Zobrazeno 1 - 10
of 105
pro vyhledávání: '"Murali Kodialam"'
Publikováno v:
IEEE Open Journal of the Communications Society, Vol 2, Pp 488-499 (2021)
Network traffic matrix (TM) is a critical input for capacity planning, anomaly detection and many other network management related tasks. The TMs are often computed from link load measurements. The TM estimation problem is the determination of the TM
Externí odkaz:
https://doaj.org/article/293e8e85219e48ba9a4651a31976a17e
Publikováno v:
IEEE Open Journal of the Communications Society, Vol 2, Pp 656-670 (2021)
Applications such as virtual reality and online gaming require low delays for acceptable user experience. A key task for over-the-top (OTT) service providers who provide these applications is sending traffic through the networks to minimize delays. O
Externí odkaz:
https://doaj.org/article/f04986f7c68c4f97a692e509f78b7bfe
Autor:
Sarit Mukherjee, Jacobus Kobus Van der Merwe, Hyunseok Chang, Zirak Zaheer, Murali Kodialam, Tv Lakshman
Publikováno v:
IEEE Transactions on Cloud Computing. 11:291-307
Publikováno v:
IEEE Transactions on Network and Service Management. 18:4576-4588
Dynamic resource allocation to satisfy varying, concurrent and unpredictable demands from multiple applications is a key need in cloud systems. A fundamental challenge is the need to find the right balance between over-allocation, which satisfies eac
Publikováno v:
2022 IFIP Networking Conference (IFIP Networking).
Publikováno v:
2022 IEEE 23rd International Conference on High Performance Switching and Routing (HPSR).
Autor:
Murali Kodialam, T.V. Lakshman
Publikováno v:
IEEE INFOCOM 2022 - IEEE Conference on Computer Communications.
Publikováno v:
AAAI
In this paper, we propose a general framework for combining deep neural networks (DNNs) with dynamic programming to solve combinatorial optimization problems. For problems that can be broken into smaller subproblems and solved by dynamic programming,
Publikováno v:
Computer Networks. :109702
Autor:
T. V. Lakshman, Murali Kodialam
Publikováno v:
HPSR
With the increasing success of machine learning based approaches for prediction problems, there has been recent effort in improving the performance of online algorithms by augmenting them with machine learning predictions. Since machine learning pred