PCI 2005 Volos, Greece Nov 2005 Efficient Active Clustering of Mobile Ad-Hoc Networks Damianos Gavalas, Grammati Pantziou, Charalampos Konstantopoulos, Basilis Mamalis Department of Cultural Technology and Communication University of the Aegean Presented by D. Gavalas

PCI 2005 Volos, Greece Nov 2005 Outline Introduction to Mobile Wireless Ad Hoc Networks Differences in routing among conventional and Ad Hoc networks Clustering in Ad Hoc Networks Existing algorithms for Ad Hoc Networks clustering & their disadvantages Adaptive Broadcast Period clustering algorithm Simulation results Conclusions

PCI 2005 Volos, Greece Nov 2005 Mobile Ad Hoc Networks Formed by wireless hosts which may be mobile Without (necessarily) using a pre-existing infrastructure Routes between nodes may potentially contain multiple hops

PCI 2005 Volos, Greece Nov 2005 Mobile Ad Hoc Networks Two mobile nodes are ‘linked’ if they are within transmission range of each other May need to traverse multiple links to reach a destination

PCI 2005 Volos, Greece Nov 2005 Mobile Ad Hoc Networks (MANETs) Mobility causes route changes

PCI 2005 Volos, Greece Nov 2005 Why Ad Hoc Networks ? Ease of deployment Speed of deployment Decreased dependence on infrastructure

PCI 2005 Volos, Greece Nov 2005 Many Applications  All applications where a network infrastructure does not exist Civilian environments taxi cab network meeting rooms, electronic conferences, e-classrooms sports stadiums boats, small aircraft Personal area networking cell phone, laptop, ear phone, wrist watch Emergency operations search-and-rescue policing and fire fighting Military environments soldiers, tanks, planes

PCI 2005 Volos, Greece Nov 2005 Challenges Limited wireless transmission range Broadcast nature of the wireless medium Packet losses due to transmission errors Mobility-induced route changes Mobility-induced packet losses Battery constraints Potentially frequent network partitions  Routing

PCI 2005 Volos, Greece Nov 2005 Why is Routing in MANET different ? Host mobility link failure/repair due to mobility may have different characteristics than those due to other causes Rate of link failure/repair may be high when nodes move fast New performance criteria may be used route stability despite mobility energy consumption Difficult to assign hierarchical IP-like addresses (sub-networks which could share the same ‘domain name’ are not fixed)

PCI 2005 Volos, Greece Nov 2005 Unicast Routing Protocols Many protocols have been proposed Some have been invented specifically for MANET Others are adapted from previously proposed protocols for wired networks No single protocol works well in all environments some attempts made to develop adaptive protocols

PCI 2005 Volos, Greece Nov 2005 Clustering in Ad Hoc Networks A promising approach to ease routing process in MANETs is to is to build hierarchies among the nodes, such that the network topology can be abstracted Logical grouping of mobile nodes in separate clusters This process is commonly referred to as clustering A mobile node in every cluster is elected as cluster head (CH) CHs store routing tables They also route incoming messages from their cluster members to neighboring clusters Different clustering schemes may differ in how clusters are determined the way cluster head is chosen duties assigned to the cluster head

PCI 2005 Volos, Greece Nov 2005 Clustering in Ad Hoc Networks S D Cluster Head Gateway Ordinary Node S: Source D: Destination

PCI 2005 Volos, Greece Nov 2005 Objectives for efficient clustering in Ad Hoc Networks Cluster stability Cluster formations should not frequently change over time (that causes exchange of significant volume of control messages) Energy preservation Mobile nodes are highly dependant to their battery power Energy consumption should be balanced among mobile nodes Minimal usage of network resources for cluster control Network bandwidth should be available for data exchange, not control messages exchange

PCI 2005 Volos, Greece Nov 2005 Clustering Algorithms: Lowest ID (LID) Mobile nodes are assigned unique IDs Nodes transmit their ID (through a special ‘Hello’ message) in a given Broadcast Period Each node ‘elects’ as cluster head the node with the lowest-ID in the neighborhood

PCI 2005 Volos, Greece Nov Clustering Algorithms: Lowest ID (LID) 1 Cluster Head Ordinary Node

PCI 2005 Volos, Greece Nov 2005 Clustering Algorithms: Highest Degree (HD) Cluster Head Ordinary Node Clustering based on location information the node with the largest number of neighbors is elected as CH

