Load Management in
Distributed Video Servers
Chaitanya Chemudugunta
[email protected]
Load Management in
Distributed Video Servers
By
Nalini Venkatasubramanian
Srinivas Ramanadhan
International Conference on Distributed Computing Systems
(ICDCS 97), May 1997
Overview
Architecture
Load Management Mechanisms
Characterizing Server Resource Usage
Adaptive Scheduling of Video Objects
Predictive Placement of Video Objects
Optimization Methods
Performance Evaluation
Load Management in Distributed
Video Servers
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A Scalable Video Server
Architecture
Distribution Network
requests
Distribution
Controller
data
Data
Source
Data
Source
...
Data
Source
Tertiary
Storage
control
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Video Servers
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Resources in a Video Server
Client
Client
Network
Communication
Modules
Data Manipulation
Modules
Processing
Module
Storage
Modules
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Video Servers
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Load Management Mechanisms
Replication
When existing copies cannot serve a new request
Request Migration
Unsuitable for distributed video servers – explicit
tear-down and reestablishment of network
connection.
Dereplication
Important – Storage space is premium
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Video Servers
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Load Placement Scenario
Data
Source
S2
Data
Source
S1
Storage:
8 objects
Bandwidth:
3 requests
Storage:
2 objects
Bandwidth:
8 requests
Access Network
...
Clients
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Video Servers
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Characterizing Server
Resource Usage
Ability to service a request on a server depends on:
resource available
characteristics of a request
Load factor(LF) for a request:
represents how far a server is from request admission
threshold.
LF (Ri, Sj) = max (DBi/DBj , Mi/Mj , CPUi/CPUj , Xi/Xj)
Ri – Request for Video Object Vi, Sj – Data Source j
DB – Disk Bandwidth, M – Memory Buffer, CPU – CPU cycles,
X – Network Transfer Bandwidth
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Video Servers
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Adaptive Scheduling
When the distribution controller receives a
request Ri for a video object Vi :
Consider only data sources that have a copy of Vi.
Consider only data sources that have sufficient resources to
support Ri.
Chooser server for which LF (Ri, Sj) is a minimum.
If no such server exists
• Reject request.
• Perform replication-on-demand.
• Perform request migration.
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Video Servers
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Predictive Placement of Video
Objects
Determines when, where and how many
replicas of a video object.
Initiated periodically.
Results in an assignment of replicas to data
sources.
Formulated as an optimization problem – metric
to be optimized is the total revenue.
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Video Servers
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Predictive Placement of Video
Objects … Continued
Each request Ri is associated with a revenue ri.
ri is dependent on
Resource required for Ri
Characteristics of Vi
Popularity of Vi
Greedy approach to solve the optimization
problem.
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Video Servers
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The Greedy Cost Placement
Matrix
S1
S2
V1
min(N1,1/LF(R1,S1))*r1
min(N1,1/LF(R1,S2))*r1
V2
min(N2,1/LF(R2,S1))*r2
min(N2,1/LF(R2,S2))*r2
V3
min(N3,1/LF(R3,S1))*r3
min(N3,1/LF(R3,S3))*r3
max(PM(Vi,S1))
max(PM(Vi,S2))
PM(Vi, Sj) is the maximum revenue that can accrue from allocating Vi to Sj.
Greedy heuristic: Map(Vi,Sj) = 1 if PM(Vi,Sj) = a b max(PM(Va,Sb))
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Video Servers
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Optimizations
To minimize the overhead of replication
Eager replication
Replication of video object in anticipation
Performed when server resources are free
Lazy Dereplication
Critical nature of storage resources
Mark reusable resources, reclaim disk space later
If disk blocks are not overwritten, can be reclaimed
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Video Servers
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Life of a video object
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Video Servers
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Performance Evaluation
Policies
Policy
Placement of Video Objects
Request Scheduling
P1
Replication on-demand
Adaptive
P2
Predictive placement
Predictive
P3
Predictive placement
Adaptive
P4
Predictive placement + eager
replication
Adaptive
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Video Servers
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Performance Evaluation Startup Latencies
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Video Servers
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Performance of the basic
configuration
p1
p2
p3
p4
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Video Servers
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Performance Evaluation Varying Replication BW
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Video Servers
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Performance Evaluation
Summary
P1: entails high startup latency, requires high
storage and replication bandwidth.
P2: Unacceptably poor performance.
P3: Similar performance to P4 in many cases.
At low transfer bandwidths, P4 outperforms P3.
P4: Performs well in all cases.
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Video Servers
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Thank You