stateless load balancing - early results

Medilink srlSezione Ricerca e Sviluppo

STATELESS LOAD BALANCING

A distributed algorithm for

Abstract: Distributing data-packets on stations with scalable and optimal store and retrival functionalities. Ensuring load balance without collecting load-info from stations.

Keywords: Distributed-Systems, Algorithms, Big-Data, Cloud, Balancing

[research early results]

Prof. Eng. O. Tomarchio

University tutor:Università di CataniaDipartimento di Ingegneria Elettrica, Elettronica e Informatica

Eng. A. Maddalena

Company supervisor:Medilink srlTeam Leader - R&D Manager

Dr. A. Tino

Trainee:Università di CataniaFacoltà di Ingegneria Informatica Specialistica

Showing results

August 2013

Dr. Andrea TinoUniversità degli Studi di CataniaIngegneria Informatica

Research trainee:Eng. Andrea MaddalenaSoftware Development

Supervisor:

Medilink srl


Prof. Eng. Orazio TomarchioDIIEI

Tutor:

Università di Catania

STATUS: SIMULATING...Some real-scenario simulations have been conducted over several rings. Now showing early results while other simulations are still running.

about simulations: state of art

Ring size: Every simulation will create a fixed number of stations, each of which is assigned a personal hash (identifier in the ring).

Packets volume: When running, a simulation will generate a fixed (usually very high) number of random packets to be fed to the the ring.

Packet size: When running, simulations will generate packets of fixed length. Each packet will be fed to a hash function.

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TUNING SIMULATIONSSimulations have been designed to be scalable, configurable and flexible. Basic functionalities enabled at the moment, further improvements planned.

Number of stations: NNumber of generated packets: MPacket length/size: P

simulation parameters

Developed in C++Template based, fast, support for reals and big-realsResults output on files: raw+stats

simulation tech details

T3

T1

T2

T4

T5

T6

s1 s2 s3 s4 s5 s6

0 hmax-1

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SIMULATIONS OVERVIEWSimulating small, medium-sized and large rings against small to large packets volums and size.

Ring size: N

Packets volume: M

Packet length/size (bytes): P

Small rings simulated: N10 to N30Mid-sized rings simulated: N30 to N50Big rings rings simulated: N50 to N100

Low volumes: M1.000 to M100.000High volumes: over M1.000.000

Simulated range: P10 to P1000

vssmall big

vsfew many

vsshort long

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INGREDIENTS 4 SIMULATIONS Simulations are designed to be flexible, configurable, fast, type independent and extensible.

Intel Threading Building Blocks (TBB)

Intel Core i7 Computer architecture

GNU C/C++ compiler (gcc/g++)

Unix RHEL based CentOS systems

Boost C++ Libraries

Tina’s rnd number generators

OpenSSL cryptographic libraries

Circos circo-diagrams drawing library

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SIMULATIONS ARCHITECTUREWhen simulating a NMP-scenario, the whole process consists of different stages.

Configuration through bash scripts

Compilation needed for fast sims

Quantities are evaluated

Simulation is executed

Results on files

dhtlb::SIM_ENV_N

dhtlb::SIM_ENV_M

dhtlb::SIM_ENV_PKTSIZEdhtlb::Ring<N,M,P>::HPart

dhtlb::Ring<N,M,P>::seed

Bash scripts are used to change the src code to configure each simulation.

Templated classes (on N,M,P as well) cause compilation as a step.

cpphpp hpp hpp

cpp cpp cpphpp

g++ -lx

obj01

out01

obj01

obj01

out01

Bash scripts create random hpartitions for stations that are passed to simulations.

sh sh sh

./x.sh out01 bin/cppsim

./x.out

Sims are executed on a long-running task machine. Simulations use use all mach cores.

out01 bin/cppsim

writing...

dat tab kry

At the end of each simulation, data is written and summarized on files.

st1: 0x0385fa6bcst2: 0x746c6aa6b

stn: 0xa12345ddd...

running

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ANATOMY OF A SIMULATIONWhen a simulation starts, many things happen...

A considerable amount of memory is needed to run a simulation.

The core part of the simulation is handled in parallel thanks to its Monte Carlo scheme.

つづく

A packet created in every parallel cycle!