PCI 2005 Volos, Greece Nov 2005 Clustering Algorithms: Vote-Based Clustering (VC) CH elections are based not exclusively on location but also on the battery power level of mobile nodes nodes with high degree (large number of neighbors) and sufficient battery power are elected as CHs

PCI 2005 Volos, Greece Nov 2005 Disadvantages of Existing Clustering Algorithms LID: CHs election is biased in favor of nodes with low IDs these nodes are likely to serve as CHs for long time and their energy supply rapidly depletes HD and VC methods imply cluster instability losing contact of a single node (due to node movement), may cause failure of the current CH to be re-elected A CH may end up dominating so many nodes that its computational, bandwidth and battery resources will rapidly exhaust Common disadvantage of LID, HD, VC: cluster formation is based on the periodic broadcast of ‘Hello’ messages In relatively static MANETs (e.g. e-classrooms), this ‘storm’ of control messages only verifies that cluster structure should remain unchanged

PCI 2005 Volos, Greece Nov 2005 Adaptive Broadcast Period (ABP) clustering algorithm: objectives A quick method for cluster formation is needed required speed should not be achieved at the expense of instable cluster configurations we extend VC algorithm so as to avoid frequent CH ‘re- elections’ Balanced distribution of energy consumption Cluster sizes should be controlled not too large neither too small clusters For relatively static MANET topologies, broadcast period should be dynamically adapted to avoid unnecessary control message exchanges

PCI 2005 Volos, Greece Nov 2005 ABP algorithm: cluster formation We introduce the concept of “cluster head competence” (CHC) which represents the competence of a MH to undertake the role of a CH Format of ‘Hello’ message: MH_ID: the ID of the mobile node CH_ID: the ID of the mobile node’ s CH CHC: cluster head competence value of the mobile node BP (Broadcast Period): used to adapt the broadcast period within a particular cluster MH_ID CH_IDCHCBP 8 bit

PCI 2005 Volos, Greece Nov 2005 ABP algorithm: cluster formation Cluster head competence (CHC) values are calculated according to: CHC = (c 1 × d + c 2 × b) – p c 1, c 2 : weighted coefficients of node degree and battery availability, respectively (c 1 + c 2 = 1) d: Number of neighbors (degree of MH) b: Remaining battery lifetime (percentage of remaining over full battery power) p: ‘handover’ penalty coefficient (used to avoid frequent CH re-elections)  Mobile nodes with maximum CHC value in the neighborhood (maximum degree and battery availability) become CHs

PCI 2005 Volos, Greece Nov 2005 ABP execution example

PCI 2005 Volos, Greece Nov 2005 ABP execution example MH IDdbCHC 1643,8 2453,6 3432,4 4342, ,4 7522,2 8511,6 9543, , , , ,8

PCI 2005 Volos, Greece Nov 2005 ABP execution example Cluster Head Ordinary Node

PCI 2005 Volos, Greece Nov 2005 Dynamically Adaptive Broadcast Period for control messages exchange A principal objective of ABP algorithm is to reduce the number of control messages within the MANET The broadcast period (BP) should adapt on mobility pattern of mobile nodes For highly mobile nodes, BP is shortened For relatively static MANETs (e.g. e-classrooms) BP is lengthened, relaxing the MANET from unnecessary control messages

PCI 2005 Volos, Greece Nov 2005 Measuring mobility rate Mobility rate is measured by CHs by keeping record of their neighbors at the end of every BP Mobility rate: The sum of nodes removed and added between successive BPs BP #1 BP #2 BP #3 BP #

PCI 2005 Volos, Greece Nov 2005 Simulation results: number of control messages

PCI 2005 Volos, Greece Nov 2005 Simulation results: cluster stability

PCI 2005 Volos, Greece Nov 2005 Simulation results: balancing energy consumption distribution

PCI 2005 Volos, Greece Nov 2005 Conclusions A novel algorithm with the following strengths:  clustering procedure is completed quickly (within three ‘Hello’ cycles)  both location and battery power metrics are taken into account in clustering process  derived cluster formations exhibit enhanced stability by preventing unnecessary CH re-elections  for relatively static network topologies, control traffic volume is minimized  Slightly increased control (‘Hello’) packet size

PCI 2005 Volos, Greece Nov 2005 Thank you! Questions?