In-packet Bloom filters: Design and networking applications

The Bloom filter (BF) is a well-known space-efficient data structure that answers set membership queries with some probability of false positives. In an attempt to solve many of the limitations of current inter-networking architectures, some recent proposals rely on including small BFs in packet headers for routing, security, accountability or other purposes that move application states into the packets themselves. In this paper, we consider the design of such in-packet Bloom filters (iBF). Our main contributions are exploring the design space and the evaluation of a series of extensions (1) to increase the practicality and performance of iBFs, (2) to enable false-negative-free element deletion, and (3) to provide security enhancements. In addition to the theoretical estimates, extensive simulations of the multiple design parameters and implementation alternatives validate the usefulness of the extensions, providing for enhanced and novel iBF networking applications.Comment: 15 pages, 11 figures, preprint submitted to Elsevier COMNET Journa

Certain minimal varieties are set-theoretic complete intersections

We present a class of homogeneous ideals which are generated by monomials and binomials of degree two and are set-theoretic complete intersections. This class includes certain reducible varieties of minimal degree and, in particular, the presentation ideals of the fiber cone algebras of monomial varieties of codimension two

iRED: A disaggregated P4-AQM fully implemented in programmable data plane hardware

Routers employ queues to temporarily hold packets when the scheduler cannot immediately process them. Congestion occurs when the arrival rate of packets exceeds the processing capacity, leading to increased queueing delay. Over time, Active Queue Management (AQM) strategies have focused on directly draining packets from queues to alleviate congestion and reduce queuing delay. On Programmable Data Plane (PDP) hardware, AQMs traditionally reside in the Egress pipeline due to the availability of queue delay information there. We argue that this approach wastes the router's resources because the dropped packet has already consumed the entire pipeline of the device. In this work, we propose ingress Random Early Detection (iRED), a more efficient approach that addresses the Egress drop problem. iRED is a disaggregated P4-AQM fully implemented in programmable data plane hardware and also supports Low Latency, Low Loss, and Scalable Throughput (L4S) framework, saving device pipeline resources by dropping packets in the Ingress block. To evaluate iRED, we conducted three experiments using a Tofino2 programmable switch: i) An in-depth analysis of state-of-the-art AQMs on PDP hardware, using 12 different network configurations varying in bandwidth, Round-Trip Time (RTT), and Maximum Transmission Unit (MTU). The results demonstrate that iRED can significantly reduce router resource consumption, with up to a 10x reduction in memory usage, 12x fewer processing cycles, and 8x less power consumption for the same traffic load; ii) A performance evaluation regarding the L4S framework. The results prove that iRED achieves fairness in bandwidth usage for different types of traffic (classic and scalable); iii) A comprehensive analysis of the QoS in a real setup of a DASH) technology. iRED demonstrated up to a 2.34x improvement in FPS and a 4.77x increase in the video player buffer fill.Comment: Preprint (TNSM under review

Ultra-Stable and Robust Response to X-Rays in 2D Layered Perovskite Micro-Crystalline Films Directly Deposited on Flexible Substrate

2D layered hybrid perovskites have recently attracted an increasing interest as active layers in LEDs and UV–Vis photodetectors. 2D perovskites crystallize in a natural self-assembled quantum well-like structure and possess several interesting features among which low-temperature (<100 °C) synthesis and low defect density. Here are presented solid-state ionizing radiation direct detectors based on the 2D layered hybrid perovskite PEA2PbBr4 (PEA = C6H5C2H4NH3+) deposited from solution using scalable techniques and directly integrated onto a pre-patterned flexible substrate in the form of micro-crystalline films displaying crystal-like behavior, as evidenced by the ultra-fast (sub-microsecond) and good detection performances under UV light. The effective detection of X-rays (up to 150 kVp) is demonstrated with sensitivity values up to 806 µC Gy−1 cm−2 and Limit of Detection of 42 nGy s−1, thus combining the excellent performance for two relevant figures of merit for solid-state detectors. Additionally, the tested devices exhibit exceptionally stable response under constant irradiation and bias, assessing the material robustness and the intimate electrical contact with the electrodes. PEA2PbBr4 micro-crystalline films directly grown on flexible pre-patterned substrate open the way for large-area solid-state detectors working at low radiation flux for ultra-fast X-ray imaging and dosimetry

Floristic and forest inventory of Santa Catarina: species of evergreen rainforest.

O presente trabalho objetivou apresentar a lista de espécies da floresta pluvial subtropical (Floresta Ombrófila Densa) em Santa Catarina, com base em 202 unidades amostrais implantadas pelo Inventário Florístico Florestal de Santa Catarina para estudo do componente arbóreo-arbustivo e da regeneração, além de coletas florísticas externas às unidades amostrais. Foram registradas 1.473espécies, 19,0% das espécies citadas para esta tipologia florestal no Brasil, dentre estas três gimnospermas e 1.470 angiospermas. As famílias mais ricas em espécies foram: Orchidaceae (143 espécies), Myrtaceae (142), Asteraceae (98), Melastomataceae (86), Fabaceae (78), Rubiaceae (65), Solanaceae (61), Bromeliaceae (57), Piperaceae (56) e Lauraceae (52). Entre as espécies registradas, oito constam na Lista Oficial das Espécies da Flora Brasileira Ameaçadas de Extinção: Aechmea blumenavii, Araucaria angustifolia, Billbergia alfonsijoannis, Euterpe edulis, Heliconia farinosa, Ocotea catharinensis, O. odorifera e O. porosa

Network Metrics Detection to Support Internet of Things Application Orchestration

Software DefinedWireless Sensor Networks (SDWSN) play an important role to serve as an infrastructure to Internet of Things (IoT) applications. In order to improve coverage, reduce costs, and make better use of the available resources, sharing the infrastructure among multiple applications is necessary. Works in the literature aim to enable resource sharing by allocating applications dynamically according to the resources available on the node. However, these works do not monitor if a node stops complying with application requirements once the application is allocated. Thus, network metrics detection is essential to identify nodes that are not able to comply with the application requirements. In this paper, we present the IT-SDN Manager architecture which is composed of a monitoring module and a resource orchestrator. The monitoring module monitors the network metrics, enabling the orchestrator to identify nodes that reach a certain threshold for energy available and packet loss. This threshold configuration depends on the metric characteristics. For packet loss, we present a study showing how it should be defined according to the network size and applications executed in the network. In order to evaluate the orchestrator detection rate, we set two application requirements to identify nodes that reach 90% of available energy and packet loss greater than the obtained threshold for each scenario studied. Results from the simulations executed show that the resource orchestrator detects all the nodes that reach the available energy threshold, and at least 85%, with an average of 97%, of the nodes that reach the packet loss threshold