The deployment of Cellular Internet of Things (CIoT) is expected to reach over six billion devices by 2030. Many of these devices will be located in remote areas where replacing or recharging their batteries would be difficult and expensive. Therefore, it is crucial to configure these devices for efficient energy use to avoid frequent battery replacements or recharging. However, optimizing the energy consumption of CIoT devices, considering their applications and operating environmental conditions, presents a complex challenge. In response to this challenge, we propose the Gradient-Boosted Learning Optimization for Battery Efficiency (GLOBE) framework for dynamic configuration of Narrowband Internet of Things (NB-IoT) devices. GLOBE adjusts the radio layer of NB-IoT devices based on data transmission patterns and network conditions, enabling swift and automated reconfiguration. Our results demonstrate that GLOBE reduces energy consumption by 30% to 75% compared to baseline configurations, offering significant benefits for both network operators and end devices by improving energy efficiency.

Fifth Generation (5G) networks are becoming the norm in the global telecommunications industry, and Mobile Network Operators (MNOs) are currently deploying 5G alongside their existing Fourth Generation (4G) networks. In this paper, we present results and insights from our large-scale measurement study on commercial 5G Non Standalone (NSA) deployments in a European country. We leverage the collected dataset, which covers two MNOs in Rome, Italy, to study network deployment and radio coverage aspects, and explore the performance of two use cases related to enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low Latency Communication (URLLC). We further leverage a machine learning (ML)-based approach to model the Dual Connectivity (DC) feature enabled by 5G NSA. Our data-driven analysis shows that 5G NSA can provide higher downlink throughput and slightly lower latency compared to 4G. However, performance is influenced by several factors, including propagation conditions, system configurations, and handovers, ultimately highlighting the need for further system optimization. Moreover, by casting the DC modeling problem into a classification problem, we compare four supervised ML algorithms and show that a high model accuracy (up to 99%) can be achieved, in particular, when several radio coverage indicators from both access networks are used as input. Finally, we conduct analyses towards aiding the explainability of the ML models.

The Cellular Internet of Things (CIoT) has seen significant growth in recent years. With the deployment of 5G, it has become essential to reduce the power consumption of these devices for long-term sustainability. The upcoming 6G cellular network introduces the concept of zero-energy CIoT devices, which do not require batteries or manual charging. This paper focuses on these devices, providing insight into their feasibility and practical implementation. The paper examines how CIoT devices use simultaneous wireless information and power transfer, beamforming, and backscatter communication techniques. It also analyzes the potential use of energy harvesting and power management in zero-energy CIoT devices. Furthermore, the paper explores how low-power transceivers can lower energy usage while maintaining dependable communication functions.

Measuring and characterizing web page performance is a challenging task. When it comes to the mobile world, the highly varying technology characteristics coupled with the opaque network configuration make it even more difficult. Aiming at reproducibility, we present a large scale empirical study of web page performance collected in eleven commercial mobile networks spanning four countries. By digging into measurement from nearly two million web browsing sessions, we shed light on the impact of different web protocols, browsers, and mobile technologies on the web performance. We find that the impact of mobile broadband access is sizeable. For example, the median page load time using mobile broadband increases by a third compared to wired access. Mobility clearly stresses the system, with handover causing the most evident performance penalties. Contrariwise, our measurements show that the adoption of HTTP/2 and QUIC has practically negligible impact. To understand the intertwining of all parameters, we adopt state-of-the-art statistical methods to identify the significance of different factors on the web performance. Our analysis confirms the importance of access technology and mobility context as well as webpage composition and browser. Our work highlights the importance of large-scale measurements. Even with our controlled setup, the complexity of the mobile web ecosystem is challenging to untangle. For this, we are releasing the dataset as open data for validation and further research.

PR-SCTP is an extension to SCTP for partial reliability that enables a content sensitive transport service where the reliability of messages can be individually controlled. In previous work, PR-SCTP has been applied for prioritization of messages and trading of reliability against timeliness for applications such as real time video streaming, IPTV transmission, SIP signaling, and syslog. As compared to TCP, it has been shown to provide significant reductions in message transfer delay and gains in application performance. Much of the previous work has, however, considered artificial loss scenarios without competing traffic. Experiments presented in this paper show that although PR-SCTP clearly outperforms TCP in artificial loss scenarios, the performance gain is not as evident in scenarios where PR-SCTP shares a bottleneck link with competing traffic. Our analysis shows that inefficiencies in the forward_tsn mechanism of PR-SCTP, overhead due to small messages, and a higher loss rate per byte encountered by PR-SCTP are contributing factors to the reduced performance when network resources are shared. Finally, a proposal for a more efficient forward_tsn mechanism is introduced.

One major concern of energy constrained WSN technology is to design energy efficient communication protocol. Clustering the whole network is an efficient solution to increase its life time. This paper proposes a clustering based communication protocol for periodical data gathering application in wireless sensor network. It uses the scheduled rotation of cluster heads, which eliminates the problem with the variability of the number of clusters generated in the dynamic, distributed and randomized protocol. Proposed protocol shows more energy efficiency by only triggering the cluster formation when cluster heads energy level falls below a certain threshold. In the simulation, our protocol shows better performance than that of LEACH (low energy adaptive clustering hierarchy) protocol in respect of energy dissipation and number of survival nodes. Furthermore this protocol performs higher number of rounds than that of LEACH in case of the first node and 60% nodes die in the network.