Network Wide Broadcast in MultiHop Wireless Networks

1
Network Wide Broadcast in Multi-Hop Wireless
Networks

• Some slides adapted from Broadcast Storm authors
  presentation

2
Network Wide Broadcast Problem

• Network Wide Broadcast (NWB)
• send a message to all nodes in the network
• May not have topology information
• NWB used for
• Routing
• Paging
• Group communication
• Try to take advantage of MAC level broadcast
• One transmission covers multiple receivers
• Dont have to know who is in range with you

3
Preliminaries

• The broadcast is spontaneous.
• no synchronization
• no prior global topology knowledge we relax
  this later
• The broadcast is unreliable.
• no acknowledgement of any kind
• Why? Think about it
• not to cause more contention
• 100 reliability is unnecessary for some
  application
• Performance Metrics?
• Overheaddoes it make sense? How about normalized
  overhead?
• Robustnesshow to measure that? (coverage?)

4
Saving Rebroadcasts
5 forwarding nodes 4 hop time
6 forwarding nodes 3 hop time
source
source
Can cover allbut extra Latency and lower
reliability
Floodinghigh overhead, But shortest paths?
5
NWB by Flooding

• A straight-forward approach
• A host rebroadcasts the message on receiving a
  broadcast message for the first time.
• Broadcast storm problem
• redundant rebroadcasts
• contention problem
• collision problem
• But maybe the redundancy is useful to improve
  robustness? Next time we examine this angle

6
Analysis of Redundancy

• Additional Coverage provided by a rebroadcast.
• The max. additional coverage is 61.
• The coverage is 41 in average.

• The expected additional coverage EAC(k)/?r2 after
  a host heard a broadcast message k times.

7
Analysis on Contention

• Analysis on Contention

• When a host broadcasts, its neighbors are likely
  to contend with each other for the medium.
• A gt B, C, D
• B, C, D could seriously contend with each other.

B
A
C
D
8
Broadcast Losses

• Higher Possibility of Collision and broadcast
  loss
• Rebroadcasts are likely to start at the same
  time.
• Backoff window runs out if medium is quiet for a
  while.
• hidden terminal problem
• Wireless propagation losses
• No Acknowledgements and retransmitslosses are
  fatal we get only one shot
• What are the implications?

9
Broadcast Storm Problem Summary

• Redundancy
• Contention
• Collision and losses
• How to derive an efficient scheme for
  broadcasting in a MANET?

10
Possible Broadcast Solutions

• Probabilistic Scheme
• Counter-Based Scheme
• Distance-Based Scheme
• Location-Based Scheme
• Cluster-Based Scheme

11
Serious Redundancy

• Optimal broadcasting vs. Flooding
• (a) optimal 2 steps
• (b) optimal 2 steps

• Severity of Redundant Coverage.

12
Probabilistic Scheme

• Rebroadcast by Tossing a Die
• A host always rebroadcasts with a certain
  probability P.
• When P 1, this is flooding.
• A smaller P will reduce the storm effect.
• This approach is also known as gossiping in
  distributed systems
• It has well known and analyzed properties

13
Simulation Parameters

• no of hosts 100
• transmission radius 500 meters
• packet size 280 bytes
• transmission rate 1 M bits/sec
• broadcast arrival rate 1 per sec. to the whole
  map
• map (1 unit 500 meters)
• 1x1, 3x3, 5x5, 7x7, 10x10
• roaming pattern random walk
• speed 010 km/hr in a 1x1 map, 030 km/hr in a
  3x3 map, etc.
• IEEE 802.11

14
Performance of Probabilistic Scheme

• RE REachability (in lines)
• SRB Saved ReBroadcast (in bars)

Latency
15
Observation

• Reachability
• In smaller maps, a low P is sufficient to achieve
  high reachability.
• A larger P is needed in a larger map.
• Saved Rebroadcast
• linear with respect to P
• Latency
• Interestingly, in smaller areas, broadcast tends
  to complete in a slower speed.

