Albert Cabellos-Aparicio

Graphene-enabled wireless communication for massive multicore architectures

Current trends in microprocessor architecture design are leading towards a dramatic increase of core-level parallelization, wherein a given number of independent processors or cores are interconnected. Since the main bottleneck is foreseen to migrate from computation to communication, efficient and scalable means of inter-core communication are crucial for guaranteeing steady performance improvements in many-core processors. As the number of cores grows, it remains unclear whether initial proposals, such as the Network-on-Chip (NoC) paradigm, will meet the stringent requirements of this scenario. This position paper presents a new research area where massive multicore architectures have wireless communication capabilities at the core level. This goal is feasible by using graphene-based planar antennas, which can radiate signals at the Terahertz band while utilizing lower chip area than its metallic counterparts. To the best of our knowledge, this is the first work that discusses the utilization of graphene-enabled wireless communication for massive multicore processors. Such wireless systems enable broadcasting, multicasting, all-to-all communication, as well as significantly reduce many of the issues present in massively multicore environments, such as data coherency, consistency, synchronization and communication problems. Several open research challenges are pointed out related to implementation, communications and multicore architectures, which pave the way for future research in this multidisciplinary area.

Analysis of the impact of sampling on NetFlow traffic classification

The traffic classification problem has recently attracted the interest of both network operators and researchers. Several machine learning (ML) methods have been proposed in the literature as a promising solution to this problem. Surprisingly, very few works have studied the traffic classification problem with Sampled NetFlow data. However, Sampled NetFlow is a widely extended monitoring solution among network operators. In this paper we aim to fulfill this gap. First, we analyze the performance of current ML methods with NetFlow by adapting a popular ML-based technique. The results show that, although the adapted method is able to obtain similar accuracy than previous packet-based methods (~90%), its accuracy degrades drastically in the presence of sampling. In order to reduce this impact, we propose a solution to network operators that is able to operate with Sampled NetFlow data and achieve good accuracy in the presence of sampling.

Detection Techniques for Diffusion-based Molecular Communication

Nanonetworks, the interconnection of nanosystems, are envisaged to greatly expand the applications of nanotechnology in the biomedical, environmental and industrial fields. However, it is still not clear how these nanosystems will communicate among them. This work considers a scenario of Diffusion-based Molecular Communication (DMC), a promising paradigm that has been recently proposed to implement nanonetworks. In a DMC network, transmitters encode information by the emission of molecules which diffuse throughout the medium, eventually reaching the receiver locations. In this scenario, a pulse-based modulation scheme is proposed and two techniques for the detection of the molecular pulses, namely, amplitude detection and energy detection, are compared. In order to evaluate the performance of DMC using both detection schemes, the most important communication metrics in each case are identified. Their analytical expressions are obtained and validated by simulation. Finally, the scalability of the obtained performance evaluation metrics in both detection techniques is compared in order to determine their suitability to particular DMC scenarios. Energy detection is found to be more suitable when the transmission distance constitutes a bottleneck in the performance of the network, whereas amplitude detection will allow achieving a higher transmission rate in the cases where the transmission distance is not a limitation. These results provide interesting insights which may serve designers as a guide to implement future DMC networks.

Simulation-based evaluation of the diffusion-based physical channel in molecular nanonetworks

Nanonetworking is an emerging field of research, where nanotechnology and communication engineering are applied on a common ground. Molecular Communication (MC) is a bio-inspired paradigm, where Nanonetworks, i.e., the interconnection of devices at the nanoscale, are based on the exchange of molecules. Amongst others, diffusion-based MC is expected to be suitable for covering short distances (nm-µm). In this work, we explore the main characteristics of diffusion-based MC through the use of N3Sim, a physical simulation framework for MC. N3Sim allows for the simulation of the physics underlying the diffusion of molecules for different scenarios. Through the N3Sim results, the Linear Time Invariant (LTI) property is proven to be a valid assumption for the free diffusion-based MC scenario. Moreover, diffusion-based noise is observed and evaluated with reference to already proposed stochastic models. The optimal pulse shape for diffusion-based MC is provided as a result of simulations. Two different pulse-based coding techniques are also compared through N3Sim in terms of available bandwidth and energy consumption for communication.

A Novel Available Bandwidth Estimation and Tracking Algorithm

The available bandwidth (AB) of an end-to-end path is its remaining capacity and it is an important metric for several applications. Thats why several available bandwidth estimation tools have been published recently. Most of these tools use the probe rate model. This model is based on the concept of self- induced congestion and requires that the tools send a packet train at a rate matching the available bandwidth. The main issue with this model is that these tools congest the path under study. In this paper we present a novel available bandwidth estimation tool that takes into account this issue. Our tool is based on a mathematical model that sends packet trains at a rate lower than the AB. The main drawback of this model is that it is not able to track the AB. To solve this issue we propose to apply Kalman filters (KF) to the model. By applying these filters we can produce real-time estimations of the available bandwidth and monitor its changes. In addition the KFs are able to filter the noisy (erroneous) measurements improving the overall accuracy. We also present an extensive evaluation of our tool in different network scenarios and we compare its performance with that of pathChirp (a state-of-the-art available bandwidth estimation tool).

