Lecture2-Jan14-clustering

Lecture2-Jan14-clustering - Clustering in Mobile Ad hoc...

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: 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. 2. 3. Discover neighbors Select clusterhead to form clusters 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 Does extra work due to packet forwarding Communicates with more number of nodes Helps to maintain same configuration Avoids frequent WCA invocation A clusterhead uses more battery power A clusterhead should be less mobile 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 ) | = v V , v v ' { dist ( v, v ) < tx } ' range ' Coordinate distance, predefined transmission range. 1. 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 = v N (v ) ' { dist ( v, v ) } ' 2 12 1 7 17 3 13 14 15 5 4 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) 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 ( X t - X t -1) + (Y t - Y t -1) 2 2 Yt Yt-1 time Xt-1 Xt where ( X t,Y t ) and v ( X t -1,Y t -1) at time coordinates of the node t are the and ( t -1) Component with less mobility is a better choice for clusterhead. Weighted Clustering Algorithm (WCA) Steps 1. 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 = w1v + 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 1. 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 = where, nc i ( x i - ) 2 nc xi is the number of clusterheads is the cardinality of cluster i and N - n c 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 1. 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. ...
View Full Document

This note was uploaded on 08/25/2011 for the course EEL 5937 taught by Professor Staff during the Spring '08 term at University of Central Florida.

Ask a homework question - tutors are online