16
Counter-Based Scheme

• If a host has received a broadcast packet gt C
  times,
• then do not rebroadcast.
• Examples Addition Coverage
• 1 time gt 41
• 2 times gt 19
• 3 times gt 9
• 4 times gt 5
• gt 4 times, very little extra area

17
Performance of Counter-Based Scheme

• We vary C 2, 3, ..., 6 to observe the
  performance.
• A larger C means more rebroadcast.

18
Observation

• Reachability
• C gt 3 can offer a reachability close to
  flooding.
• Saved Rebroadcast
• In denser area, there is more saving. In sparser
  area, there is less saving.
• Latency
• Higher latency is smaller area.

19
Distance-Based Scheme

• Calculate the distance to the sending host.
• dmin Minthe distance to each sending host
• If dmin lt D (a threshold), then do not
  rebroadcast.
• How to find distance
• signal strength
• GPS devices

20
Performance of the Distance-Based Scheme

• We vary D 147, 72, 37, 20, 11 to observe the
  effect.
• Smaller D means more rebroadcasting.

21
Observation

• Why choosing D147?
• addition coverage 0.187, equal to that of C2
• Reachability
• All look good, close to flooding.
• Saved Rebradcast
• not much
• Latency
• smaller area has higher latency

22
Location-Based Scheme

• From GPS to obtain the senders location.
• Let (x1, y1), (x2, y2), (x3, y3), ..., (xk, yk)
  be locations of senders.
• We can accurately calculate the additional
  coverage of this rebroadcast.

23
Difficulty

• Involve complicated math to calculate the extra
  coverage.
• A lot of calculus!
• Approximation
• grid simulation

S1
A
S3
S2
24
Performance of the Location-Based Scheme

• We vary A (addition coverage) from 0.1 to 0.01.
• Smaller A means more rebroadcast.

25
Observation

• Why choosing A0.187?
• This is additional coverage offered by C2.
• Best performance over all the above schemes!

26
Modified Location-Based Schemes

• Polygon Test
• If a node is within the polygon formed by the
  locations of senders, then DO NOT rebroadcast.
  (Fig. (a))
• Otherwise, rebroadcast. (Fig. (b))
• If a host is within the convex, the maximum
  additional coverage is well below 22. (Fig. (c))

27
A Short Summary

• Main Concern
• Extra coverage of a rebroadcast
• Different levels of accuracy
• probabilistic, counter, distance, location,
  polygon
• Probabilistic not sensitive to the importance of
  a retransmission
• Maybe ok in dense networks
• Others are sensitive, with increasing accuracy of
  estimate (and increasing amount of work needed)
• Counter-Based Scheme lt Distance-Based Scheme lt
  Location-Based

28
Cluster-Based Scheme

• Cluster formation algorithm
• Each host has a unique ID
• A host with a local minimal ID will elect itself
  as a cluster head.
• This head host together with its neighbor will
  form a cluster.
• These neighbor hosts are called member of the
  cluster.

29
Cluster-Based Scheme

• Cluster formation protocol
• A heads rebroadcast can cover all other hosts in
  that cluster if its transmission experience no
  collision.
• Gateway hosts should take the reponsibility to
  propogate the broadcast msg to hosts in other
  clusters.
• There is no need for a non-gateway member to
  rebroadcast the msg.

30
Follow up work by the same authors (ICDCS 2001)

• In the above solutions, the thresholds used are
  ALL FIXED.
• NOT sensitive to the current status of the
  network.
• Example In the counter-based scheme, we may need
  different threshold C depending on the density of
  the network.
• Why not make the threshold adaptive to the
  network status?
• They explore this idea it works fine

31
Brief Taxonomy of Approaches

• Topology Ambivalent (or flooding based)
• No knowledge of neighbors assumed
• Starting point is flooding
• These are the broadcast storm solutions weve
  seen so far
• Another approach is possible Topology aware
• General approach use network topology
  information to intelligently decide who should
  rebroadcast
• Cluster based approach is an example
• Centralized solution figure out the minimum set
  of rebroadcasting nodes to cover all (Minimum
  Connected Dominating Set MCDS)
• Centralized unrealistic
• Does not consider that rebroadcasts are unreliable

