Hop-based Energy Aw are Routing Schem e for W ireless Sensor Netw - PowerPoint PPT Presentation

Hop-based Energy Aw are Routing Schem e for W ireless Sensor Netw orks Jin Wang Advisor: Prof. Sungyoung Lee Date: November 19, 2009 Computer Engineering Department, Kyung Hee University UC Lab, KHU Ph. D. Defense 1

Contents 1 Introduction 2 Related work 3 Proposed idea: HEAR 4 HEAR algorithm for WSNs 5 Performance evaluation 6 Conclusions and future work UC Lab, KHU Ph. D. Defense 2

Problem statem ent  Transm ission m anner  Small scale network: single hop transmission is preferred  Large scale network: multi-hop transmission is preferred  How to determine the transmission manner under diff. networks?  Hot spot phenom enon  Nodes close to BS die early using multi-hop transmission  Nodes far from BS die early using single hop transmission  How to alleviate this phenomenon under diff. transmission manner?  Optim al hop num ber  Commonly agreed that multi-hop trans. is more energy efficient.  How to determine the optimal hop number and intermediate nodes?  Up to now , the hop-based routing in W SNs is not w ell addressed UC Lab, KHU Ph. D. Defense 3

Motivations  By using hop-based routing m echanism , the energy consum ption can get reduced  The netw ork lifetim e can get prolonged  I t can alleviate the hot spot phenom enon  I t should be energy balancing and efficient  I t is distributed, localized and easy to apply UC Lab, KHU Ph. D. Defense 4

Contributions  We propose a Hop-based Energy Aware Routing (HEAR) algorithm for WSNs.  By using our HEAR algorithm, the hot node phenomena in WSNs can get alleviated.  We make extensive simulations to validate the performance of our hop-based energy aware routing algorithm. UC Lab, KHU Ph. D. Defense 5

Focus of this dissertation  Objective: • prolong network lifetime  Means: • reduce and balance energy consumption  Research topic: • routing  Uniqueness: • from hop number point of view UC Lab, KHU Ph. D. Defense 6

2 . Related W ork: Routing protocols for W SNs Hierarchical Location- Flat-based based -based Routing Routing Routing Representative Representative Representative ones: ones: ones: Directed diffusion LEACH [32, 33] GAF [21, 22] [36, 37] PEGASIS [41] TTDD [39] SPIN [31, 38] HEED [48] MECN [50] GRAB [42] Others: [27-65] Others: [27-65] Others: [27-65] . UC Lab, KHU Ph. D. Defense 7

3 . Related w orks  Other hop-based routing algorithm s [52, 53] [32, 33] [43,44,45] [30] The authors study The LEACH authors The authors study The author explain diff. energy models treat node differently. selection of trans. the influence of hop and optimal hop But: manner . number on many number. 1. They only use But: network metrics. But: direct trans. by CH 1. They only treat 2 But: 1. They treat each 2. No study of hop hops routing as 1. Theoretical node equally number multi-hop routing analysis of hop 2. More simulation is 3. No study of the 2. Further analysis number is needed needed performance of hop- and simulation is 2. More simulation 3. Study under real based routing [2002] needed [2006/2007] is needed [2004] sensor network is needed [2001] UC Lab, KHU Ph. D. Defense 8

3 . Proposed I dea : HEAR  How to determine the next hop node is one critical issue in routing  The next hop node selection criteria:  Lowest ID  Max-degree  Shortest-path  Max. residual energy  Greedy routing  Probability based  Others… UC Lab, KHU Ph. D. Defense 9

4 . HEAR algorithm for W SNs  Relevant m odels Traffic model Time-based & Event-based Energy model The first order radio model Propagation model Free space & Multi-path model Network model Directed graph with G= < V,E> UC Lab, KHU Ph. D. Defense 10

Netw ork m odel  W SN can be regarded as a directed graph G= < V, E> w here V represents the set of vertices and E represents the set of edges  Assum ptions about W SN  Sensors are stationary  Sensors are homogeneous  Sensors are left unattended  Sensors are location aware  There is only one sink node  Comm. links are symmetric  There is no big obstacle UC Lab, KHU Ph. D. Defense 11

Propagation m odel  Free space m odel  Multi-path m odel UC Lab, KHU Ph. D. Defense 12

