Architectural Framework for Large-Scale Multicast in Mobile Ad Hoc Networks
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Ahmed Helmy, USC 1
Architectural Framework for Large-Scale Multicast in Mobile
Ad Hoc Networks
Ahmed Helmy
Electrical Engineering Department
University of Southern California (USC)
http://ceng.usc.edu/~helmy
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Ahmed Helmy, USC 2
Outline
• Motivation
• Architectural Design Requirements
• Architectural Components– Multicast Service Bootstrap/Rendezvous Model– Contact-based Small World Hierarchy
Formation
• Future Work
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Ahmed Helmy, USC 3
Motivation• Target Environment
– Infrastructure-less mobile ad hoc networks (MANets)– MANets are self-organizing, cooperative networks– Expect common interests & sharing among nodes– Tens of thousands of mobile wireless nodes– Need scalable group-communication (multicast)
• Example applications:– Search and rescue (disaster relief)– Location-based service (tourist/visitor info, navigation)– Rapidly deployable remote reconnaissance and
exploration missions (military, oceanography,…)
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Ahmed Helmy, USC 4
Architectural Design Requirements
• Functional Requirements (Multicast Service)– Dynamic creation of groups– Dynamic membership (nodes join/leave at will)
• participants unknown a priori
• Robustness– Adaptive to link/node failure, and to mobility
• Scalability & Energy Efficiency– Avoids global flooding– Provides simple hierarchy formation
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Ahmed Helmy, USC 5
Architectural Components
• (1) Mechanisms for Bootstrapping of groups and Rendezvous of participants
• (2) Simple Hierarchy Formation Scheme– zone-based architecture– small world contact extensions
• (3) Multicast Routing (on-going/future work)
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Ahmed Helmy, USC 6
First Architectural Component: (1) Bootstrap and Rendezvous Mechanisms
• Problem Statement:– 1. Provide a rendezvous mechanism for group
participants (senders and receivers) to meet– 2. Provide a bootstrap mechanism to initiate and
discover new groups
• Approach:– View the problem as that of resource discovery
• Design a scalable efficient scheme to search for and discover resources (information about groups and senders)
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Ahmed Helmy, USC 7
Alternative Multicast Rendezvous Designs
• Broadcast-and-prune (flooding of packets or sender advertisements)
• Expanding ring search (scoped flooding)
• Center-based tree (rendezvous-point)
• Hierarchical (e.g., domain-based, needs AS hierarchy)
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Ahmed Helmy, USC 8
The Multicast Model• New Multicast Model: sender push, servers
cache, receivers pull
• Where are the servers located? And how do participants find these servers?– Do we have to resort to global flooding?– Can we maintain this info. in well-known
rendezvous node? (A node can move or fail, so bootstrapping will be hard)
– Use multiple nodes within a known Rendezvous Region (RR) (Still need bootstrap)
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Ahmed Helmy, USC 9
Search and Resource Discovery Scheme
• The geographic topology is divided into rendezvous regions (RRs)
• The multicast space is divided into group prefixes (Gprefix)
• Mapping between Gprefix RR is provided to all nodes (e.g., through a small table, or could also be algorithmic)
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Ahmed Helmy, USC 10
Assumptions
• Nodes know their (approximate location) [using GPS or GPS-less schemes]
• Nodes capable of geographic routing (as in location-aided routing (LAR) and geocast)
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Ahmed Helmy, USC 11
RR1 RR2 RR3
RR4 RR5 RR6
RR7 RR8 RR9
Get location ~(x,y)
RR1 Gprefix1
RR2 Gprefix2
… ...
RRn Gprefixn
(x,y)RRiGprefixi
SDS: sender discovery server
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Ahmed Helmy, USC 12
RR1 RR2 RR3
RR4 RR5 RR6
RR7 RR8 RR9
RRleave
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Ahmed Helmy, USC 13
RR1 RR2 RR3
RR4 RR5 RR6
RR7 RR8 RR9
Sender to group G
RR1 Gprefix1
RR2 Gprefix2
… ...
RRn Gprefixn
GGprefixi RRi
S
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Ahmed Helmy, USC 14
RR1 RR2 RR3
RR4 RR5 RR6
RR7 RR8 RR9
contact
geo-cast
S
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Ahmed Helmy, USC 15
RR1 RR2 RR3
RR4 RR5 RR6
RR7 RR8 RR9
contact
S
RReceiver for G
GGprefixi RRi
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Ahmed Helmy, USC 16
Bootstrap Mechanism• The goal:
– To create sessions/groups dynamically– To announce these groups– To enable interested potential participants to obtain
information about new groups
• Approach:– Designate a well-known group (WKG) address for the
‘session/group announcement group’ as a bootstrap group.
– As any other group, this group is also supported by RR
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Ahmed Helmy, USC 17
RR1 RR2 RR3
RR4 RR5 RR6
RR7 RR8 RR9
RR1 Gprefix1
RR2 Gprefix2
… ...
RRn Gprefixn
WKGGprefixj RRj
Group Initiator
WKG: Well-known Group (a bootstrap group for initiating further groups)
Bootstrap (initiating, and knowing about, groups)
GI
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Ahmed Helmy, USC 18
RR1 RR2 RR3
RR4 RR5 RR6
RR7 RR8 RR9
Bootstrap (initiating, and knowing about, groups)
GI
GI: Group Initiator
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Ahmed Helmy, USC 19
RR1 RR2 RR3
RR4 RR5 RR6
RR7 RR8 RR9
Bootstrap (initiating, and knowing about, groups)
GI
MMMulticast Member
RR1 Gprefix1
RR2 Gprefix2
… ...
