Wi-Fi HaLow (also known as IEEE 802.11ah) is an amendment to the IEEE 802.11 standard that focuses on Internet of Things (IoT) applications in sub-GHz channels. One of its key features is the Restricted Access Window (RAW) mechanism, by which devices can be grouped into RAW groups and subsequently divided into RAW slots, so that channel contention can be limited by the access point (AP) according to some criteria. To date, most studies have focused on optimization of RAW parameter values assuming a certain configuration for the grouping of devices. However, the choice of algorithm(s) to perform real-time grouping of stations is also a critical step, since it may interfere with the overall network performance if the created groups do not reflect the desired goal. This paper presents a simulation-based performance comparison of two clustering algorithms, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and K-Means, regarding their ability to group devices to achieve higher fairness in channel access time and, consequently, compatible average throughput within groups. For the scenarios investigated, we show that both algorithms deliver similar performance if their parameters are properly chosen, which is a critical matter in both cases if the network dynamics varies substantially over time.

This paper presents a foundation toward building a smart home environment tailored to individuals with Autism Spectrum Disorder (ASD). In this paper we developed a simulated single resident room in Unity to prototype and test real-time sensing, communication, and behavior monitoring. Using MQTT (Message Queuing Telemetry Transport) as a messaging protocol, we integrated environmental sensors, such as light, into a virtual IoT (Internet of Things) system. We used these tools to detect unusual or repetitive behaviors, and implemented a method of a non-invasive RF-based sensing that simulates Wi-Fi signal Channel State Information (CSI) to classify movement states like walking, stationary, waving or fall detection. This system aims to enable an adaptive environment, with an advantage of privacy-preserving monitoring through CSI. This work serves as a foundation for future applications in real ASD-supportive smart homes focused on comfort, autonomy, and safety.

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by social difficulties, sensory sensitivities, and repetitive behaviors, often necessitating environmental support. This paper presents a personalized intervention framework that leverages Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) within a simulated smart home environment based on the Unity platform. Two complementary methods are employed: (1) a vision-based system analyzing multi-view spatiotemporal data to classify ASD-like movements, and (2) an IoT architecture that dynamically transmits real-time binary classification inferences. The system utilizes synthetic data to simulate interactions and evaluate communication latency for relaying inference data to a caregiver. By combining movement analysis with responsive environmental control, this research aims to design an Artificial Intelligence of Things (AIoT) system that enhances autonomy, reduces stress, and improves quality of life for individuals with ASD and their caregivers.

360-degree videos introduce unique challenges to storytelling, especially if filmmakers want to draw the user’s attention to specific regions of the surrounding sphere to ensure the proper flow of narrative at any given time. For instance, at scene cuts, a user might lose track of a story if he/she looks toward a direction that prevents an intended Region of Interest (RoI) to appear in the viewport of the user’s Head-mounted Display (HMD). Because of that, new editing techniques for 360-degree videos are being investigated, and the use of dynamic (i.e., real time) alignment of intended RoI across scene cuts is receiving growing attention. To support research on this topic, we introduce 360EAVP, an open source web-based application for streaming and visualization of 360-degree edited videos on HMDs. The 360EAVP is built on top of the VR DASH Tile Player, which is based on cube mapping projection, and adds new capabilities to handle dynamic video editing. Specifically, 360EAVP introduces (1) real-time track of a user’s viewport direction on the HMD; (2) support for dynamic editing via “snap-change” or “fade-rotation” effects; (3) visibility mapping of the user’s Field of View (FoV) with respect to the player’s cube mapping projection (for purposes of video tile requests during streaming); (4) incorporation of editing timing information into the operation of an ABR algorithm; (5) viewport prediction module based on linear regression or ridge regression models; and (6) video playback data collection and log module. To showcase the use of 360EAVP, we present the results of a small-scale subjective experiment that aimed to evaluate the impact of the “snap-change” and “fade-rotation” editing techniques on user’s Quality of Experience (QoE), comfort, and head movement. Our findings indicate that these editing techniques do not compromise the overall QoE; in fact, in certain scenarios, an improvement is observed. In addition, some subjects significantly reduced their head movements with the editing techniques implemented.

