eQoSystem: Supporting Fluid

Distributed Service-Oriented Workflows

Vinod Muthusamy, Young Yoon, Mo Sadoghi, Arno Jacobsenmuthusamy@eecg.toronto.edu, yoon@msrg.utoronto.ca,

mo@cs.toronto.edu, jacobsen@eecg.toronto.edu

Middleware Systems Research Groupwww.msrg.org

University of Toronto

Currently, business goals must be manually considered at every stage of the business

process development cycle

N

Y

Far?Get

destinationValidaterequest

Find flight

Find train

cost < $0.02

service time < 3s

Only trusted partners

WebSphere Business Modeler(business analyst)

WebSphere Integration Developer(architect, developer)

WebSphere Process Server(administrator)

WebSphere Business Monitor(analyst, architect, administrator)

Model

Services

Events

Objective: Exploit SLAs in BPM life cycle

Modelling

Development

Execution

Monitoring

Adapt to changing conditions to achieve the goals with minimal development and administrative effort

SimplicityAn analyst can specify goals without detailed knowledge of the implementation technologies

FlexibilityThe requirements and implementation technologies can be independently updated

End-to-end specificationRequirements captured in the tools can be enforced and monitored throughout the development cycle

Adaptive efficiencyThe system can allocate resources to meet changing requirements

Layer SLA Metric Example

Business process

Cost Cost of search service < $0.02 per use

Fidelity/quality/utility Map resolution > 300x300

Trust/reputation Only use trusted payment service

Deployment/ Operations

Service time Execution time < 3s

Throughput Throughput > 100/min

Availability Uptime > 99.9%

Load balance Server utilization delta < 10%

Network Latency Service RTT < 100ms

Bandwidth Max bandwidth < 3Mbps

Jitter Delay jitter < 10ms

Service Level AgreementsSLAs are a contract between service consumers and providers that specifies the expected behaviour of each party and the penalties of

violating the contract

SLAs specify business goals declaratively

SLA

Optim.criteria

Runtime Uses of SLAs

A B C D

p

q

Web service Task agent

2

1b service time < 1s

ESB

A,B

D

1a

C

service time < 2s

Dynamic service selectionDiscover services with capabilities that satisfy goals.

Distributed MonitoringOnly monitor the business events related to goals.Treat monitoring as a process.Feed back measurements to support runtime adaptations.

Distributed executionFine-grained allocation of process to available resources.Move portions of process to strategic locations.

ESB adaptationReconfigure the ESB topology to satisfy goals.

M

M

M

Process Execution ArchitecturesCentralized One execution engine May not scale Central point of failure

Agent-based Distributed execution engine In-network processing

Lower bandwidth and latency Fine-grained use of resources

Clustered Replicated execution engines Centralized control and data

High bandwidth and latency Still may not scale

ABCD

ABCD

ABCD

D

C

A,B

Dynamic Process Redeployment

Business process executing on nine execution engines Process hotspot varies over time

No optimal static deployment Dynamic redeployment suffers temporarily after process hotspot

moves Traffic with redeployment is 42% of the static case

Distribution cost Cdist = Cd3 * (Cd1 + Cd2)Cd1 Message rateCd2 Message sizeCd3 Latency

Engine cost Ceng = f(Ce1, Ce2,Ce3)Ce1 Load (number of instances)Ce2 Resources (CPU, memory, etc.)Ce3 Task complexity

Service cost Cserv = Cs1 + Cs2 + Cs3

Cs1 Latency of external serviceCs2 Execution time of external serviceCs3 Marshalling/unmarshalling

Cost(agent) = ∑wiCi

Cost(process) = ∑cost(agent)

The cost of a process is based on three cost components

These costs can be weighted to achieve different objectives

Optimize timewd1 = wd3 = we3 = Cserv = 1, other wi = 0

Optimize network overheadwd2 = wd3 = 1, other wi = 0

Various optimization criteria can be specified

Threshold criteria: ∑wiCi > x E.g., Report SLA violations within 3 s.

