1. A Survey on Routing Protocols for Wireless Sensor Networks Kemal Akkaya, Mohamed Younis 19 th July, 2005 Seo, DongMahn

2. 19th July, 20052/33 Contents Introduction Data-centric protocols Hierarchical protocols Location-based protocols Network flow and QoS-aware protocols Conclusion and Open Issues

3. 19th July, 20053/33 Introduction (1) Micro Sensor micro-electro-mechanical systems (MEMS), low power and highly integrated digital electronics data processing, communication capabilities ambient conditions an electric signal command center (sink) data concentration center (gateway) disposable, unattended military, civil application, dangerous mission, landmine constraints – energy supply, bandwidth

4. 19th July, 20054/33 Introduction (2) Routing in sensor networks Characteristics No global addressing scheme require the flow of sensed data from multiple regions (sources) to a particular sink redundancy of data traffic constraints - transmission power, on-board energy, processing capacity and storage classification data-centric hierarchical location-based network flow QoS awareness

5. 19th July, 20055/33 Introduction (3) System Architecture and Design Issues Network Dynamics Node Deployment Energy Considerations Data Delivery Models Node Capabilities Data Aggregation/Fusion

6. 19th July, 20056/33 Introduction (4) Related Work I.F. Akyildiz et al., “Wireless sensor networks: a survey”, Computer Networks, Vol. 38, pp. 393-422, March 2002. survey of design issues and techniques physical constraints protocols proposed in all layers of network stack No classification of routing protocol S.Tilak et al., “A Taxonomy of Wireless Microsensor Network Models”, in ACM Mobile Computing and Communication Review (MC2R), June 2002. high level description of typical sensor network architecture classification of sensor network with considering several architectural factors No routing protocol

7. 19th July, 20057/33 Data-centric protocols (1) Flooding and Gossiping

8. 19th July, 20058/33 Data-centric protocols (2) Sensor Protocols for Information via Negotiation (SPIN)

9. 19th July, 20059/33 Data-centric protocols (3) Directed Diffusion

10. 19th July, 200510/33 Data-centric protocols (4) Energy-aware routing set of sub-optimal path means of a probability function, energy consumption of each path network survivability 3 phases Setup phase localized flooding - to find routes and to create the routing tables) Data Communication Phase randomly choosing a node Route maintenance phase localized flooding - to keep all the paths alive

11. 19th July, 200511/33 Data-centric protocols (5) Rumor routing variation of DD between event flooding and query flooding agent (event flooding), query flooding event table Simulation result significant evergy saving can handle node’s failure only when the number of events is small

12. 19th July, 200512/33 Data-centric protocols (6) Gradient-Based Routing (GBR) changed version of DD height of the node – number of hops gradient – difference between a node’s height and that of is neighbor the largest gradient data combining entity (to aggregate data) three different data spreading techniques Stochastic Scheme Energy-based scheme Stream-based scheme

13. 19th July, 200513/33 Data-centric protocols (7) Constrained anisotropic diffusion routing (CADR) information-driven sensor querying (IDSQ) constrained anisotropic diffusion routing (CADR) maximizing the information gain minimizing the latency and bandwidth CADR evaluation of information/cost/cost objective and routes based on local information/cost gradient and end-user requirements IDSQ query node - the most useful information

14. 19th July, 200514/33 Data-centric protocols (8) COUGAR a huge distributed database system select a leader node network-layer independent solution drawbacks extra overhead synchronization failure of leader nodes

15. 19th July, 200515/33 Data-centric protocols (9) Active Query forwarding In sensoR nEtworks (ACQUIRE) new data-centric mechanism a distributed database, complex queries one-shot respond partially and forward to another sensor look-ahead of d hops d = 4, mathematical modeling no validation of result through simulation

16. 19th July, 200516/33 Hierarchical protocols (1) Low-Energy Adaptive Clustering Hierarchy (LEACH) clusters of the sensor nodes 5% of the total number of all sensor nodes choosing header with random number between 0 and 1 not for large network dynamic clustering with extra overhead

17. 19th July, 200517/33 Hierarchical protocols (2) PEGASIS & Hierarchical-PEGASIS Power-Efficient Gathering in Sensor Information Systems chains from sensor nodes Hierarchical-PEGASIS chain based binary scheme CDMA, spatially separated nodes

18. 19th July, 200518/33 Hierarchical protocols (3) TEEN and APTEEN Threshold sensitive Energy Efficient sensor Network Protocol clustering, hard and soft thresholds, TDMA not good for periodic applications AdaPtive Threshold sensitive Energy Efficient sensor Network protocol hybrid network, TDMA (intra), CDMA (inter) periodic data collections and reacting to time-critical events three query types historical, to analyze past data values one-tome, to take a snapshot view of the network persistent to monitor an event for a period of time

19. 19th July, 200519/33 Hierarchical protocols (4)

20. 19th July, 200520/33 Hierarchical protocols (5) Energy-aware routing for cluster-based sensor networks 3 tier architecture

21. 19th July, 200521/33 Hierarchical protocols (6) Self-organizing protocol based on taxonomy Router node Local Markov Loops (LML) 4 phases Discovery phase Organization phase Maintenance phase Self-reorganization phase

22. 19th July, 200522/33 Location-based protocols (1) MECN & SMECN Minimum Energy Communication Network minimum energy network for wireless networks utilizing low power GPS 2 phases two-dimensional plane, sparse graph (enclosure) find optimal links with distributed Belmann- Ford shortest path algorithm Small MECN can transmit to every other node

23. 19th July, 200523/33 Location-based protocols (2) Geographic Adaptive Fidelity (GAF) energy-aware location-based routing algorithm ad hoc networks, GPS

24. 19th July, 200524/33 Location-based protocols (3) Geographic and Energy Aware Routing (GEAR) use of geographic information to restrict the number of interests in DD 2 phases Forwarding packet towards the target region Forwarding the pachkts within the region

25. 19th July, 200525/33 Network flow and QoS-aware protocols (1) Maximum lifetime energy routing network flow approach maximize network lifetime Minimum Transmitted Energy (MTE) algorithm Bellman-Ford shortest path algorithm

26. 19th July, 200526/33 Network flow and QoS-aware protocols (2) Maximum lifetime data gathering Maximum Lifetime Data Aggregation (MLDA) Lifetime T data-gathering schedule S Maximum Lifetime Data Routing (MLDR)

27. 19th July, 200527/33 Network flow and QoS-aware protocols (3) Minimum cost forwarding minimum cost path effect of delay, throughput and energy consumption from any node to the sink 2 phases setup phase second phase

28. 19th July, 200528/33 Network flow and QoS-aware protocols (4) Sequential Assignment Routing (SAR) the first protocol table-driven multi-path approach taking QoS metric, energy resource on each path and priority level of each packet fault-tolerance and easy recovery overhead of maintaining the tables and states at each sensor node

29. 19th July, 200529/33 Network flow and QoS-aware protocols (5) Energy-Aware QoS Routing Protocol extended version of Dijkstra’s algorithm

30. 19th July, 200530/33 Network flow and QoS-aware protocols (6) SPEED soft real-time end-to-end guarantees end-to-end delay for the packets congestion avoidance routing module – Stateless Geographic Non- Deterministic forwarding (SNFG)

31. 19th July, 200531/33 Conclusion and Open Issues (1)

32. 19th July, 200532/33 Conclusion and Open Issues (2) more issues Quality of Service (QoS) video and imaging sensors real-time applications Energy-aware QoS routing node mobility integration of WSN with wired networks

33. 19th July, 200533/33