Clustering in

1
Clustering in Mobile Ad hoc Networks
2
Why Clustering?

• Cluster-based control structures provides more
  efficient use of resources for large dynamic
  networks
• Clustering can be used for
• Transmission management (link-cluster
  architecture)
• Backbone formation
• Routing Efficiency

3
Link-Clustered ArchitectureBaker 1981a,
1981b, Ephremides 1987

• Reduces interference in multiple-access broadcast
  environment
• Distinct clusters are formed to schedule
  transmissions in a contention-free way
• Each cluster has a clusterhead, one or more
  gateways and zero or more ordinary nodes
• Clusterhead schedules transmission and allocates
  resources within its cluster
• Gateways connect adjacent clusters
• To establish link-clustered control structure
• Discover neighbors
• Select clusterhead to form clusters
• Decide on gateways between clusters

4
Link-Clustered ArchitectureBaker 1981a,
1981b, Ephremides 1987
5
Clusterheads

• Resemble base stations in cellular networks, but
  dynamic
• Responsible for resource allocation
• Maintains network topology
• Acts as routers forwards packets from one node
  to another
• Aware of its cluster members
• Aware of its one-hop neighboring clusterheads
• Since clusterheads decide network topology,
• election
• of clusterheads optimally is critical

6
Previous Work

• Highest-Degree Heuristic Gerla 1995, Parekh
  1994
• Computes the degree of a node based on the
  distance (transmission range) between the node
  and the other nodes
• The node with the maximum number of neighbors
  (maximum degree) is chosen to be a clusterhead
  and any tie is broken by the node ids
• Drawbacks
• A clusterhead cannot handle a large number of
  nodes due to resource limitations
• Load handling capacity of the clusterhead puts an
  upper bound on the node-degree
• The throughput of the system drops as the number
  of nodes in cluster increases

7
Previous Work

• Lowest-ID Heuristic Baker 1981a, 1981b,
  Ephremides 1987
• The node with the minimum node-id is chosen to be
  a clusterhead
• A node is called a gateway if it lies within the
  transmission range of two or more clusters
• Distributed gateway is a pair of nodes that
  reside within different clusters, but they are
  within the transmission range of each other
• Drawbacks
• Since it is biased towards nodes with smaller
  node-ids, leading to battery drainage
• It does not attempt to balance the load across
  all the nodes

8
Previous Work

• Node-Weight Heuristic Basagni 1999a, 1999b
• Node-weights are assigned to nodes based on the
  suitability of a node being a clusterhead
• The node is chosen to be a clusterhead if its
  node-weight is higher than any of its neighbors
  node-weights and any tie is broken by the minimum
  node ids
• Drawbacks
• No concrete criteria of assigning the
  node-weights
• Works well for quasi-static networks where the
  nodes do not move much or move very slowly

9

Weighted Clustering Algorithm (WCA) Chatterjee
2000, 2002

• A clusterhead can ideally support nodes
• Ensures efficient MAC functioning
• Minimizes delay and maximizes throughput
• A clusterhead uses more battery power
• Does extra work due to packet forwarding
• Communicates with more number of nodes
• A clusterhead should be less mobile
• Helps maintain same configuration
• Avoids frequent WCA invocation
• A better power usage with physically closer nodes
• More power for distant nodes due to signal
  attenuation

10
Weighted Clustering Algorithm (WCA) Steps

• 1. Compute the degree dv each node v
• Coordinate distance, predefined transmission
  range.
• Compute the degree-difference for every node
• For efficient MAC (medium access control)
  functioning.
• Upper bound on of nodes a cluster head can
  handle.

11
Weighted Clustering Algorithm (WCA) Steps

• 3. Compute the sum of the distances Dv with all
  neighbors
• Energy consumption more energy for greater
  dist. communication.
• Power required to support a link increases
  faster than
• linearly with distance. (For cellular
  networks)

12
Weighted Clustering Algorithm (WCA) Steps

• 4. Compute the average speed of every node
  gives a measure of
• mobility Mv
• where and are the
• coordinates of the node at time and
• Component with less mobility is a better
  choice for clusterhead.

