Towards a Reference Architecture for Swarm Intelligence-based Internet of Things

International audienceThe Internet of Things (IoT) represents the global network which interconnects digital and physical entities. It aims at providing objects with intelligence that allows them to perceive, decide and cooperate with other objects, machines, systems and even humans to enable a whole new class of applications and services. Agent-Based Computing paradigm has been exploited to deal with the IoT system development. Many research works focus on making objects able to think by themselves thus imitating human brain. Swarm Intelligence studies the collective behavior of systems composed of many individuals who interact locally with each other and with their environment using decentralized and self-organized control to achieve complex tasks. Swarm intelligence-based systems provide decentralized, self-organized and robust systems with consideration of coordination frameworks. We explore in this paper the exploitation of swarm intelligence-based features in IoT-based systems. Therefore, we present a reference swarm-based architectural model that enables cooperation among devices in IoT systems

Big data acquired by Internet of Things-enabled industrial multichannel wireless sensors networks for active monitoring and control in the smart grid industry 4.0

Smart Grid Industry 4.0 (SGI4.0) defines a new paradigm to provide high-quality electricity at a low cost by reacting quickly and effectively to changing energy demands in the highly volatile global markets. However, in SGI4.0, the reliable and efficient gathering and transmission of the observed information from the Internet of Things (IoT)-enabled Cyber-physical systems, such as sensors located in remote places to the control center is the biggest challenge for the Industrial Multichannel Wireless Sensors Networks (IMWSNs). This is due to the harsh nature of the smart grid environment that causes high noise, signal fading, multipath effects, heat, and electromagnetic interference, which reduces the transmission quality and trigger errors in the IMWSNs. Thus, an efficient monitoring and real-time control of unexpected changes in the power generation and distribution processes is essential to guarantee the quality of service (QoS) requirements in the smart grid. In this context, this paper describes the dataset contains measurements acquired by the IMWSNs during events monitoring and control in the smart grid. This work provides an updated detail comparison of our proposed work, including channel detection, channel assignment, and packets forwarding algorithms, collectively called CARP [1] with existing G-RPL [2] and EQSHC [3] schemes in the smart grid. The experimental outcomes show that the dataset and is useful for the design, development, testing, and validation of algorithms for real-time events monitoring and control applications in the smart grid

Cyberattack patterns in blockchain-based communication networks for distributed renewable energy systems : A study on big datasets

Blockchain-based reliable, resilient, and secure communication for Distributed Energy Resources (DERs) is essential in Smart Grid (SG). The Solana blockchain, due to its high stability, scalability, and throughput, along with low latency, is envisioned to enhance the reliability, resilience, and security of DERs in SGs. This paper presents big datasets focusing on SQL Injection, Spoofing, and Man-in-the-Middle (MitM) cyberattacks, which have been collected from Solana blockchain-based Industrial Wireless Sensor Networks (IWSNs) for events monitoring and control in DERs. The datasets provided include both raw (unprocessed) and refined (processed) data, which highlight distinct trends in cyberattacks in DERs. These distinctive patterns demonstrate problems like superfluous mass data generation, transmitting invalid packets, sending deceptive data packets, heavily using network bandwidth, rerouting, causing memory overflow, overheads, and creating high latency. These issues result in ineffective real-time events monitoring and control of DERs in SGs. The thorough nature of these datasets is expected to play a crucial role in identifying and mitigating a wide range of cyberattacks across different smart grid applications.© 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)fi=vertaisarvioitu|en=peerReviewed

Energy efficient multi channel packet forwarding mechanism for wireless sensor networks in smart grid applications

Multichannel Wireless Sensor Networks (MWSNs) paradigm provides an opportunity for the Power Grid (PG) to be upgraded into an intelligent power grid known as the Smart Grid (SG) for efficiently managing the continuously growing energy demand of the 21st century. However, the nature of the intelligent grid environments is affected by the equipment noise, electromagnetic interference, and multipath effects, which pose significant challenges in existing schemes to find optimal vacant channels for MWSNs-based SG applications. This research proposed three schemes to address these issues. The first scheme was an Energy Efficient Routing (ERM) scheme to select the best-optimized route to increase the network performance between the source and the sink in the MWSNs. Secondly, an Efficient Channel Detection (ECD) scheme to detect vacant channels for the Primary Users (PUs) with improved channel detection probability and low probability of missed detection and false alarms in the MWSNs. Finally, a Dynamic Channel Assignment (DCA) scheme that dealt with channel scarcities by dynamically switching between different channels that provided higher data rate channels with longer idle probability to Secondary Users (SUs) at extremely low interference in the MWSNs. These three schemes were integrated as the Energy Efficient Multichannel Packet Forwarding Mechanism (CARP) for Wireless Sensor Networks in Smart Grid Applications. The extensive simulation studies were carried through an EstiNet software version 9.0. The obtained experimental simulation facts exhibited that the proposed schemes in the CARP mechanism achieved improved network performance in terms of packets delivery ratio (26%), congestion management (15%), throughput (23%), probability of channel detection (21%), reduces packet error rate (22%), end-to-end delay (25%), probability of channel missed-detection (25%), probability of false alarms (23.3%), and energy consumption (17%); as compared to the relevant schemes in both EQSHC and G-RPL mechanisms. To conclude, the proposed mechanism significantly improves the Quality of Service (QoS) data delivery performance for MWSNs in SG

