In this paper, we explore the integration of a reconfigurable intelligent surface (RIS) with a multi-antenna base station (BS) for downlink multi-user multiple-input-single-output (MU-MISO) systems. We aim to enhance energy efficiency (EE) by jointly optimizing beamforming and phase shifts at the BS and RIS, respectively, while ensuring each mobile user meets their link budget requirements. The resulting optimization problem is inherently non-convex. To address this challenge, we employ proximal policy optimization (PPO), known for efficiently managing non-convex problems and reducing training overhead in continuous action spaces through a clip factor. Furthermore, by leveraging deep neural networks (DNN), the proposed PPO-based solution provides the optimum values for the beamforming at the BS and the phase shift at the RIS, respectively. Finally, we demonstrate the effectiveness and accuracy of the proposed PPO-based algorithm through an extensive simulation campaign, comparing its performance against baseline methods (i.e., fractional programming (FP) and deep deterministic policy gradient (DDPG)). The results show that our proposed PPO-based algorithm outperforms the considered baseline approaches (i.e., FP and DDPG) in terms of EE by 34.2% and 15.8%, respectively.

Internet-of-Things (IoT) networks provide massive connectivity for many application scenarios. Recently, much work has been dedicated to develop spectrum access strategies for IoT networks with a massive number of nodes and sporadic data traffic behavior. The case becomes more challenging in critical applications when Ultra-Reliable Low-Latency (URLL) transmissions are required. Such networks entail spectrum-efficient transmission schemes in which Non-Orthogonal Multiple-Access (NOMA) is considered a key enabler. We proposed a Distributed Queuing (DQ) approach in NOMA for critical massive IoT (mIoT) applications. More specifically, we introduce a frame structure to support DQ-based NOMA so that dynamic NOMA clustering (at the nodes) and dynamic Successive Interference Cancellation (SIC) ordering at the Base Station (BS) are supported. We also use adaptive power back-off strategy to reduce power collisions by utilizing both nodes’ and clusters’ activation index. We investigate network performance metrics, such as reliability, delay violation probability, and effective sum rate. These metrics are derived analytically, and the effect of different network parameters such as blocklength, active node arrival rate, and the number of contention subslots on the network metrics are investigated and compared with the S-ALOHA-TD benchmark.

We investigate the use of reconfigurable intelligent surfaces (RISs) in wireless networks to maximize the sum secrecy rate (i.e., the sum maximum rate that can be communicated under perfect secrecy). Specifically, we focus on a network that utilizes RIS-assisted unmanned aerial vehicles (UAVs) under imperfect channel state information (CSI). Our objective is to maximize the sum secrecy rate while dealing with the presence of multiple eavesdroppers. To achieve this, we jointly optimize the active (UAV) and passive (RIS) beamforming together with the UAV's trajectories. The formulated problem is non-convex due to the coupling of CSI with the maneuverability of the UAV. To overcome this challenge, we propose a policy-based deep reinforcement learning (DRL) approach that solves the non-convex optimization problem in a centralized fashion. Finally, simulation results show that our proposed approach significantly improves average sum secrecy rates over conventional approaches.

We propose a new algorithm for the execution of Discrete Event System Specification (DEVS) simulations on parallel shared memory architectures. Our approach executes parallel discrete-event simulations by executing all tasks in the PDEVS simulation protocol in parallel. The algorithm works by distributing the computations among different cores on shared memory architectures. To show the benefits of our algorithm, we present the results of a set of experiments using a synthetic benchmark and a real-world scenario using two independent computer architectures. The results obtained show how our algorithm accelerates simulations up to eight times, improving previous approaches. In addition, we show that our approach scales when we increase the number of CPU-cores used.

