Performance evaluation of IoT middleware

Cruz, Mauro A. A. da; Rodrigues, Joel J. P. C.; Sangaiah, Arun Kumar; Al‐Muhtadi, Jalal; Korotaev, Valery V.

doi:10.1016/j.jnca.2018.02.013

Cited by 79 publications

(50 citation statements)

References 13 publications

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“…The business layer is a loosely defined one that aggregates general functions to deal with an entire IoT system, including business models and security/privacy. Different extensions of the 3-layer IoT architecture added only one new layer, a middleware/service layer [6,19], and a security and management layer [20]. As for the latter, here we consider that orthogonal layers more adequately address these non-functional requirements.…”

Section: Iot Architectures and Platformsmentioning

confidence: 99%

“…An IoT platform-also known as IoT software platform [22] or IoT middleware [19,23]implements an IoT architecture providing a variety of building blocks to facilitate the development of an IoT smart application, such as device connectivity, device management, data management, data analytics, security, and visualization. An IoT platform gathers data from IoT devices and enables the development and of smart applications that control, monitor, and manage these devices.…”

Section: Of 24mentioning

confidence: 99%

“…Practitioners can rely on different IoT platforms available, both open-source and commercial solutions [11,19,24]. These platforms may use multiple protocols and standards or even proprietary solutions.…”

Section: Of 24mentioning

confidence: 99%

“…Since smart applications will typically have to deal with thousands of devices-or considerably more-performance and scalability concerns are key to any successful IoT deployment. Yet, most current reported experiences show: (a) small-scale pilots [7,44]; (b) simulation-based or analytical results [21,45]; (c) measurement-based results with limited scope [19,46]; (d) no quantitative results at all [2,3,5,8,9,11,12,16,24,37,47]. Also, different architectural and deployment choices for IoT systems affect scalability, and real-time decision-making is possible in an environment composed of thousands of sensors [4,48].…”

Section: Performance and Scalability Of Iot Systemsmentioning

confidence: 99%

“…Cruz et al [19] proposed qualitative and quantitative metrics and evaluated the performance of various IoT platforms. Out of 11 platforms initially analyzed by the qualitative approach, five were selected for the performance analysis.…”

Section: Performance and Scalability Of Iot Systemsmentioning

confidence: 99%

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Architecting and Deploying IoT Smart Applications: A Performance–Oriented Approach

Zyrianoff

Heideker

Silva

et al. 2019

Sensors

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Layered internet of things (IoT) architectures have been proposed over the last years as they facilitate understanding the roles of different networking, hardware, and software components of smart applications. These are inherently distributed, spanning from devices installed in the field up to a cloud datacenter and further to a user smartphone, passing by intermediary stages at different levels of fog computing infrastructure. However, IoT architectures provide almost no hints on where components should be deployed. IoT Software Platforms derived from the layered architectures are expected to adapt to scenarios with different characteristics, requirements, and constraints from stakeholders and applications. In such a complex environment, a one-size-fits-all approach does not adapt well to varying demands and may hinder the adoption of IoT Smart Applications. In this paper, we propose a 5-layer IoT Architecture and a 5-stage IoT Computing Continuum, as well as provide insights on the mapping of software components of the former into physical locations of the latter. Also, we conduct a performance analysis study with six configurations where components are deployed into different stages. Our results show that different deployment configurations of layered components into staged locations generate bottlenecks that affect system performance and scalability. Based on that, policies for static deployment and dynamic migration of layered components into staged locations can be identified.

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Section: Iot Architectures and Platformsmentioning

confidence: 99%

Section: Of 24mentioning

confidence: 99%

Section: Of 24mentioning

confidence: 99%

Section: Performance and Scalability Of Iot Systemsmentioning

confidence: 99%

Section: Performance and Scalability Of Iot Systemsmentioning

confidence: 99%

See 3 more Smart Citations

Architecting and Deploying IoT Smart Applications: A Performance–Oriented Approach

Zyrianoff

Heideker

Silva

et al. 2019

Sensors

View full text Add to dashboard Cite

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A novel holistic approach for performance evaluation in Internet of Things

Martinez‐Caro

Cano

2020

Int J Communication

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Summary The deployment of Internet of Things (IoT) solutions in smart cities or industrial environments (Industrial IoT, IIoT) demands careful consideration in terms of user‐centric or system‐centric target metrics. A better monitoring system able to transform performance outputs into decision‐making and intelligent actions requires less restrictive performance evaluation methods. Classic approaches to performance evaluation in telecommunication networks rely on Quality of Service (QoS) and/or Quality of user Experience (QoE) assessment models. However, the new IoT paradigm establishes a completely different scenario, where, for instance, consumers might no longer be users but machines. In this paper, we propose the evaluation of the performance of IoT services and applications comprising the combination of four quality measures, namely, Quality of Data (QoD), Quality of Information (QoI), Quality of user Experience (QoE), and Quality Cost (QC). The proposal is analyzed using computing simulations. Specifically, we improve the simulation tool FLoRa (Framework for LoRa) incorporating additional LoRa Wide Area Network (LoRaWAN) features. LoRaWAN is a Low‐Power Wide Area Network (LPWAN) technology that operates on the LoRa modulation scheme. Long coverage ranges, low power consumption, and support for a massive number of IoT devices using a limited infrastructure are the main assets of LoRaWAN, establishing it as one of the top IoT technologies. Results show that it is easier and more efficient to disassociate metrics into different dimensions in order to provide a clear vision of the performance of IoT services. This performance evaluation method can be customized and applied to different IoT markets.

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A new IoT‐based smart energy meter for smart grids

et al. 2020

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The significant increase in energy consumption by the growth of the population or by the use of new equipment has brought big challenges to the energy security as well as the environment. There is a need that consumers can track their daily use and understand consumption standards for better organizing themselves to obtain financial and energetic efficiency. With the improvement of smart networks technology for better energy supply, a smart meter is not just a simple measurement gadget anymore, but it has additional functions including smart equipment control, bidirectional communication that allows integration of users and networks, and other functionalities. Smart meters are the most fundamental components in smart power grids. Besides, the meters used with a management system can be utilized for monitoring and controlling home appliances and other gadgets according to the users' need. A solution of an integrated and single system should be more efficient and economical. Smart measurement systems allow monitoring the energy consumption of the final consumers while providing useful information about the energy quality. The information provided by these systems is used by the operators to enhance the energy supply, and different techniques can be also applied for this end, such as charge scheduling, management from the demand side, and nonintrusive load monitoring. The Internet of Things (IoT) is becoming a great ally in the management of smart distribution and energy consumption in smart systems scenarios. To address these issues, this paper proposes and demonstrates a new smart energy meter following an IoT approach and its associated costs and benefits. The developed device incorporates several communication interfaces. In order to easily integrate with any monitoring software solution, the meter has a multi-protocol connection. Finally, the provided solution is validated and demonstrated in real-life environments and it is also under use.

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Performance evaluation of IoT middleware

Cited by 79 publications

References 13 publications

Architecting and Deploying IoT Smart Applications: A Performance–Oriented Approach

Architecting and Deploying IoT Smart Applications: A Performance–Oriented Approach

A novel holistic approach for performance evaluation in Internet of Things

A new IoT‐based smart energy meter for smart grids

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