32
Minimum Forwarding Set Problem

• Define
• Given a source A
• let D and P be the sets of k and k1 hop
  neighbors of A
• Find a minimum-size subset F of D such that every
  node in P is within the coverage area of at least
  one node from F
• In general graph
• NP-complete reduce Set Cover to it
• Approximation ratio logn
• In unit disk graph
• Unknown
• Approximation ratio constant

33
Minimum Broadcasting Set Problem

• Define
• Given a source A
• Find a spanning tree T such that the number of
  internal nodes is minimum
• In general graph
• NP-hard hard to Minimum Connected Dominating
  Set
• Approximation ratio log? (? is the maximum
  node degree)
• In unit disk graph
• NP-hard
• Approximation ratio constant

34
Hiearchical Domination-set-based
School bus routing
Next few slides from Prof. Jie Wu at FAU
35
Graph-theoretic Definition
A set in G(V, E) is dominating if all the nodes
in the system are either in the set or neighbors
of nodes in the set.
36
Five-Queen Problem (1850s)
37
Desirable Features

• Simple and quick
• Connected dominating set

Figure 6 A simple ad hoc wireless network of
five wireless mobile hosts.
38
Existing Approaches

• Graph theory community
• Bounds on the domination number (Haynes,
  Hedetniemi, and Slater, 1998).
• Special classes of graph for which the domination
  problem can be solved in polynomial time.

39
Existing Approaches (Contd.)

• Ad hoc wireless network community
• Global MCDS (Sivakumar, Das, and Bharghavan,
  1998).
• Quasi-global spanning-tree-based (Wan, Alzoubi,
  and Frieder, 2002).
• Quasi-local cluster-based (Lin and Gerla, 1999).
• Local marking process (Wu and Li, 1999).

40
MCDS (Sivakumar, Das, and Bharghavan, UIUC)

• All nodes are initially colored white.
• The node with the maximum node degree is selected
  as the root and colored black. All the neighbors
  of the root are colored gray.
• Select a gray node that has the maximum white
  neighbors. The gray node is colored black and its
  white neighbors are marked gray.
• Repeat step (3) until there is no more white node.

41
MCDS (Contd.)

• black nodes CDS (connected dominating set)

Figure 7 MCDS as an approximation of CDS
42
Spanning-tree-based (Wan, Alzoubi, and Frieder,
IIT)

• A spanning tree rooted at v (selected through an
  election process) is first constructed.
• Nodes are labeled according to a topological
  sorting order of the tree.

43
Spanning-tree-based (Contd.)

• Nodes are marked based on their positions in the
  order starting from root v.
• All nodes are white initially.
• V is marked black and all nodes are labeled black
  unless there is a black neighbor.
• Each black node (except root v) selects a
  neighbor with the largest label but smaller than
  its own label and mark it gray.

44
Spanning-tree-based (Contd.)

• black nodes DS
• black nodes gray nodes CDS

Figure 8 selecting CDS in a spanning tree
45
Cluster-based (Lee and Gerla, UCLA)

• All nodes are initially white.
• When a white node finds itself having the lowest
  id among all its white neighbors, it becomes a
  cluster head and colors itself black.
• All its neighbors join in the cluster and change
  their colors to gray.

46
Cluster-based (Contd.)

• Repeat steps (1) and (2) until there is no white
  node left.
• Special gray nodes gray nodes that have two
  neighbors in different clusters.

47
Cluster-based (Contd.)
black nodes DS black nodes special gray
nodes CDS
Figure 9 sequential propagation in the
cluster-based approach.
48
Localized Algorithms

• Processors (hosts) only interact with others in a
  restricted vicinity.
• Each processor performs exceedingly simple tasks
  (such as maintaining and propagating information
  markers).
• Collectively these processors achieve a desired
  global objective.
• There is no sequential propagation of
  information.