Regional authorities will publish public transit route and timetable service offerings through the General Transit Feed Specification (GTFS) as a standard format. Systematically collected GTFS data can be used to study the structure, organization, and availability of public transit services nationally. In this work, we provide a systematic approach to collection of public transit data from various sources, preparation of a high-quality GTFS data inventory and analysis of the public transit offerings lending to numerous insights about transit availability at various geographic scales. Using Canada as a case study, we collected GTFS for the 213 candidate census subdivisions ([CSDs] representing cities, towns, municipalities, etc.) with populations greater than 20,000. These data were then cleaned and leveraged along with CSD-specific census statistics to comprehensively compare public transit offerings between provinces/territories and across CSD types. We determined that, despite a systematic collection process, the majority of CSDs lack official GTFS data, certain provinces are under- or over-represented in our analysis. We further proposed using the median of transit stop spatial density as a national baseline revealing that provinces such as Québec are severely lacking in public transit offerings. GTFS data analysis is insightful for understanding the current state and progress in urban public transportation, which is highly relevant to the United Nation’s Sustainability Development Goals. Our aggregated dataset and open-sourced codebase are publicly available at: github.com/chazingtheinfinite/canada-transit-study.

The COVID-19 pandemic has contributed to un-precedented rates of unemployment and greater uncertainty in the job market. There is a growing need for data-driven tools and analyses to better inform the public on trends within the job market. In particular, obtaining a “snapshot” of available employment opportunities mid-pandemic promises insights to inform policy and support retraining programs. In this work, we combine data scraped from the Canadian Job Bank and Numbeo globally crowd-sourced repository to explore the relationship between job postings during a global pandemic and Key Performance Indicators (e.g. quality of life [QOL] index, cost of living) for major cities across Canada. This analysis aims to help Canadians make informed career decisions, collect a “snapshot” of the Canadian employment opportunities amid a pandemic, and inform job seekers in identifying the correct fit between the desired lifestyle of a city and their career. We collected a new high-quality dataset of job postings from jobbank.gc.ca obtained with the use of ethical web scraping and performed exploratory data analysis on this dataset to identify job opportunity trends. When optimizing for average salary of job openings with QOL, affordability, cost of living, and traffic indices, it was found that Edmonton, AB consistently scores higher than the mean, and is therefore an attractive place to move. Furthermore, we identified optimal provinces to relocate to with respect to individual skill levels. It was determined that Ajax, Marathon, and Chapleau, ON are each attractive cities for IT professionals, construction workers, and healthcare workers respectively when maximizing average salary. Finally, we publicly release our scraped dataset as a mid-pandemic snapshot of Canadian employment opportunities and present a public web application that provides an interactive visual interface that summarizes our findings for the general public and the broader research community.

The music industry and personal music consumption have evolved dramatically with the advent of streaming plat-forms. In this evolving landscape, there is considerable interest in understanding what factors contribute to a song's popularity. Extrinsic (i.e. non-acoustic) features of a given song, such as the record label, and/or intrinsic (i.e. acoustic) features such as its energy may contribute to popularity on a given digital platform. In this work, we, for the first time, sought to systematically study how a song's Spotify acoustic descriptive features correlated with popularity metrics on various Internet platforms. Since each platform defines “popularity” according to platform-specific metrics, a large-scale correlation-based analysis was generated. The digital platforms considered in this article are Google Trends, WhoSampled, TikTok, Twitter, YouTube, and the Billboard Top-100. Platform-specific scrapers were created and all data was aggregated with the Spotify Echo Nest dataset of descriptive acoustic metrics. While the majority of correlations were unre-markable considering both Spearman and Pearson coefficients, a number of corroborating and contradictory findings resulted, with notable implications for acoustic features on various digital platforms. Notably, the YouTube view count was found to be positively correlated to the Spotify song popularity (p = 0.822), year (p = 0.600), and energy (p = 0.455) and moderately negatively correlated to accousticness (p = −0.542) and instrumentalness (p = −0.345). All reproducing code and aggregated data from this work are open-source for use by the broader research community.

Cell-DEVS is a formalism that enables the simulation of cellular models asynchronously with different timing delays. Indoor CO2 diffusion by breathing occupants has been studied taking into consideration room dimensions, ventilation, doors, windows, and occupants as a source. We present a method to define floor plans, and create 2D or 3D models quickly. We added ducts between rooms and show the indoor concentration and diffusion of CO2 with the presence of these ducts.

Lack of documentation for simulation models impedes their shareability, reusability and composability. There are many organizational challenges that lead to a lack of documentation, and this can have long term consequences: wasted time and effort in the best of cases and irrevocable loss in the worst of cases. A standardized metadata approach is a way to preserve digital resources across time, to support reusability and to mitigate organizational challenges that result in undocumented models. In this paper, we present a metadata specification inspired from the Dublin Core Metadata Initiative (DCMI) with additional elements to capture information specific to Discrete Event System Specification (DEVS) simulation models. This work is meant as an initial step towards the establishment of a metadata standard for the preservation of simulation models.

