Coalition Formation and Combinatorial Auctions; Applications to Self-organization and Self-management in Utility Computing

In this paper we propose a two-stage protocol for resource management in a hierarchically organized cloud. The first stage exploits spatial locality for the formation of coalitions of supply agents; the second stage, a combinatorial auction, is based on a modified proxy-based clock algorithm and has two phases, a clock phase and a proxy phase. The clock phase supports price discovery; in the second phase a proxy conducts multiple rounds of a combinatorial auction for the package of services requested by each client. The protocol strikes a balance between low-cost services for cloud clients and a decent profit for the service providers. We also report the results of an empirical investigation of the combinatorial auction stage of the protocol.Comment: 14 page

CloudML based dynamic deployment configuration for scaling enterprise applications in the cloud

Arvutustehnika populaarsuse seisukohalt on väga tähtis pilve tarnija muutmise võimalus. Kuigi, enamikul juhtudest süsteemi konfiguratsioon sõltub tarnija teenusest. Näiteks koormuse tasakaalustamisest või databaasidest, ning see teeb tarnija muutmise raskemaks. See töö seletab CloudMLile põhinevaid lahendusi, mis on võimeline rakendama keerulisi süsteeme kasutades erinevaid pilve tarnijaid. Selline võimalus lubab luua kaleeritavat kon-figuratiooni mis on iseseisvad tarnija koormuse tasakaalustamise teenusest ning lubavad igal osal süsteemis olla skaleeritav nõudlus. Pakutav lahendus omab ka integreeritudg-eneerilist LP( lineaarne programeerimine) mudelit kontrollimaks süsteemi ketendamist. Me tegime eksperimente läbi näitamaks kuidas süsteem võib olla kasutusel rakendamaks keerulisi süsteeme mis on väga populaarsed. Tulemus näitas et süsteem on võimeline skaleerima ja toetama sissetulevat töökorraldust hoolimata komponentide arvust.In light of the popularity of cloud computing, it is really important to be free to change cloud providers when needed. However, in most cases, system configuration relies on provider services, such as load balancing or databases and this makes it much harder to change the provider. This thesis describes a CloudML based solution that is capable of deploying complex systems using different cloud providers with minimum changes including embedded load balancers. This feature allows the creation of scalable configurations that are independent from providers' load balancing services and allow any component of the system to be scalable on demand. The proposed solution also has an integrated generic LP (linear programming) model to control system scaling. We conducted a number of experiments to show that the system could be used for deploying complex systems that follow most popular workflows. The results of the experiments show that this system is capable of scaling properly to support incoming workflow regardless of chosen workflow or number of the system components