Zobrazeno 1 - 10
of 199
pro vyhledávání: '"ELMROTH, ERIK"'
Autor:
Mudgal, Ankur, Verma, Abhishek, Singh, Munesh, Sahoo, Kshira Sagar, Elmroth, Erik, Bhuyan, Monowar
Software Defined Networking (SDN) has evolved to revolutionize next-generation networks, offering programmability for on-the-fly service provisioning, primarily supported by the OpenFlow (OF) protocol. The limited storage capacity of Ternary Content
Externí odkaz:
http://arxiv.org/abs/2410.19832
Considering the growing prominence of production-level AI and the threat of adversarial attacks that can evade a model at run-time, evaluating the robustness of models to these evasion attacks is of critical importance. Additionally, testing model ch
Externí odkaz:
http://arxiv.org/abs/2409.07609
Machine learning models -- deep neural networks in particular -- have performed remarkably well on benchmark datasets across a wide variety of domains. However, the ease of finding adversarial counter-examples remains a persistent problem when traini
Externí odkaz:
http://arxiv.org/abs/2401.13751
Autor:
Duque, Aleksandra Obeso, Klein, Cristian, Feng, Jinhua, Cai, Xuejun, Skubic, Björn, Elmroth, Erik
Publikováno v:
2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid)
Service mesh is getting widely adopted as the cloud-native mechanism for traffic management in microservice-based applications, in particular for generic IT workloads hosted in more centralized cloud environments. Performance-demanding applications c
Externí odkaz:
http://arxiv.org/abs/2205.06057
Service meshes factor out code dealing with inter-micro-service communication, such as circuit breaking. Circuit breaking actuation is currently limited to an "on/off" switch, i.e., a tripped circuit breaker will return an application-level error ind
Externí odkaz:
http://arxiv.org/abs/2104.02463
Autor:
Hieu, Nguyen Quang, Anh, Tran The, Luong, Nguyen Cong, Niyato, Dusit, Kim, Dong In, Elmroth, Erik
Blockchain-enabled Federated Learning (BFL) enables mobile devices to collaboratively train neural network models required by a Machine Learning Model Owner (MLMO) while keeping data on the mobile devices. Then, the model updates are stored in the bl
Externí odkaz:
http://arxiv.org/abs/2004.04104
By intrinsic necessity, Kubernetes is a complex platform. Its complexity makes conducting performance analysis in that environment fraught with difficulties and emergent behavior. Applications leveraging more "moving parts" such as the Istio service
Externí odkaz:
http://arxiv.org/abs/2004.00372
Publikováno v:
Future Generation Computer Systems, Elsevier, Vol. 81, pp. 114-128, 2018
Dynamic Voltage and Frequency Scaling (DVFS), CPU pinning, horizontal, and vertical scaling, are four techniques that have been proposed as actuators to control the performance and energy consumption on data center servers. This work investigates the
Externí odkaz:
http://arxiv.org/abs/1903.05488
Autor:
Li, Zheng, Tesfatsion, Selome, Bastani, Saeed, Ali-Eldin, Ahmed, Elmroth, Erik, Kihl, Maria, Ranjan, Rajiv
Publikováno v:
IEEE Transactions on Sustainable Computing, 2017
Given the complexity and heterogeneity in Cloud computing scenarios, the modeling approach has widely been employed to investigate and analyze the energy consumption of Cloud applications, by abstracting real-world objects and processes that are diff
Externí odkaz:
http://arxiv.org/abs/1708.00777