Monitoring the QoS for Web services

QoS metrics

• Provider-advertised (execution price)
  
• Consumer-rated (service reputation)
  
• Observable
• IT Level
• Business Level

The QoS value needs to be recomputed whenever the execution of a service instance is computed

observational model

• service monitoring architecture
• QoS metric computation
• high volume of service operational events
• complexity of metric computation
• metric value persistence

computing/updating metric values in realtime using a high performance metric computation engine

contributions of the paper:

• monitoring-enabled SOA infrastructure
• declarative event detection
• event routing
  
• mointoring QoS with small programming efforts
• Efficient QoS computation
• compilation interpretation approach
• improve event processing throughput
• custom executable ECA rule at buil time
• observatoin model is transformed to invoke generated code
• model driven planning to enable wait free concurrent threading

QoS is a broad concept encompassing a large number of context-dependent and domain-specific nonfunctional properties.

1. Process Monitor Context
2. Service Mointor Context (Service Interface Monitor Context)
   
3. QoS metrics

Event (eventPattern)[condition]|expression

• eventPattern = service operational event / change in the metric
• condition = circumstance to fire an event
• expression = association predicate + value assignment
  

Metric computation engine takes observation models as input and generates event subscriptions for the semantic pub/sub engine. Thus, the events from one service engine are delivered to another service engine.

High Performance Metric Computation for QoS Metrics

ECA rules are mapped to a state chart with the transitions from events to metrics or metrics to metrics.

There are two parts to execution of state charts.

• Interpretation of state chart logic
• Interpretation of the expressions within the states
• Thread scheduling for executing events