Multi-Source Latency Variation

Synchronization for Collaborative Applications

Abhishek Bhattacharya, Zhenyu Yang & Deng Pan

Roadmap

•Introduction•Problem•Motivation•Heuristic Solution•Results•Summary

Introduction

• Single-source/Single-stream Multicast Network: Construction of a MST connecting a single source and multiple receiver nodes

• Single-source/Multi-stream Multicast Network: Content distribution systems using MDC/SVC streams.

• Multi-source/Single-stream Multicast: Constructing a forest of trees connecting multiple sources with multiple receiver nodes.

• Multi-source/Multi-stream systems such as 3D Virtual Immersive Systems, 3D Videoconferencing, Online games, etc.

Example – Multi-source/Multi-stream System

• 3DTI environment provides a collaborative virtual space for geographically distributed users.

• Multiple 3D cameras installed for capturing the same scene from various viewpoints.

• Each 3D camera produces a video stream.

• Multiple streams are transmitted from each node to all other nodes since each node acts a source and a receiver.

Node A

Node B

Node C3D Camera

Display Unit

S1AB

S2AB

S7BA

S6BA

S8CB

S1CB

S5BC

S4BC

S3AC

S3AC

S7CA

S6CA

Skij camera stream ‘k’ from node ‘i’ to node ‘j’

Introduction• Latency Variation is an important QoS constraint for

Multi-source/Multi-stream systems.

• Problem known as Delay Variation Bounded Multicast Network (DVBMN) in the literature. Proved to be NP-complete by Rouskas et al. and thereafter many heuristics proposed.

• Multi-source/Multi-stream latency and latency-variation constraints: E2E from source to destination, Inter-stream, Inter-Source & Intra-Source Latency Variation.

• Intra-source is important for 3DTI applications due to the high correlation factor among the multiple streams from the same source.

Node A

Node B

Node C

S1AB

S2AB

S7BA

S6BA

S8CB

S1CB

S5BC

S4BC

S3AC

S3AC

S7CA

S6CAIntra-SourceVariation

Inter-Source Variation

Problem

P:

C1:

C2:

C3:

E2E Latency from Source to Destination:

Inter-Stream Latency Variation:

Inter-Source Latency Variation:

Motivation

V1

V3

V2

V4

V6

V7

V5

6

5

8

12

10

2

12

74

8

9

∆ = 22

S16 : V1 V4 V6 : 12

S17 : V1 V4 V7 : 16

S26 : V2 V4 V6 : 16

S27 : V2 V5 V7 : 12

β = 16 – 12 = 4

λ6 = 16 – 12 = 4 ; λ7 = 16 – 12 = 4

λT = Max(λ6 , λ7) = 4

V1 V3 V4 V6 : 17 V1 V3 V4 V7 : 21V2 V1 V4 V6 : 17V2 V4 V7 : 20

β = 21 – 17 = 4

λ6 = 17 – 17 = 0 ; λ7 = 21 – 20 = 1

λT = Max(λ6 , λ7) = 1

Motivation Path

Latency List

K-shortest Paths Latency

S16

V1 V4 V6 12

V1 V3 V4 V6 17

V1 V3 V6 18

S17

V1 V4 V7 16

V1 V2 V5 V7 17

V1 V3 V4 V7 21

S26

V2 V4 V6 16

V2 V1 V4 V6 17

V2 V5 V7 V6 21

S27

V2 V5 V7 12

V2 V4 V7 20

V2 V1 V4 V7 21

Heuristic Solution: Algorithm A 2-step framework:

K-shortest-path Algorithm:

Involves the computation of k-shortest path from each source to all the destination nodes. Generates ‘d*s’ lists with ‘k’ elements in each list.

State-of-art ksp Algorithm: Recursive Enumeration Algorithm(REA) by Jimenez et al.

Heuristic Solution: Algorithm M SLV Algorithm:

Involve a selection of paths for the construction of forest i.e., multiple multicast trees connecting one source node to the set of destination nodes.

Selecting ‘d*s’ path latency values from ‘d*s*k’ elements. Path Latency values. The Path Latency values should satisfy the constraints: C1: E2E latency bound (∆), C2: Latency Variation among any path(β), and C3: Inter-Source LatencyVariation(λT).

Heuristic Solution: Algorithm

17 18

T = 4; λ6 = 4; λ7 = 4; λT = 4

12S16

S26

S17

S27

17 2116

20 2412

17 2116

12

16

12

16

1712 T = 5; λ6 = 1; λ7 = 4; λT = 4

2012

T = 4; λ6 = 1; λ7 = 4; λT = 4

16 17

T = 4; λ6 = 1; λ7 = 3; λT = 316 17

T = 3; λ6 = 0; λ7 = 3; λT = 3

17 18

T = 4; λ6 = 0; λ7 = 1; λT = 1

17 21

T = 4; λ6 = 4; λ7 = 1; λT = 4

17 21

T = 3; λ6 = 3; λ7 = 1; λT = 3

∆ = 25 ; β = 4

Heuristic Solution: Time Complexity ksp-Algorithm: O(m + nk * log(m/n))

m number of total edges in the network graph

n number of total nodes in the network graph k number of shortest paths

MSLV Algorithm: O(dsk * log(ds)) d number of destination nodes in the multicast set

s number of source nodes in the multicast set

Results

Detailed results in the paper

Summary• Studied construction of multicast networks with multiple sources and receivers.

• Satisfying different Latency Variation constraints which are important for real-time multi-party/multi-stream systems.

• A 2-step heuristic framework consisting of an initial ksp-algorithm to generate shortest paths from sources to receivers followed by a path selection process to satisfy the various hard/soft constraints.

• Future work involves to investigate the problem with link capacities as time-varying functions and decentralized solutions with node/network dynamics.