Channel Characterization for Chip-scale Wireless Communications within Computing Packages

Wireless Network-on-Chip (WNoC) appears as a promising alternative to conventional interconnect fabrics for chip-scale communications. WNoC takes advantage of an overlaid network composed by a set of millimeter-wave antennas to reduce latency and increase throughput in the communication between cores. Similarly, wireless inter-chip communication has been also proposed to improve the information transfer between processors, memory, and accelerators in multi-chip settings. However, the wireless channel remains largely unknown in both scenarios, especially in the presence of realistic chip packages. This work addresses the issue by accurately modeling flip-chip packages and investigating the propagation both its interior and its surroundings. Through parametric studies, package configurations that minimize path loss are obtained and the trade-offs observed when applying such optimizations are discussed. Single-chip and multi-chip architectures are compared in terms of the path loss exponent, confirming that the amount of bulk silicon found in the pathway between transmitter and receiver is the main determinant of losses.Comment: To be presented 12th IEEE/ACM International Symposium on Networks-on-Chip (NOCS 2018); Torino, Italy; October 201

Fault Tolerance in Programmable Metasurfaces: The Beam Steering Case

Metasurfaces, the two-dimensional counterpart of metamaterials, have caught great attention thanks to their powerful control over electromagnetic waves. Recent times have seen the emergence of a variety of metasurfaces exhibiting not only countless functionalities, but also a reconfigurable or even programmable response. Reconfigurability, however, entails the integration of tuning and control circuits within the metasurface structure and, as this new paradigm moves forward, new reliability challenges may arise. This paper examines, for the first time, the reliability problem in programmable metamaterials by proposing an error model and a general methodology for error analysis. To derive the error model, the causes and potential impact of faults are identified and discussed qualitatively. The methodology is presented and instantiated for beam steering, which constitutes a relevant example for programmable metasurfaces. Results show that performance degradation depends on the type of error and its spatial distribution and that, in beam steering, error rates over 10% can still be considered acceptable

Impact of transient CSMA/CA access delays on active bandwidth measurements

Proceedings of: 9th ACM SIGCOMM Conference on Internet Measurement Conference (IMC'09), November 4–6, 2009, Chicago, IllinoisWLAN devices based on CSMA/CA access schemes have become a fundamental component of network deployments. In such wireless scenarios, traditional networking applications, tools, and protocols, with their built-in measurement techniques, are usually run unchanged. However, their actual interaction with the dynamics of underlying wireless systems is not yet fully understood. A relevant example of such built-in techniques is bandwidth measurement. When considering WLAN environments, various preliminary studies have shown that the application of results obtained in wired setups is not straightforward. Indeed, the contention for medium sharing among multiple users inherent to CSMA/CA access schemes has remarkable consequences on the behavior of and results obtained by bandwidth measurement techniques. In this paper, we focus on evaluating the effect of CSMA/CA-based contention on active bandwidth measurement techniques. As a result, it presents the rate response curve in steady state of a system with both FIFO and CSMA/CA-based contending cross-traffic. We also find out that the distribution of access delay shows a transient regime before reaching a stationary state. The duration of such transient regime is characterized and bounded. We also show how dispersion-based measurements that use a short number of probing packets are biased measurements of the achievable throughput, the origin of this bias lying on the transient detected in the access delay of probing packets. Overall, the results presented in this paper have several consequences that are expected to influence the design of bandwidth measurement tools as well as to better understand the results obtained with them in CSMA/CA links.European Community's Seventh Framework ProgramThis work has been partially funded by the COST Action IC0703 "Data Traffic Monitoring and Analysis", by the Spanish Ministry of Science and Innovation under grant number TEC2008-06826/TEC (project ARTICO), and by the Catalan Regional Government under grants 2009SGR-1140 and 2009SGR-940Publicad

Building a Graph-based Deep Learning network model from captured traffic traces

Currently the state of the art network models are based or depend on Discrete Event Simulation (DES). While DES is highly accurate, it is also computationally costly and cumbersome to parallelize, making it unpractical to simulate high performance networks. Additionally, simulated scenarios fail to capture all of the complexities present in real network scenarios. While there exists network models based on Machine Learning (ML) techniques to minimize these issues, these models are also trained with simulated data and hence vulnerable to the same pitfalls. Consequently, the Graph Neural Networking Challenge 2023 introduces a dataset of captured traffic traces that can be used to build a ML-based network model without these limitations. In this paper we propose a Graph Neural Network (GNN)-based solution specifically designed to better capture the complexities of real network scenarios. This is done through a novel encoding method to capture information from the sequence of captured packets, and an improved message passing algorithm to better represent the dependencies present in physical networks. We show that the proposed solution it is able to learn and generalize to unseen captured network scenarios.Comment: 8 pages, 4 figure