RRn Gprefixn
WKGGprefixi RRi
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Ahmed Helmy, USC 20
RR1 RR2 RR3
RR4 RR5 RR6
RR7 RR8 RR9
Bootstrap (initiating, and knowing about, groups)
GI
MM
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Ahmed Helmy, USC 21
Performance Discussion
• What is the extent of the search for servers?
• We expect group initiators to choose groups that map to nearby RRs
• We expect popularity of groups in certain locations (e.g., for location-based services)
• These factors increase the chances of localizing the search for servers
• More evaluation needed (on-going work)
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Ahmed Helmy, USC 22
Architectural Components
• (1) Mechanisms for Bootstrapping of groups and Rendezvous of participants
• (2) Simple Hierarchy Formation Scheme– zone-based architecture– small world contact extensions
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Ahmed Helmy, USC 23
Second Architectural Component:(2) Simple Hierarchy formation
• Problem Statement:– To discover group/sender servers with reduced
overhead (than in flooding or pure geocast)
• Approach:– Design a simple hierarchical architecture
• Complex mechanisms incur lots of overhead with mobility and network dynamics
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Ahmed Helmy, USC 24
Alternative Hierarchical Designs• Cluster-based hierarchy using cluster heads
– Cluster heads are elected dynamically– Traffic funnels through cluster head
• Landmark Hierarchy– Landmarks advertised and used for mgmt/addressing– Re-configuration needed if landmarks move
• Needs adoption/promotion/demotion mechanisms
• Zone-based Routing– Each node has its own neighboring zone– Hybrid routing:
• pro-active within zone, re-active out of zone
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Ahmed Helmy, USC 25
Contact-based ‘small world’ Hierarchy• Neighboring zone knowledge
– A node knows routes to neighbors up to R hops away (R is the zone radius) pro-actively
– A node maintains contacts to increase its view of the network
• Simplicity & Efficiency– No elections of cluster head or landmarks– Mobility does not lead to major re-configuration– Uses the concept of Small World Graphs (six
degrees of separation)
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Ahmed Helmy, USC 26
How to Create a Small World[Watts 98]
Small-World
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Ahmed Helmy, USC 27
i
- Clustering Coefficient (C) captures how many of a node’s neighbors are also neighbors for each other
i
Clustering = 3 Clustering = n.(n-1)/2 = 6
Clustering Coefficient for node i (Ci) = 3/6 = 0.5
(a) Given network (b) Fully connected network
Node i has n neighbors
Clustering
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Ahmed Helmy, USC 28
Small World Characteristics
0
0.2
0.4
0.6
0.8
1
0.0001 0.001 0.01 0.1 1
probability of re-wiring (p)
Clustering
Path Length
Desirable Region [Watts 98]
(C)
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Ahmed Helmy, USC 29
Taking Advantage of Mobility• Small world graphs
– Adding a small number of random short-cuts drastically reduces the average path length of graph
– For our case: choosing random nodes leads to unpredictable overhead.
• Choosing contacts:• Choose nodes whose characteristics you know (your
neighbors).
• When they move, they will have a network view with less overlap.
• The resulting graph may tend to a small world graph.
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Ahmed Helmy, USC 30
Center NodeInternal NodeR
C
1 3
4
56
7
2
Border Node
Zone Radius
Mobility
• Example of zoning: – Zone for center node C is shown (with radius R). Border nodes are
numbered (1-7). Nodes 1,3 and 6 are moving/drifting out of zone.
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Ahmed Helmy, USC 31
R
R
R
R
C
5
1
4
3
6
7
2
contact
contact
contact
Route
• C stays in contact with the drifting nodes using low overhead,
which enables it to obtain better network coverage.
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Ahmed Helmy, USC 32
Choosing Contacts• A node chooses its contacts with probability p
proportional to – Energy estimates Eest of the node and the contact,
– Their relative stability Sest, and
– Activity level of the node Aest measured as rate of discovery requests.
• Also, p is inversely proportional to the number of zone contacts Zest.
• p EestSest Aest / Zest
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Ahmed Helmy, USC 33
Choosing Contacts (contd.)• Eest: Energy estimate for the lifetime of the node
itself and the contact node– Eleft: Energy left
E: Energy drainage rate
– Eest (Eleft / E)node(Eleft / E)contact
• Sest: Relative stability (possible presentation)
– (,t) model: estimates probability that nodes within range at t0 will be in range at t
– Received Power model: • RxdPwr/TxdPwr = 1/dn; where n=2 or 4
• RxdPwrnew/RxdPwrold << 1 then nodes moving away
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Ahmed Helmy, USC 34
Conclusion• Designed architectural framework to
support multicast service in large-scale Ad Hoc networks
• Introduced the concept of rendezvous regions (RRs) as a base for bootstrapping and rendezvous mechanisms
• Introduced a new contact-based zone hierarchy based on small world concepts
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Ahmed Helmy, USC 35
On-going and Future Work• Detail and evaluate contact selection and
maintenance mechanisms
• Investigate contact-based hierarchy parameters– zone radius (R), number of contacts, max contact
distance, depth of contact query– performance evaluation in terms of degrees of
separation, selection/maintenance overhead, query response delay
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Ahmed Helmy, USC 36
Future Work (contd.)• Study characteristics of the graphs resulting
from the contact-based hierarchy
• Evaluate the efficiency of the search for group/sender servers under various scenarios
• Design the multicast routing component– Mesh-based with on-demand activation of
alternative paths
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Ahmed Helmy, USC 37
RR1 RR2 RR3
RR4 RR5 RR6
RR7 RR8 RR9
S
R1
R2
R3 R4
Popularity overhead
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Ahmed Helmy, USC 38
RR1 RR2 RR3
RR4 RR5 RR6
RR7 RR8 RR9
S
R1
R2
R3 R4
elected local SDS
Popularity-based optimization: Local SDS election based on group popularity