Minimized criteria: min( ∑wiCi ) E.g., Minimize distribution overhead

Cost Model

Summary of Approach

Process instrumentation.Monitoring rules generation.

SLA validation.

Autonomic reconfiguration tomaintain SLA.

Fine grained resource usage.Automatic service composition.

Goal-based discovery.

Distributed, scalable architecture.Real-time monitoring.

Loosely coupled system.

Transparent, live reconfiguration.Localize process modification.

Distributed process search.Continuous search.

Process monitoring Distributed execution Service selection

Formal SLA model

Distributed event-based messaging middleware

A formal SLA model can drive various stages of distributed application development.

An event-based system is an enabling technology for certain features.

Features (Execution Time)

Distributed BPEL engine Scalable execution of large business processes Event-based interaction among activities

Autonomous SLA-aware process reconfiguration Distributed optimization algorithms Decoupled event-based interactions enable

reconfiguration of live process

Adaptive event-based SLA monitoring Optimize monitoring overhead No additional instrumentation required

A

B C

D

E

F

Fault

Task A doneTrigger

M

ESB

A,B

D

C

StartTime

ExecutionTime

EndTime

ExecutionTimeSLO

Charge Business

Partner

ESB

Features (Discovery)

Event-based service discovery Fully distributed architecture Support a number of modes

including real-time discovery

Automatic service composition Search a distributed set of

service repositories Utilize distributed pub/sub data

structures to index service compatibility relationships

Incrementally construct a DAG of candidate processes

Search Request

Search Result

Service Agent

Request Agent

Pub/Sub Broker Network

Server Farm

Computers

ComputersDatabase

Laptops

Computers

Laptops

Database Server

Server

Deploy Control UpdateVisualize

Monitor ...

6

43

7

Content-based Routing

Workflow and Business Process Execution

start halt

Workflow Management and Business Activity Monitoring

Redirectresume

addremove

Content-based RouterClients (publisher/subscriber)

Switch

Server

Switch

Computing, Storage, Instruments and Networking Resources

Event ManagementFramework

BusinessActivityEvents

Business ProcessEvents

Business ProcessExecution Events

Network andSystem Events

Switch

CA*net 4

CommunicationEvents

Publish/Subscribe Point-to-Point Request/Reply Orchestration

Communication Abstractions

Vision

Redeployment Manager Compute the cost of deploying local agents A i at

candidate engines Ej

GivenF(Ai): Cost functionP(Ai): PredecessorsS(Ai): Successors

MeasurementsC(Ai): Cost at local engineE(P(Ai)): Location of predecessorsE(S(Ai)): Location of successors

ComputeC(Ai,Ej) for every Ai,Ej:

Estimated cost of deploying agent Ai at candidate engine Ej

ComplexityMemory: O( |Ai| |Ej| )

Computation: O( |Ai| |Ej| |Navg(Ai)| )Cost Model

Demonstration

B C

p q

1 4 7

Execution engineBroker

Process

Topology

A

5 Deployer

A C B

ProcessID:PROCESS_3START:TASKAGLOBALVARIABLES:acond true bcond true ccond true bprob 0.1 cprob 0.9 count 1

<TASK> TaskID:TASKA PreNode:OR_SPLIT PostNode:SEQUENCE Decision PostIDs:TASKB PostPubCondition PreSubCondition:START TASKB TargetEngine:A </TASK><TASK> TaskID:TASKB PreNode:OR_SPLIT PostNode:OR_JOINT Decision PostIDs:TASKXXX PostPubCondition:bcond true TASKA else TASKC PreSubCondition:TASKA TASKC TargetEngine:A</TASK><TASK> TaskID:TASKC PreNode:SEQUENCE PostNode:OR_JOINT Decision PostIDs:TASKXXX PostPubCondition:ccond true TASKB else END PreSubCondition:TASKB TargetEngine:A</TASK>

For More Information

Visithttp://eqosystem.msrg.utoronto.ca