"Superpolynomial Lower Bounds Against Low-Depth Algebraic Circuits," by Nutan Limaye et al., achieves a landmark in the larger quest of understanding hardness,...Nitin Saxena From Communications of the ACM | February 2024
This paper discusses algorithmic priority inversion in mission-critical machine inference pipelines used in modern neural-network-based perception subsystems and...Shengzhong Liu, Shuochao Yao, Xinzhe Fu, Rohan Tabish, Simon Yu, Ayoosh Bansal, Heechul Yun, Lui Sha, Tarek Abdelzaher From Communications of the ACM | February 2024
"Locating Everyday Objects Using NFC Textiles," by Jingxian Wang et al., describes the potential of Near-Field Communication for advanced home automation.
Polly Huang From Communications of the ACM | October 2023
This paper builds a Near-Field Communication-based localization system that allows ordinary surfaces to locate surrounding objects with high accuracy in the near...Jingxian Wang, Junbo Zhang, Ke Li, Chengfeng Pan, Carmel Majidi, Swarun Kumar From Communications of the ACM | October 2023
"Leveraging Social Media to Buy Fake Reviews," by Sherry He et al., represents a breakthrough in our empirical understanding of fake reviews on Amazon.
Shreyas Sekar From Communications of the ACM | October 2023
In "A Manifold View of Connectivity in the Private Backbone Networks of Hyperscalers," Salamatian et al. assemble techniques from the two broad strategies developed...Sara Alouf From Communications of the ACM | August 2023
We present a new empirical approach for elucidating connectivity in privately owned and operated backbone networks.
Loqman Salamatian, Scott Anderson, Joshua Mathews, Paul Barford, Walter Willinger, Mark Crovella From Communications of the ACM | August 2023
"Symbol-Synchronous Buses," by Jonathan Oostvogels et al., conceives a notion of a symbol-synchronous bus, which effectively makes a multi-hop wireless network...Luca Mottola From Communications of the ACM | April 2023
We describe a novel networking paradigm that aims to enable a new class of latency-sensitive applications by systematically breaking networking abstractions.
Jonathan Oostvogels, Fan Yang, Sam Michiels, Danny Hughes From Communications of the ACM | April 2023
The work explored in "Hummingbird," by Sujay Narayana et al., focuses on the energy consumption of a typical GPS receiver and its operational challenges in a nanosat...Karthik Dantu From Communications of the ACM | November 2022
In this work, we elucidate the design of a low-cost, low-power GPS receiver for small satellites.
Sujay Narayana, R. Venkatesha Prasad, Vijay S. Rao, Luca Mottola, T. V. Prabhakar From Communications of the ACM | November 2022
"Traffic Classification in an Increasingly Encrypted Web," by Iman Akbari et al., does a great job in reviewing related work in the network traffic classification...Athina Markopoulou From Communications of the ACM | October 2022
In this paper, we design a novel feature engineering approach used for encrypted Web protocols, and develop a neural network architecture based on stacked long...Iman Akbari, Mohammad A. Salahuddin, Leni Ven, Noura Limam, Raouf Boutaba, Bertrand Mathieu, Stephanie Moteau, Stephane Tuffin From Communications of the ACM | October 2022
"Polymorphic Wireless Receivers," by Francesco Restuccia and Tommaso Melodia, tackles the problem of physical layer resilience in wireless systems from a completely...Falko Dressler From Communications of the ACM | September 2022
We introduce PolymoRF, a deep learning-based polymorphic receiver able to reconfigure itself in real time based on the inferred waveform parameters.
Francesco Restuccia, Tommaso Melodia From Communications of the ACM | September 2022
In "hXDP: Efficient Software Packet Processing on FPGA NICs," the authors offer an interesting solution to bridging the performance gap between the CPU and the...Noa Zilberman From Communications of the ACM | August 2022
We present hXDP, a solution to run on FPGAs software packet processing tasks described with the eBPF technology and targeting the Linux's eXpress Data Path.
Marco Spaziani Brunella, Giacomo Belocchi, Marco Bonola, Salvatore Pontarelli, Giuseppe Siracusano, Giuseppe Bianchi, Aniello Cammarano, Alessandro Palumbo, Luca Petrucci, Roberto Bifulco From Communications of the ACM | August 2022
In "FANG," the authors focus on a strategy of automatically detecting disinformation campaigns on online media with a new graph-based, contextual technique for...Philippe Cudré-Mauroux From Communications of the ACM | April 2022
We propose Factual News Graph (FANG), a novel graphical social context representation and learning framework for fake news detection.
Van-Hoang Nguyen, Kazunari Sugiyama, Preslav Nakov, Min-Yen Kan From Communications of the ACM | April 2022