Susceptible-Infected-Recovered (SIR) models have been used to study the spread of COVID-19. In previous works, the standard SIR model has been expanded to include new states as well as geographical level transmission dynamics. We present an extended model using the Cell-DEVS formalism that simulates the effect asymptomatic COVID-19 cases have on a population. The model is an easily adaptable framework that allows for rapid-prototyping and modifications. We exemplify how to build and easily change the model using public health units of Ontario as a case study. The results show the effect asymptomatic carriers have on overall case counts and exposures at the provincial level as well as at the city level.

Summary Real‐time (RT) systems include hardware and software components interacting in a tight fashion. Although formal methods for RT systems development have advanced, they are sometimes difficult to apply in practical applications, and scalability is compromised as the complexity of the system scales up. Instead, using modeling and simulation (M&S) methods and tools has showed to be useful for verification of practical aspects of RT systems (and having the advantage to be able to including models of the physical environment they interact with). Although several efforts exist in M&S of RT systems, none of them has considered problems of transient overloading in the RT systems specifications. Here, we introduce a new theoretical framework called I‐DEVS (imprecise discrete event systems specification) with the goal of guaranteeing responses to inputs within specified time constraints under such transient overloading conditions. The solution presented here has the advantages of a formal specification and the practicality of an M&S‐based approach. We also discuss how to define hierarchical models running in RT, and we present a set of tools that can be applied to develop RT‐embedded applications, and RT simulations.

Motivated by the need for formal methods as well as supporting tools to model and simulate social systems, we propose cellular discrete-event system specification as a formalism for modeling social systems. We also propose the use of a toolkit that implements the formalism of cellular discrete-event system specifications to implement and visualize models of social systems. We present examples of social system models that are different in sizes, nature, and rules controlling the interactions within those systems. We show that cellular discrete-event system specification with its unique features can successfully deal with the shortcoming of other modeling techniques. In addition, we show that together with its supporting toolkit, cellular discrete-event system specification is suitable for modeling, simulating, implementing, and visualizing social systems.

We describe an Abstract Model for Diffusion Processes to simu-late diffusion processes in multiplex dynamic networks using formal modeling and simulation (M&S) methodologies (in this case, the DEVS formalism). This approach helps the users to implement diffusion processes over a network by using the net-work specification and the diffusion rules. The result of combin-ing the network specifications and the diffusion rules is an Ab-stract Model for Diffusion Processes, which is formally defined in DEVS, and can be converted into a computerized model. Using the proposed Abstract Model for Diffusion Processes, we can study a diffusion process in multiplex networks with a formal simulation algorithm, improving the model's definition. We present a case study using the CDBoost simulation engine.

Summary Discrete Event System Specification (DEVS) is a formalism for the modeling and analysis of discrete event systems. Parallel DEVS (PDEVS) is an extension of DEVS for supporting Parallel and Discrete Event Simulation, which is a powerful tool for evaluating the performance of large scale systems. In this work, we propose an optimistic approximate and semi‐asynchronous parallel strategy. The level of optimism is efficiently managed throughout the simulation execution, and it is automatically adjusted based on the simulation evolution. Load balance and model partitioning is automatically made by means of an algorithm that takes advantage of the communication pattern of the simulated model. Our proposal is designed for Web search engines, which are complex and highly optimized systems devised to operate on large clusters of processors and dealing with dynamic and unpredictable user query bursts. The results show that our proposal is able to reduce both execution times and memory usage of standard optimistic simulations of Web search engine models, at the expense of small errors.