This paper presents the resources utilized for and gathered from a subjective QoE experiment conducted with 45 participants who watched 360° videos processed with offline alignment edits. The aim of these edits is to redirect the assumed field of view to a specified region of interest by rotating the 360° video around the horizon. The user experiment involved alignment edits employing both gradual and instant rotation. We employed the Double Stimulus method, whereby participants evaluated each original-processed video pair, resulting in a dataset with 5400 comfort and sense of presence ratings. During video consumption, head motion was recorded from the Meta Quest 2 device. The resulting dataset, containing the original and processed videos, is made publicly accessible. The accompanying web application, developed for the execution of the experiment, is released alongside scripts for the evaluation of head rotation data in a public repository. A cross-analysis of QoE and HM behavior provides insight into the efficacy of alignment edits for attention alignment within the same scene. This comprehensive set of experimental resources establishes a foundation for further research of 360° videos processed with alignment edits.

Photorealistic media aim to faithfully represent the world, creating an experience that is perceptually indistinguishable from a real world experience. In the past few years, this area has grown significantly, with new multimedia areas emerging, such as light fields, point clouds, ultra-high definition, high frame rate, high dynamic range imaging, and novel 3D audio and sound field technologies. In spite of all the advances done so far, there are several technological challenges to overcome. In particular, research in this field typically requires the use of big datasets, software tools, and powerful infrastructures. Among these, the availability of meaningful datasets, with a diverse and high-quality content, is of significant importance and, to date, most available datasets are limited and do not provide researchers adequate tools to advance the area of photorealistic applications. To help advancing research efforts in this area, this workshop aims to engage experts and researchers on the synthesis of photorealistic images and/or virtual environments, particularly in the form of public datasets, software tools, or infrastructures, for not only multimedia systems research, but also for other fields, such as machine learning, robotics, computer vision, mixed reality, and virtual reality.

The IEEE 802.11ah amendment extends the success of traditional IEEE 802.11 networks to sub-GHz frequency bands by allowing higher signal coverage and introducing new capabilities to handle a massive number of stations in applications for the Internet of Things. The restricted access window (RAW) mechanism is the key technique to limit contention by dividing stations into RAW groups and RAW time slots according to AID numbers that can be changed dynamically via AID Switch Response frames. To date, however, such feature has not been investigated, especially in cooperation with some grouping scheme. This paper presents the first investigation on the use of AID Switch Response frames to implement dynamic grouping. The goal is to improve throughput fairness among stations that are geographically distributed over some area. The grouping scheme is based on the K-Means algorithm, which takes as input the length and signal strength of data frames received by the AP, and the modulation and coding schemes (MCS) adopted by stations. Simulation results show significant gains in throughput fairness obtained with the proposed grouping scheme compared to random grouping over different network scenarios.

This paper introduces a Slotted ALOHA protocol targeted at wireless powered communication networks where nodes have very limited resources: each wireless energy transfer (WET) allows only basic operations and a single packet generation and transmission attempt. The hybrid access point (HAP) keeps track of the number of packet transmission attempts over the channel to perform WET once a given threshold value is reached. The numerical results indicate that there exists an optimal threshold value that maximizes throughput for a given number of nodes, packet generation rate, and number of energy packets.

This paper presents a discrete-time Markov model for the operation of a station in a single-hop IEEE 802.11ah network under saturated traffic and ideal channel conditions. In the proposed model, each beacon interval has only one RAW group that is further divided into a number of RAW slots to which stations are evenly assigned with equal priority. A novel feature in the model is the consideration of the event of RAW slot completion time using a specific probability. Two empirical expressions for this probability are proposed, and we study the average aggregate throughput for various numbers of RAW slots and stations in the network. Numerical results derived from the analytical model show similar behavior to those obtained with an IEEE 802.11ah model available for the ns-3 simulator.

In this paper, we propose a taxonomy for 360° videos that categorizes videos based on moving objects and camera motion. We gathered and produced 28 videos based on the taxonomy, and recorded viewport traces from 60 participants watching the videos. In addition to the viewport traces, we provide the viewers' feedback on their experience watching the videos, and we also analyze viewport patterns on each category.