49
Marking Process (Wu and Li, 1999)

• A node is marked true if it has two unconnected
  neighbors.
• A set of marked nodes (gateways nodes) V form a
  connected dominating set.

50
Marking Process (Contd.)
Figure 10 A sample ad hoc wireless network
51
Dominating Set Reduction

• Reduce the size of the dominating set.
• Role of gateway/non-gateway is rotated.

52
Dominating Set Reduction (Contd.)

• N v N (v) U v is a closed neighbor set of v
• Rule 1 If N v ? N u in G and id(v) lt id(u),
  then unmark v.
• Rule 2 If N (v) ? N (u) U N (w) in G and id(v)
  minid(v), id(u), id(w), then unmark v.

53
Dominating Set Reduction (Contd.)
Figure 12 two sample examples
54
Example
Figure 13 (a) Dominating set from the marking
process (b) Dominating set after dominating set
reduction
55
Topology Aware Approaches

• Neighborhood information
• How to decide forwarding nodes
• Dynamically, or Neighborhood base
• Scalable Broadcast Algorithm (SBA), Flooding with
  Self pruning
• Statically, or Set cover base
• Multipoint relaying, Dominant pruning, Ad hoc
  Broadcast Protocol (AHBP)
• MCDS base

56
Scalable Broadcast Algorithm (SBA)

• Information
• Hello message (2-hop)
• Forwarding node decision
• Node vj who receives the packet from vi checks
  whether the set N(vj)-N(vi)-vi is empty
• Node vj schedules the packet for delivery with a
  RAD
• (Random Assessment Delay)
• Dynamically adjust the RAD to
• (nodes with the most neighbors usually
  broadcast
• before the others)

57
Self pruning

• Information
• Hello message (1-hop)
• Piggyback adjacent node list in broadcast packets
• (2-hop)
• Store adjacent node list in cache
• Forwarding node decision
• Node vj who receives the packet from vi checks
  whether the set N(vj)-N(vi)-vi is empty

vj
vi
58
Multipoint relaying

• Information
• Hello message (2-hop)
• Forwarding node decision
• The sending node A selects forwarding nodes from
  its adjacent nodes
• A select a minimum node set F ? N(A) such that
• A node set U N(N(A)) N(A)
• Piggyback forward list in Hello packets

59
Dominant pruning

• Information
• Hello message (2-hop)
• Forwarding node decision
• The sending node selects forwarding nodes from
  its adjacent nodes
• Node vj who receives the packet from vi , vj
  select a minimum node set F ? N(vj) - N(vi) such
  that
• A node set U N(N(vj)) N(vi) N(vj)
• Piggyback forward list in broadcast packets

60
Dominant pruning
N(N(vj))
N(vi)
N(vj)
B(vi,vj)
U
61
The drawback of present set cover based protocols1
When a node vi received the broadcast packet
from node vi-1, it will select some forwarding
nodes from N(vi)-N(vi-1) to cover all nodes in
U. However, some nodes in U are not i2 level
nodes, and some nodes in N(vi)-N(vj) are not
i1 level nodes.
vi
vi-1
s

i-1
i
i1
i2
62
The drawback of present set cover based protocols2
When we will select some level i1 nodes to cover
all level i2 nodes, the number of forwarding
nodes selected by distributed algorithm can not
be bounded to some ratio of the optimal solution
?
vi2
vi-1
s
vi1

i-1
i
i1
i2
63
Comparison
350x350 r100
64
Robustness of Network Wide Broadcasts (NWBs)
65
NWB Algorithms--Recap

• Optimized NWB algorithms cut down on the number
  of broadcasts Redundancy control
• Topology Aware vs. Topology Ambivalent
• Aware Collect neighbor information, construct a
  virtual backbone (CDS Approaches)
• Ambivalent Start with flooding, cut down on some
  broadcasts (based on local criteria)
• Tradeoffs Aware can reduce redundancy, has
  additional neighbor-tracking overhead