Embedded real-time software construction has usually posed interesting challenges due to the complexity of the tasks these systems have to execute. Most methods for developing these systems are either hard to scale up for large systems, or require a difficult testing effort with no guarantee for bug-free software products. Although formal methods have showed promising results, they are difficult to apply when the complexity of the system under development scales up. Instead, systems engineers have often relied on the use of modeling and simulation (M&S) techniques in order to make system development tasks manageable. Construction of system models and their analysis through simulation reduces both end costs and risks, while enhancing system capabilities and improving the quality of the final products. M&S let users experiment with “virtual’ systems, allowing them to explore changes, and test dynamic conditions in a risk-free environment. This is a useful approach, moreover considering that testing under actual operating conditions may be impractical and in some cases impossible. In this talk, we will present a Modeling and Simulation-based framework to develop embedded systems based on the DEVS (Discrete Event systems Specification) formalism. DEVS provides a formal foundation to M&S that proved to be successful for different complex systems. This approach combines the advantages of a simulationbased approach with the rigor of a formal methodology. We will discuss how to use this framework to incrementally develop embedded applications, and to integrate simulation models with hardware components seamlessly. One of the main aspects of the methodology is that it can be integrated with models of the environment in which the embedded controller will act. We will show how the Cell-DEVS and the QSS methods can be used for this task. We will introduce the main characteristics of the Cell-DEVS and QSS methods, and will show how to model physical systems. We will introduce an integrated environment that deals with these issues, orchestrating a cellular-based simulator (CD++), a GIS (GRASS) and data visualization (Google Earth), to simulate behavior and analyze results supporting the decision making for varied environmental scenarios. Our approach does not impose any order in the deployment of the actual hardware components, providing flexibility to the overall process. The use of DEVS improves reliability (in terms of logical correctness and timing), enables model reuse, and permits reducing development and testing times for the overall process. Consequently, the development cycle is shortened, its cost reduced, and quality and reliability of the final product is improved.

Embedded systems are becoming increasingly complex and heterogeneous. Formal methods have proven effective in ensuring reliability and safety. However, they are hard to scale up. Modeling and Simulation (M&S)-based methods, on the other hand, deal effectively with scalability issues and provide the benefits of a risk-free testing environment. Yet, they are usually at most semi-formal, and models are not directly executed on the target hardware. To address the above challenges, we present a formal M&S-based kernel that runs on bare-metal and execute the original simulation models on the target hardware.

Embedded real-time software construction has usually posed interesting challenges due to the complexity of the tasks executed. Most methods are either hard to scale up for large systems, or require a difficult testing effort with no guarantee for bug-free software products. Formal methods have showed promising results; nevertheless, they are difficult to apply when the complexity of the system under development scales up. Instead, systems engineers have often relied on the use of modeling and simulation (M&S) techniques in order to make system development tasks manageable. Construction of system models and their analysis through simulation reduces both end costs and risks, while enhancing system capabilities and improving the quality of the final products. M&S let users experiment with "virtual" systems, allowing them to explore changes, and test dynamic conditions in a risk-free environment. This is a useful approach, moreover considering that testing under actual operating conditions may be impractical and in some cases impossible. In this talk, we will present a Modeling and Simulation-based framework to develop embedded systems based on the DEVS (Discrete Event systems Specification) formalism. DEVS provides a formal foundation to M&S that proved to be successful in different complex systems. This approach combines the advantages of a simulation-based approach with the rigor of a formal methodology. Another advantage of using DEVS is that different existing techniques (Bond Graphs, Cellular Automata, Partial Differential Equations, Queuing models, etc.) have been successfully transformed into DEVS models. We will discuss how to use this framework to incrementally develop embedded applications, and to seamlessly integrate simulation models with hardware components. Our approach does not impose any order in the deployment of the actual hardware components, providing flexibility to the overall process. The use of DEVS improves reliability (in terms of logical correctness and timing), enables model reuse, and permits reducing development and testing times for the overall process. Consequently, the development cycle is shortened, its cost reduced, and quality and reliability of the final product is improved.

In this paper, we discuss how Cellular Discrete Event System Specification (Cell-DEVS) theory can be used in modeling and simulation of the crowd. We will show that the efficient cell update mechanism of Cell-DEVS allows for more efficient entity-based simulation of the crowd compared to cellular automata. On the other hand the formal interfacing mechanisms provided by this theory allows for integration of other components such as DEVS atomic processing component or visualization and building information modeling components with the Cell-DEVS model. Finally, we describe in details of the design and development of several pedestrian models and present the results.

