@article{gao_rouskas_2020, title={Congestion Minimization for Service Chain Routing Problems With Path Length Considerations}, volume={28}, ISSN={["1558-2566"]}, url={https://doi.org/10.1109/TNET.2020.3017792}, DOI={10.1109/TNET.2020.3017792}, abstractNote={Network function virtualization (NFV), with its perceived potential to accelerate service deployment and to introduce flexibility in service provisioning, has drawn a growing interest from industry and academia alike over the past few years. One of the key challenges in realizing NFV is the service chain routing problem, whereby traffic must be routed so as to traverse the various components of a network service that have been mapped onto the underlying network. In this work, we consider the online service chain routing problem. We route the service chain with the goal of jointly minimizing the maximum network congestion and the number of hops from the source to the destination. To this end, we present a simple yet effective online algorithm in which the routing decision is irrevocably made without prior knowledge of future requests. We prove that our algorithm is <inline-formula> <tex-math notation="LaTeX">$O(\log m)$ </tex-math></inline-formula>-competitive in terms of congestion minimization, where <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> is the number of edges of the underlying network topology, and we show that this ratio is asymptotically optimal.}, number={6}, journal={IEEE-ACM TRANSACTIONS ON NETWORKING}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Gao, Lingnan and Rouskas, George N.}, year={2020}, month={Dec}, pages={2643–2656} }
 @article{gao_rouskas_2020, title={Service Chain Rerouting for NFV Load Balancing}, ISSN={["2576-6813"]}, DOI={10.1109/GLOBECOM42002.2020.9322265}, abstractNote={Network function virtualization (NFV), with its potential to facilitate network service provisioning, has drawn growing interest from both academia and industry. One essential challenge is to allocate efficiently the bandwidth and computational resources to the service requests. In an online context, service chain requests may arrive, depart or evolve in an arbitrary fashion, adding more difficulty to the problem. Service chain reconfiguration may help improve the performance by individually rerouting a subset of the service chain requests. In this paper, we propose a new service chain reconfiguration framework to achieve load balancing in an NFV environment under varying levels of support from the underlying infrastructure. We show that our framework can achieve an approximation ratio of O(lnm/ln lnm) with high probability for the service chain request rerouting problem.}, journal={2020 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM)}, author={Gao, Lingnan and Rouskas, George N.}, year={2020} }
 @inproceedings{gao_rouskas_2016, title={Network-aware virtual request partitioning based on spectral clustering}, DOI={10.1109/icccn.2016.7568548}, abstractNote={Virtual request partitioning is an essential subproblem of two common problems in virtual networks, namely, virtual network embedding (VNE) and virtual machine placement (VMP). In this study, we consider a network-aware variant of the problem where the objective is to partition a virtual request so as to minimize the total amount of inter-cluster traffic. This problem is equivalent to the (k,v)-balanced partitioning problem, an NP-complete problem. To handle the inherent complexity of this problem, we develop a spectral clustering-based partitioning scheme that produces good solutions in a reasonable amount of time. Our solution consists of several components: (a) spectral clustering, (b) a constrained k-means partitioning algorithm that ensures that capacity limits for clusters are met, and for which we present a polynomial-time greedy algorithm, and (c) a greedy refinement algorithm using simulated annealing to further improve the clustering solution. Simulation results indicate that our algorithm outperforms existing partitioning schemes in terms of inter-cluster traffic minimization.}, booktitle={2016 25th international conference on computer communications and networks (icccn)}, author={Gao, L. N. and Rouskas, George}, year={2016} }