Optimal Distributed MQTT Broker and Services Placement for SDN-Edge Based Smart City Architecture

Fawwaz, Dzaky Zakiyal; Chung, Sang-Hwa; Ahn, C.; Kim, Won-Suk

doi:10.3390/s22093431

Cited by 13 publications

(14 citation statements)

References 28 publications

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“…This survey aims to justify the importance of distributed MQTT broker architecture and their enhancements. Fawwaz et al 20 proposed a novel distributed MQTT broker-optimized architecture. The proposed architecture aims to take advantage of edge computing by efficiently managing consumed topics in the network.…”

Section: On the Timeliness Of Distributed Mqtt Architecturementioning

confidence: 99%

“…As Table 1 shows there is no solution that enables data fusion, filtering, and aggregation in distributed MQTT. On the one hand, there are several approaches [20][21][22][23] that proposed distributed architecture for MQTT without considering data fusion, filtering, and aggregation. On the other hand, there are numerous works 29,32,33 regarding data fusion, filtering, and aggregation From the previous works, two contributions caught our attention the most.…”

Section: Novelty Of Mqtt-sdmentioning

confidence: 99%

“…The transmission of data over the cloud can potentially increase the delay and the load of communications, raising significant challenges for real‐time applications. To address the limitations of the centralized broker architecture, several researchers focused on using distributed MQTT broker architectures, such as References 20–23. Distributed MQTT broker architectures consist of distributing several MQTT brokers much closer to the devices by deploying them in fog, edge, and mist nodes.…”

Section: Introductionmentioning

confidence: 99%

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Improvement of MQTT semantic to minimize data flow in IoT platforms based on distributed brokers

Kamoun,

Hmissi,

Ouni

et al. 2024

Trans Emerging Tel Tech

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Message queuing telemetry transport (MQTT) is an application layer protocol that enables effective device communication in the Internet of Things (IoT). MQTT operates according to a publish‐subscribe model, where a broker receives messages from the publishers and then forwards them to the subscribers. However, existing cloud‐based MQTT brokers lead to network bottlenecks due to the large number of devices that interact with them. Therefore, mist computing is involved, where the MQTT brokers are deployed closer to the IoT devices and the workload is distributed across multiple brokers. Nevertheless, the distributed mist‐based MQTT architecture introduces serious issues caused by the massive volume of flow exchanged by IoT devices. In this article, we introduce MQTT‐SD to address these issues. MQTT‐SD enhances MQTT protocol syntax with fusion semantic aggregation. It accomplishes MQTT topic fusion on the MQTT broker side with consideration of topics' distribution. We carried out extensive simulation and emulation to demonstrate MQTT‐SD efficacy. The results show that MQTT‐SD reduces MQTT flow and has the lowest traffic load compared to MQTT+ and MQTT‐MFA.

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Section: On the Timeliness Of Distributed Mqtt Architecturementioning

confidence: 99%

Section: Novelty Of Mqtt-sdmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Improvement of MQTT semantic to minimize data flow in IoT platforms based on distributed brokers

Kamoun,

Hmissi,

Ouni

et al. 2024

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…MEC is significantly expected to be utilized by future Internet applications. Therefore, various uses of MEC have been proposed [52][53][54][55]. Especially, machine learning and artificial intelligence are effective in a MEC platform [56][57][58][59].…”

Section: Related Workmentioning

confidence: 99%

Optimal Task Allocation Algorithm Based on Queueing Theory for Future Internet Application in Mobile Edge Computing Platform

Katayama

Tachibana

2022

Sensors

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For 5G and future Internet, in this paper, we propose a task allocation method for future Internet application to reduce the total latency in a mobile edge computing (MEC) platform with three types of servers: a dedicated MEC server, a shared MEC server, and a cloud server. For this platform, we first calculate the delay between sending a task and receiving a response for the dedicated MEC server, shared MEC server, and cloud server by considering the processing time and transmission delay. Here, the transmission delay for the shared MEC server is derived using queueing theory. Then, we formulate an optimization problem for task allocation to minimize the total latency for all tasks. By solving this optimization problem, tasks can be allocated to the MEC servers and cloud server appropriately. In addition, we propose a heuristic algorithm to obtain the approximate optimal solution in a shorter time. This heuristic algorithm consists of four algorithms: a main algorithm and three additional algorithms. In this algorithm, tasks are divided into two groups, and task allocation is executed for each group. We compare the performance of our proposed heuristic algorithm with the solution obtained by three other methods and investigate the effectiveness of our algorithm. Numerical examples are used to demonstrate the effectiveness of our proposed heuristic algorithm. From some results, we observe that our proposed heuristic algorithm can perform task allocation in a short time and can effectively reduce the total latency in a short time. We conclude that our proposed heuristic algorithm is effective for task allocation in a MEC platform with multiple types of MEC servers.

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“…Florita et al [ 33 ] proposed a resilient system that is dependent on SDN and container to ensure the reliability and functionality of IoT devices when internet access is inconsistent or slow. Fawwaz et al [ 34 ] proposed a distributed MQTT broker for edge resources to reduce network traffic and data delivery latency. Authors [ 35 ] propose CRMS (Cloudless Resource Monitoring System), a self-configuration orchestrator for advanced IoT applications.…”

Section: Background and Related Workmentioning

confidence: 99%

Empowering SDN-Docker Based Architecture for Internet of Things Heterogeneity

2022

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Internet of Things (IoT), an emerging technology, connects billions of smart devices to the Internet through heterogeneous communication technologies enabling novel services and applications. This complex and variable environment encounters several challenges such as managing and controlling the network and IoT applications, programming IoT devices, responding to some specific Quality of Service requirements of certain applications. The current IoT network based on the complex, static, and closed traditional architecture represents a serious concern, especially with the amounts of data generated from the huge and heterogeneous IoT devices. In this paper, we present a new model for IoT architecture that brings together the benefits of Software Defined Networking (SDN) architecture and containerization (i.e., Docker) to address most IoT challenges and abstract the underlying communication and hardware subsystem. The SDN concept decoupled the control plane from data plane which implies a centralized global network view and provides flexibility in network configuration and resource management. Moreover, containerization technique through the docker in the device brings the portability and scalability of the applications. First, we propose, an SDN-based architecture for IoT. Then, with lightweight virtualization of IoT device supplied by Docker, we empower the functionalities and effectiveness of the SDN based architecture solution to challenge the IoT heterogeneity. Furthermore, we use the smart supermarket as a use case to validate our SDN-Docker based architecture in a real IoT scenario. The experimental results validate the architecture implementation.

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Optimal Distributed MQTT Broker and Services Placement for SDN-Edge Based Smart City Architecture

Cited by 13 publications

References 28 publications

Improvement of MQTT semantic to minimize data flow in IoT platforms based on distributed brokers

Improvement of MQTT semantic to minimize data flow in IoT platforms based on distributed brokers

Optimal Task Allocation Algorithm Based on Queueing Theory for Future Internet Application in Mobile Edge Computing Platform

Empowering SDN-Docker Based Architecture for Internet of Things Heterogeneity

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