Forgalom modellezési módszerek fejlesztése = Advanced traffic modeling techniques

A projekt alapvetően sikeresen járult hozzá a vizsgált szakterület eredményeinek bővítéséhez és a résztvevő kutatócsoport fejlődéséhez. A projekt eredményihez kapcsolódó dolgozatok alapján PHD fokozatot szerzett Bodrog Levente és Saffer Zsolt. A projekt eredményeit összegző publikációk együttes impakt faktora ~22. A szakmai eredmenyek közül Markov érkezési folyamatok alapvető tulajdonságait összegző cikk (A minimal representation of Markov arrival processes and a moments matching method) emelhető ki, amelyik időközben az ezen folyamatok illesztési korlátait vizsgálló munkák alapjává vált. | The project successfully enhanced the field of traffic modeling of computer and communication systems and helped to improve the carrier of the involved research group. Based on the their theses summarizing parts of the results of the project Bodrog Levente and Saffer Zsolt were awarded the doctor of philosophy degree. The cumulated impact factor of the journal papers publish the research results of the project is about 22. The most remarkable research results are in the paper summarizing some basic properties of Markov arrival processes (A minimal representation of Markov arrival processes and a moments matching method), which become a basic reference for subsequent works dealing with the fitting properties of these processes

Evaluation of load balancing approaches for Erlang concurrent application in cloud systems

Cloud system accommodates the computing environment including PaaS (platform as a service), SaaS (software as a service), and IaaS (infrastructure as service) that enables the services of cloud systems.  Cloud system allows multiple users to employ computing services through browsers, which reflects an alternative service model that alters the local computing workload to a distant site. Cloud virtualization is another characteristic of the clouds that deliver virtual computing services and imitate the functionality of physical computing resources. It refers to an elastic load balancing management that provides the flexible model of on-demand services. The virtualization allows organizations to improve high levels of reliability, accessibility, and scalability by having a capability to execute applications on multiple resources simultaneously. In this paper we use a queuing model to consider a flexible load balancing and evaluate performance metrics such as mean queue length, throughput, mean waiting time, utilization, and mean traversal time. The model is aware of the arrival of concurrent applications with an Erlang distribution. Simulation results regarding performance metrics are investigated. Results point out that in Cloud systems both the fairness and load balancing are to be significantly considered