Clustering in
Mobile Ad hoc Networks
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
Link-Clustered Architecture
[Baker+ 1981a, 1981b, Ephremides+ 1987]
–
Reduces interference in multiple-access broadcast environment
–
Distinct clusters are formed to schedule transmissions in a contentionfree 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
1.
Discover neighbors
2.
Select clusterhead to form clusters
3.
Decide on gateways between clusters
Link-Clustered Architecture
[Baker+ 1981a, 1981b, Ephremides+ 1987]
Cluster
Clusterhead
Gateway
Ordinary node
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
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
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 balance the load for across all the nodes
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 neighbor’s 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
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 to maintain same configuration
– Avoids frequent WCA invocation
 A better power usage with physically closer nodes
– More power for distant nodes due to signal attenuation
Weighted Clustering Algorithm (WCA) Steps
1. Compute the degree dv each node v
d v  | N (v ) | 
 dist v, v   tx 
'
range
'
'
v V , v v
Coordinate distance, predefined transmission range.
2. Compute the degree-difference for every node
v  | d v   |
For efficient MAC (medium access control) functioning.
Upper bound on # of nodes a cluster head can handle.
Weighted Clustering Algorithm (WCA) Steps
3. Compute the sum of the distances Dv with all neighbors
Dv 
 dist v, v 
3
2
12
'
v N (v )
'
1
7
17
13
14
16
6
Energy consumption; more energy for greater dist.
communication.
Power required to support a link increases faster than
linearly with distance. (For cellular networks)
4
15
5
Weighted Clustering Algorithm (WCA) Steps
4. Compute the average speed of every node; gives a measure of
mobility Mv
1 T
Mv  T 
t 1
where
X t  X t 1  Y t Y t 1
X t , Y t 
2
X t 1,Y t 1 are the
and
coordinates of the node
2
v
at time
t
and
Yt
Yt-1
time
Xt-1 Xt
t 1
Component with less mobility is a better choice for clusterhead.
Weighted Clustering Algorithm (WCA) Steps
5. Compute the total (cumulative) time Pv a node acts as
clusterhead
Battery drainage = Power consumed
6. Calculate the combined weight Wv for each node
Wv = w1Δv + 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
8. Repeat steps 2 to 7 for the remaining nodes
Load Balancing Factor (LBF)
 It is desirable to balance the loads among the clusters
 Load balancing factor (LBF) has defined as (should be high)
LBF 
nc
i  x i   
2
where,
nc
xi


is the number of clusterheads
is the cardinality of cluster i
and
N  nc is the average number of neighbors of a clusterhead
nc
(N being the total number of nodes in the system)
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)
connectivity 
size of largest component
N
 Probability that a node is reachable from any other node
( 0 – 1; 1 being most desirable)
Scattered nodes in the network
Clusterheads are identified
Clusters are formed
Clusters are connected
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
Performance Metric
1. Number of clusterheads
2. Number of reaffiliations
– a process where a node detaches from one clusterhead and
attaches
to another
3. 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
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
Experimental Results
Max displacement = 5 (const)
Transmission range = 0 - 70
Number of nodes = 20 - 60
Ideal degree
= 10
Experimental Results
Max displacement = 1 - 10
Transmission range = 30 (const)
Number of nodes = 20 - 60
Ideal degree
= 10
Load Balancing
Connectivity
Performance of WCA
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.