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Placement of Continuous Media in Wireless Peer-to-Peer Network

Placement of Continuous Media in Wireless Peer-to-Peer Network. Shahramram Ghandeharizadeh, Bhaskar Krishnamachari, and Shanshan Song IEEE Transactions on Multimedia, April 2004. Home-to-Home Online (H2O) devices collaborate to deliver continuous media H2O may act as: A producer of data

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Placement of Continuous Media in Wireless Peer-to-Peer Network

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  1. Placement of Continuous Media in Wireless Peer-to-Peer Network Shahramram Ghandeharizadeh, Bhaskar Krishnamachari, and Shanshan Song IEEE Transactions on Multimedia, April 2004

  2. Home-to-Home Online (H2O) devices collaborate to deliver continuous media H2O may act as: A producer of data An active client A router H2O Framework

  3. Motivation • A new replication technique that • Provide on-demand access to continuous media • Minimize the total storage space required

  4. Assumptions • CBR continuous data • Total size of available clips exceeds the storage capacity of one device • Bandwidth between two H2O devices exceeds the bandwidth required to display a clip • One hop distance is a constant

  5. Hi: the Farthest Number of Hops a Block Can be Located • Cycle: period to display a block • D=Sb/BDisplay • The farthest number of hops that the block i can be located: • Hi=((i-1)D)/h block size playback rate time to retrieve a block from one hop away

  6. Data Placement and Replication • For each video clip X: • Divide X into equal-sized blocks with size Sb • Place first block, b1 on each node. • For each block bi, 1<i<=z, compute delay tolerance Hi • Compute ri based on Hi • Construct ri replicas of bi and place them • ri is a topology dependent computation

  7. Topology I: Worst Case Linear Topology • Block i should be replicated ri times: • Hi=(i-1)D/h • ri=N-Hi • Reset ri to one if ri is zero or negative • Total storage space (SC,R) occupied by a clip with z blocks: … 1 2 3 8 9

  8. Percentage Saving Compared with Full Replication in Linear Topology • N=1000, h=0.5, • BDisplay = 4Mbps • y: 100x(1-SC,R)/(SCxN)

  9. Topology II: Grid Topology • Organize N nodes in a square area • At least one copy of bi must be placed within Hi hops • There are nodes within Hi hops of every node • Total storage required:

  10. Total Storage Space Required as a Function of Block Size (1/2) • h=0.75s • 2 min clip (total 60MB)

  11. Total Storage Space Required as a Function of Block Size (2/2) • h=0.75s • 2 hour clip (total 3600MB)

  12. Topology III: Average Case Topology (1/2) • Network connectivity depends on radio range R • N nodes are scattered in area A • There are on average between and nodes within Hi nodes.

  13. Topology III: Average Case Topology (2/2) • Using the upper boundary, the H number of replicas ri required by bi is: • Total storage required for a clip:S

  14. Percentage Saving Comparison

  15. Distributed Implementation • H2Op: publish a clip X • Compute block size Sb, number of blocks z, and Hi for each block • Flood the network to query which H2O will host a copy of which block of X • H2Oj: each recipient of the message • Compute a binary array Aj that consists of z elements whose values are 0 or 1 • Two computation methods: TIMER or ZONE

  16. Technique I: TIMER • When H2Oj receives query message • Perform z rounds of elections • Pick a random timer value between 1 and M then count down • The one first count down to zero stores a copy and send suppress message within Hi hops • May generate more than one copies of a block within Hi hops

  17. Technique II: ZONE • Assume each node is aware of its (x, y) coordinate • Place each copy in a separate square zone whose size is such that all nodes can be reached within Hi hops

  18. Simulation: TIMER vs. ZONE • N=300, R=100m, A=1km2, z=60

  19. Simulation: Comparison of Analytical Models for Graph Topology with 2 Implementations • SC=60MB • R=100m • A=1km2

  20. Simulation: How Many Blocks a H2O Device Have When Using TIMER • N=300, R=100m, A=1km2 • Average # of blocks per node for a clip is marked as dashed line

  21. Conclusion • Provide a novel replication technique for on-demand clips • Minimize startup delay • Storage saving compared with full replication • Provide two distributed implementations

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