1. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology Low Energy Adaptive Clustering Hierarchy with Deterministic Cluster-Head Selection M. J. Handy, M. Haase, D. Timmermann Institute of Applied Microelectronics and Computer Science University of Rostock

2. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology Outline  Introduction / Motivation  sensor networks, lifetime, communication models  Problem Formulation  cluster-head selection, LEACH algorithm  Contribution  improved CH-selection algorithm, definition of sensor network lifetime  Simulations  simulation tool, simulation set-up, results

3. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology - Only the sandbags know -Useful application of wireless microsensor networks -Equip each sandbag with a moisture sensor -Collect and evaluate data How do sensors collaborate efficiently? Introduction Where is the spot of leakage?

4. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology Efficient collaboration of sensors means: -Ensure connectivity -Efficient role assignment -Collect only significant data -Decrease latency -Save energy Our Goal: Extend network lifetime Introduction

5. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology Introduction How to increase sensor lifetime? Reduce energy consumption -Hardware issue (e.g. circuit design) -Software issue Applications / OS Algorithms Protocols Increase energy supply -Energy density is the problem -Battery capacity increases only by 30-50 % in 5 years -Compare with Moore‘s Law -Micro-sensors vs. macro- batteries?

6. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology - Direct transmission - Multihop transmission - Clustering Communication Models [1] [1] Heinzelman, Chandrakasan `01

7. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology Cluster-Based Communication A Simple Algorithm The problem: Select j cluster-heads of N nodes without communication among the nodes The simplest solution: -Each node determines a random number x between 0 and 1 -If x < j / N  node becomes cluster-head...it‘s good, but: Cluster-heads dissipate much more energy than non cluster-heads! How to distribute energy consumption?

8. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology LEACH Communication Protocol Low-Energy Adaptive Clustering Hierarchy -Cluster-based communication protocol for sensor networks, developed at MIT -Adaptive, self-configuring cluster formation - The operation of LEACH is divided into rounds - During each round a different set of nodes are cluster-heads -Each node n determines a random number x between 0 and 1 -If x < T(n)  node becomes cluster-head for current round

9. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology Cluster-Head Selection LEACH Algorithm P = cluster-head probability ( j/N ) r = number of the current round G =set of nodes not been cluster-heads in the last 1/P rounds Every node becomes cluster-head exactly once within 1/P rounds

10. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology Cluster-Head Selection LEACH Algorithm P = cluster-head probability ( j/N ) r = number of the current round G =set of nodes not been cluster-heads in the last 1/P rounds Every node becomes cluster-head exactly once within 1/P rounds Drawback: Selection of cluster-heads is completely stochastic!

11. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology Cluster-Head Selection, Our Approach I E n_current = current energy of node n E n_max = initial energy of node n Simulations showed: + longer network lifetime -After a certain number of rounds the network is stuck, although there are still nodes alive -The reason: T( n ) is too low since the remaining nodes have very low energy level Basic Idea: Include the remaining energy level

12. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology Idea: Increase T(n) when network is stuck r s = number of rounds a node has not been cluster-head (reset to 0 when a node becomes cluster-head) -T(n) is increased when the network is stuck -Possible deadlock of the network is solved Significant longer network lifetime Cluster-Head Selection, Our Approach II

13. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology Lifetime of Microsensor Networks Introducing 3 New Metrics First Node Dies (FND) -Network quality decreases considerably as soon as one node dies Half of the Nodes Alive (HNA) -The loss of a single or few nodes does not diminish the QOS of the network Last Node Dies (LND) -Estimated value for overall lifetime of the network

14. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology Simulations Simulation Tool -YANASim (Yet Another Network Analyzing and Simulation Tool) -Simulates energy consumption of microsensor networks -Uses Clustering, Multihop and Direct Transmission -Visualisation of simulation results -Platform independent (Java)

15. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology Simulations Energy Model Transmit: Receive: k = message length d = distance λ = path-loss index

16. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology Simulations Simulation Results (1) Simulation Setup: Nodes: 200 Area: 200m*200m Base Station Pos.: (100,300)m Initial Energy / Node: 1 J Message Length: 200 bit CH-Probability: 0.05 Path-Loss (intra-cluster): 2 Path-Loss (to BS): 2.5 30 % longer lifetime for FND, 20 % for HNA

17. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology Simulations Simulation Results (2) Simulation Setup: Nodes: 200 Area: 200m*200m Base Station Pos.: (100,500)m Initial Energy / Node: 1 J Message Length: 200 bit CH-Probability: 0.05 Path-Loss (intra-cluster): 2 Path-Loss (to BS): 2.5 25 % longer lifetime for FND, 18 % for HNA

18. matthias.handy@etechnik.uni-rostock.de http://www-md.e-technik.uni-rostock.de/ University of Rostock Applied Microelectronics and Computer Science Dept. of Electrical Engineering and Information Technology Contribution / Conclusions -Improvement of LEACH‘s cluster-head selection algorithm -30 % increase of lifetime of sensor networks -Only local information is necessary for cluster-head selection -Communication with the base station or an arbiter node is not necessary -Three new lifetime metrics FNA, HNA, and LND -Use of metrics depends on application.