Presented by: Hossein Ahmadi

1. Presented by: Hossein Ahmadi

2. Ad-hoc and Sensor networks Both: No infrastructure Mobile nodes Dynamic links Ad-hoc networks: One-to-one communication Sensor networks: Energy constrained Data centric -> Many-to-one communication Application oriented ->Data aggregation

3. Ad-hoc routing protocols

4. Destination-Sequenced Distance-vector Routing (DSDV)? Common Bellman-Ford routing Periodic updates Full Dump Incremental Use 2 Tables Routing Table Table to keep track of incremental updates

5. Cluster Gateway Switch Routing (CGSR)? Hierarchical architecture based on DSDV Clusters of nodes with a cluster head. Cluster head is responsible to forward to/from its cluster. Gateway: nodes within the communication range of two or more cluster head Use 2 tables Cluster member table (Inter-cluster)? Routing table (Intra-cluster)?

6. Cluster Gateway Switch Routing (CGSR)?

7. The Wireless Routing Protocol (WRP)? Update: Neighborhood update messages Discovery: any message (Ack, hello, �)? Uses 4 tables: Distance table Routing table Link-cost table Message retransmission list (MRL) table Loop Freedom: Keeping second-to-last hop to the destination

8. Table-driven routing comparison

9. Ad Hoc On-demand Routing Nodes does not maintain up-to-date routing table Exchange information when needed Less update exchange and message complexity At the cost of path initiation More efficient in highly dynamic environments

10. Ad Hoc On-demand Distance Vector Routing (AODV)? Improvement to DSDV Path Discovery Request is flooded to reach the destination. Sequence number � Loop free Path is formed using the response assuming the links are symmetric Route stored �node that PREP had came from Routes are cached and expire after some time Link failure notification Optional use of hello messages

11. Dynamic Source Routing (DSR)? Source Routing Discovery: Path information is stored in request and reply. Paths are cached Multiple paths can be used

12. Dynamic Source Routing (DSR)? Asymmetric links: A new request for route to the source. Reply is piggybacked on the request packet. Route Maintenance: Error is discovered (observing retransmission or direct ACK)? Route Error is generated Recovers fast using alternative paths

13. Temporally Ordered Routing Algorithm (TORA)? Each node has a Height Height is determined by the time request is received. A route is represented by Directed Acyclic Graph (DAG) build based on the height. Height changes based on the link failures. Link reversal when facing error.

14. Temporally Ordered Routing Algorithm (TORA)? Nodes need to be synchronized Routes need to be clear Multiple routes Low message overhead for route reconstruction Similar to Distance Vector algorithms Count to infinity

15. Directed Diffusion Sink floods interest Constrained or Directional Refreshed Interest are cached to remember routing directions Interests can be aggregated Gradients: Pointing back to where interests came from Multi-path routing from source to sink

16. Data Propagation and Reinforcement The source routes measurements along gradients at specified rate Intermediate nodes downconvert rates as necessary Reinforce some of the neighbor � Increase their gradient rate Intermediate nodes propagate reinforcements to balance the flow

17. Evaluation Simulated in NS2 Random node placement 50 to 250 nodes (incremented by 50) with the same average density Radio range: 40m Simulate node failures Energy profile Transmit: 660mw Receive: 395mw Idle time: 35mW 802.11 MAC Fixed Workload

18. Average Dissipated Energy and Delay High energy efficiency due to in-network aggregation. Low delay due to reinforcements and MAC behavior

19. Impact of node failures and Negative reinforcements Robust against failure. Negative reinforcement prunes-off energy consuming paths

20. Associativity-Based Routing (ABR)? Routing metric: connection-stability Associativity (stability) table Associativity increases by receiving more beacon messages. Route Discovery (BQ)? Destination node examines the best routes by associativity values Favor long-lived routes Local Recovery (RN, LQ)?