On the area and energy scalability of wireless network-on-chip: a model-based benchmarked design space exploration

Networks-on-chip (NoCs) are emerging as the way to interconnect the processing cores and the memory within a chip multiprocessor. As recent years have seen a significant increase in the number of cores per chip, it is crucial to guarantee the scalability of NoCs in order to avoid communication to become the next performance bottleneck in multicore processors. Among other alternatives, the concept of wireless network-on-chip (WNoC) has been proposed, wherein on-chip antennas would provide native broadcast capabilities leading to enhanced network performance. Since energy consumption and chip area are the two primary constraints, this work is aimed to explore the area and energy implications of scaling a WNoC in terms of: 1) the number of cores within the chip, and 2) the capacity of each link in the network. To this end, an integral design space exploration is performed, covering implementation aspects (area and energy), communication aspects (link capacity), and network-level considerations (number of cores and network architecture). The study is entirely based upon analytical models, which will allow to benchmark the WNoC scalability against a baseline NoC. Eventually, this investigation will provide qualitative and quantitative guidelines for the design of future transceivers for wireless on-chip communication.

Physical channel characterization for medium-range nanonetworks using flagellated bacteria

Nanonetworks are the interconnection of nanomachines and as such expand the limited capabilities of a single nanomachine. Several techniques have been proposed so far to interconnect nanomachines. For short distances (nm-mm ranges), researchers are proposing to use molecular motors and calcium signaling. For long distances (mm-m), pheromones are envisioned to transport information. In this work we propose a new mechanism for medium-range communications (nm-µm): flagellated bacteria. This technique is based on the transport of DNA-encoded information between emitters and receivers by means of a bacterium. We present a physical channel characterization and a simulator that, based on the previous characterization, simulates the transmission of a DNA packet between two nanomachines.

Use of Terahertz Photoconductive Sources to Characterize Tunable Graphene RF Plasmonic Antennas

Graphene, owing to its ability to support plasmon polariton waves in the terahertz frequency range, enables the miniaturization and electrical tunability of antennas to allow wireless communications among nanosystems. One of the main challenges in the characterization and demonstration of graphene antennas is finding suitable terahertz sources to feed the antenna. This paper characterizes the performance of a graphene RF plasmonic antenna fed with a photoconductive source. The terahertz source is modeled and, by means of a full-wave EM solver, the radiated power as well as the tunable resonant frequency of the device is estimated with respect to material, laser illumination, and antenna geometry parameters. The results show that with this setup the antenna radiates terahertz pulses with an average power up to 1 μW and shows promising electrical frequency tunability.

N3Sim: Simulation Framework for Diffusion-based Molecular Communication Nanonetworks

Diffusion-based molecular communication is a promising bio-inspired paradigm to implement nanonetworks, i.e., the interconnection of nanomachines. The peculiarities of the physical channel in diffusion-based molecular communication require the development of novel models, architectures and protocols for this new scenario, which need to be validated by simulation. N3Sim is a simulation framework for nanonetworks with transmitter, receiver, and harvester nodes using Diffusion-based Molecular Communication (DMC). In DMC, transmitters encode the information by releasing molecules into the medium, thus varying their local concentration. N3Sim models the movement of these molecules according to Brownian dynamics, and it also takes into account their inertia and the interactions among them. Harvesters collect molecules from the environment to reuse them for later transmissions. Receivers decode the information by sensing the particle concentration in their neighborhood. The benefits of N3Sim are multiple: the validation of channel models for DMC and the evaluation of novel modulation schemes are just a few examples.

Networking challenges and principles in diffusion-based molecular communication

Nanotechnology has allowed building nanomachines capable of performing simple tasks, such as sensing, data storage, and actuation. Nanonetworks, networks of nanomachines, will allow cooperation and information sharing among them, thereby greatly expanding the applications of nanotechnology in the biomedical, environmental, and industrial fields. One of the most promising paradigms to implement nanonetworks is diffusion-based molecular communication (DMC). In DMC, nanomachines transmit information by the emission of molecules that diffuse throughout the medium until they reach their destination. Most of the existing literature in DMC has focused on the analysis of its physical channel. In this work, the key differences of the physical channel of DMC with respect to the wireless electromagnetic channel are reviewed with the purpose of learning how they impact the design of networks using DMC. In particular, we find that the uniqueness of the physical channel of DMC will require revisiting most of the protocols and techniques developed for traditional wireless networks in order to adapt them to DMC networks. Furthermore, guidelines for the design of a novel network architecture for DMC networks, including fundamental aspects such as coding, medium access control, addressing, routing and synchronization, are provided.