1. 2015/7/15 H igh- S peed N etworking L ab. Dynamic Forwarding over Tree-on-DAG for Scalable Data Aggregation in Sensor Networks High-Speed Networking Lab. Dept. of CSIE, Fu-Jen Catholic University Adviser: Jenn Wei Lin Speaker: Tzung-Lin Yu

2. 2015/7/15 H igh- S peed N etworking L ab. Outline AbstractAbstract IntroductionIntroduction Related WorkRelated Work –DAA (Data Aware Anycast) Dynamic Forwarding over ToDDynamic Forwarding over ToD –One dimentional –Two dimentional Performance EvaluationPerformance Evaluation ConclusionConclusion ReferenceReference

3. 2015/7/15 H igh- S peed N etworking L ab. Computing and maintaining network structures for efficient data aggregation incurs high overhead for dynamic events where the set of nodes sensing an event changes with time.Computing and maintaining network structures for efficient data aggregation incurs high overhead for dynamic events where the set of nodes sensing an event changes with time. We propose Tree on DAG (ToD), a semistructured approach that uses Dynamic Forwarding to support to make the network efficient aggregation in large-scale networks.We propose Tree on DAG (ToD), a semistructured approach that uses Dynamic Forwarding to support to make the network efficient aggregation in large-scale networks. I. Abstract

4. 2015/7/15 H igh- S peed N etworking L ab. Direct Communication Sensor node Base station

5. 2015/7/15 H igh- S peed N etworking L ab. LEACH

6. 2015/7/15 H igh- S peed N etworking L ab. II. Introduction Sensor networks data aggregation can often reduce the communication cost by eliminating redundancy.Sensor networks data aggregation can often reduce the communication cost by eliminating redundancy. Various structured approaches for data aggregation have been proposed for data gathering applications and event-based applications.  fixed structures cannot efficiently aggregate data  change the structure dynamically incur high maintenance overheadVarious structured approaches for data aggregation have been proposed for data gathering applications and event-based applications.  fixed structures cannot efficiently aggregate data  change the structure dynamically incur high maintenance overhead

7. 2015/7/15 H igh- S peed N etworking L ab. II. Introduction We propose an efficient and scalable data aggregation mechanism that can achieve early aggregation without incurring overhead of constructing a structure.We propose an efficient and scalable data aggregation mechanism that can achieve early aggregation without incurring overhead of constructing a structure.

8. 2015/7/15 H igh- S peed N etworking L ab. III. Related Work DAA (Data Aware Anycast)DAA (Data Aware Anycast) –Structureless protocol –Packets have to be transmitted to the same node at the same time to be aggregated –Spatial convergence: forward to the nodes that have packets (by radio) –Temporal convergence: using Randomized Waiting to increase the chance Disadvantage: –if no neighbor has packets for aggregation  to sink (high cost) or return to DAA –Does not guarantee the aggregation of all packets when the network grows.

9. 2015/7/15 H igh- S peed N etworking L ab. III. Related Work Fixed tree structures –Long stretch problem: Packets from adjacent nodes have to be forwarded many hops away before aggregation. Event Source Event Source Sink

10. 2015/7/15 H igh- S peed N etworking L ab. IV. Dynamic Forwarding over ToD When no further aggregation can be achieved, we forward packets on ToD instead of forwarding to the sink (DAA).When no further aggregation can be achieved, we forward packets on ToD instead of forwarding to the sink (DAA). We propose a dynamic forwarding mechanism over ToD to avoid the long stretch problem of fixed structure.We propose a dynamic forwarding mechanism over ToD to avoid the long stretch problem of fixed structure.

11. 2015/7/15 H igh- S peed N etworking L ab. IV. Dynamic Forwarding over ToD ToD in One-Dimentional NetworkToD in One-Dimentional Network – basic of Two-Dimentional – Network is divided into cells – cell: a square (length =  )  > Max-diameter of an event can span

12. 2015/7/15 H igh- S peed N etworking L ab. F-aggregator S-aggregator IV. Dynamic Forwarding over ToD F&S-Tree, Cell, Cluster, and Aggregator – Each F-aggregator creates a shortest path (SPT) to the sink. –F-clusters’ size is large enough to cover the cells an event can span.

