RANI NALAMARU DEPARTMENT OF COMPUTER SCIENCE BALL STATE UNIVERSITY RANI NALAMARU DEPARTMENT OF COMPUTER SCIENCE BALL STATE UNIVERSITY Efficient Transmission.

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Presentation transcript:

RANI NALAMARU DEPARTMENT OF COMPUTER SCIENCE BALL STATE UNIVERSITY RANI NALAMARU DEPARTMENT OF COMPUTER SCIENCE BALL STATE UNIVERSITY Efficient Transmission of Stored Video for Improved Management of Network Bandwidth

Overview of presentation l Introduction l Background l Problem Statement l The New VP Algorithm l Evaluation of OBA, Optimal and VP Algorithms l Summary and Future work

Introduction Network video l Many emerging applications » Entertainment, Distance learning, Catalogue browsing etc. Video packet Client Video Server Network Client Storage

Introduction Networking challenges for video l Huge bandwidth requirement if no compression l With compression traffic is bursty » Bursty traffic complicates network management Goal: Efficient transmission of high quality stored streaming video

Video compression and burstiness Burstiness can occur due to: » Type of frames used in encoding » Background changes or changes in scene content Introduction Frame sizes of a stored video

Background Transmission plan l Pre-calculated schedule to transmit a video file l Mechanism to smooth the bandwidth requirement Start End Bandwidth Read video frames from disk Implement the transmission plan Transmission of frames to network Decode and display of frames Buffering of frames in client buffer Receive frames from network Server Client Network

Background Given the parameters : Frame sizes for n frames l Client buffer size b Constraints at the client buffer Avoid buffer underflow l Avoid buffer overflow l Have all video frames in advance » Knowledge of frame sizes Goal: Find a transmission plans with minimum number of rate changes and minimized sum of rate variation Work-ahead smoothing

Background Optimal Bandwidth Allocation (OBA) algorithm (1995) Developed by Feng, Jahanian, and Sechrest (Univ. of Michigan) l Goal of OBA algorithm is to develop a transmission plan with » smallest peak bandwidth » largest minimum bandwidth » fewest possible changes in bandwidth (rate changes)

Background Optimal algorithm (1996) Developed by Salehi, Kurose, and Towsley (Univ. of Mass.) l Goal of Optimal algorithm was to develop a transmission plan with » smallest peak bandwidth » least variation between bandwidth changes (rate variation)

Problem Statement Problems with existing algorithms l Buffer sizes in the range of 20-30Mbytes are required l Retains the VBR property of stored video l Time complexity is of the order of O(N logN) and O(N 2 ) » N is the number of frames

Problem Statement Possibility of improvement l When to change transmission rate ? We wish to use best of both

Visibility Polygon (VP) Algorithm Solution - VP algorithm l Develop an algorithm based on visibility concept » Developed by Subhash Suri ( John Hopkins, 1986) What is visibility ? l Set of points that are visible from a given point in a region visible to a a b c not visible to a

Visibility Polygon (VP) Algorithm Steps in VP algorithm 1) Given frame sizes and client buffer size b. We construct the feasible region P.

Visibility Polygon (VP) Algorithm Steps in VP algorithm 2) Triangulate the feasible region P, let T represent the triangulation of P.

Visibility Polygon (VP) Algorithm Steps in VP algorithm 3) Construct the dual graph G of triangulated polygon.

Visibility Polygon (VP) Algorithm Steps in VP algorithm 4) Identify the shortest path from first frame to last frame. 5) Compute the windows, from which transmission plan is obtained.

Visibility Polygon (VP) Algorithm Complexity of VP algorithm l Triangulation O(N) l Dual Graph Construction O(N) l Breadth First Search O(N) Visibility Polygon & Windows computation Hence VP algorithm takes linear time An i mprovement over the previous algorithms which are O(N logN) and O(N 2 )

Evaluation Comparison of OBA, Optimal and VP Algorithms l Simulation model l Use trace files of representative videos Parameters for evaluation l Peak-rate bandwidth l Number of rate changes l Variation between rate changes l Time complexity

Evaluation Peak-rate bandwidth

Evaluation Rate changes and variation between rate change Intervals Variation

Evaluation Time complexity l Measure the number of seconds for calculating transmission plan

Evaluation Experimental setup Java Simulation Program Video frames retrieved from server storage Transmission plan

Evaluation Validation of simulation model Conservative results

Evaluation Inputs l Videos were selected to be representative with respect to length and subject material

Evaluation Peak-rate bandwidth 8 % 3.7 % OBA Optimal

Evaluation Number of rate changes 19 % 8.3 % OBA Optimal

Evaluation Amount of variation 15.3 % 9.6 % OBA Optimal

Evaluation Time complexity 73.6 % OBA 3.8 % Optimal

Evaluation What does all this mean to end users ? If VP algorithms is used If other algorithms are used Video Server Clients

Summary and future work Summary l Problems with efficiently transmitting stored (compression) video l Reviewed OBA and Optimal algorithms l New VP algorithm proposed l Simulation results showed VP algorithm has better performance to its predecessors

Summary and future work Future work l To implement VP algorithm on an actual video server l To study issues of multicast support of VP algorithm