Computational Fluid Dynamics (CFD) deals with computing the equations of fluid flows using numerical methods. The Discrete-Event System specification (DEVS) theory has been used to approximate the continuous systems by applying a quantized state system approach. In this research, we employ Cellular DEVS theory (Cell-DEVS) – originally proposed for modeling and simulation of spatial environments – to create a uniform set of rules for CFD. This harmonized set of state changes can effectively render the fluid dynamics, by applying the accurate rule that represents the behavior of the fluid. The combination of the simplicity and the mathematical backbone allows for constructing models computable on an average computer or an array of cluster computers. 1.

In recent years, numerous applications have been deployed into mobile devices. However, until now, there have been no attempts to run simulations on handheld devices. We want investigate different architectures for running and man-aging simulations on handheld devices, and putting the simulation services in the Cloud. We propose a hybrid simulation and visualization approach, where a dedicated mobile application is running on the client side and the RISE simulation server is hosted in the Cloud. In particular, with our prototype, we explore the remote management of a simulation tool using a dedicated native application running on an Android Smartphone, and showing the evolution of a simulation model for a forest fire spread, mashing-up the generated graphics with online GIS services.

In recent years, various environmental disasters (tsunamis, earthquakes, forest fires and nuclear incidents) have caused numerous losses in lives and infrastructure. In such emergency, remote access to the simulation resources can increase the emergency response success. We propose a new architecture based on the RISE simulation services middleware and on Tavern a workflow to execute the entire simulation process into the Cloud. We present its use through an emergency flooding scenario use case in which emergency crew can order a new simulation and visualize result on Google Earth.

Two new Modelica libraries are presented. The first library, named GGADLib, supports the DEVS graph notation in Modelica. The second Modelica library, named UDPLib, allows sending and receiving data using the User Datagram Protocol (UDP). GGADLib uses UDPLib. As a result, DEVS graph models composed using GGADLib can receive and send data (input and output events, according to DEVS terminology) using UDP. This feature allows Modelica DEVS graph models to communicate with hardware and with other models, e.g., with models developed using other languages and tools, and running in other computers. The implementation of UDPLib and GGADLib is discussed in this paper. Their use is illustrated by means of a case study: evaluating an obstacle avoidance controller for the e-puck mobile robot. The UDPLib and GGAD-Lib Modelica libraries can be freely downloaded from

An approach to carrying out asynchronous distributed simulation of multiprocessor message passing architectures is presented. Aiming at achieving better performance on Conservative DEVS-based simulations, we introduce the GLM protocol which borrows the idea of safe processing intervals from the conservative time window algorithm and maintains global synchronization in a fashion similar to the distributed snapshot technique. Under the GLM scheme, a central look ahead manager (LM) exists which is in charge of receiving every LP's look ahead, identifying the global minimum look ahead of the system, and broadcasting it via null messages to all LPs. The simulation is divided into cycles of two phases: Parallel phase and Broadcast phase. The GLM protocol is asynchronous and the central look ahead manager is not expected to be a bottleneck since the only message transmissions involving it take place when all LPs are blocked waiting for permission to advance their LVTs. The results presented in this paper show that the GLM protocol not only significantly reduces the total number of null messages, but it improves the performance and higher speedups are achieved.

Rational Time-Advance DEVS (RTA-DEVS) is an extension to DEVS that enables formal verification of simulation models using standard model-checking algorithms and tools. In order to enable formal verification of DEVS models, we introduce a procedure to approximate DEVS with RTA-DEVS. We include conditions for valid approximation and a calculation method for approximation errors that may be introduced. The resulting RTA-DEVS models are behaviorally equivalent to the original DEVS.

We propose a flexible and scalable message-oriented mechanism allowing interoperability between seven different DEVS implementations towards DEVS standardization. The main objective of the proposed protocol is to enable different DEVS implementations to interface and coordinate among each other to simulate the same model structure across their diverse domains. To do so, the proposed simulation protocol uses SOAP-based Web-Services technology as the communication framework to exchange control and simulation messages. The objective is achievable with minimum design changes to each DEVS implementation, mainly by hiding the detailed implementation behind a wrapper and focusing only on the exchanged messages.

