Thomas DreibholzInstitute for Experimental Mathematics

University of Duisburg-Essen, Germany

dreibh@iem.uni-due.de

University of Duisburg-Essen, Institute for Experimental Mathematics

A New Server Selection Strategyfor Reliable Server Pooling in Widely

Distributed Environments

Thomas DreibholzA New Server Selection Strategy for Reliable Server Pooling in Widely Distributed Environments P. 2

Table of Contents

What is Reliable Server Pooling? Prototype Demonstration Terminology and Protocols Motivation and Application Scenarios

The Challenge on Network Delay on Server Selection

The Least Used with Degradation Policy

Evaluation

Conclusion and Outlook

Thomas Dreibholz's Reliable Server Pooling Pagehttp://tdrwww.iem.uni-due.de/dreibholz/rserpool/

Thomas Dreibholz's Reliable Server Pooling Pagehttp://tdrwww.iem.uni-due.de/dreibholz/rserpool/

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What is „Reliable Server Pooling“?Prototype Demonstration

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Reliable Server Pooling (RSerPool)

Terminology: Pool Element (PE): Server Pool: Set of PEs PE ID: ID of a PE in a pool Pool Handle: Unique pool ID Handlespace: Set of pools Pool Registrar (PR) Pool User (PU): Client

Support for Existing Applications Proxy Pool User (PPU) Proxy Pool Element (PPE)

Protocols: ASAP (Aggregate Server Access Protocol) ENRP (Endpoint Handlespace Redundancy Protocol)

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What is a Pool Policy? A rule for the selection of the PEs Defined in our IETF Working Group draft (draft-ietf-rserpool-policies-07.txt)

Application of Policies Registrar: Creates PE list upon request by PU Pool User: Selection of a PE from the list Both according to the pool policies (pool-specific!)

Non-Adaptive Policies Stateless: Random (RAND) Stateful: Round Robin (RR) (Default policy, must be supported)

Adaptive Policy Least Used (LU)

Load definition is application-specific! Round robin among multiple least-loaded PEs

Server Selection Rules(Pool Policies)

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The Challenge of Network Delay on Server Selection

Challenge of Least Used Load states get out of date, due to

Network latency Cache

Solution: Least Used with Degradation (LUD) Policy Information:

Load = Current Load (obvious) Load Increment = How much is load increased by a new request?

Select PE, which has lowest sum of (Load + Load Increment) Round robin among equal-valued PEs Upon selection:

Increment load by load increment Incrementation only local on selection component

(i.e. registrar and PU's cache)!

Upon update: Load is reset to latest known load state

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The Application Model

Server– PE Capacity– Shared among sessions

(multi-tasking principle)

Client– Requests are generated

• Request Size (effort)• Request Interval (frequency)

– Waiting queue for requests– Sequential processing

System Utilization– PU:PE Ratio

– Provisioning for certain Target Utilization, e.g. 80%

yAvgCapacitrvalRquestInte

RquestSize

opuToPERatiizationsystemUtil *

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Performance Metrics

Provider's Perspective“Does my server capacity gain revenue?”

Average Utilization of server resources [%]

User's Perspective“How much time is

needed to process

my requests?”

Avg. Handling Speed

[% of average

server capacity]

Depends on: Queuing Startup Server

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Increasing the Network Delay -A Proof of Concept

Example setup as a proof of concept

Network latency reduces the handling speed ...

... but with LUD, there is a significant speed benefit compared to LU

More investigations necessary Workload parameters Number of registrars Cache

Handling SpeedHandling Speed

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Variation of Workload Parameters:PU:PE Ratio

Small PU:PE ratio is critical (high per-PU workload)

LUD achieves significant performance improvement over LU

Handling SpeedHandling SpeedUtilizationUtilization

LU, Req.Int=10s (critical!)LU, Req.Int=10s (critical!)

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Variation of Workload Parameters:Request Interval

Small request interval is critical (especially for small PU:PE ratio!)

For PU:PE ratio > 1, LUD again achieves a significant improvement

Handling SpeedHandling SpeedUtilizationUtilization

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Increasing the Number of Registrars

Handlespace synchronization Necessary to cope with PR failures Additional load update latency

Results: LUD again achieves a significant

benefit over LU ... ... for realistic number of PRs (less

than 10)

Handling SpeedHandling Speed

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Using the PU-Side Cache

Cache at the PU: Stores partial, temporary subset of

the handlespace Reduces number of PR queries Contents get out of date

Results: Again, LUD outperforms LU

Handling SpeedHandling Speed

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Conclusion and Outlook

Conclusion RSerPool is the IETF's upcoming standard for service availability Network delay leads to out-of-date load states for Least Used policy Least Used with Degradation (LUD)

Local increment upon selection, until update arrives Improved system performance, especially for critical workload parameter

settings

Future Work From simulation to reality:

Tests with our prototype implementation in the PlanetLab First results already available [KiVS2007]

Security analysis and robustness against DoS attacks

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Thank You for Your Attention!Any Questions?

Visit Our Project Homepage:http://tdrwww.iem.uni-due.de/dreibholz/rserpool/

Thomas Dreibholz, dreibh@iem.uni-due.de

To be continued ...To be continued ...

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The RSerPool Protocol Stack

Aggregate Server Access Protocol (ASAP) PR PE: Registration, Deregistration and Monitoring by Home-PR (PR-H) PR PU: Server Selection, Failure Reports

Endpoint Handlespace Redundancy Protocol (ENRP) PR PR: Handlespace Synchronisation

ASAP is IETF's first

Session Layer standard!

ASAP is IETF's first

Session Layer standard!

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Motivation

Motivation of RSerPool: Unified, application-independent solution for service availability Not available before => Foundation of the IETF RSerPool Working Group

Application Scenarios for RSerPool: Main motivation: Telephone Signalling (SS7) over IP Under discussion by the IETF:

Load Balancing Voice over IP (VoIP) with SIP IP Flow Information Export (IPFIX)

... and many more!

Requirements for RSerPool: “Lightweight” (low resource requirements, e.g. embedded devices!) Real-Time (quick failover) Scalability (e.g. to large (corporate) networks) Extensibility (e.g. by new server selection rules) Simple (automatic configuration: “just turn on, and it works!”)