1 / 25

Quantifying Impact of Mobility on Data Availability in Mobile Ad Hoc Networks

Quantifying Impact of Mobility on Data Availability in Mobile Ad Hoc Networks. Takahiro Hara IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 9, NO. 2, FEBRUARY 2010. 1. Mobility model. 1. Random Walk (RW)

tymon
Download Presentation

Quantifying Impact of Mobility on Data Availability in Mobile Ad Hoc Networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Quantifying Impact of Mobility on Data Availability in Mobile Ad Hoc Networks Takahiro Hara IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 9, NO. 2, FEBRUARY 2010. 1

  2. Mobility model • 1. Random Walk (RW) • At every unit of experimental time, each MH randomly determines a movement direction and speed from 0 to V [m/s]. • 2. Random WayPoint (RWP) • MHs selects a random destinations with the speed. After reaching the destination, it again pauses, and then, repeats this behavior. • 3. Manhattan Mobility (MM) • MM emulates the node movement on streets where nodes only travel on the pathways in the map. • 4. Reference Point Group Mobility (RPGM) • Each group has a logical “center” called a reference point. MHs moves to the reference point (nearby) based on the RWP model. • 5. Random Waypoint with Locality (RWP-L) • The concept of Home area. • MHs choose a random destination insider the home area with high prob. H and one outside the region with prob. 1-H. H: the home area ratio. 2

  3. metrics • For Data availability (data storage capacity) • 1. Average size of partitions (Network) • 2. Distribution of partition sizes (Network) • 3. Size of partitions belonged to (Node) • 4. Change in size of partitions belonged to (Node) • 5. Distribution of connected nodes (Node) • For Data distribution (data replication) • 6. Total number of connected nodes (Direct) • 7. Total number of data-reachable nodes (Indirect)

  4. 1. Average size of partitions l: 幾個interval m: 節點數 n1:表示第1個t時間內的partition個數 Time t t t t t t T = l * t l = 6

  5. 2. Distribution of partition sizes 5

  6. 3. Size of partitions belonged to Mk: Mobile node k 6 Q:在ti時間，某1個節點，有不同二個partition的連結。

  7. 4. Change in size of partitions belonged to 7

  8. 5. Distribution of connected nodes 8

  9. 6. Total number of connected nodes 7. Total number of data-reachable nodes 9

  10. 7. Total number of data-reachable nodes Ri denotes a set of mobile nodes that mobile nodes in Ni connected to from the beginning of ti until the end of the observation time l’ * t Cs,f,Mj denotes a set of mobile nodes that Mjhave connected to during the duration from ts to tf . Ni denotes a set of mobile nodes that Mk first connected to at the beginning of ti but have never connected to before that. 10

  11. 1. Average size of partitions Reference Point Group Mobility Map:2500m x 2500m Node:300 Transmission range: 100m 11

  12. 2. Distribution of partition sizes 1. Group mobility 2. Random Way Point 3. Manhattan Mobility 4. Random Waypoint with Locality 5. Random Walk 12

  13. 3. Size of partitions belonged to 1. Group mobility 2. Random Way Point 3. Manhattan Mobility 4. Random Waypoint with Locality 5. Random Walk 13

  14. 4. Change in size of partitions belonged to 14

  15. 5. Distribution of connected nodes 15

  16. 6. Total number of connected nodes

  17. 7. Total number of data-reachable nodes

  18. T as 10,000,000 seconds t =1, l = 10,000,000 The first 1000s is removed. 19

  19. 20

  20. 21

  21. 22

  22. 23

  23. Related work In [8] Network wide metrics: Number of partitions Average size of partitions Average partition change rate Node-centric metrics: Node partition change rate Node separation time The first two metrics represent the capacity of data storage (memory space) of each partition The larger the partition is, the more data can be stored in it. The other three metrics just represent how frequently members of each partition change or how long before each pair of two nodes disconnects. [8] J. Hahner et.al. “Quantifying Network Partitioning in Mobile Ad Hoc Networks,” Proc. Int’l Conf. Mobile Data Management, pp. 174-181, 2007. 24

  24. Motivation • More specifically, these metrics cannot distinguish whether only one node disconnects from the partition or the partition is split into two partitions with the same size. • Also, they do not represent how many nodes each node connects with at a certain interval. Thus, they do not truly represent the dynamism of partitions. • In this paper, we propose new metrics to represent the dynamism of partitions in MANETs.

More Related