Improving Robustness in Distributed SystemsJeremy RussellSoftware Engineering Honours Project

Overview

Introduction What is a distributed system What is robustness Aims of study

Method Development of simulated model Investigation of model

Results & Findings

Introduction

What is a distributed system? Network of connected entities (agents) Entities communicate via message

passing Agents can engage with any other agent

Decentralised control Contrast to P2P with centralised indexes

Behavior of individual agents conform to the goals of the system

Introduction

Example: Web services Services are offered by a collection

remote computers in a network Services are combined to build

complex super-services Appearance that super-services are

provided by a single interface agent (web-server)

Introduction

Insurance policy comparison service

Insurance Broker

Introduction

What is robustness? Correct operation under varied

conditions High tolerance of failure (extreme

conditions) Graceful in defeat

Introduction

Aim of study To improve robustness in distributed systems Implementation and comparison of two

alternative systems

How is robustness achieved? Redundancy Regeneracy (Adaptation) Load balancing

Method

Simulation model Offers services (tasks) Responds to service requests Services are highly coupled Agent based network consisting of 20

agents Measures

Success Response time

Method

Model framework Components Network mechanics Sequence of execution Representation of time Agent communication

Messages

Method

Components Object oriented Simulator object

Controls timing of events Agent objects

Provide services Communicate with other agents

Message objects Method of communication

Method

Components

Method

Components

Method

Network mechanics Underlying interconnection network (Internet) An agent can engage any other agent Agents form a subset of all possible

relationships Routing and propagation latencies are

abstracted by the Simulator Message types

Service Capability sharing Agent information

MethodNetwork mechanics (underlying network)

MethodNetwork mechanics (agent relationships)

Method

Sequence of execution Simulation is sliced into a sequence of time

steps (abstraction of real time) In each time step:

Messages are forwarded by Simulator Agents are prompted sequentially (any ordering)

to execute the time step Execute scheduled services Respond to received messages

Messages are received and ordered by Simulator

Method

Sequence of execution

Method

Representation of time Floating point number

Global time (GT) Current time step

Local time (LT) Function of the total number of processing cycles

used prior to event

Result: Time = GT.LT

available cycles total

used cycles totalused time%

Method

Agent communication Messages

Passed between agents Forwarded via Simulator Types

Request, Response, Forward, Receipt 11 across the 3 areas:

Service Capability sharing Agent information

Method

Agent communication Role of Simulator

Accepts messages and calculates delivery time

Applies latency

Orders messages according to time of delivery

Forwards all messages that reach their destination within the current time step

Method

Agent communication (sending)

Method

Agent communication (sending)

Method

Agent communication (receiving) Messages in inbox are processed

according to delivery time At start of time step inbox contains all

messages for that time step Agent only reads a message when agent

time reaches time of delivery

Method

Service Unit of work provided by an agent Can be requested by external users or

agents within the system Complex workflows (dependencies)

Dependence represents the results of a service being used by another service

Virtual knowledge communities

Method

Service Example, task 1

1: do part12: do part23: request task2,task3,task4 wait task24: do part3 wait task3,task45: do finish

Method

Virtual knowledge communities Groups of agents with similar interests

Coupled services Benefits

More advantageous agent relationships Priority treatment for agents within a

community Improvements in reliability and response

times

Method

Virtual knowledge communities

Method

Agent implementation Service advertising Knowledge

Validation Scheduling Failure Performance metrics Entropy Strategy

Method

Service advertising (indexing) Performance metrics mitigate risk of

inefficient routing

Method

Knowledge Two forms

Neighbour relationships Capabilities (services)

Fixed storage allocation Services require twice the storage of a

relationship Initialised to:

8 relationships (50%) 4 services (50%)

Method

Knowledge Neighbour relationships

Services offered by neighbour is recorded Service directory is stored by each agent

Ranked collection of agents that provide a service Ranking based on weighted average of past results

Performance and utilization metrics are recorded Capabilities (services)

Space not used by simulation Allocation represents the demands of data carried

by a service (i.e. databases)

Method

Knowledge Validation

Occurs at set intervals Updates services advertised by

neighbours Updates neighbour utilization

Method

Routing Agents have multiple options Choose the best route based on

knowledge Rerouting requests upon failure

Investigations Limiting number of hops Limiting number of routing options

Method

Routing

Method

Scheduling Agent receives service request for

service offered by agent Agent schedules service by

appending to service schedule Services are suspended if blocked Services resumed are pre-pended to

service schedule Fairness

Method

Failure Period of time an agent is non-

responsive Randomly generated for each time step Based on the reliability (parameter) of

network Implemented as a failure schedule

100 time steps, looped Ensures identical conditions for comparison

of the systems under analysis

Method

Performance metrics Weighted measures of ability

Response times Failures

Used to assess and rank neighbours Usage records

Popularity of Relationships Services

Used to reallocate storage

Method

Entropy Perceived unreliability of system Maintained by each agent Formed through interactions with

neighbours and subsequent analysis Will evolve over time Triggers strategic response

Method

Strategy Response to environmental conditions Aims to improve service delivery

Two alternatives implemented/tested Standard approach Adaptive memory approach

Method

Standard approach Fixed allocations of storage Aims to store most frequently used

Relationships Services

Weighted usage records Swap least popular allocated knowledge

with most popular unallocated knowledge

Swapping occurs at set intervals

Method

Adaptive memory approach Dynamic allocations of storage Manipulation

Triggered by entropy Tied to strategy

Low reliability = Increase neighbours High reliability = Increase services

Limited to avoid extreme reactions

Method

Adaptive memory approach Expectations

High reliability More services offered by agents Less time of response to global requests Agents specialise in services according to its

employment. Low reliability

More contingencies or routing options maintained by agents

Higher probability of success Brokers and workers

Run-time evolution

Method

Investigation of model Effect of varying indexing depth Effect of limiting hops from source of

a request Effect of limiting routing options

explored by agents Effect of enforcing a minimum level of

redundancy

Method

Effect of varying indexing depth

Results & Findings

Effect of varying indexing depth on success (Depth 2)

Results & Findings

Effect of varying indexing depth on success (Depth 3)

Results & Findings

Effect of varying indexing depth on success (Depth 4)

Results & Findings

Effect of varying indexing depth on time (Depth 2)

Results & Findings

Effect of varying indexing depth on time (Depth 3)

Results & Findings

Effect of varying indexing depth on time (Depth 4)

Results & Findings

Conclusions Comparison of two systems indicates

occasional improvements made by adaptive memory technique Improved through optimisations

Results indicate that increasing indexing depth does not improve robustness

Affecters Limitations of hops and routing options Service dependencies

Questions