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Performance. Performance is about time and the software system’s ability to meet timing requirements. Performance. Event arrival p atterns: Periodic : events arrive predictably at regular time intervals. Stochastic : events arrive according to some probabilistic distribution.

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performance
Performance

Performance is about time and the software system’s ability to meet timing requirements.

performance1
Performance
  • Event arrival patterns:
  • Periodic: events arrive predictably at regular time intervals.
  • Stochastic: events arrive according to some probabilistic distribution.
  • Sporadic: events arrive according to a pattern that is nether periodic nor stochastic.
  • Response measures:
  • Latency: the time between the event arrival and the system’s response.
  • Deadline: for complete processing
  • Throughput: number of transactions that the system can process in a unit time
  • Jitter: allowable variation in latency
  • Miss rate: the number of events that the system is not able to process
  • Response time:
  • Processing time: when the system is working to response by consuming resources
  • Blocked time: when the system is unable to response, because of resource contention
    • Contention for resources
    • Availability of resources
    • Dependency on other computation
performance tactics1
Performance Tactics
  • Control Resource Demand by reducing the number of events processed
  • Manage sample rate: reduce the sampling frequency
  • Limit event response: process events only up to a set maximum rate
  • Prioritize events: impose a priority scheme that ranks all events according to their importance for services
  • Reduce overhead: remove intermediaries to improve latency (conflict with modifiability)
  • Bound execution times: place a limit on how much execution time is used to response to an event
  • Increase resource efficiency: improving the algorithms used in critical areas to decrese latency
performance tactics2
Performance Tactics
  • Manage Resources
  • Increase resources: add additional hardware resources
  • Introduce concurrency: do parallel processing when possible and not extra overhead
  • Maintain multiple copies of computations: use multiple/replicated servers
  • Maintain multiple copies of data: use caching and data replication
  • Bound queue size: control the maximum number of queued arrivals and the resources used to process the arrivals. Need to deal with overflow.
  • Schedule resources: understand the characteristics of each resource’s use and choose the scheduling strategy that is compatible with it.
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