Carrier-Sense Multiple Access with Transmission Acquisition (CSMA/TA) and channel-access prioritization is presented. CSMA/TA is intended for wireless local area networks of stations endowed with half-duplex transceivers and single antennas. It leverages the small turnaround times of current half-duplex radios to increase the likelihood of having the last transmission from a group of overlapping transmissions succeed, especially if turnaround times are smaller or slightly larger than propagation delays. In CSMA/TA, a station senses the channel before sending a pilot and waits for a short time after sending its pilot before sensing the channel again. If the channel is sensed idle again, the station transmits its data packet. By using appropriate pilot lengths, CSMA/TA allows traffic prioritization at the channel-access level, which supplements traditional output traffic prioritization at stations. It is shown that non-priority CSMA/TA can surpass the performance of such protocols as CSMA, FAMA-PJ, and CSMA/CD if turnaround times are larger than propagation delays, but not too much larger. In addition, it is shown that CSMA/TA can improve traffic prioritization significantly across different traffic classes, under different traffic load proportions, compared to CSMA under the same conditions.

We present and analyze CSMA/CDS, a simple extension of carrier-sense multiple access (CSMA) that attains collision detection (CD) through the collaboration among nodes endowed with half-duplex radios in wireless local area networks (WLAN). CSMA/CDS uses two mechanisms to provide feedback to nodes attempting to transmit data packets concurrently. Using carrier sensing to access the channel, a node transmits a common pilot before sending its data packet, and a designated passive listener sends a collision pilot if it does not hear the common pilot after detecting carrier. This ensures that no collisions of data packets can occur. The throughput of CSMA/CDS is analyzed and compared with the performance of CSMA with priority ACKs and CSMA with collision detection (CSMA/CD), which assumes full-duplex transceivers. The results show that the throughput of CSMA/CDS is much better than the throughput of CSMA and is comparable to that of CSMA/CD.

We introduce the Selective-Awakening MAC (SA‐MAC) protocol which is a synchronized duty‐cycled protocol with pipelined scheduling for Linear Sensor Networks (LSNs). In the proposed protocol, nodes selectively awake depending on node density and traffic load conditions and on the state of the buffers of the receiving nodes. In order to characterize the performance of the proposed protocol, we present a Discrete‐Time Markov Chain‐based analysis that is validated through extensive discrete‐event simulations. Our results show that SA‐MAC significantly outperforms previous proposals in terms of energy consumption, throughput, and packet loss probability. This is particularly true under high node density and high traffic load conditions, which are expected to be common scenarios in the context of IoT applications. We also present an analysis by grade (i.e., the number of hops to the sink, which is located at one end of the LSN) that reveals that LSNs exhibit heterogeneous performance depending on the nodes’ grade. Such results can be used as a design guideline for future LSN implementations.

To date, a significant body of work has already been done in the design of receiver-initiated medium access control (MAC) protocols for wireless ad hoc networks. Most of these works, however, have not appropriately dealt with the fundamental issues inherently related to this class of protocols, such as the rate at which polling is triggered by a node, and the way in which nodes are selected for polling. Moreover, previous works on receiver-initiated protocols have not considered the impact of physical layer aspects on network performance. We analyze the effects of considering such aspects and then we show how to improve these issues with ideas based on the operation of the IEEE 802.11. In addition, we present an algorithm that prioritizes the transmission of polling nodes to nodes that are more likely to have a successful handshake with them. This way, we are actually improving the network overall performance. Our analytical results confirm that even when physical layer aspects are considered, receiver-initiated protocols outperforms sender-initiated protocols, but with a margin significantly lower than that obtained in previous works.

This paper presents the first analytical model of wireless ad hoc networks that considers the impact of realistic antenna-gain patterns on network performance. As such, our modeling approach allows the study of ad hoc networks in which nodes are equipped with directional antennas. This modeling capability stands out from all previous analytical models, which have only dealt with omnidirectional or over-simplified antenna gain patterns, and which have not addressed the specific mechanisms of the medium access control (MAC) protocols used (e.g., the backoff mechanism). A new analytical model for the IEEE 802.11 DCF MAC is introduced that allows the study of different carrier-sensing mechanisms, such as the directional virtual carrier sensing (DVCS) protocol that we use to validate our analytical model and show its applicability. Our numerical results show that our new analytical model predicts the results obtained by discrete-event simulations very accurately, and does it with a processing time that is orders of magnitude faster than the time required by simulations.

