clustering in mobile ad hoc networks

Clustering inMobile Ad hoc Networks

Why Clustering?

– Cluster-based control structures provides more efficient use Cluster-based control structures provides more efficient use of resources for large dynamic networksof resources for large dynamic networks

Clustering can be used forClustering can be used for

– Transmission management (link-cluster architecture)Transmission management (link-cluster architecture)

– Backbone formationBackbone formation

– Routing Efficiency Routing Efficiency

Link-Clustered Architecture

[Baker+ 1981a, 1981b, Ephremides+ 1987]

– Reduces interference in multiple-access broadcast environmentReduces interference in multiple-access broadcast environment

– Distinct clusters are formed to schedule transmissions in a contention-Distinct clusters are formed to schedule transmissions in a contention-free wayfree way

– Each cluster has a clusterhead, one or more gateways and zero or Each cluster has a clusterhead, one or more gateways and zero or more ordinary nodesmore ordinary nodes

– Clusterhead schedules transmission and allocates resources within its Clusterhead schedules transmission and allocates resources within its clustercluster

– Gateways connect adjacent clustersGateways connect adjacent clusters

To establish link-clustered control structureTo establish link-clustered control structure

1.1. Discover neighborsDiscover neighbors

2.2. Select clusterhead to form clustersSelect clusterhead to form clusters

3.3. Decide on gateways between clustersDecide on gateways between clusters

Link-Clustered Architecture

[Baker+ 1981a, 1981b, Ephremides+ 1987]

Clusterhead

Gateway

Ordinary node

Cluster

Clusterheads

– Resemble base stations in cellular networks, but dynamicResemble base stations in cellular networks, but dynamic

– Responsible for resource allocationResponsible for resource allocation

– Maintains network topologyMaintains network topology

– Acts as routers – forwards packets from one node to anotherActs as routers – forwards packets from one node to another

– Aware of its cluster membersAware of its cluster members

– Aware of its one-hop neighboring clusterheadsAware of its one-hop neighboring clusterheads

Since clusterheads decide network topology, Since clusterheads decide network topology, electionelection

of clusterheads optimally is criticalof clusterheads optimally is critical

Previous Work

Highest-Degree Heuristic [Gerla+ 1995, Parekh 1994]

Computes the degree of a node based on the distance Computes the degree of a node based on the distance (transmission range) between the node and the other nodes(transmission range) between the node and the other nodes

The node with the maximum number of neighbors (maximum The node with the maximum number of neighbors (maximum degree) is chosen to be a clusterhead and any tie is broken degree) is chosen to be a clusterhead and any tie is broken by the node idsby the node ids

Drawbacks: A clusterhead cannot handle a large number of nodes due to A clusterhead cannot handle a large number of nodes due to

resource limitationsresource limitations Load handling capacity of the clusterhead puts an upper Load handling capacity of the clusterhead puts an upper

bound on the node-degreebound on the node-degree The throughput of the system drops as the number of nodes The throughput of the system drops as the number of nodes

in cluster increasesin cluster increases

Previous Work

Lowest-ID Heuristic [Baker+ 1981a, 1981b, Ephremides+ 1987]

The node with the minimum node-id is chosen to be a The node with the minimum node-id is chosen to be a clusterheadclusterhead

A node is called a A node is called a gateway gateway if it lies within the transmission range if it lies within the transmission range of two or more clustersof two or more clusters

Distributed gateway Distributed gateway is a pair of nodes that reside within different is a pair of nodes that reside within different clusters, but they are within the transmission range of each otherclusters, but they are within the transmission range of each other

Drawbacks: Since it is biased towards nodes with smaller node-ids, leading Since it is biased towards nodes with smaller node-ids, leading

to battery drainage to battery drainage It does not attempt balance the load for across all the nodesIt does not attempt balance the load for across all the nodes

Previous Work

Node-Weight Heuristic [Basagni 1999a, 1999b]

Node-weightsNode-weights are assigned to nodes based on the suitability are assigned to nodes based on the suitability of a node being a clusterheadof a node being a clusterhead

The node is chosen to be a clusterhead if its node-weight is 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 higher than any of its neighbor’s node-weights and any tie is broken by the minimum node idsbroken by the minimum node ids

Drawbacks: No concrete criteria of assigning the node-weightsNo concrete criteria of assigning the node-weights Works well for “quasi-static” networks where the nodes do Works well for “quasi-static” networks where the nodes do

not move much or move very slowlynot move much or move very slowly

AA clusterhead can clusterhead can ideallyideally support nodes support nodes– Ensures efficient MAC functioningEnsures efficient MAC functioning– Minimizes delay and maximizes throughputMinimizes delay and maximizes throughput

A clusterhead uses more battery power A clusterhead uses more battery power – Does extra work due to packet forwardingDoes extra work due to packet forwarding– Communicates with more number of nodesCommunicates with more number of nodes

A clusterhead should be less mobileA clusterhead should be less mobile– Helps to maintain same configuration Helps to maintain same configuration – Avoids frequent WCA invocationAvoids frequent WCA invocation

A better power usage with physically closer nodesA better power usage with physically closer nodes– More power for distant nodes due to signal attenuationMore power for distant nodes due to signal attenuation

Weighted Clustering Algorithm (WCA)[Chatterjee+ 2000, 2002]

Weighted Clustering Algorithm (WCA) Steps

1.1. Compute the Compute the degreedegree ddvv each node each node vv

Coordinate distance, predefined transmission range. Coordinate distance, predefined transmission range.

