@article{jarma_boloor_amorim_viniotis_callaway_2013, title={Dynamic Service Contract Enforcement in Service-Oriented Networks}, volume={6}, ISSN={["1939-1374"]}, DOI={10.1109/tsc.2011.45}, abstractNote={In recent years, service-oriented architectures (SOA) have emerged as the main solution for the integration of legacy systems with new technologies in the enterprise world. A service is usually governed by a client service contract (CSC) that specifies, among other requirements, the rate at which a service should be accessed, and limits it to no more than a number of service requests during an observation period. Several approaches, using both static and dynamic credit-based strategies, have been developed to enforce the rate specified in the CSC. Existing approaches have problems related to starvation, approximations used in calculations, and rapid credit consumption under certain conditions. In this paper, we propose and validate DoWSS, a doubly weighted algorithm for service traffic shaping. We show via simulation that DoWSS possesses several advantages: It eliminates the approximation issues, prevents starvation, and contains the rapid credit consumption issue in existing credit-based approaches.}, number={1}, journal={IEEE TRANSACTIONS ON SERVICES COMPUTING}, author={Jarma, Yesid and Boloor, Keerthana and Amorim, Marcelo Dias and Viniotis, Yannis and Callaway, Robert D.}, year={2013}, pages={130–142} }
 @inproceedings{boloor_chirkova_salo_viniotis_2011, title={Analysis of response time percentile service level agreements in SOA-based applications}, DOI={10.1109/glocom.2011.6133866}, abstractNote={A large number of enterprise, web-based, distributed software applications are designed on Service Oriented Architecture (SOA) principles and hosted in large scale datacenters managed by cloud providers. Typically, Service Level Agreements (SLAs) are negotiated between the consumers of the cloud platform services and the cloud provider. In this work, we consider SLAs that involve percentiles of response times as part of the performance metrics; the SLAs stipulate that a penalty be charged to the cloud provider if the SLA targets are not met. The main motivation for considering such SLAs is their potential for price differentiation. We focus our analysis on the effects the penalty function has on the achieved response time percentiles. In particular, we analyze the effect of three commonly deployed choices (linear, exponential or step-wise functions) to relate the penalty charged and the achieved percentile. This analysis is NP-hard, so we employ a heuristic algorithm that is based on simulated annealing. Our results indicate that the linear penalty charging function is ``best'' in the sense that it maximizes the achieved response time percentiles.}, booktitle={2011 ieee global telecommunications conference (globecom 2011)}, author={Boloor, K. and Chirkova, R. and Salo, T. and Viniotis, Y.}, year={2011} }
 @inproceedings{boloor_chirkova_salo_viniotis_2010, title={Heuristic-based request scheduling subject to a percentile response time SLA in a distributed cloud}, DOI={10.1109/glocom.2010.5683946}, abstractNote={We consider geographically distributed data centers forming a collectively managed cloud computing system hosting multiple applications, each subject to Service Level Agreements (SLA). The Service Level Agreements for each application require the response time of a certain percentile of the input requests to be less than a specified value, with the non-conforming requests being charged a penalty. We present a novel approach of heuristic-based request scheduling at each server, in each of the geographically distributed data centers, to globally minimize the penalty charged to the cloud computing system. We evaluate two variants of our heuristic-based approach, one based on the simulated annealing method of neighborhood searches and another based on gi-FIFO scheduling, which has been analytically proven to be the best schedule for percentile goals in a single machine, multi-class problem. We also compare our approaches with First In First Out (FIFO) and Weighted Round Robin (WRR) scheduling policies.}, booktitle={2010 ieee global telecommunications conference globecom 2010}, author={Boloor, K. and Chirkova, R. and Salo, T. and Viniotis, Y.}, year={2010} }