Implementation of Epidemic Routing with IP Convergence Layer in ns-3

We present the Epidemic routing protocol implementation in ns-3. It is a full-featured DTN protocol in that it supports the message abstraction and store-and-haul behavior. We compare the performance of our Epidemic routing ns-3 implementation with the existing implementation of Epidemic in the ONE simulator, and discuss the differences

NR-U and Wi-Fi Coexistence in sub-7 GHz bands: Implementation and Evaluation of NR-U Type 1 Channel Access in ns-3

This paper addresses the challenge of optimising coexistence between 5G New Radio Unlicensed (NR-U) and Wi-Fi networks in the unlicensed spectrum at the sub-7 GHz bands. Leveraging the latest 3GPP standard TS 37.213, we align the listen-before-talk procedure with the latest standardisation, including implementation improvements. Through simulations, we demonstrate the advantages and limitations of the Type 1 channel access procedure. This work brings valuable insights, proposes solutions, and sets the groundwork for an NR-U extension crucial for future research. In particular, we evaluate the interplay between the NR-U numerologies and the channel access procedure set with different priorities

A module for Data Centric Storage in ns-3

Demo in Workshop on ns-3 (WNS3 2015). 13 to 14, May, 2015. Castelldefels, Spain.Management of data in large wireless sensor networks presents many hurdles, mainly caused by the limited energy available to the sensors, and by the limited knowledge of the sensors regarding the topology of the network. The first problem has been targeted by the introduction of in-network storage of sensed data, which can save much communication energy. The second issue found some relief with the introduction of geographical protocols that do not need knowledge regarding the network at large. Data Centric Storage systems such as QNiGHT [1][2] assume that each sensor knows its own geographical location, and they use geographical routing such as the Enhanced Greedy Perimeter Stateless Routing (EGPSR) protocol, sketched in Figure 1, to deliver packets to the sensor closest to a given point in the sensing area

A module for the FTT-SE protocol in ns-3

Demo in Workshop on ns-3 (WNS3 2015). 13 to 14, May, 2015. Castelldefels, Spain.The Flexible Time Triggered Switched Ethernet (FFT-SE) protocol allows the concurrent transmission of both real-time (i.e., synchronous and asynchronous) traffic and best-effort traffic over Ethernet. Communications within an FTT-SE network are done based on the reservation of fixed duration time slots called Elementary Cycles (ECs). The construction of the ECs and the media access control are managed by the master node. The FTTSE protocol uses the master/slave paradigm, in which the slave nodes make petitions for transmission to the master node, and the master node grants them access for transmission according to the scheduling algorithm chosen by the master node (e.g., Rate Monotonic, Earliest Deadline First, etc.)

Survey on wireless technology trade-offs for the industrial internet of things

Aside from vast deployment cost reduction, Industrial Wireless Sensor and Actuator Networks (IWSAN) introduce a new level of industrial connectivity. Wireless connection of sensors and actuators in industrial environments not only enables wireless monitoring and actuation, it also enables coordination of production stages, connecting mobile robots and autonomous transport vehicles, as well as localization and tracking of assets. All these opportunities already inspired the development of many wireless technologies in an effort to fully enable Industry 4.0. However, different technologies significantly differ in performance and capabilities, none being capable of supporting all industrial use cases. When designing a network solution, one must be aware of the capabilities and the trade-offs that prospective technologies have. This paper evaluates the technologies potentially suitable for IWSAN solutions covering an entire industrial site with limited infrastructure cost and discusses their trade-offs in an effort to provide information for choosing the most suitable technology for the use case of interest. The comparative discussion presented in this paper aims to enable engineers to choose the most suitable wireless technology for their specific IWSAN deployment

A module for the XDense architecture in ns-3

Demo in Workshop on ns-3 (WNS3 2015). 13 to 14, May, 2015. Castelldefels, Spain.The acquisition of data regarding some dynamic phenomena can require extremely dense deployments of sensors and high sampling rates. We propose XDense [1], a wired mesh grid sensor network architecture (see Figure 1a) tailored for scenarios that benefit from thousands of sensors per square meter. XDense has scalable network topology and it enables complex feature extraction in real-time from the observed phenomena, by exploiting distributed processing capabilities and inter-node communication, the latter being represented in Figure 1b

An Extension of the ns-3 LTE Module to Simulate Fractional Frequency Reuse Algorithms

We developed an extension for the LTE module of the ns-3 simulator in order to allow the simulation of Fractional Frequency Reuse algorithms and the evaluation of their performance in an LTE scenario. In this paper, we describe the technical components of such extension, namely the new API for Fractional Frequency Reuse algorithms, the implementation of several state-of-the-art-algorithms based on such API, and the implementation of the LTE downlink and uplink power control functionality which are required by many of these algorithms. Additionally, we provide an overview of the test suites that are included with our extension in order to validate its correct functionality, and discuss some example scenarios illustrating how our extension can be used in an LTE simulation

Optimization-oriented RAW modeling of IEEE 802.11ah heterogeneous networks

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The new medium access method of IEEE 802.11ah, called Restricted Access Window (RAW), divides stations into different groups, and only allows stations in the same group to access the channel simultaneously, in order to reduce collisions and thus achieve better performance (e.g., throughput). However, the existing station grouping strategies only support homogeneous scenarios where all stations use the same modulation and coding scheme (MCS) and packet size. A surrogate model is an efficient mathematical model that represents the behavior of a complex system, trained with a limited set of labeled input-output data samples. In this paper, we present a surrogate model that can accurately predict RAW performance under a given Restricted Access Window (RAW) configuration in heterogeneous networks. Different from the homogeneous scenario, heterogeneous networks are defined by a large number of parameters, leading to an enormous design space, i.e., the order of 1017 possible data points. This is too big to achieve feasible training convergence. In this paper, we present a novel training methodology that leads to a new design space with highly reduced size, i.e., the order of 105 data points. The surrogate model converges when less than 6000 labeled data points are used for training, which is only a tiny portion of the whole design space. The results show that, the relative error between model prediction and simulation results is less than 0.1 for 95% of the data points, in the areas of the design space studied. Its low complexity and high precision make the proposed model a valuable tool to develop real-time RAW optimization algorithms for heterogeneous IEEE 802.11ah networks.Postprint (author's final draft