Krithika Hegde, Mcafee
Amith Shetty, Mcafee
It’s common for humans to err, so goes with software makers. We don’t just come across performance issues they generally are designed into the product. We make reasonable assumptions when we design and write the code and that’s where we stumble. With the increasing adoption of virtualization and the transition towards Cloud Computing platforms, modern business information systems are becoming increasingly complex and dynamic. This raises the challenge of guaranteeing system performance and scalability while at the same time ensuring efficient resource usage.
This paper exhibits an approach for analyzing the performance of layered, service-based enterprise architecture models, which comprises of two phases- analysis of workload parameters with’top-down’ propagation, and a ‘bottom-up’ propagation of performance or cost measures. It also aims at detecting and predicting performance problems at the early stages of development process by evaluating the software design or deployment using simulation, modeling or measurement. Considering the trade-offs that come with security parameters and their impact on performance. People use terms ‘performance’ and ‘scalability’ as synonyms, this paper concludes with few highlights on how the two are quite different problems having the same symptoms.
- Extraction of architectural performance models from execution traces.
- A quantitative perspective on how higher layers impose a workload on lower layers, while the performance characteristics of the lower layers directly influence the performance of the higher layers.
- Understand how synchronous and asynchronous invocations, active and reactive objects or multi-threading or process/thread scheduling for resource utilization when not used appropriately hinder performance.
- Determine how assigning of software components or object to computing resources play a crucial role in determining performance.
- Impact of Security mechanisms such as encryption or security protocols come at a cost in terms of computing resources.”