Memoryinitialization

Packets handling

Data manipulation

Results on files

Resource collection

Packet generation Routing Result in

memoryHash/PhiH

computation

seeddat tab kry

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ANATOMY OF A SIMULATIONA better scheme allows the possibility to run more simulations on the same set of packets.

Packets are ALL generated at once first.

Each parallel cycle will find corresponding packet in a specific assigned array position.

終わり

Memoryinitialization

Packets handling

Data manipulation

Results on files

Resource collection

seeddat tab kry

Hash/PhiHcomputation Routing Result in

memoryPackets

generation

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OTHER FACTSThe simulator has several aspects to be detailed and many extensible components.

Packet generation policy can be decided through compilation flags.

To achieve fast implementations, compilation is necessary everytime a simulation parameter changes.

advantages drawbacks

Templated classes to support hash values real, big-reals and packet internal representation.Parallel vs. single implementations. Simulations can be run as parallel or not using different classes.High performance on Intel multi-core architectures when in parallel mode.

Parallel mode only available for Intel architectures.

Compilation does not take much time, bash scripts handle compilation.

Single mode available for all architectures.

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Medilink srl



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SHOWING RESULTSSimulations are still ongoing, so far good results to be detailed in next slides.

Showing heavy simulations’ results collected so far.

and still counting...

Showing simulation machine details...

OVERALLSIMTIME

19d

OVERALL# OF SIMS

84

AVG TIME PER SIM

3h

O V E R A L LGENTD PKTS #

14.1M

Machine architectureOperating systemCPU details

HP ProLiant DL180 G6CentOS 6 (RHEL)Intel Xeon (4-Core)

= data updating in time

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GROUPING SIMULATIONSFor a better analysis, we are going to group simulations in clusters basing on the ring size.

Focusing on different rings: from 10 to 100 stations.

Packets volume ranging 100k...3M

N 1 0SIMS #

41

N 3 0SIMS #

60

N 5 0SIMS #

10

N 1 0 0SIMS #

10

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N10MxPy SIMULATIONSRing size 10. Many packet volumes.

SIMS # 41P A C K E T S VO L U M E S

31x100k

10x1M

Ov. SIMT I M E

13h

G E NPKTS #13.1M

Dispersion against std. deviation for H.

Std. deviation for PHI & HPART for each simulation.

Dispersion against std. deviation for PHI.

Relating HPART variance to PHI variance.

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Std deviation for HPART. Mult. coe�: E37 Std deviation for PHIStd deviation for PHI

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Std deviation for PHI

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SIMS # 60





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P A C K E T S VO L U M E S

49x1M10x3M1x10M

Ov. SIMT I M E

17g

G E NPKTS #89.0M

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SIMS # 10





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G E NPKTS #10.0M

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N30 SIMS CIRCO-DIAGS + LLEVELSLoad balancing performed! Showing load-levels and circo-diagrams for pkt-migrations.

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How

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How

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終わり

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FOCUSING ON A N30M1MP1kShowing an ideal case: almost perfect balancing, levels get more homogeneous.

How

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Showing H load-levels.

Showing PHI load-levels.

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FOCUSING ON A N30M1MP1kShowing a NOT SO ideal case: almost perfect balancing but one level drops significantly.

How

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“Ho

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ons”Sometimes strange behaviors

appear: very narrow-coverage stations are not correctly balanced.

Symptom: very high hpart std.dev.std_dev = 1.2e37 (MD5: 0..2^128-1)

N30M1MP1k2013.11.27:204818

Showing H load-levels. Showing PHI load-levels.

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SEARCHING FOR HIDDEN PATTERNSUsing circo-diagrams it is possible to reveal hidden patterns.

Wide-covarage stations are more likely to donate packets to other stations.

Narrow-covarage stations are more likely to receive packets to other stations.

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HOW TO READ SIMULATIONSSimulation data are presented using dimension-reduction in order to grasp and understand patterns in a faster way. In this slide, find a little guide introducing most important quantities.

Migration flow: a number of pkts virtually moving from one station to another one upon 2 different station assignments.

Assignments using H and PHI hash functions.

Circo-diagrams showing migration flows.

Function H: MD5 (128 bit, cryptographic hash function).Function PHI: Balancing hash function (secret).

August 2013

stateless load balancing - early results

Technology

tuning simulations simulations

simulations overview

simulations architecture

catania ingegneria informatica

realscenario simulations

packet size

n50big rings rings

tomarchio company supervisor