The Broadcast Storm Problem

Transcription

1 The Broadcast Storm Problem Alexander Hamann Seminar: Ad-Hoc Networks

2 Outline I. Introduction II. Broadcast Storm Problem III. Scheme-based flooding IV. Performance simulation V. Conclusion Ad-Hoc Networks: The Broadcast Storm Problem 2

3 I. Introduction Ad-Hoc Networks: The Broadcast Storm Problem 3

4 Recap mobile ad-hoc networks (MANETs) most often deployed in battlefield situations, disaster recovery situations networks need to come up quickly no base stations / network infrastructure CSMA/CA Ad-Hoc Networks: The Broadcast Storm Problem 4

5 Recap due to radio power limitation, channel utilization considerations, power-saving concerns direct communication between the hosts often not possible in one hop multihop scenario Ad-Hoc Networks: The Broadcast Storm Problem 5

6 Why broadcasting? common operation to solve many issues paging, sending alarm signals, routing (e.g., DSR, ZRP, AODV), providing multicast in rapidly changing topologies Ad-Hoc Networks: The Broadcast Storm Problem 6

7 II. Broadcast Storm Problem Ad-Hoc Networks: The Broadcast Storm Problem 7

8 Flooding problem: send a msg to the other hosts straight-forward: broadcasting by flooding if done blindly: many redundant rebroadcasts (high load), (heavy) contention, collisions Broadcast Storm Problem! Ad-Hoc Networks: The Broadcast Storm Problem 8

9 Analysis: Redundancy optimal broadcasting white: source host grey: relay host Ad-Hoc Networks: The Broadcast Storm Problem 9

10 Analysis: Redundancy intersection area: add. coverage: additional coverage of rebroadcasts: 0 ~ 61% Ad-Hoc Networks: The Broadcast Storm Problem 10

11 Analysis: Redundancy expected additional coverage Ad-Hoc Networks: The Broadcast Storm Problem 11

12 Analysis: Redundancy rebroadcasts are costly max. gain in coverage: 61% avg. gain 1st rebroadcast: 41% avg. gain 2nd rebroadcast: 19% avg. gain from 4th rebroadcast on: < 0,05% use them with caution! Ad-Hoc Networks: The Broadcast Storm Problem 12

13 Analysis: Contention probability of contention: example: 2 receiving hosts B and C B randomly located at A s (sender) transmission range B and C might contend if C is in expected probability: Ad-Hoc Networks: The Broadcast Storm Problem 13

14 Analysis: Contention probabilities of having k contention-free hosts among n receiving hosts: cf(n,k) Ad-Hoc Networks: The Broadcast Storm Problem 14

15 Analysis: Contention contention problem is serious prob. of all n hosts experiencing contention cf(n,0), n=2: 59% cf(n,0), n>6: >80% prob. of having one contention-free host cf(n,1), n=3: 35% cf(n,1), n>5: <10% more than one contention-free host is very unlikely (esp. when n>6) Ad-Hoc Networks: The Broadcast Storm Problem 15

16 Analysis: Collision CSMA/CA - backoff after transmission or when medium is busy backoff-procedure: counter set to an integer randomly picked from backoff window if CCA (channel clear assessment) detects no activity during past slot: counter 1 counter == 0 backoff finished Ad-Hoc Networks: The Broadcast Storm Problem 16

17 Analysis: Collision example: X sender of a broadcast X s surrounding has been quiet for some time: X s neighbours might have finished their backoff may all start rebroadcasting at the same time RTS/CTS not used for broadcast: more serious damage lack of CD: host finishes its transmission, even if bits have been garbled Ad-Hoc Networks: The Broadcast Storm Problem 17

18 Analysis: Outcome Broadcast Storm Problem deserves serious studies! Ad-Hoc Networks: The Broadcast Storm Problem 18

19 III. Scheme-based Flooding Ad-Hoc Networks: The Broadcast Storm Problem 19

20 Overview inhibit certain hosts from rebroadcasting to alleviate the problem five schemes: probabilistic counter-based distance-based location-based cluster-based Ad-Hoc Networks: The Broadcast Storm Problem 20

