Ekrem Kocaguneli 11/29/2010

Introduction CLISSPE and its background Application to be Modeled Steps of the Model Assessment of Performance Interpretation of Results Follow up Literature (3 of 5)

Hard to design complex and distributed client/server (C/S) applications Performance concerns are delayed till last phases One of the solutions: Combine design and performance analysis in an iterative manner The proposed language/system CLISSPE Uses use-cases to map performance specifications

To provide an example application Relational database intensive C/S system is chosen Project is observed from beginning till the end The design of the project is done in an OO manner By using CLISSPE designers specify Objects (server, client, database, tables, transactions and networks) Relations between these objects The transactions executed in the system

CLISSPE uses a queuing network to model the system It needs: Arrival rates: Can be estimated Demand at each resource: Requires deep knowledge of the platform CLISSPE can estimate the demands in 3 steps: 1. Declaration Part: Objects (clients, servers, disks, DBs, networks etc.) are defined 2. Mapping Part: Objects mapped to one another (clients to servers etc.) 3. Transaction Specification Part: Logic of transactions

A recruitment and training system More than 20 year old mainframe application Legacy code written in multiple languages Observed project is the renewal of the legacy system New system includes Several recruitment centers Connected with a 10-Mbps Ethernet LAN Recruitment centers may or may not have a local server The headquarters has with multiple servers

There are 8 steps to the model 1. Use-case definition: Interaction scenarios between user and system 2. Structural-model definition: Modeling real world objects into classes Defines static structure of the system 3. Behavioral-model definition Defines dynamic structure of the system The interaction of objects defined on object collaboration diagram as a sequence 4. Mapping structural-model to relational database Objects identified during structural modeling are mapped to DB Objects and interactions are defined in a relational DB

There are 8 steps to the model(cntd.) 5. Client-Server Software Architecture Development Object defined earlier are mapped to alternative C/S architectures 2 tier: Interface, application on client; DB on server 3 tier: Interface on client, application and DB on different servers 6. Transaction specification Business logic is specified CLISSPE language provides transaction specification 7. Hardware/Software Mappings Mapping of system objects to actual physical components 8. Performance Modeling and Assessment All previously defined objects, mappings and transactions are evaluated by CLISSPE compiler

Use-Case Structural-modelCollaboration-diagram Database mapping

System is defined as a QN with Q = (R;W; λ;D) R corresponds to resources, W corresponds to workload, λ corresponds to a vector of arrival rates D corresponds to a matrix of service demands The calculation formula for demand is: n s is number of executions of statement s p s is probability of execution D s i,r is the demand of object r at resource i The database statements are separately modeled by compiler According to every and each DBMS property (indexing, hashing etc.)

The results are presented for actual and model estimated response times There are 8 different scenarios proposed Each scenario is encoded as follows: In mD(p)nA(q) m: # of database servers p: # of processors in a database server n: # of application server q: # of pre-processors in the application server In Comb(p) Application and the database servers on same machine with p processors SC: selective caching (some tables kept in main memory)

The M5 Simulator: Modeling Networked Systems [4] Simulator for TCP/IP networked C/S Similar to CLISPE, it adopts OO simulation infrastructure M5 is able to support CPU models Time buffers: Array of mutual communications between objects Memory I/O devices Ethernet Tested on a warehouse for transmit, receive, web-server Estimated response times are compared to actual values

Model-Based Performance Prediction in Software Development: A Survey [2] The focus is model-based performance analysis methods Makes use of a 3 dimensional classification Integration level: In which part of the lifecycle does the analysis method interfere? Automation Degree: How much automation is required or adopted by the analysis method? Integration level: How much integration is accomplished between software model and performance model? CLISSPE is classified among the architectural pattern- based methodologies (together with M5)

Joint Optimization of Hardware and Network Costs for Distributed Computer Systems [1] Makes use of alternative design options to combine hardware and network design in a single cost function Design choices to be modeled as variables are: Server sizing and localization Multiple tier allocations Server sharing by multiple server applications Server sharing among different user classes Optimal reuse of legacy systems Defined variables are fitted into an optimization model: Various decision variables Constraints An objective function

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