Efficient strategy to optimize key devices positions in large-scale RF mesh networks

Mezher, Ahmad Mohamad; Rivera, Pedro Enrique Iturria; Cárdenas-Barrera, Julián; Meng, Julian; Guerra, Eduardo Castillo

doi:10.1016/j.adhoc.2020.102192

Cited by 5 publications

(3 citation statements)

References 9 publications

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“…WMNs remain functional even if one of the nodes fails, since they are not dependent on each other. It is also extremely easy to add new nodes without having to change the rest of the network [3,5]. WMNs differ from traditional topologies found in wired networks, such as star or tree topologies, in that they do not form a hierarchy between devices, such as switches and bridges.…”

Section: Wireless Mesh Networkmentioning

confidence: 99%

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Performance Assessment of ESP8266 Wireless Mesh Networks

et al. 2022

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This paper presents a wireless mesh network testbed based on ESP8266 devices using painlessMesh library. It evaluates its feasibility and potential effectiveness as a solution to monitor perishable goods, such as fresh fruit and vegetables, which are often stored and transported inside refrigerated containers. Performance testing experiments with different numbers of nodes and traffic loads and different message payload sizes are conducted under unicast transmission. The impact on network performance is evaluated in terms of delivery ratio and delivery delay, which, consequently, affect the energy consumption and, hence, network lifetime. The results of this investigation are an important contribution to help researchers to propose mechanisms, schemes, and protocols to improve performance in such challenging networks.

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Section: Wireless Mesh Networkmentioning

confidence: 99%

“…This lack of hierarchy, which contrasts with commonly used topologies, such as star topologies, makes the network more efficient and fault tolerant, since the nodes are not dependent on each other [4]. It is also extremely easy to add new nodes to an existing network since it is not necessary to change the rest of the network [5].…”

Section: Introductionmentioning

confidence: 99%

Performance Assessment of ESP8266 Wireless Mesh Networks

et al. 2022

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“…In [39], a proportioned strategy was adopted to optimize collectors and router positions jointly in multi-hop radio-frequency mesh networks, to reduce the running time for highly dense networks as well as to minimize the effect on QoS metrics. The authors in [40] developed a two-hop evolutionary aggregation approach (EAA) using a clustering technique for a wireless remote-metering network.…”

Section: Literature Reviewmentioning

confidence: 99%

A QoS-Aware Machine Learning-Based Framework for AMI Applications in Smart Grids

et al. 2021

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The Internet of things (IoT) enables a diverse set of applications such as distribution automation, smart cities, wireless sensor networks, and advanced metering infrastructure (AMI). In smart grids (SGs), quality of service (QoS) and AMI traffic management need to be considered in the design of efficient AMI architectures. In this article, we propose a QoS-aware machine-learning-based framework for AMI applications in smart grids. Our proposed framework comprises a three-tier hierarchical architecture for AMI applications, a machine-learning-based hierarchical clustering approach, and a priority-based scheduling technique to ensure QoS in AMI applications in smart grids. We introduce a three-tier hierarchical architecture for AMI applications in smart grids to take advantage of IoT communication technologies and the cloud infrastructure. In this architecture, smart meters are deployed over a georeferenced area where the control center has remote access over the Internet to these network devices. More specifically, these devices can be digitally controlled and monitored using simple web interfaces such as REST APIs. We modify the existing K-means algorithm to construct a hierarchical clustering topology that employs Wi-SUN technology for bi-directional communication between smart meters and data concentrators. Further, we develop a queuing model in which different priorities are assigned to each item of the critical and normal AMI traffic based on its latency and packet size. The critical AMI traffic is scheduled first using priority-based scheduling while the normal traffic is scheduled with a first-in–first-out scheduling scheme to ensure the QoS requirements of both traffic classes in the smart grid network. The numerical results demonstrate that the target coverage and connectivity requirements of all smart meters are fulfilled with the least number of data concentrators in the design. Additionally, the numerical results show that the architectural cost is reduced, and the bottleneck problem of the data concentrator is eliminated. Furthermore, the performance of the proposed framework is evaluated and validated on the CloudSim simulator. The simulation results of our proposed framework show efficient performance in terms of CPU utilization compared to a traditional framework that uses single-hop communication from smart meters to data concentrators with a first-in–first-out scheduling scheme.

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