CHARIOT: An IoT Middleware for the Integration of Heterogeneous Entities in a Smart Urban Factory

Akpolat, Cem; Şahinel, Doruk; Sivrikaya, Fikret; Lehmann, Grzegorz; Albayrak, Şahin

doi:10.15439/2017f527

Cited by 10 publications

(6 citation statements)

References 8 publications

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“…In this scenario, we consider highly frequent but small data frames, as it is a typical case in many industrial or residential IoT applications [31,32]. The UDP payload size is set to 16 bytes at a packet interval of 1 ms, which is again close to the channel capacity of the legacy multicast mode.…”

Section: Iot Scenariomentioning

confidence: 99%

Transmission Rate Sampling and Selection for Reliable Wireless Multicast

Geithner

Sivrikaya

2020

Wireless Communications and Mobile Computing

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The multicast communication concept offers a scalable and efficient method for many classes of applications; however, its potential remains largely unexploited when it comes to link-layer multicasting in wireless local area networks. The fundamental lacking feature for this is a transmission rate control mechanism that offers higher transmission performance and lower channel utilization, while ensuring the reliability of wireless multicast transmissions. This is much harder to achieve in a scalable manner for multicast when compared with unicast transmissions, which employs explicit acknowledgment mechanisms for rate control. This article introduces EWRiM, a reliable multicast transmission rate control protocol for IEEE 802.11 networks. It adapts the transmission rate sampling concept to multicast through an aggregated receiver feedback scheme and combines it with a sliding window forward error correction (FEC) mechanism for ensuring reliability at the link layer. An inherent novelty of EWRiM is the close interaction of its FEC and transmission rate selection components to address the performance-reliability tradeoff in multicast communications. The performance of EWRiM was tested in three scenarios with intrinsically different traffic patterns; namely, music streaming scenario, large data frame delivery scenario, and an IoT scenario with frequent distribution of small data packets. Evaluation results demonstrate that the proposed approach adapts well to all of these realistic multicast traffic scenarios and provides significant improvements over the legacy multicast- and unicast-based transmissions.

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Section: Iot Scenariomentioning

confidence: 99%

Transmission Rate Sampling and Selection for Reliable Wireless Multicast

Geithner

Sivrikaya

2020

Wireless Communications and Mobile Computing

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“…To demonstrate the applicability of our pipeline, we implement it on a small-scale conveyor belt as part of a project called CHARIOT (https://chariot.gt-arc.com/, accessed on 30 April 2021) [10], which aims at the holistic inter-networking of a heterogeneous set of devices and human actors through unified IoT middleware and data models. As a core part of the middleware, a knowledge management system provides services for data storage and access as well as cloud-based machine learning and data analysis services.…”

Section: Introductionmentioning

confidence: 99%

Integrating Predictive Maintenance in Adaptive Process Scheduling for a Safe and Efficient Industrial Process

Görür

Sivrikaya³

2021

Applied Sciences

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Predictive maintenance (PM) algorithms are widely applied for detecting operational anomalies on industrial processes to schedule for a maintenance intervention before a possible breakdown; however, much less focus has been devoted to the use of such prognostics in process scheduling. The existing solutions mostly integrate preventive approaches to protect the machines, usually causing downtimes. The premise of this study is to develop a process scheduling mechanism that selects an acceptable operating condition for an industrial process to adapt to the predicted anomalies. As PM is largely a data-driven approach (hence, it relies on the setup), we first compare different PM approaches and identify a one-class support vector machine (OCSVM) as the best performing option for the anomaly detection on our setup. Then, we propose a novel pipeline to integrate maintenance predictions into a real-time, adaptive process scheduling mechanism. According to the abnormal readings, it schedules for the most suitable operation, i.e., optimizing for machine health and process efficiency, toward preventing breakdowns while maintaining its availability and operational state, thereby reducing downtimes. To demonstrate the pipeline on the action, we implement our approach on a small-scale conveyor belt, utilizing our Internet of Things (IoT) framework. The results show that our PM-based adaptive process control retains an efficient process under abnormal conditions with less or no downtime. We also conclude that a PM approach does not provide sufficient efficiency without its integration into an autonomous planning process.

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“…In [59] propose an IoT platform called CHARIOT, which devises a runtime environment integrating heterogeneous resource-constrained IoT devices communicating with various protocols, as well as a scalable and dynamic communication layer that abstracts the connected devices and enables their intercommunication.…”

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confidence: 99%

“…Only three studies propose a system with the feature to connect IoT things using different protocols and technologies. For instance, the system in [58,59] supports MQTT and Constrained Application Protocol (COAP) connections. In our case, RabbitMQ provides additional protocols from those previously mentioned, such as STOMP and HTTP.…”

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An IoT Platform Based on Microservices and Serverless Paradigms for Smart Farming Purposes

Trilles

González‐Pérez

Huerta

2020

Sensors

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Nowadays, the concept of “Everything is connected to Everything” has spread to reach increasingly diverse scenarios, due to the benefits of constantly being able to know, in real-time, the status of your factory, your city, your health or your smallholding. This wide variety of scenarios creates different challenges such as the heterogeneity of IoT devices, support for large numbers of connected devices, reliable and safe systems, energy efficiency and the possibility of using this system by third-parties in other scenarios. A transversal middleware in all IoT solutions is called an IoT platform. the IoT platform is a piece of software that works like a kind of “glue” to combine platforms and orchestrate capabilities that connect devices, users and applications/services in a “cyber-physical” world. In this way, the IoT platform can help solve the challenges listed above. This paper proposes an IoT agnostic architecture, highlighting the role of the IoT platform, within a broader ecosystem of interconnected tools, aiming at increasing scalability, stability, interoperability and reusability. For that purpose, different paradigms of computing will be used, such as microservices architecture and serverless computing. Additionally, a technological proposal of the architecture, called SEnviro Connect, is presented. This proposal is validated in the IoT scenario of smart farming, where five IoT devices (SEnviro nodes) have been deployed to improve wine production. A comprehensive performance evaluation is carried out to guarantee a scalable and stable platform.

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CHARIOT: An IoT Middleware for the Integration of Heterogeneous Entities in a Smart Urban Factory

Cited by 10 publications

References 8 publications

Transmission Rate Sampling and Selection for Reliable Wireless Multicast

Transmission Rate Sampling and Selection for Reliable Wireless Multicast

Integrating Predictive Maintenance in Adaptive Process Scheduling for a Safe and Efficient Industrial Process

An IoT Platform Based on Microservices and Serverless Paradigms for Smart Farming Purposes

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