Title: Sociological Influences on Mobile Wireless Networks
1Sociological Influences on Mobile Wireless
Networks
- Chunming Qiao, Ph.D., Professor
- University at Buffalo (SUNY)
- Director, Laboratory for Advanced Network Design,
Evaluation and Research (LANDER) - Computer Science and Engineering Department
2Sociological Orbits
3Key Concepts
- Users movements are often socially influenced
- hubs places of social interest to users
- User mobility an orbit involving a list of
hubs - Mobility profile a list of hubs likely to be
visited - Remarks
- User mobility profiles exist but difficult to
obtain - Usefulness for routing in MANET and ICMAN and
Mobile wireless applications
4Mobility Profiling
- Obtain mobility traces (e.g., AP system logs)
- Convert AP-based traces to hub-based movements
- Obtain daily hub lists for individuals
- Apply clustering algorithms to group hub lists
together to identify patterns in movement - Represent the patterns as mobility profiles
- Profiles have been shown useful for hub-level
location predictions
5Profiling illustration
6Profile based Predictions
7Applications of Orbital Mobility Profiles
- Anomaly based intrusion detection ? unexpected
movement (in time or space) sets off an alarm - Customizable traffic alerts ? alert only the
individuals who might be affected by a specific
traffic condition - Targeted inspection ? examine only the persons
who have routinely visited specific regions upon
re-entrance. - Environmental/health monitoring ? identify
travelers who can relay data sensed at locations
with no APs - Routing within MANET and ICMAN (described next)
8Profile based Routing within MANET
- Build a sociological orbit based mobility model
(Random Orbit) - Assume that mobility profiles are obtained
- Devise routing protocols to leverage mobility
information within MANET setting - Key assumption geographical forwarding is
feasible
9A Random Orbit Model(Random Waypoint Corridor
Path)
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10Random Orbit Model
11Sociological Orbit Aware Routing - Basic
- Every node knows
- Own coordinates, Own Hub list, All Hub
coordinates - Periodically broadcasts Hello
- SOAR-1 own location Hub list
- SOAR-2 own location Hub list 1-hop neighbor
Hub lists - Cache neighbors Hello
- Build a distributed database of acquaintances
Hub lists - Unlike acquaintanceship in ABSoLoM, SOAR has
- No formal acquaintanceship request/response ? its
not mutual - Hub lists are valid longer than exact locations ?
lesser updates - For unknown destination, query acquaintances for
destinations Hub list (instead of destinations
location), in a process similar to ABSoLoM
12Sociological Orbit Aware Routing - Advanced
- Subset of acquaintances to query
- Problem Lots of acquaintances ? lot of query
overhead - Solution 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
13Sociological Orbit Aware Routing
Illustration(Random Waypoint P2P Linear)
Hub E
Hub A
Hub H
Hub D
Hub B
Hub G
Hub F
Hub I
Hub C
14Performance Analysis Metrics
- Data Throughput ()
- Data packets received / Data packets generated
- Relative Control Overhead (bytes)
- Control bytes send / Data packets received
- Approximation Factor for E2E Delay
- Observed delay / Ideal delay
- To address fairness issues!
15Performance Analysis Parameters
16Results I.a Throughput vs. Hubs
17Results I.b Overhead vs. Hubs
18Results I.c Delay vs. Hubs
19Routing challenges in ICMAN
- May not have an end-to-end path from source to
destination at any given point in time
(intermittently connected) - Conventional MANET routing strategies fail
- User mobility may not be deterministic or
controllable - Devices are constrained by power, memory, etc.
- Applications need to be delay/disruption tolerant
20User level routing strategy
- Deliver packets to the destination itself
- Intermediate users store-carry-forward the
packets - Mobility profiles used to compute pair wise user
contact probability (CP) to form weighted graph - Apply modified Dijkstras to obtain k-shortest
paths (KSP) with corresponding Delivery
probability (DP) - S-SOLAR-KSP (static) protocol
- Source only stores set of unique next-hops on its
KSP - Forwards only to max k users of the chosen set
that come within radio range within time T - D-SOLAR-KSP (dynamic) protocol
- Source always considers the current set of
neighbors - Forwards to max k users with higher DP to
destination
21Hub level routing strategy
- Deliver packets to the hubs visited by
destination - Intermediate users store-carry-forward the
packets - Packet stored in a hub by other users staying in
that hub (or using a fixed hub storage device if
any) - Mobility profiles used to obtain delivery
probabilities (DP), not the visit probability, of
a user to a given hub - Fractional data delivered to each hub
proportional to the probability of finding the
destination in it - SOLAR-HUB protocol
- Source transmits up to k copies of message
- k/2 to neighbors with higher DP to most visited
hub - k/2 to neighbors with higher DP to 2nd most
visited hub - Downstream users forward up to k users
- with higher DP to the hub chosen by upstream node
22Data Throughput vs. Number of Users
23End-to-End Data Delay vs. Number of Users
24Network Overhead vs. Number of Users
25Future Directions
- Collect and analyze user location-based traces
- Apply advanced clustering/profiling techniques
- Optimization techniques for profile information
management - Design and analyze routing algorithms
- Experimenting with Applications
26Thank You !