most citedRethinking Internet Communication Through LLMs: How Close Are We?

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2024

FusedInf: Efficient Swapping of DNN Models for On-Demand Serverless Inference Services on the Edge

Sifat Ut Taki, Arthi Padmanabhan, Spyridon Mastorakis

Edge AI computing boxes are a new class of computing devices that are aimed to revolutionize the AI industry. These compact and robust hardware units bring the power of AI processi…

cs.LG2024

UnifiedNN: Efficient Neural Network Training on the Cloud

Sifat Ut Taki, Arthi Padmanabhan, Spyridon Mastorakis

Nowadays, cloud-based services are widely favored over the traditional approach of locally training a Neural Network (NN) model. Oftentimes, a cloud service processes multiple requ…

cs.AR2023

Gem5Pred: Predictive Approaches For Gem5 Simulation Time

Tian Yan, Xueyang Li, Sifat Ut Taki +1

Gem5, an open-source, flexible, and cost-effective simulator, is widely recognized and utilized in both academic and industry fields for hardware simulation. However, the typically…

cs.NI20231 cited

Rethinking Internet Communication Through LLMs: How Close Are We?

Sifat Ut Taki, Spyridon Mastorakis

In this paper, we rethink the way that communication among users over the Internet, one of the fundamental outcomes of the Internet evolution, takes place. Instead of users communi…

cs.CR2023

The Case for the Anonymization of Offloaded Computation

Md Washik Al Azad, Shifat Sarwar, Sifat Ut Taki +1

Computation offloading (often to external computing resources over a network) has become a necessity for modern applications. At the same time, the proliferation of machine learnin…

cs.NI2023

An NDN-Enabled Fog Radio Access Network Architecture With Distributed In-Network Caching

Sifat Ut Taki, Spyridon Mastorakis

To meet the increasing demands of next-generation cellular networks (e.g., 6G), advanced networking technologies must be incorporated. On one hand, the Fog Radio Access Network (F-…