13
Weighted Clustering Algorithm (WCA) Steps

• Compute the total (cumulative) time Pv that a
  node acts as clusterhead
• Battery drainage Power consumed
• 6. Calculate the combined weight Wv for each
  node
• Wv w1?v w2Dv w3Mv w4Pv for each
  node
• 7. Find min Wv choose node v as the cluster
  head, remove all
• neighbors of v for further WCA
• Repeat steps 2 to 7 for the remaining nodes

14
Load Balancing Factor (LBF)

• It is desirable to balance the loads among the
  clusters
• Load balancing factor (LBF) has defined as
  (should be high)

where,
is the number of clusterheads
is the cardinality of cluster i and
is the average number of neighbors of a
clusterhead (N being the total number of nodes
in the system)
15
Connectivity

• For clusters to communicate with each other, it
  is assumed that clusterheads are capable of
  operating in dual power mode
• A clusterhead uses low power mode to communicate
  with its immediate neighbors within its
  transmission range and high power mode is used
  for communication with neighboring clusters
• Connectivity is defined as (for multiple
  component graph)
• Probability that a node is reachable from any
  other node
• ( 0 1 1 being most desirable)

16

Scattered nodes in the network
17

Clusterheads are identified
18

Clusters are formed
19

Clusters are connected
20
Features of WCA

• Invocation of WCA is on-demand
• Reduces information exchange by less system
  updates
• Reduces computation/communication costs
• Manages mobility by reaffiliations
• Delays (avoids) invocation of clustering as far
  as possible
• WCA is distributive
• No clusterhead is over loaded
• Balances load by limiting the cluster size

21
Performance Metric

• Number of clusterheads
• Number of reaffiliations
• a process where a node detaches from one
  clusterhead and attaches to another
• Number of dominant set updates
• when a node can no longer attach to any of the
  existing clusterheads
• These parameters are studied for the varying
• number of nodes
• transmission range
• maximum displacement

22
Simulation Environment

• System with N nodes on a 100x100 grid
• N was varied between 20 and 60
• Nodes moved in all directions randomly
• Velocity of nodes were varied uniformly between 0
  and 10
• Transmission range of nodes was varied between 0
  and 70
• Ideal degree was fixed at 10
• Weighing factors w1 0.7, w2 0.2, w3 0.05
  and w4 0.05

23
Experimental Results
24
Experimental Results
25
Load Balancing
26
Connectivity
27
Performance of WCA
28
References

• Baker 1981a D.J. Baker and A. Ephremides, A
  Distributed Algorithm for Organizing Mobile Radio
  Telecommunication Networks, Proceedings of the
  2nd International Conference on Distributed
  Computer Systems, April 1981, pp. 476-483.
• Baker 1981b D.J. Baker and A. Ephremides, The
  Architectural Organization of a Mobile Radio
  Network via a Distributed Algorithm, IEEE
  Transactions on Communications COM-29(11), 1981,
  pp. 1694-1701.
• Basagni 1999a S. Basagni, Distributed
  Clustering for Ad hoc Networks, Proceedings of
  International Symposium on Parallel
  Architectures, Algorithms and Networks, June
  1999, pp. 310-315.
• Basagni 1999b S. Basagni, Distributive and
  Mobility-Adaptive Clustering for Multimedia
  Support in Multi-hop Wireless Networks,
  Proceedings of Vehicular Technology Conference,
  VTC, Vol. 2, 1999-Fall, pp. 889-893.
• Chatterjee 2002 M. Chatterjee, S. K. Das and
  D. Turgut, WCA A Weighted Clustering Algorithm
  for Mobile Ad hoc Networks. Journal of Cluster
  Computing (Special Issue on Mobile Ad hoc
  Networks), Vol. 5, No. 2, April 2002, pp.
  193-204.
• Chatterjee 2000 M. Chatterjee, S. K. Das and
  D. Turgut, An On-Demand Weighted Clustering
  Algorithm (WCA) for Ad hoc Networks. IEEE
  GLOBECOM 2000, pp. 1697-1701.
• Ephremides 1987 A. Ephremides J.E. Wieselthier
  and D.J. Baker, A Design Concept for Reliable
  Mobile Radio Networks with Frequency Hopping
  Signaling, Proceedings of IEEE, Vol. 75(1), 1987,
  pp. 56-73.
• Parekh 1994 A.K. Parekh, Selecting Routers in
  Ad-hoc Wireless Networks, Proceedings of the
  SBT/IEEE International Telecommunications
  Symposium, August 1994.