2.2. Compute the Compute the degree-differencedegree-difference for every nodefor every node

For efficient MAC (medium access control) functioning.For efficient MAC (medium access control) functioning.

Upper bound on # of nodes a cluster head can handle.Upper bound on # of nodes a cluster head can handle.

vvv

txvvdistvNvV

ranged''

,

',|)(|

|| dvv


3.3. Compute the Compute the sum of the distancessum of the distances DDvv with all neighbors with all neighbors

Energy consumption; more energy for greater dist.Energy consumption; more energy for greater dist.

communication.communication.

Power required to support a link increases faster thanPower required to support a link increases faster than

linearly with distance.linearly with distance. (For cellular networks)(For cellular networks)

)('

',vNv

vvdistvD 1

2 3

4

5

6

7

12 1314

1516

17


4.4. Compute the average speed of every node; gives a measure of Compute the average speed of every node; gives a measure of

mobilitymobility MMvv

where where and and are the are the

coordinates of the node at time coordinates of the node at time and and

Component with less mobility is a better choice for clusterhead.Component with less mobility is a better choice for clusterhead.

T

tYYXXM ttttTv

111

1 22

YX tt, YX tt 11,

v t 1t

Yt

Yt-1

XtXt-1

time


5.5. Compute the total (cumulative) Compute the total (cumulative) timetime PPvv a node acts as a node acts as

clusterheadclusterhead

Battery drainage = Power consumedBattery drainage = Power consumed

6.6. Calculate the Calculate the combined weightcombined weight WWvv for each node for each node

WWvv = w = w11ΔΔv v + w + w22DDv v + w + w33MMv v + w + w44PPvv for each nodefor each node

7.7. Find min Find min WWvv;; choose node choose node vv as the cluster head, remove all as the cluster head, remove all

neighbors of neighbors of vv for further WCA for further WCA

8.8. Repeat steps 2 to 7 for the remaining nodesRepeat steps 2 to 7 for the remaining nodes

Load Balancing Factor (LBF)

It is desirable to balance the loads among the clustersIt is desirable to balance the loads among the clusters

Load balancing factor (LBF) has defined as (should be high)Load balancing factor (LBF) has defined as (should be high)

i i

cLBF

xn

2

where, where,

nc is the number of clusterheads is the number of clusterheads

xi is the cardinality of cluster is the cardinality of cluster ii and and

nc

ncN is the average number of neighbors of a clusterheadis the average number of neighbors of a clusterhead

((N N being the total number of nodes in the system)being the total number of nodes in the system)

Connectivity

For clusters to communicate with each other, it is assumed that For clusters to communicate with each other, it is assumed that

clusterheads are capable of operating in clusterheads are capable of operating in dual dual power mode power mode

A clusterhead uses A clusterhead uses lowlow power mode to communicate with its immediate power mode to communicate with its immediate

neighbors within its transmission range and neighbors within its transmission range and highhigh power mode is used for power mode is used for

communication with neighboring clusterscommunication with neighboring clusters

ConnectivityConnectivity is defined as (for multiple component graph) is defined as (for multiple component graph)

Probability that a node is reachable from any other nodeProbability that a node is reachable from any other node

( 0 – 1; 1 being most desirable)( 0 – 1; 1 being most desirable)

N

componentlargestofsizetyconnectivi

Scattered nodes in the network

Clusterheads are identified

Clusters are formed

Clusters are connected

Features of WCA

Invocation of WCA is Invocation of WCA is on-demandon-demand

– Reduces information exchange by less system updates Reduces information exchange by less system updates

– Reduces computation/communication costsReduces computation/communication costs

– Manages mobility by Manages mobility by reaffiliationsreaffiliations

– Delays (avoids) invocation of clustering as far as possibleDelays (avoids) invocation of clustering as far as possible

WCA is WCA is distributivedistributive

– No clusterhead is over loadedNo clusterhead is over loaded

– Balances load by limiting the cluster sizeBalances load by limiting the cluster size

Performance Metric

1.1. Number of clusterheadsNumber of clusterheads

2.2. Number of reaffiliationsNumber of reaffiliations

– a process where a node detaches from one clusterhead and a process where a node detaches from one clusterhead and

attachesattaches

to anotherto another

3.3. Number of dominant set updatesNumber of dominant set updates

– when a node can no longer attach to any of the existing when a node can no longer attach to any of the existing

clusterheadsclusterheads

These parameters are studied for the varying These parameters are studied for the varying

number of nodesnumber of nodes

transmission rangetransmission range

maximum displacementmaximum displacement

Simulation Environment

System with N nodes on a 100x100 gridSystem with N nodes on a 100x100 grid

N was varied between 20 and 60N was varied between 20 and 60

Nodes moved in all directions randomly Nodes moved in all directions randomly

Velocity of nodes were varied uniformly between 0 and 10Velocity of nodes were varied uniformly between 0 and 10

Transmission range of nodes was varied between 0 and 70Transmission range of nodes was varied between 0 and 70

Ideal degree was fixed at = 10Ideal degree was fixed at = 10

Weighing factors: wWeighing factors: w1 1 = 0.7, w= 0.7, w22 = 0.2, w = 0.2, w33 = 0.05 and w = 0.05 and w44 = 0.05 = 0.05

Experimental Results

Max displacement = 5 (const)Transmission range = 0 - 70Number of nodes = 20 - 60Ideal degree = 10

Experimental Results

Max displacement = 1 - 10Transmission range = 30 (const)Number of nodes = 20 - 60Ideal 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.

clustering in mobile ad hoc networks

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