13. 2015/7/15 H igh- S peed N etworking L ab. IV. Dynamic Forwarding over ToD For all sets of nearby cells that can be triggered by an event, either they will be in the same F-cluster, or they will be the same S-cluster.  to avoid the long stretch problemFor all sets of nearby cells that can be triggered by an event, either they will be in the same F-cluster, or they will be the same S-cluster.  to avoid the long stretch problem

14. 2015/7/15 H igh- S peed N etworking L ab. IV. Dynamic Forwarding over ToD Dynamic Forwarding 1.using the DAA to aggregate 2.no further aggregation: forwarding their packets to their F-aggregators (i) event in single F-cluster using F-tree forward the packets to the sink ex: cell A, B (ii) event in multiple F-cluster select the S-aggregator for further aggregation ex: cell C, D [Property1] For any two adjacent nodes in ToD in 1D network, their packets will be aggregated either at an F-aggregator or S- aggregator.

15. 2015/7/15 H igh- S peed N etworking L ab. IV. Dynamic Forwarding over ToD ToD in Two-Dimentional Network ToD in 1D works because an event always in the same F-cluster or S-cluster. In 2D scenarios, if an event spans multiple F-clusters, each F-aggregator may have multiple choices of S- aggregators. Assumption: 1. size of a grid cell > maximum size of an event 2. event is contiguous 3. Dynamic Forwarding requires each F-aggregator knows the location of S-aggregator.

16. 2015/7/15 H igh- S peed N etworking L ab. IV. Dynamic Forwarding over ToD 5 × 5 F-clusters F-Cluster cell S-Cluster F-Cluster F-aggregator

17. 2015/7/15 H igh- S peed N etworking L ab. IV. Dynamic Forwarding over ToD an event spans cells in the (1) same F-cluster  aggregated at the F-aggregator (2) multiple F-clustersan event spans cells in the (1) same F-cluster  aggregated at the F-aggregator (2) multiple F-clusters four basic scenariosfour basic scenarios Generate Packets ( Source) Corresponding S-cluster

18. 2015/7/15 H igh- S peed N etworking L ab. IV. Dynamic Forwarding over ToD (2) multiple F-clusters packets originate from (i) 3 or 4 cells in the same F-cluster  no other nodes in other F-clusters have packets  forward to the sink F -cluster

19. 2015/7/15 H igh- S peed N etworking L ab. (ii) 1 or 2 cells  possible that other F-clusters also have packet (a) 1 cell: in the same S-cluster  F-aggregator forward packets to S-aggregator (b) 2 cells: must be in different S-cluster  3 cases : F -cluster S -cluster F -cluster

20. 2015/7/15 H igh- S peed N etworking L ab. IV. Dynamic Forwarding over ToD Case 2: X-Cluster  2 cell, Y-Cluster  1 cell –to guarantee that the packets can meet at least at one S- aggregator  two F-aggregators select one S-aggregator (closer to the sink) be the 2 nd S-aggregators –S-aggregator only forwards packets to the 2 nd S-aggregators if the packets it received come from two cells in one F-cluster –2 nd S-aggregator wait longer than the 1 st S-aggregator

21. 2015/7/15 H igh- S peed N etworking L ab. IV. Dynamic Forwarding over ToD [Property2] any two adjacent nodes in ToD, their packet will be aggregated at the F-aggregator, at the 1 st S-aggregator, or at the 2 nd S-aggregator even if the size of event is not known, this approach can work and efficiently than DAAeven if the size of event is not known, this approach can work and efficiently than DAA

22. 2015/7/15 H igh- S peed N etworking L ab. IV. Dynamic Forwarding over ToD F&S-clusters select an aggregator – nodes play this role in turn  distribute the energy consumption – nodes can elect themselves –Frequency of updating can be low. –Using a hash function to hash current time to a node.  select the k th node be the aggregator

23. 2015/7/15 H igh- S peed N etworking L ab. IV. Dynamic Forwarding over ToD choose a Aggregating Cluster to Simplify the cluster-head selection processto Simplify the cluster-head selection process Choose an F-cluster, called Aggregating Cluster, for each S- cluster. (closet to the sink)Choose an F-cluster, called Aggregating Cluster, for each S- cluster. (closet to the sink) Use the F-aggregator of Aggregating Cluster as the S-cluster’s S-aggregator.Use the F-aggregator of Aggregating Cluster as the S-cluster’s S-aggregator. The common aggregator for both the shaded F-cluster and S- clusterThe common aggregator for both the shaded F-cluster and S- cluster F S Aggregating Cluster aggregator (Use the F-aggregator as the S- aggregator) Aggregating Cluster aggregator (Use the F-aggregator as the S- aggregator) Select the Aggregating Cluster aggregator instead of S-Cluster