21 Probabilistic scheme on receiving broadcast msg for the 1st time: rebroadcast with probability P a few slots delay before rebroadcasting should be added (to reduce collisions) P = 1 equals flooding Ad-Hoc Networks: The Broadcast Storm Problem 21

22 Counter-based scheme rebroadcast message may be blocked busy medium, backoff procedure, other queued messages counter c keeps track of repeated arrivals of the same message if a certain counter threshold C is reached ( EAC(k) too low), the rebroadcast is canceled Ad-Hoc Networks: The Broadcast Storm Problem 22

23 Counter-based scheme Algorithm Ad-Hoc Networks: The Broadcast Storm Problem 23

24 Distance-based scheme relative distance d between hosts decides whether rebroadcast is dropped or not larger d larger additional coverage if msg is heard more than once: distance from the nearest host ( ) is used if distance is below threshold D, rebroadcast is canceled Ad-Hoc Networks: The Broadcast Storm Problem 24

25 Distance-based scheme Algorithm Ad-Hoc Networks: The Broadcast Storm Problem 25

26 Location-based scheme exact locations of broadcasting hosts used (e.g., 3D-coordinates with GPS) additional coverage AC can be calculated with higher precision coverage threshold A to decide whether the host should rebroadcast or not Ad-Hoc Networks: The Broadcast Storm Problem 26

27 Location-based scheme Algorithm Ad-Hoc Networks: The Broadcast Storm Problem 27

28 Location-based scheme calculating AC is already difficult with 4 circles convex polygons to approximate AC max. coverage loss: 22% Ad-Hoc Networks: The Broadcast Storm Problem 28

29 Cluster-based scheme approach based on graph modeling cluster formation algorithm: every hosts advertises its presence thus every host can determine its connectivity the host with the local minimal ID elects itself as a cluster head, all surrounding hosts are cluster members a member who can communicate with a member of another cluster is called gateway when two heads meet, the one with the larger ID gives up his head role Ad-Hoc Networks: The Broadcast Storm Problem 29

30 Cluster-based scheme Ad-Hoc Networks: The Broadcast Storm Problem 30

31 Cluster-based scheme Algorithm Ad-Hoc Networks: The Broadcast Storm Problem 31

32 IV. Performance simulation Ad-Hoc Networks: The Broadcast Storm Problem 32

33 Parameters transmission radius: 500m (= 1 unit) packet size: 280 bytes transmission rate: 1 Mbit/s 100 mobile hosts map sizes: 1x1, 3x3, 5x5, 7x7, 9x9, 11x11 units one broadcast per second 10,000 broadcast requests broadcasting host randomly chosen Ad-Hoc Networks: The Broadcast Storm Problem 33

34 Performance metrics Reachability (RE) (number of hosts receiving the broadcast / total number of hosts reachable from source) Saved Rebroadcast (SRB) [(received broadcasts transmitted rebroadcasts) / received broadcasts] Average latency (time, last host finishes rebroadcasting broadcast initiation time) Ad-Hoc Networks: The Broadcast Storm Problem 34

35 Counter-based scheme (a) Counter threshold C vs. reachability RE (shown in lines) and saved rebroadcast SRB (shown in bars). (b) Counter threshold C vs. average latency. Ad-Hoc Networks: The Broadcast Storm Problem 35

36 Location-based scheme (a) Coverage threshold A vs. reachability RE (shown in lines) and saved rebroadcast SRB (shown in bars). (b) Coverage threshold A vs. average latency. Ad-Hoc Networks: The Broadcast Storm Problem 36

37 V. Conclusion Ad-Hoc Networks: The Broadcast Storm Problem 37

38 Conclusion The Broadcast Storm is a serious problem a simple counter-based scheme can eliminate many redundant rebroadcasts when host distribution is dense if location information is available, the location-based scheme is dominant (reduces redundancy w/out compromising the reachability) Ad-Hoc Networks: The Broadcast Storm Problem 38

39 References [1] S.-Y. Ni, Y.-C. Tseng, Y.-S. Chen, and J.-P. Sheu, "The broadcast storm problem in a mobile ad hoc network," in Proceedings of the Fifth Annual ACM/IEEE International Conference on Mobile Computing and Networking, August 1999, pp Ad-Hoc Networks: The Broadcast Storm Problem 39