Simulation based validation of quantitative requirements in Service Oriented Architectures

Abstract

Large Service Oriented Architectures (SOAs) have to fulfill qualitative and quantitative requirements. Usually Service Level Agreements (SLAs) are defined to fix the maximal load the system can accept and the minimal performance and dependability requirements the system has to provide. In a complex SOA where services use other services and thus performance and dependability of a service depend on the performance and dependability of lower level services, it is hard to give reasonable bounds for quantitative measures without performing experiments with the whole system. Since field experiments are too costly, model based analysis, often using simulation is a reliable alternative. The paper presents an approach to model complex SOAs and the corresponding SLAs hierarchically, map the model on a simulator and analyze the model to validate or disprove the different SLAs.

FIT for SOA? Introducing the F.I.T.-Metric to Optimize the Availability of Service Oriented Architectures

“…Metrics to measure granularity, complexity and reuse [15,35,36], performance [5,13] and QoS [28,31] of SOAbased services also rely on design-time data. Most work on operation and optimization has been done on how to handle service level agreements primarily based on design-time data: how to formally describe them [19,34,39,40], technically implement, test and enforce them [4,10,15,17,18,23,25,26,32,33,42,44,45] or how to monitor them [2,20,21]. Contributions available on SLA design deal with isolated approaches: Sauvé et al [38] and Marques et al [27] are in favor of deriving the service level targets directly from the business impact of the given service (i.e.…”

Arrival and delay curve estimation for SLA Calculus

“…Request events are discrete arrivals to systems weighted by their request size or processing complexity (Bause et al 2009). Thus an event e i = (t i , w i , a i ) has an arrival time t i , a weight w i (default w i = 1) and an identifier a i .…”

Modeling quantitative requirements in SLAs with Network Calculus

“…As SOA systems take an important role in business applications they have to meet requirements in availability and response times. These requirements are laid down in Service Level Agreements (SLA) [2,10] being part of contracts between customer and service provider.…”

“…The second type of properties are the non-functional or so-called quantitative requirements. They include maximal load and minimal service level, response times and availability of services [2].…”

“…Modeling of SOA including SLAs has already been done with simulation models [5]. In [2] process models are simulated to validate SLAs with statistic methods. A downside of simulation is that models have to be very detailed to replicate real system performance.…”