24. 2015/7/15 H igh- S peed N etworking L ab. V. Performance Evaluation Kansei sensor testbed –Nodes: 105 Mica2-based motes –7×15 grid network with 3-ft spacing –Each mote is hooked onto a Stargate –Stargate: »a 32-bit hardware device from CrossBow running Linux »be connected to the server using wired Ethernet »program motes, send messages and signals to motes through Stargate –Radio signal: using default transmission power covers most nodes –Limit nodes only to receive packets from two-grid neighboring nodes  neighbors : Each node has a maximum of 12 neighbors –Event size: not limit –Generated an Event report: Node is triggered by an event (store in a report queue) –Both the application layer and Anycast MAC layer can access the report queue –Divide the network into 2 F-clusters in ToD –The smallest cell to have only 9 sensor nodes do not consider energy of consumption on idle listening

25. 2015/7/15 H igh- S peed N etworking L ab. V. Performance Evaluation Protocol –Dynamic Forwarding over (ToD) –DAA: structureless approach –SPT: node send packets to the sink through the SPT immediately after sensing an event –SPT-D (SPT with Fixed Delay ): SPT with delay according to their height Normalized number of transmissions (NNT) = Number of transmissions in the entire network ÷ useful information from sources to the sinkNormalized number of transmissions (NNT) = Number of transmissions in the entire network ÷ useful information from sources to the sink

26. 2015/7/15 H igh- S peed N etworking L ab. V. Performance Evaluation NNT vs. Event SizeNNT vs. Event Size –fixed event location –Diameter: 12 ~ 36 ft –Node 2~6 grid-hops of the event will be triggered –Sink : at one corner Performance: Size , ToD Size , ToD  (more chances to aggregated) (more chances to aggregated) Size ,SPT-D  (long stretch problem)Size ,SPT-D  (long stretch problem) fixed structured affects performance significantlyfixed structured affects performance significantly

27. 2015/7/15 H igh- S peed N etworking L ab. V. Performance Evaluation NNT vs. Maximum DelayNNT vs. Maximum Delay –Delay: 0 ~ 8 sec. –All node generate one packet every 10 sec. Performance: SPT-D (structured-based) heavily depends on the delaySPT-D (structured-based) heavily depends on the delay

28. 2015/7/15 H igh- S peed N etworking L ab. V. Performance Evaluation Large-Scale SimulationLarge-Scale Simulation –NS2 simulator –ToD, DAA, SPT and OPT –2000 × 1200 m grid network with 35-m node separation –1938 nodes –Transmission range of nodes: >50m –Event moves: random waypoint mobility model at speed of 10 m/s for 400 seconds. Event Size: 400m in diameter –OPT (Optimal Aggregation Tree): »nodes forward their packets on the aggregation tree »aggregation tree: rooted at center of the event »Nodes know where to forward packet to and how long to wait »change when event moves »not considerate the construction overhead

29. 2015/7/15 H igh- S peed N etworking L ab. Total Unit of Useful Info. Received by Sink vs. Event Size OPT: best performance, but overhead not considered V. Performance Evaluation NTT vs. Event Size NNT vs. Event Size closer to the source Aggregate packets early

30. 2015/7/15 H igh- S peed N etworking L ab. V. Performance Evaluation NNT vs. Distance to the Sink NTT vs. Distance to the Sink Number of Packet Received at the sink per event vs. Distance to the Sink The lower the better (ratio of aggregation is high)

31. 2015/7/15 H igh- S peed N etworking L ab. VI. Conclusion We proposed a semistructured approach. Dynamic Forwarding on ToD to avoid the long stretch problem in fixed structured and eliminates the overhead of constructing and maintaining dynamic structures.

32. 2015/7/15 H igh- S peed N etworking L ab. VII. Reference Dynamic Forwarding over Tree-on-DAG for Scalable Data Aggregation in Sensor Networks Fan, Kai-Wei; Liu, Sha; Sinha, Prasun; Mobile Computing, IEEE Transactions on Volume 7, Issue 10, Oct. 2008 Page(s):1271 - 1284 Digital Object Identifier 10.1109/TMC.2008.55Dynamic Forwarding over Tree-on-DAG for Scalable Data Aggregation in Sensor Networks Fan, Kai-Wei; Liu, Sha; Sinha, Prasun; Mobile Computing, IEEE Transactions on Volume 7, Issue 10, Oct. 2008 Page(s):1271 - 1284 Digital Object Identifier 10.1109/TMC.2008.55 Mobile Computing, IEEE Transactions onIssue 10 Mobile Computing, IEEE Transactions onIssue 10