21. Signal Stability Routing (SSR)? Based on signal strength between nodes Uses 2 tables Signal Strength Table (SST)? Routing Table (RT)? Two static and dynamic routing protocols

22. On-demand routing comparison

23. Discussion Energy aware routing? Use less power consuming paths Balanced energy consumption End-to-end throughput? Low latency, high connectivity, more stability Network capacity? High total throughput in the shared medium Abstraction for routing in many-to-one communication? Multicast and replication

24. Learn on the Fly: Data-driven Link Estimationand Routing in Sensor Network Backbones Hongwei Zhang, Anish Arora and Prasun Sinha Computer Science and Engineering The Ohio State University, USA Presented by: Hossein Ahmadi & Debessay Fesehaye

25. Contents Existing routing methods General Description Drawbacks Proposed data-driven routing (LOF)? How it works The routing metric (ELD) used Experimental Results Discussion

26. Existing routing methods: General Description Existing routing protocols use beacon-based link estimation Neighbors periodically exchange broadcast beacons Estimate unicast properties via those of broadcast Note: application data is transmitted using unicast

27. Existing routing methods: Drawbacks In beacon-based estimation Network condition experienced by beacons may not apply to data Traffic pattern may change quickly (especially in event-detection applications), and Traffic pattern affects link properties due to interference It is hard to precisely estimate unicast properties via those of broadcast beacons Temporal link properties (e.g., correlation, variance): non-trivial to model, and not considered in well-known approaches such as ETX

28. Existing routing methods: Drawbacks�cont�d Network condition varies significantly across different interference scenarios (e.g., up to 39.26%); variations change with distance There is significant estimation error, especially in the transitional region; error changes with distance and interference pattern Beacon-based link estimation tends to be imprecise

29. Proposed data-driven routing (LOF): How it works It circumvents the drawbacks and complexity of beacon-based estimation Estimate unicast link properties via data transmission itself MAC (medium access control) feedback carries information on Success or failure MAC latency time spent in transmitting a packet (including retries)?

30. Proposed data-driven routing (LOF): How it works�cont�d LOF chooses routes that minimize the end-to-end MAC latency to destination minimize the expected MAC latency per unit-distance (ELD) to destination Hence uses ELD as its routing metric Select a neighbor with the lowest E[LD] = ELD Break ties by preferring stabler links (i.e., links with smaller variance)?

31. Proposed data-driven routing (LOF): Routing metric: ELD The routing metric is the Expected MAC latency per unit-distance to destination (LD)? Mostly static network, thus we use geography-based routing metric freedom of periodic beaconing Mostly static network, thus we use geography-based routing metric freedom of periodic beaconing

32. Numerical Results Beacon-based routing ETX: expected transmission count; geography unaware (Alec Woo et al. 2003, Douglas Couto et al. 2003)? PRD: product of link reliability and distance progress; geography based (Karim Seada et al., 2004)? Other versions of LOF L-ns: no exploratory sampling L-sd: consider every neighbor in exploratory sampling (i.e., including dead neighbor)? L-se: try exploratory sampling after every packet transmission L-hop: assume geographic-uniformity Different node distribution density: power levels Different node distribution patterns: partially future work ETX is similar to ETT when transmission rate is fixed Different node distribution density: power levels Different node distribution patterns: partially future work ETX is similar to ETT when transmission rate is fixed

33. Numerical Reults...cont'd 802.11b testbed of Kansei....Indoor testbed 15 ? 13 grid Evaluation criteria End-to-end MAC latency Energy efficiency Links used in routing

34. Numerical Results---End-to-end MAC latency Compared with ETX and PRD, LOF reduces MAC latency by a factor of 3 LOF has the smallest MAC latency compared with L-*, showing the importance of proper exploratory sampling not assuming geographic uniformity End-to-end MAC latency in ETX and PRD is around 3 times that in LOF;End-to-end MAC latency in ETX and PRD is around 3 times that in LOF;

35. Numerical Results-Average number of unicast transmissions per packet received Compared with ETX and PRD, LOF improves efficiency by a factor of 1.49 and 2.37 respectively LOF is more efficient than L-* Besides energy saved by not using periodic beaconingBesides energy saved by not using periodic beaconing

36. Numerical Reults--Links used: reliability and length LOF uses reliable links 1112 and 786 failures in ETX and PRD respectively; only 5 failures in LOF L-ns uses reliable but shorter links than LOF does 1112 and 786 for ETX and PRD respectively; 5 for LOF; 711 for L-hop1112 and 786 for ETX and PRD respectively; 5 for LOF; 711 for L-hop

37. Discussion LOF when nodes are moving Neighborhood vs The network as a whole Loop free? Convergence? Number of forwarders....sampling neighbors sample size Sampling MAC latency�sample size How about measuring ETX metric with data traffic