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The Internet of things (IoT) extends the Internet space by allowing smart things to sense and/or interact with the physical environment and communicate with other physical objects (or things) around us. In IoT, sensors, actuators, smart devices, cameras, protocols, and cloud services are used to support many intelligent applications such as environmental monitoring, traffic monitoring, remote monitoring of patients, security surveillance, and smart home automation. To optimize the usage of an IoT network, certain challenges must be addressed such as energy constraints, scalability, reliability, heterogeneity, security, privacy, routing, quality of service (QoS), and congestion. To avoid congestion in IoT, efficient load balancing (LB) is needed for distributing traffic loads among different routes. To this end, this survey presents the IoT architectures and the networking paradigms (i.e., edge–fog–cloud paradigms) adopted in these architectures. Then, it analyzes and compares previous related surveys on LB in the IoT. It reviews and classifies dynamic LB techniques in the IoT for cloud and edge/fog networks. Lastly, it presents some lessons learned and open research issues. [ABSTRACT FROM AUTHOR]

An open-source management system of Web-based teaching interventions is presented that can be used in general for science curriculum courses and especially for computer science courses. The proposed solution is called System of Teaching Intelligent Interventions (STII) and facilitates the authoring, deployment, and evaluation of Web-based metaphors. This paper discusses the use of metaphors for assisting students to comprehend the substance of cognitive concepts and their basic background. STII has been applied in a particular educational scenario during the learning process of 228 students attending the course "computer applications." The presentation of results from a pilot evaluation of two metaphors demonstrates the usefulness of the system. The evaluation focuses on the impact of the two metaphors on student learning, and on detecting potential correlations between metaphors and students' groups. STII evaluation conclusions strongly support that multimedia metaphors can be used as an alternative instructional tool to assist students in confronting their cognitive constraints and developing functional understanding of curriculum courses. [ABSTRACT FROM AUTHOR]

• We developed a Delay-based Adaptive Congestion Control TCP variant (DACC). • DACC has an initialization method that obtains an optimal initial value for the congestion window. • It has a queueing-delay variation-based scheme that contemplates the contribution of all contention traffic flows. • It has improved performance in goodput, throughput, file transfer time, and fairness. Delay-based congestion control policies of the Transmission Control Protocol (TCP) mainly use the Round-Trip-Time (RTT) and bottleneck queue size to detect congestion. However, these policies identify congestion by only taking into account the contribution of their own data flow. Thus, the congestion identification in these policies fails to be completely accurate. Moreover, these policies experience many packet losses resulting in retransmissions, which can further reduce channel utilization. This article proposes a queuing delay variation-based adaptive congestion control TCP variant, called Delay-based Adaptive Congestion Control (DACC), that considers the presence of background flows. DACC quickly adapts to the current network conditions and adjusts the transmission rate accordingly. The simulation results exemplify the significance of DACC as it yields better outcomes in terms of goodput, Packet Loss Ratio (PLR), inter-protocol fairness, intra-protocol fairness, and fast file transfers. [Display omitted] [ABSTRACT FROM AUTHOR]