This paper presents the first analytical model for ad hoc networks equipped with multiple-input multiple-output (MIMO) radios using space-time coding (STC) that considers the impact of the underlying radio-based topology on network performance. In particular, we consider the space-time block coding (STBC) technique known as the “Alamouti scheme.” We derive the effective signal-to-interference-plus-noise density ratio (SINR) of the Alamouti scheme under multiple access interference (MAI), and we propose the moment generating function (MGF) method to derive closed-form expressions for its symbol error probability under different modulation schemes when fading paths are independent but not necessarily identically distributed. The impact of the Alamouti scheme on IEEE 802.11 ad hoc networks is studied by introducing a new analytical model for the IEEE 802.11 DCF MAC. The model we introduce takes into account the impact of errors in both control and data frames, the carrier-sensing activity, and the finite-retry limit of frame retransmissions. Both PHY- and MAC-layer analytical models are incorporated into our previously-designed, general analytical model for ad hoc networks based on interference matrices. We apply the Alamouti scheme to different antenna system configurations and compare their performance with respect to the basic single-input-single-output (SISO) IEEE 802.11 DCF MAC.

This paper presents an analytical model to predict energy consumption in saturated IEEE 802.11 single-hop ad hoc networks under ideal channel conditions. The model we introduce takes into account the different operational modes of the IEEE 802.11 DCF MAC, and is validated against packet-level simulations. In contrast to previous works that attempted to characterize the energy consumption of IEEE 802.11 cards in isolated, contention-free channels (i.e., single sender/receiver pair), this paper investigates the extreme opposite case, i.e., when nodes need to contend for channel access under saturation conditions. In such scenarios, our main findings include: (1) contrary to what most previous results indicate, the radio's transmit mode has marginal impact on overall energy consumption, while other modes (receive, idle, etc.) are responsible for most of the energy consumed; (2) the energy cost to transmit useful data increases almost linearly with the network size; and (3) transmitting large payloads is more energy efficient under saturation conditions

A new modeling framework is introduced for the analytical study of medium access control (MAC) protocols operating in multihop ad hoc networks. The model takes into account the effect of physical-layer parameters on the success of transmissions, the MAC protocol on the likelihood that nodes can access the channnel, and the connectivity of nodes in the network. A key feature of the model is that nodes can be modeled individually, i.e., it allows a per-node setup of many layer-specific parameters. Moreover, no spatial probability distribution or a particular arrangement of nodes is assumed; the model allows the computation of individual (per-node) performance metrics for any given network topology and radio channel model. To show the applicability of the modeling framework, we model multihop ad hoc networks using the IEEE 802.11 distributed coordination function and validate the results from the model with discrete-event simulations in Qualnet. The results show that our model predicts results that are very close to those attained by simulations, and requires seconds to complete compared to several hours of simulation time.

An analytical model for single-hop ad hoc networks is introduced that considers the impact of the physical layer on the operation and performance of saturated IEEE 802.11. Using the bottom-up approach, aspects of the physical layer are explicitly incorporated in the dynamics of the events governing the operation of the IEEE 802.11 binary exponential backoff algorithm leading to a more realistic computation of the node's average service time and throughput. We study the impact of frequency-nonselective slowly time-variant Rician fading channels on the performance of single-hop ad hoc networks using the IEEE 802.11 distributed coordination function in saturation. We validate our model through simulations and study of the throughput performance of the four-way handshake mechanism under direct sequence spread spectrum (DSSS) with differential binary phase shift keying (DBPSK) modulation.

This paper presents an analytical model to compute the average service time and jitter experienced by a packet when transmitted in a saturated IEEE 802.11 ad hoc network. In contrast to traditional work in the literature, in which a distribution is usually fitted or assumed, we use a bottom-up approach and build the first two moments of the service time based on the IEEE 802.11 binary exponential backoff algorithm and the events underneath its operation. Our model is general enough to be applied to any type of IEEE 802.11 wireless ad hoc network where the channel state probabilities driving a node's backoff operation are known. We apply our model to saturated single-hop ad hoc networks under ideal channel conditions. We validate our model through extensive simulations and conduct a performance evaluation of a node's average service time and jitter for both direct sequence and frequency-hopping spread spectrum physical layers.