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Resilient Approach for Energy Management on Hot Spots in WSNs

Resilient Approach for Energy Management on Hot Spots in WSNs. Fernando Henrique Gielow Michele Nogueira Aldri Luiz dos Santos {fhgielow,michele,aldri}@inf.ufpr.br NR2 – Federal University of Paraná IFIP/IEEE IM2011 Dublin, May 23th, 2011. Outline. Introduction and motivation

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Resilient Approach for Energy Management on Hot Spots in WSNs

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  1. Resilient Approach for Energy Management on Hot Spots in WSNs Fernando Henrique Gielow Michele Nogueira Aldri Luiz dos Santos {fhgielow,michele,aldri}@inf.ufpr.br NR2 – Federal University of Paraná IFIP/IEEE IM2011 Dublin, May 23th, 2011

  2. Outline • Introduction and motivation • Related work • CEA – Cluster-based Energy Architecture • RRUCR • Definition of scopes • Clustering • Initial backbone creation • Cluster-heads rotations • Data gathering & Routes maintenance • Evaluation • Conclusion

  3. Introduction and motivation • Sensor nodes: constrained resources • Low processing and storage capabilities • Limited lifetime • Applications • Surveillance/monitoring systems • Data gathering applications

  4. Introduction and motivation • Traffic patterns • Unequal traffic distribution • Data gathering applications • Areas burdened with higher traffic rates n to n n to 1

  5. Introduction and motivation • Hot Spots • There are more important nodes in the network • Unequal traffic distribution • Areas burdened with higher traffic rates • Mitigation through sink mobility, biased deployment, unequal clustering

  6. Related work • Hot Spot mitigation • Sink mobility • The nodes close to the sink will change eventually • Unpractical in the majority of scenarios • E.g. [Thanigaivelu and Murugan, 2009] • Biased deployment • Manually deploying more nodes near the sink • Unpractical in the majority of scenarios • E.g. [Wu and Chen, 2006] • Unequal clustering • Smaller clusters near the sink • More routes to reach the sink • E.g. [Chen et al, 2009]

  7. CEA: Cluster-based Energy Architecture • Generic behavior • Cluster-based • Hot spot mitigation • Intra/inter clusters energy management • Route management

  8. The RRUCR protocol • Rotation Reactive Unequal Cluster based Routing • Cluster-based multi-hop protocol for networks with n to 1 traffic pattern • Data gathering applications • Unequal clusters to mitigate hot spots • Dynamic maintenance of routes

  9. Operations of RRUCR • Definition of scopes • Clustering • Initial backbone creation • Cluster-heads rotations • Data gathering & Routes maintenance

  10. RRUCRDefinition of scopes • Transmission powers ordered and indexed • The sink covers those powers 4 3 2 4 4 2 3 4 3 2 1 Potence index used by the sink to cover nearest node Potence index used by the sink to cover most distant node Potence index used by current node to reach the sink 2 3 Potence index limit to this operation

  11. RRUCRClustering • Unequal sized • Hot spot mitigation (funneling of routes) • Previously defined scope power • Balanced quantity • Avoids dense areas • Still cover all nodes

  12. RRUCRInitial backbone creation • Process initialized by the sink • Process carried by cluster-heads • Update route and forward message once

  13. RRUCRCluster-heads rotations • Balance internal energy consumption • Prolong network lifetime • Generate broken links when selecting farther nodes • Force route update of the node that rotated( ) and of the nodes which used the previous CH ( )

  14. RRUCRData gathering & Routes maintenance • CHs route the data to the sink in a multi-hop way • That message carries a field which indicates the distance from the node up to the sink • Used to update routes • If obligatory and a node with shorter distance found • Reactive approach, with low overhead

  15. EvaluationParameters • 1000x1000m • 700 nodes • Initial energy between 0.9 and 1.1 J • 1% prob. of generating 32 bytes of data at each 0.1s • 5000s • Radio parameters set according to Mica2 • 3 scenarios • Without failures • With failures close to the sink • With failures far from the sink • ns-2.30 simulator • 35 simulations – interval of confidence of 95% • Compared to UCR

  16. Evaluation 17% 13% 21%

  17. Evaluation

  18. Evaluation

  19. Conclusion • Address the Hot spot impacts on WSN • Less deaths close to the sink • Improve network lifetime • RRUCR • Balanced quantity of clusters • Increased network lifetime in 21.36%, when compared to UCR • Increased data delivery rates • Work extended to a generic architecture (CEA)

  20. Future work • Operations that check the integrity on WSN links • More complex route maintenance • A TinyOS implementation of RRUCR

  21. Project page with more information • www.nr2.ufpr.br/~fernando/rrucr/ • Source code available under LGPL • ns-2.30 simulation • Installation script Email for contact: fhgielow@inf.ufpr.br Doubts?

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