Energy m odel UC Lab, KHU Ph. D. Defense 13

Traffic m odel  There are four types of traffic models for WSNs, namely time- based, event-based, query-based and hybrid traffic models.  Time-based traffic model is used in applications like seismic and temperature monitoring, video surveillance etc.  Event-based traffic model is used in applications like target tracking, intrusion/event detection etc.  Query-based traffic model is used in applications where the remote control center sends a query for certain information at some area.  Hybrid traffic means more than one traffic mode above are used simultaneously. For example, during time-based traffic monitoring period, remote center can also send query for info.  In this thesis, we mainly use time-based and event-based traffic models. UC Lab, KHU Ph. D. Defense 14

Problem form ulation UC Lab, KHU Ph. D. Defense 15

Determ ination of the optim al hop num ber  Unfortunately, the optim al hop num ber can not be used directly for 3 reasons:  Hop number should be an integer value rather than a decimal one  Constraint conditions like d>d0 (d<d0) should be met under different radio parameters  It is impossible to find such optimal intermediate nodes under practical sensor network  Therefore, w e have to find the sub-optim al hop num ber and proper interm ediate nodes under practical sensor netw ork UC Lab, KHU Ph. D. Defense 16

Determ ination of the transm ission m anner UC Lab, KHU Ph. D. Defense 17

Determ ination of the sub-optim al hop num ber  W e can not use the optim al hop num ber for 3 reasons.  W e propose an em pirical selection criterion of the sub- optim al hop num ber. UC Lab, KHU Ph. D. Defense 18

HEAR algorithm  HEAR is a distributed and localized algorithm which combines the general routing mechanism with hop-based nature during routing process.  Each sensor node has two tables. One is the routing table and another is neighboring table.  Each node can make intelligent decision of the next hop locally and it is easy to implement for practical engineering applications.  HEAR algorithm consists of two phases which are route setup and route maintenance phase. UC Lab, KHU Ph. D. Defense 19

HEAR w orkflow and features  HEAR features  Random and dynamic network  Distributed and localized  Hop-based  Energy efficient  Energy balancing  Alleviate hop spot phenomenon  Easy to implement UC Lab, KHU Ph. D. Defense 20

5 . Perform ance evaluation Hop number B A C Energy Network lifetime consumption Performance Evaluation D E Hot spot Packet phenomenon reachability UC Lab, KHU Ph. D. Defense 21

Sim ulation environm ent UC Lab, KHU Ph. D. Defense 22

Energy consum ption under diff. R  Observations  HEAR>Greedy>MRE> Direct transmission  When R is small, more energy is consumed ∈  can ensure [ 90 , 120 ] R good performance for greedy and MRE algo. UC Lab, KHU Ph. D. Defense 23

Energy consum ption under diff. d  Observations  HEAR>Greedy>MRE> Direct transmission  Energy consumption increases with d  Similar performance for 4 algorithms when d is small UC Lab, KHU Ph. D. Defense 24

Energy consum ption under diff. N  Observations  HEAR>Greedy>MRE>D irect transmission  When N is small, the value changes a lot due to random topology  The fluctuation becomes smaller as N increases UC Lab, KHU Ph. D. Defense 25

Energy consum ption under diff. BS location  Observations  HEAR>Greedy>MRE  It is symmetric based on line x=150  The energy consumption increases as BS moves from (150,150) until outside UC Lab, KHU Ph. D. Defense 26

Energy consum ption under diff. net. scale UC Lab, KHU Ph. D. Defense 27

Energy consum ption under diff. traffic m odel UC Lab, KHU Ph. D. Defense 28

Hop num ber under diff. netw ork topology  Observations  Direct transmission> HEAR>Greedy>MRE  HEAR and greedy have stable performance  MRE performance varies very much under different network topology UC Lab, KHU Ph. D. Defense 29

Hop num ber under diff. R  Observations  Direct transmission> HEAR>Greedy>MRE  Performance decreases with R on average  When R<110, HEAR and greedy algorithms have similar performance UC Lab, KHU Ph. D. Defense 30

Hop num ber under diff. BS location  Observations  Direct transmission> HEAR>Greedy>MRE  It is nearly symmetric based on line x=150  The hop number increases as BS moves from (150,150) until outside UC Lab, KHU Ph. D. Defense 31

Netw ork lifetim e under diff. netw ork topology  Observations  HEAR>Greedy>MRE> Direct transmission  Performance of HEAR changes under diff. network topology  HEAR has a factor of 2 to 4 times longer network lifetime than the other 3 algorithms UC Lab, KHU Ph. D. Defense 32

Netw ork lifetim e under diff. BS location UC Lab, KHU Ph. D. Defense 33