SOLAR Joy Ghosh, Sumesh J. Philip, Chunming Qiao {joyghosh, sumeshjp, qiao}@cse.buffalo
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Transcript of SOLAR Joy Ghosh, Sumesh J. Philip, Chunming Qiao {joyghosh, sumeshjp, qiao}@cse.buffalo
SOLAR Joy Ghosh, Sumesh J. Philip, Chunming Qiao
{joyghosh, sumeshjp, qiao}@cse.buffalo.edu
Sociological Orbit aware Location Approximation and Routing
A Random Orbit Model and its Parameters
Living
Kitchen Porch
Conf. Room
Cafe Cubicle
HomeSchool
Outdoors
Home Town
City 2Friends
City 3Relatives
MANET
Level 3
Level 2
Level 1
IntermittentlyConnectedNetworks
Sociological Orbits
Conference Track 1
Conference Track 3
Cafeteria
Lounge
Conference Track 2
Conference Track 4
PostersRegistration
Exhibits
Hub A
Hub C
Hub B
Green’s IHO: Hubs A, B, C
Hub D Hub E
Hub F
Blue’s IHO: Hubs D, F
Red’s IHO: Hubs E, F
IHM of individual nodes
IHM: Random Waypoint; IHO: P2P Linear
SOLAR Variations: Ongoing Research
• Non-probabilistic – Geographic forwarding to hubso SOLAR Sequential – to all hubs in sequenceo SOLAR Simulcast – to all hubs simultaneouslyo SOLAR Multicast – to a multicast tree of hubs
• Probabilistic – Intermittently connected networkso SOLAR-P – forward to hubs in probabilistic ordero SOLAR-KSP – K-shortest paths; store & forward routing
Key Concepts
• Every user periodically visits a list of places of social interests (i.e., hubs)• Can utilize such mobility information for location approximation and routing• Examples (at right):
• User 1 (green), User 2 (blue) and User 3 (red) attending a conference• User 3 queries User 2 for the hub list of User 1• User 3 sends data to User 1
• Advantage of Macro-level (hub-based) sociological orbital mobility profile• does not require continuous location monitoring• does not depend on exact movement in time or space• acquaintance-based soft location management• captures probabilistic routing in MANET & other networks (e.g., ICN)
Query Optimization – 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 H’ of H such that:
• This is a minimum set cover problem – NP Complete• Possible solutions: Greedy Set Cover, Primal-Dual Schema, etc.• Minimizes the number of queries and optimizes the cache size
General Parameters
Simulation time 1000s Terrain size 1000m X 1000m
No. of nodes Vary, (Default = 100) Radio range Vary, (Default = 200m)
MAC protocol IEEE 802.11 Mobility model Random Orbit
SOLAR Parameters
Total hubs Vary, (Default = 15) Hub size Vary, (Default = 200m)
Hub stay time 50s – 100s IHO Timeout 250s – 500s
Hub list size 2 – Total hubs Inter-hub speed Vary,
(Default = 10m/s – 30m/s)
Intra-hub pause 1s Intra-hub speed 1m/s – 10m/s
Traffic Parameters
CBR connections
200 Random
(5 packets each)
Data payload 512 bytes per packet
Conference Track 2
SOLAR Simulcast: Location Query and RoutingConference Track 1
Conference Track 3
Cafeteria
Lounge
Conference Track 2
PostersRegistration
Exhibits
(b) Geographic forwarding of data to destination
Conference Track 4Conference Track 4
Conference Track 1
Conference Track 3
Cafeteria
Lounge
PostersRegistration
Exhibits
(a) Geographic forwarding of location query to acquaintance
Hub Centers
Research Issues:
• Routing Objectives: • Maximize data throughput (under energy and memory constraints)• Minimize control overhead (number of location queries/updates)• Minimize number of logical hops required for each location query• Minimize number of acquaintances maintaining throughput• Minimize the end-to-end delay (location query + data delivery)
• Routing Variable:• Cache size (number of acquaintances)• Logical hop threshold (acquaintance to acquaintance lookup)• Hub list discovery probability (reliability of location approximation)
• Optimization problems:• What is the minimum cache size required to achieve a desired discovery probability within a fixed number of search steps?• Given a fixed cache size, what is the minimum number of search steps required to achieve desired reliability?• What is the probability of Hub list discovery within a fixed number of search steps given a fixed cache size?
Performance of SOLAR vs. conventional protocols
SOLAR achieves high throughput, low control (signaling) overhead, and reasonable delay (even for destinations far away)
Laboratory for Advanced Network Design, Evaluation and Research (LANDER)