Energy‐efficient fog computing in Internet of Things based on Routing Protocol for Low‐Power and Lossy Network with Contiki

Abstract

Summary The traditional centralized cloud computing (CC) model faces a range of problems with the exponential growth of the Internet of Things (IoT) applications, like high latency, reduced bandwidth, and network instability. Fog computing (FC) takes the cloud closer to IoT computers to overcome these problems. Rather than moving them to the cloud, the FC provides local IoT data processing and storage on IoT computers. This paper focuses on the Routing Protocol for Low‐Power and Lossy Network (RPL), a universally routing protocol for a static environment that is used for reducing energy consumption, delay, and packet loss with data aggregation at the border router using a fog simulation model in Contiki Cooja. The objective function (OF) choice has an impact on network topology, as each node selects a set of potential parents to send to the destination. However, no systematic analysis of the effects of OF behavior in the RPL environment has been undertaken. Here, three different OFs, Objective Function Zero (OF0), Advanced Objective Function Zero (AOF0), and Minimum Rank with Hysteresis Objective Function (MRHOF) for RPL in the static environment for different node numbers, have been compared. The findings demonstrate that altering all three OFs has a significant impact on RPL. The energy consumption is reduced in the case of the AOF0 in the fog node by 50.86%, which is less than the case of the OF0 and MRHOF function. Extensive simulations show that AOF0 outperforms the existing OFs.

Federated learning‐based IoT: A systematic literature review

“…Then, with the aid of federal learning, we may gather them. Finally, as an update, the integrated model may be provided to clients 19,20 …”

“…Finally, as an update, the integrated model may be provided to clients. 19,20 Table 1 presents the related survey studies on the FL-based IoT domain based on a comprehensive literature analysis and survey research and includes each study's main topic, publication year, publisher, review type, paper selection process, open issues, taxonomy, and covered year.…”

A Reference Architecture for IoT-Enabled Smart Buildings

“…Then, we defined the artifacts and the design processes that would be used to build those artifacts. The literature was reviewed to [24,36,[41][42][43][44][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61] Lack of integration between reference architecture and metamodel in smart building context [24,45,60] Lack of real-life validation of reference architecture in smart building context [52,59] determine if the knowledge base provides support to the artifact design. The artifacts were then designed, and an evaluation method was proposed to test the designed artifacts.…”

“…It lacks big data analytics focus and highlights that it is a key challenge. Kuma et al [56] present IoT-based fog computing model. It lacks a focus on big data management and analytics for IoT data.…”

An optimized joint medium access control and routing protocol with iterative contention window adjustment mechanism for a guaranteed lifetime in Internet of Things‐based wireless sensor networks

“…The Internet of Things (IoT) uses embedded sensors that are dynamic and distributed or already occur in various components to gather data at a minimal cost, offering a useful solution for such important aspects of complex sensing applications in essential infrastructure. They are monitoring systems, intelligent traffic control, automated vehicles in traffic surroundings, and a weather monitoring system 1–4 . A wide variety of sensors can be replaced by a few sensors in advanced IoT systems like smart buildings, smart cities, smart healthcare, and the smart industry.…”