66
NWB Algorithms - 2

• Static vs. Dynamic (Topology-Aware)
• Static Forwarding nodes pre-selected by
  previous hop
• Dynamic Nodes locally decide whether to
  rebroadcast (calculates whether some neighbors
  are uncovered)
• Tradeoffs Static algorithms are more optimal
  (lower overhead), dynamic algorithms adapt to
  losses better

67
NWB Robustness Problem

• Optimizing NWBs cuts down on redundancy
• Key broadcasts can be lost, isolating sections of
  the network
• Metrics of interest
• Coverage Percentage of reachable network
  covered
• Normalized Overhead Cost associated with the
  NWB operation

68
Simulation Information

• NS-2, 802.11 MAC protocol
• 20 scenarios of 30 nodes (randomly distributed)
  20 random seeds for each scenario
• Static scenarios (some tests done with
  probabilistic random walk)
• Propagation models
• Two Ray Ground
• Shadowing Idealized harsh signal fading model

69
Characterization of NWB Robustness - Flooding
Coverage
70
NWB Robustness

• Protocols studied
• Flooding
• Location-Based Algorithm from broadcast storm
  paper
• Topology ambivalent
• Ad Hoc Broadcast Protocol (AHBP)
• Static CDS
• Scalable Broadcast Algorithm (SBA)
• Dynamic CDS
• Double-Covered Broadcast (DCB)
• Static CDS with double coverage (Infocom 2004)
• Only topology-aware algorithm with robustness
  control

71
NWB Robustness Trends

• Sparse networks are more prone to losses
• Topology-aware protocols are not as robust when
  losses occur
• Topology-aware protocols have lower overhead
• Static CDS approaches are not as robust as
  dynamic approaches

72
Coverage of NWB Protocols
73
NWB Coverage (Mobility)
74
Robustness Control

• Broadcast Storm? optimize to reduce redundancy
• Losses?figure out when to introduce redundancy to
  compensate
• Robustness control
• An effective NWB must include both aspects
• Core issue is MAC level broadcast is unreliable
• Robustness vs. Reliability

75
Solution Space for Robustness Control

• Loss-sensitive vs. fixed redundancy
• Loss-sensitive
• implicit or explicit loss detection?
• Fixed redundancy
• State-sensitive or blind redundancy?
• Network level vs. MAC level implementation
• Network level easier to implement and deploy
• can take wider range of measures in space or
  time
• -But must build on what exist at MAC level

76
Explicit Feedback

• Receivers directly receive feedback information
  regarding the NWB success
• Granularity of feedback Every packet or
  periodically?
• Number of reports Every node, some nodes, or a
  single node?

77
Implicit Feedback

• Predict losses based on observed behavior
• No explicit feedback
• Difference between a reception and a loss is the
  subsequent rebroadcasts
• Observe overheard rebroadcasts
• Can do better with some state information on
  expected rebroadcast behavior

78
MAC Primitive by Pei and Gerla (circa 1999)

• Not directly focused at NWBrather, they just
  want to make MAC broadcast more reliable
• Idea, Broadcast, but require acknowledgements
• No ACKs? Rebroadcast
• One ACK? Good, at least one person received it
• ACK explosion?
• There will be noise on the channel due to ACK
  collisions
• Optimistically guess that it is ACKs
• Ensures at least one receiver
• What is this approach in terms of the solution
  space?
• How will it work?
• Requires

79
Another MAC Primitive--Directed Broadcast

• Problemmany potential receivers difficult to
  carry out ACK/retransmit with multiple partners
• Directed Broadcast pick a partner to ACK
• Partner responds with ACK
• Others receiver but do not ACK
• Public Unicast
• Also does not ensure that all receive
• But minor modifications to MAC no new physical
  abilities needed
• Reduces load on network (not all need to ACK)
• Allows use of RTS/CTS if desired

80
Directed Broadcast

• Gives control of who is guaranteed to receive
• this can be exploited by topology-aware NWB
  algorithms
• E.g., CDS algorithms can pick a CDS member as
  partner
• Works very well for these algorithms
• But, is more difficult to use by
  topology-ambivalent algorithms
• You need to know at least one partner
• What type of solution is it?