We present a DEVS and Cell-DEVS simulation system based on Microsoftpsilas .NET Remoting, an execution framework for Windows programs. Remoting is the process of programs interacting across different processes or machines. The numerous remoting services in .NET provide the ability to invoke objects that exist anywhere on the network. We modified PCD++ (a parallel DEVS and Cell-DEVS simulation tool based on the Message Passing Interface - MPI) to make use of these services. The new tool, called PCD++/.NET integrates .NET Remoting into PCD++ to execute distributed DEVS and Cell-DEVS simulation. PCD++/.NET can be suitable for the model which has modest remote messages and presents tolerable performance.

This paper proposes a novel lightweight time warp (LTW) protocol for high-performance parallel optimistic simulation of large-scale DEVS and cell-DEVS models. By exploiting the characteristics of the simulation process, the protocol is able to set free most logical processes (LPs) from the time warp mechanism, while the overall simulation still executes optimistically, driven by only a few full-fledged time warp LPs. The LTW protocol includes a rule-based event-scheduling mechanism using two types of event queues, an aggregated state-saving technique for optimal risk-free state management, and a new rollback algorithm that recovers lightweight LPs from causality errors without sending anti-messages. The impact on global control mechanisms such as GVT computation, fossil collection, and load migration is also discussed. The basic concepts of the protocol could also apply to a broad range of time warp systems under certain conditions and with appropriate control over the LPs.

Abstract ATLAS is a modeling language that permits a static view of a city section to be defined for simulating traffic in closed areas. We propose a methodology that is focused on the user while being able to improve the software development activities. The models are formally specified, avoiding a high number of errors in the application, thus reducing the problem solving time. Streets are characterized by their traffic direction, number of lanes, etc. Once the urban section is outlined, the traffic flow is automatically set up. Specialized behavior is included to model traffic lights, trucks, traffic signs, railways, etc. The basic idea is to provide a mapping into DEVS and Cell‐DEVS models that can be easily executed with a simulation tool. As the modelers can focus on the problem to solve, development times for the simulators can be dramatically reduced. A front‐end system allows the user to draw city sections (and then parse the drawing to create a valid ATLAS file), and an output subsystem permitting cars to be shown with realistic 3D graphics. Copyright © 2007 John Wiley & Sons, Ltd.

DEVS (Discrete EVents systems Specification) is a sound, formal modeling and simulation (M&S) framework that supports hierarchical, modular model composition. DEVS-based M&S environments have been used successfully to understand, analyze, and develop a wide variety of systems. As the systems under study become larger and more complex, the performance of the simulator becomes critical. Nevertheless, evaluating the performance of such simulators is a complex process that requires the execution of large numbers of models with different characteristics. We present DEVStone, a synthetic benchmark devoted to automate the evaluation of DEVS-based simulation approaches, which generates models similar to those existing in the real world. DEVStone facilitates performance analysis for successive versions (e.g., upgrades or fixes) of the same simulation engine, and provides a common metric to compare different M&S environments.

DEVS theory (originally defined for modeling and simulation of discrete event systems) was extended for modeling and simulation of continuous/hybrid systems. We present the M/CD++, a tool to build such models using a subset of Modelica, a modular and acausal specification language for physical systems. Models are created using Modelica standard notation, and a translator converts them into DEVS models. We show how to model these dynamic systems under the discrete event abstraction, including different execution results.

Abstract The features of a toolkit for modeling and simulation based on the DEVS formalism are presented. The tool is built as a set of independent software pieces running on different platforms. Not only are the main characteristics of the environment presented, a focus on its use is also considered by inclusion of application examples for a variety of problems. Many models can be defined in an automated fashion, simplifying the construction of new models and easing their verification. The use of this formal approach has allowed the development of safe and cost‐effective simulations, significantly reducing development time. Copyright © 2002 John Wiley & Sons, Ltd.

Alfa-1 is a simulated computer designed for computer organization courses. Alfa-1 and its accompanying toolkit allow students to acquire practical insights into developing hardware by extending existing components. The DEVS formalism is used to model individual components and to integrate them into a hierarchy that describes the detailed behavior of different levels of a computer's architecture. We introduce Alfa-1 and the toolkit, show how to extend existing components, and describe how to use Alfa-1 for educational purposes. We also explain how to assemble, link, and execute applications and how to test new extensions usingthe testing tools.