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 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 1.Discover neighbors 2.Select clusterhead to form clusters 3.Decide 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 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

 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) [Chatterjee+ 2000, 2002]

Weighted Clustering Algorithm (WCA) Steps 1. Compute the degree d v each node v Coordinate distance, predefined transmission range. 2.Compute the degree-difference for every node 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 D v 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 than Power required to support a link increases faster than linearly with distance. (For cellular networks) linearly with distance. (For cellular networks)

Weighted Clustering Algorithm (WCA) Steps 4. Compute the average speed of every node; gives a measure of mobility M v mobility M v where and are the coordinates of the node at time and Component with less mobility is a better choice for clusterhead. Component with less mobility is a better choice for clusterhead. YtYt Y t-1 XtXt X t-1 time

Weighted Clustering Algorithm (WCA) Steps 5.Compute the total (cumulative) time P v a node acts as clusterhead Battery drainage = Power consumed 6. Calculate the combined weight W v for each node W v = w 1 Δ v + w 2 D v + w 3 M v + w 4 P v for each node W v = w 1 Δ v + w 2 D v + w 3 M v + w 4 P v for each node 7.Find min W v ; 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) 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) (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)  Probability that a node is reachable from any other node ( 0 – 1; 1 being most desirable) ( 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 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 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: w 1 = 0.7, w 2 = 0.2, w 3 = 0.05 and w 4 = 0.05

Experimental Results Max displacement = 5 (const) Transmission range = Number of nodes = Ideal degree = 10

Experimental Results Max displacement = Transmission range = 30 (const) Number of nodes = 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 2 nd International Conference on Distributed Computer Systems, April 1981, pp [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 [Basagni 1999a] S. Basagni, Distributed Clustering for Ad hoc Networks, Proceedings of International Symposium on Parallel Architectures, Algorithms and Networks, June 1999, pp [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 [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 [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 [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 [Parekh 1994] A.K. Parekh, Selecting Routers in Ad-hoc Wireless Networks, Proceedings of the SBT/IEEE International Telecommunications Symposium, August 1994.