Towards Agent-Based Model Specification of Smart Grid: A Cognitive Agent-Based Computing Approach

A smart grid can be considered as a complex network where each node represents a generation unit or a consumer, whereas links can be used to represent transmission lines. One way to study complex systems is by using the agent-based modeling paradigm. The agent-based modeling is a way of representing a complex system of autonomous agents interacting with each other. Previously, a number of studies have been presented in the smart grid domain making use of the agent-based modeling paradigm. However, to the best of our knowledge, none of these studies have focused on the specification aspect of the model. The model specification is important not only for understanding but also for replication of the model. To fill this gap, this study focuses on specification methods for smart grid modeling. We adopt two specification methods named as Overview, design concept, and details and Descriptive agent-based modeling. By using specification methods, we provide tutorials and guidelines for model developing of smart grid starting from conceptual modeling to validated agent-based model through simulation. The specification study is exemplified through a case study from the smart grid domain. In the case study, we consider a large set of network, in which different consumers and power generation units are connected with each other through different configuration. In such a network, communication takes place between consumers and generating units for energy transmission and data routing. We demonstrate how to effectively model a complex system such as a smart grid using specification methods. We analyze these two specification approaches qualitatively as well as quantitatively. Extensive experiments demonstrate that Descriptive agent-based modeling is a more useful approach as compared with Overview, design concept, and details method for modeling as well as for replication of models for the smart grid

Metodologia de sensoriamento e acesso dinâmico aos canais em redes de sensores sem fio

A melhora na eficiência do uso do espectro de radiofrequência é fundamental para permitir um desempenho adequado dos diversos sistemas sem fio cuja complexidade e requerimentos aumentam a cada dia. O panorama atual de atribuição de canais é estático, tolerando assim, que o espectro de radiofrequência seja usado de forma desequilibrada, gerando com isso, problemas de coexistência em algumas faixas e subutilização de recursos em outras. Para contornar esse problema, tem sido proposta a ideia de introduzir algoritmos de cognição nos dispositivos sem fio, a fim de permitir um modelo de alocação dinâmico adicional. Neste, os usuários secundários equipados com rádios cognitivos podem utilizar de forma dinâmica os canais subutilizados de usuários primários. Um usuário primário tem prioridade de uso do canal como consequência da atribuição estática, porém, o uso do canal por um usuário secundário qualquer é oportunista e limitando ao tempo de inatividade do usuário primário em um determinado local. As redes de sensores sem fio trabalham em uma banda concorrida e são sistemas que podem melhorar seu desempenho utilizando um mecanismo de acesso dinâmico aos canais, possibilitando o aproveitamento dos períodos de inatividade de usuários primários ou aumentando sua capacidade de coexistência na banda de operação atual. Segundo a literatura pesquisada são vários os desafios existentes para conseguir um método distribuído de acesso dinâmico aos canais que considere as restrições de trocas de sinalizações, consumo de energia e complexidade dos dispositivos de uma rede de sensores sem fio. Neste contexto, propõe-se uma metodologia de sensoriamento e acesso dinâmico aos canais para uma rede de sensores sem fio considerando a simplicidade dos dispositivos. Como fatores de inovação, optou-se pela definição de uma política de sensoriamento por clusters que permite realizar uma aprendizagem cooperativa por reforço da situação dos canais de operação. Além disso, a definição de um mecanismo de acesso dinâmico aos canais fundamentado no padrão IEEE 802.15.4 permite comunicação e coordenação distribuída de forma assíncrona. O funcionamento da metodologia proposta é avaliado e comparado usando simulações e experimentos mediante um estudo de caso específico. As comparações são realizadas com métodos de seleção de canal: fixa, cega ou baseada em recompensas por acesso. Os resultados mostram a eficiência no acesso dinâmico aos canais com aumentos na taxa de entrega de mensagens e na capacidade de coexistir com as redes primárias.The efficiency improvement of the use of radiofrequency spectrum is fundamental to allow more complex and more optimal wireless systems. The current channel allocation is static. It tolerates unbalanced use of the radiofrequency spectrum generating coexistence problems in some bands and underutilization of resources in other bands. The introduction of cognitive algorithms into wireless devices has been proposed to overcome that problem, in order to allow an additional dynamic allocation model. In this, the secondary users equipped with cognitive radios will be able to use dynamically the underutilized channels of primary users. A primary user has channel usage priority related to the static allocation, on the other hand, the use of the channel by any secondary user is opportunistic and limited to the inactivity time of the primary user in a specific place. Wireless sensor networks work in a competitive band. These systems can improve their performance using a dynamic access to the channels and consequently to enable the utilization of inactivity periods of primary users or to increase the coexistence capability at their current operation band. According to the researched literature, several challenges exist to find a distributed method for dynamic access to the channels considering the restrictions on control signaling, energy consumption and computational complexity of wireless sensor network devices. In this context, a methodology of sensing and dynamic access to the channels in a wireless sensor network considering the restrictions of the devices is proposed. As innovation, we opted for the definition of a sensing policy by clusters that allows the cooperative reinforcement learning of the situation of channels. In addition, a mechanism for dynamic access to the channels based on the IEEE 802.15.4 standard is defined to allow asynchronous and distributed coordination. The behavior of the proposed methodology is evaluated and compared using simulations and experiments through a specific case study. The comparisons are performed with channel selection methods: fixed, blind and access based. The results show good efficiency in the dynamic allocation of the channels, increasing the message delivery rate and the coexistence capability