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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.