Hub F
Hub I
Hub C
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Performance Analysis Metrics

• Data Throughput ()
• Data packets received / Data packet generated
• Relative Control Overhead (bytes)
• Control bytes send / Data packets received
• Approximation Factor for E2E Delay
• Observed delay / Ideal delay ? fairness issues!

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Routing Protocols (without location services)

• Dynamic Source Routing (DSR) basic flooding
• Location Aided Routing (LAR) location aware
• SOLAR with query hop threshold set to 2
• SOLAR-1 nodes only share their own hub lists
• SOLAR-2 nodes also share 1-hop neighbors hub
  lists

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Simulation Parameters (GloMoSim)
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Results Ia Throughput vs. No of Hubs
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Results Ia Overhead vs. No of Hubs
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Results Ia Delay vs. No of Hubs
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Summary

• User mobility exhibits orbital pattern
• Macro-level hub based random orbit model
• Use acquaintances to disseminate hub lists
• Query destinations hub list route to hubs
• High throughput, low overhead, low delay

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Current Work I (Probabilistic Routing)

• Intermittently Connected Mobile Ad hoc Network
  (ICMAN) with Sociological Orbits
• No contemporaneous path from source to
  destination through peers
• Store-n-forward routing techniques in addition to
  normal multihop transmissions
• Probabilities associated with hubs visited
• Study of offline and online K-shortest path
  algorithms and other SOLAR variations
• Analytical model for contact probabilities via
  Continuous Markov Chains
• Submitted to Infocom 2006

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Current Work II (Mobility Trace Analysis)

• ETH Zurich, Dept. of Computer Science
• Event logs from Access Points (4/1/04 3/31/05)
• Dr. Thomas Gross, Cristian Tuduce
• Dartmouth NH, Dept. of Computer Science
• Syslogs and SNMP Data from APs (2003 2004)
• Dr. David Kotz, Dr. Minkyong Kim
• Setting up data collection in University at
  Buffalo
• SOLAR specific analysis
• Periodic hub visits ? existence of hub lists
• Hub list size distribution ? memory constraints
• Hub list change distribution ? bound on updates

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Sociological Orbit aware Location Approximation
Routing (SOLAR) in MANET
Suggestions Comments
Joy Ghosh, Sumesh J Philip,
Chunming Qiao
Laboratory for Advanced Network Design,
Evaluation and Research (LANDER)
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Subset of acquaintances to query

• Acquaintance Ai has a Hub list Hi h1, h2, ,
  hm where hi is a Hub
• H H1, H2, , Hn is the set of Hub lists
  covered by A1, A2, , An
• C H1 U H2 U U Hn is the set of all Hubs
  covered by A1, A2, , An
• Objective find a minimum subset
• This is a minimum set cover problem NP Complete
• We use the Quine-McCluskey optimization technique

Return
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Quine-McCluskey optimization

• Acquaintance
• _
• a
• Example A 1,2, B 2,3,4, C 1,3
• A, B, C are Prime acquaintances
• B is an Essential Prime acquaintance
• Choose all the Essential Prime acquaintances
  first
• If any Hub is still uncovered, iteratively choose
  non-essential Prime acquaintances that cover the
  max number of remaining Hubs, till all Hubs are
  covered

Return
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Performance variation with Radio Hops
Return
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Results II Hub Size variations
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Results III Node Speed variations
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Results IV Radio Range variations
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Results V No. of Nodes variations
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A Random Orbit model

• Rectangular hubs placed at random in terrain
• Inter-hub Orbit (IHO) for each user (node)
• Number of hubs bounded by Hub List Size
• Time spent in hubs bounded by Hub Stay Time
• IHO Timeout allows for hub lists to change
• Mobility pattern involves two different parts
• Inter-hub Point-to-Point Linear
• Intra-hub Random Waypoint
• Any practical mobility model can be chosen for
  either or both of the two parts mentioned above!!