81
Receiver Driven Sequence Numbers (Gerla)

• NWB originator uses sequence numbers for its
  broadcasts
• Each receiver keeps the last few broadcasts
• Big drawback
• When a receiver receives a packet from one of its
  neighbors, and it discovers a hole in the
  sequence numbers, it asks for a rebroadcast of
  the missing packet
• Explicit feedback, NAK based
• Can it ensure full reliability?
• Delay bounded?

82
Variations/Other possibilities

• Stagger ACKs to allow multiple responders
• Why?
• Tricky, especially when responders not known
• Variation of this exploited for Anycastwill
  discuss later
• Directed Broadcast with multiple partners
• Repeat the broadcast to a subset of nodes
• If all nodes, it becomes unicast
• Can pick all members of the CDS for example
• All of these (schemes these variations) are MAC
  based, explicit feedback with packet level
  granularity

83
Other Robustness Control

• Hyper-gossipping/Hyper-flooding
• Start with flooding or gossiping, and with a
  probability retransmit again
• Network-level, fixed redundancy, not- state
  aware
• Only Gossiping and flooding supported, not the
  more advanced redundancy control mechanisms
• But maybe the other schemes can be supported too?
• Double-Covered Broadcast (DCB)Construct a CDS
  that is doubly covered
• Each node is part of the CDS or is covered by 2
  CDS members
• Tradeoff vs. a traditional CDS?
• Network-level, fixed redundancy, not-state aware

84
Selective Additional Rebroadcast (SAR)
85
SAR

• Areas of concern are situations where loss is
  likely and the network has low redundancy
• Can we use implicit feedback to speculate whether
  a packet has been lost or not?
• Can we use state information to improve our
  guess?
• Network-level, implicit feedback, possibly state
  aware
• Basic idea
• Implicit loss detection
• Retransmit if loss is suspected
• Can be layered on top of any redundancy control
  NWB approach

86
Loss Prediction Approaches - 1

• Probabilistic
• A node that broadcasts will perform a second
  broadcast based on some probability p
• Does not use any feedback, resulting in poorer
  results
• Blindly adds robustness
• Counter-based
• A node that broadcasts waits to hear if the
  packet was sent by n neighbors
• Uses implicit feedback
• Not blind, but not adaptive

87
Loss Prediction Approaches - 2

• State-Aware (Adaptive)
• Disable SAR if past broadcasts have not been
  helpful
• Neighbor-knowledge protocols can ensure
  rebroadcasting nodes heard the broadcast
• Observe MAC utilization

88
SAR Approaches Comparison

• Probabilistic Fixed level of overhead, some
  gain in coverage, some rebroadcasts are wasteful,
  some needed rebroadcasts were missed
• Counter-Based Gain in coverage, not
  fully-optimized in terms of overhead (leaf nodes
  tend to rebroadcast)
• Adaptive Results at or above counter-based,
  lower overhead. Adjusts to network conditions

89
SAR Results
90
SAR Overhead
91
Link Quality Sensitive CDS
92
Signal Fading

• Chance of packet reception is based on a number
  of factors
• Transmit power
• Distance between nodes
• Obstacles in propagation path

93
Packet Reception
94
Link Quality Aware CDS

• Like DCB, this is a fixed-redundancy
  topology-aware approach
• Sensitive to link states
• One good link may be better than two poor links
• Build CDS that keeps weights on each path
• Attempt to cover all nodes with some probability P

95
Example
0.1
A
B
0.6
0.6
C
96
LQ CDS Coverage
97
LQ CDS Overhead
98
LQ-CDS

• Work in progress obviously needs a lot of work
• Problems
• Shadowing model is too harsh
• Most links have extremely poor qualitynetwork
  effectively very poorly connected
• Should consider a less harsh model or denser
  scenarios where there are at least some ok links
  to work with
• Does not consider that the probability of
  coverage is conditional on all the sources being
  covered
• Heuristic Solution increase retransmit
  probability with number of hops from source
• Track the cumulative probability