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Distributed Clustering in Ad-hoc Sensor Networks: A Hybrid, Energy-Efficient Approach Ossama Younis and Sonia Fahmy Department of Computer Sciences, Purdue University Infocom'04 Ossama Younis, Purdue University 1 Contributions A new distributed clustering protocol for sensor networks that has the following properties: Energy-efficient Terminates rapidly Considers cluster quality, e.g., load-balanced clusters or dense clusters Has low message/processing overhead Infocom'04 Ossama Younis, Purdue University 2 Sensor Networks Application-specific, e.g., Monitoring seismic activities Surveying military fields Reporting radiation levels at nuclear plants Nodes are usually: Densely deployed Limited in processing, memory, and communication capabilities Constrained in battery lifetime Left unattended Infocom'04 Ossama Younis, Purdue University 3 Goals Scalability, data and state aggregation, robustness, and prolonged network lifetime What is network lifetime? Time until the first Time until the last node dies node dies How to prolong the network lifetime? Deploy redundant nodes Apply energy-efficient protocols, e.g., MAC layer protocols can reduce energy waste Topology management can distribute energy consumption Infocom'04 Ossama Younis, Purdue University 4 Topology management Cell-based approach Cluster-based approach observer Infocom'04 Ossama Younis, Purdue University 5 Outline System model and requirements The Hybrid, Energy-Efficient, Distributed clustering protocol (HEED) HEED properties Evaluation Related Work Conclusion Infocom'04 Ossama Younis, Purdue University 6 System Model A set of n sensor nodes are dispersed uniformly and independently in a field Sensor nodes are Quasi-stationary Unattended Equally significant Location un-aware Homogeneous (similar capabilities) Serving multiple observers Possess a fixed number of transmission power levels Infocom'04 Ossama Younis, Purdue University 7 Requirements Our goal is to design a new clustering approach that has the following properties: Completely distributed Terminates in O(1) iterations Has low message/processing overhead Generates high energy, well-distributed cluster heads Can provide other characteristics, such as balanced or dense clusters Infocom'04 Ossama Younis, Purdue University 8 Approach (HEED) We propose the Hybrid, Energy-Efficient, Distributed clustering approach (HEED) Heed is hybrid: Clustering is based on two parameters HEED is distributed: Every node only uses information from its 1-hop neighbors (within cluster range) HEED is energy-efficient: Elects cluster heads that are rich in residual energy Re-clustering results in distributing energy consumption Infocom'04 Ossama Younis, Purdue University 9 HEED - Parameters Parameters for electing cluster heads Primary parameter: residual energy (Er) Secondary parameter: communication cost (used to break ties) i.e., maximize energy and minimize cost Infocom'04 Ossama Younis, Purdue University 10 HEED – Algorithm at node v Initialization Discover neighbors within cluster range Compute the initial cluster head probability CHprob = f(Er/Emax) Main If v received some cluster head messages, processing choose one head with min cost If v does not have a cluster head, elect to become a cluster head with CHprob . CHprob = min(CHprob * 2, 1) Repeat until CHprob reaches 1 Finalization If cluster head is found, join its cluster Otherwise, elect to be cluster head Infocom'04 Ossama Younis, Purdue University 11 HEED - Example (0.4,3) a13 a10 (0.1,4) a11 (0.2,2) (0.2,5) a12 (0.2,3) a7 (0.6,2) c2 c3 (0.8,4) (0.1,2) a6 (0.2,3) (0.1,4) a5 a14 c1 c4 (0.7,5) (0.3,2) a3 (0.2,3) Compute CHprob and cost Elect to become cluster head a2 a4 (0.6,4) a9 (0.9,4) (0.5,4) Infocom'04 a8 (0.5,3) Discover neighbors (0.3,2) a1 Ossama Younis, Purdue University Resolve ties Select your cluster head 12 HEED - Analysis HEED has the following properties: Completely distributed Clustering terminates in O(1) iterations: 1 N iter log 2 1 p min Message overhead: O(1) per node Processing overhead: O(n) per node Cluster heads are well distributed. Pr{two CHs are within the same cluster range}: 1 (p = initial CHprob ) log( ) 1 p pnbr 1 p2 i 2 i 0 Infocom'04 Ossama Younis, Purdue University 13 HEED – Inter-cluster communication Lemma 1 (Blough and Santi’02): Assume n nodes are dispersed uniformly and independently in an area R=[0,L]2. If Rc2n=aL2lnL, for some a>0, Rc << L, and n>>1, then limn,N→∞E(number R R of empty cells) = 0, where a cell is an 2 2 area c c Lemma 2: There exists at least one cluster head a.a.s. in any area of 1 1 ) Rc ( 2 ) Rc size (2 2 Infocom'04 2 Ossama Younis, Purdue University 14 HEED – Inter-cluster communication Theorem 1: 2.7Rc Two cluster heads in two neighboring areas can communicate if CH2 2.7Rc Rt 6 Rc Rt CH1 Theorem 2: HEED produces a connected multi-hop cluster head graph (structure) asymptotically almost surely Infocom'04 Ossama Younis, Purdue University 15 Performance evaluation 2000x2000 network field with 1000 nodes Demonstrating HEED properties: fast termination, rich-energy cluster heads, and cluster quality Infocom'04 Ossama Younis, Purdue University 16 Performance evaluation (cont’d) Apply HEED to an application where nodes directly contact a far observer Compare to multi-hop LEACH clustering 100x100 network Initial Er = 2 Joule 1 round = 5 TDMA frames Infocom'04 Ossama Younis, Purdue University 17 Related Work Topology management protocols suffered from at least one of the following problems: Dependence on location awareness (e.g., GAF) Slow convergence (i.e., dependent on the network diameter) (e.g., DCA) Energy efficiency was not the main goal of many protocols, e.g., Max-Min D-clustering No focus on clustering quality, such as having cluster heads well-distributed in the network (e.g. LEACH) Infocom'04 Ossama Younis, Purdue University 18 Conclusion We have proposed HEED clustering HEED is fast and has low overhead HEED can provide other features, such as loadbalancing HEED is independent of: Homogeneity of node dispersion in the field Network density or diameter Distribution of energy consumption among nodes Proximity of querying observers HEED can be extended to provide multi-level hierarchy Infocom'04 Ossama Younis, Purdue University 19