Search

When lab resources are shared among multiple research projects, issues such as experimental integrity, replicability, and data safety become important. Different research projects often need different software and settings that may well conflict with one another, and data collected for one project may not be safeguarded from exposure to researchers from other projects. In this paper we provide an infrastructure design and an open-source tool, labManager, that render multi-user lab facilities in the behavioral sciences accessible to research projects with widely varying needs. The solutions proposed ensure ease of management while simultaneously offering maximum flexibility by providing research projects with fully separated bare metal environments. This solution also ensures that collected data is kept separate, and compliant with relevant ethical standards and regulations such as General Data Protection Regulation (GDPR) legislation. Furthermore, we discuss preconditions for running shared lab facilities and provide practical advice. [ABSTRACT FROM AUTHOR]

Signal loss remains a persistent challenge in communication systems, impacting Multiple Input Multiple Output (MIMO) systems, especially in the millimeter-wave (mm-Wave) context. This paper explores the effectiveness of the proposed Hybrid Precoding/Combining Design (HPCD) algorithm within a fully connected structure of an mm-Wave downlink massive MIMO system. The primary objective is to enhance the overall system's performance, specifically focusing on improving spectral efficiency. Simulation results consistently demonstrate the superiority of the HPCD algorithm over state-of-the-art techniques, revealing substantial improvements in spectral efficiency. This thorough examination highlights the potential of the proposed approach, positioning it as a compelling solution for next-generation communication networks. The findings are anticipated to significantly contribute to spectral efficiency optimization, facilitating the seamless integration of the proposed technique into practical communication scenarios. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To solve the current problems of inefficiency, low utilization of intensive network resources, and high system cost in handling multi-user applications, a multi-user fine-grained task offloading scheduling approach under cloud-edge-end collaboration was proposed. Latency, energy consumption, and server rental costs were jointly considered. Application tasks were firstly divided and subtask priorities were designed. Then, a multi-user subtask scheduling scheme was proposed and an improved simulated annealing particle swarm algorithm was designed to minimize the total system cost to achieve the optimal offloading decision. Experimental results show that the proposed method reduces the total cost by at least 12.28% and 7.42% compared to other methods such as particle swarm and simulated annealing binary particle swarm, respectively.

Summary: The simulation training system based on VR technology has been applied in clinical medicine due to its immersive interactive experience, economy, and safety. In response to the limitation that most medical surgery training systems can only achieve single user operations, a hybrid synchronous model based multi‐user collaborative framework design is proposed to meet the needs of collaborative training in virtual reality teaching processes. Based on the characteristics of frame synchronization and state synchronization, the synchronization method has been improved. Based on frame synchronization, specific state synchronization is used on interactive events to improve the consistency of operation details and real‐time action. On this basis, a system prototype has been implemented using Unity 3D, and compared with traditional schemes, analysis shows that it has faster response speed for disconnected reconnection and more stable interaction state. [ABSTRACT FROM AUTHOR]

Previous studies on joint optimization of computation offloading and service caching policies in Mobile Edge Computing (MEC) have often neglected the impact of dependency-aware subtasks, edge server resource constraints, and multiple users on policy formulation. To remedy this deficiency, this paper proposes a many-objective joint optimization dependencyaware task offloading and service caching model (MaJDTOSC). MaJDTOSC considers the impact of dependencies between subtasks on the joint optimization problem of task offloading and service caching in multi-user, resource-constrained MEC scenarios, and takes the task completion time, energy consumption, subtask hit rate, load variability, and storage resource utilization as optimization objectives. Meanwhile, in order to better solve MaJDTOSC, a many-objective evolutionary algorithm TSMSNSGAIII based on a three-stage mating selection strategy is proposed. Simulation results show that TSMSNSGAIII exhibits an excellent and stable performance in solving MaJDTOSC with different number of users setting and can converge faster. Therefore, it is believed that TSMSNSGAIII can provide appropriate sub-task offloading and service caching strategies in multi-user and resource-constrained MEC scenarios, which can greatly improve the system offloading efficiency and enhance the user experience. [ABSTRACT FROM AUTHOR]

Data outsourcing has become more and more popular due to its low cost and flexibility. However, there is a problem that the cloud server used to store data is partially trusted. Searchable encryption is an efficient technology that is devoted to helping people conduct accurate searches without leaking information. Nonetheless, most existing schemes cannot support dynamic updates or meet the privacy requirements of all users. There have been some experiments to solve these issues by implementing a dynamically searchable asymmetric encryption scheme. This paper proposes an efficient searchable encryption scheme based on the Authenticator Bloom Filter (ABF). The solution can support dynamic updates and multiple users and meet forward and backward security. This paper uses an ABF to improve the efficiency of searches and updates while playing a significant role in dynamic updates. This paper designs a new token encryption scheme and file set encryption scheme, which not only helps users reduce time in searches and updates but also supports multi-user modes. Experiments show that the proposed scheme takes less time in searching and updating algorithms, especially when the keyword does not exist. The solution also takes into account the problem of history storage when updating, which reduces the unnecessary consumption of memory and avoids multiple storage states for the same file. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Interactive, multi-user experiences are meant to define the present and future of Virtual Reality (VR). Such immersive experiences will typically consist of remote collaborations where content is streamed and/or synchronized over a network connection. Thus, real-time collaboration will be key. In this light, the responsiveness of the system and the network will define the overall experience. As such, understanding the effect of network distortions, especially related to time delay, on end-user's perception (in terms of Quality-of-Experience (QoE)), performance, and collaboration becomes crucial. The existing literature, however, has mostly focused on network requirements from a system point-of-view, where the key performance parameters are only provided in the form of Quality-of-Service (QoS) parameters (such as end-to-end latency). However, the translation of these network impairments to the end-user experience is often omitted. The purpose of this paper is to fill the gap by providing a thorough investigation of the impact of latency on the perception of users while performing collaborative tasks in multi-user VR. To this end, an experimental framework was designed, developed, and tested. It is based on a multi-device synchronizing architecture, enabling two simultaneous users to work together in a gamified virtual environment. The developed test environment also allows for the identification of the most prominent network requirements and objective analysis for each traffic link. To experimentally investigate the impact of latency on user perception, a user study was conducted. Participants were paired and asked to perform the collaborative task under different latency-prone scenarios. The results show that users are able to easily distinguish between distorted and non-distorted network configurations. However, making a distinction between different manifestations of latency is much less straightforward. Moreover, factors such as the user's role in the experience and the required task, and the level of interactivity and movement have an important influence on the subjective level of perception, the strength of the user's preferences, and the occurrence of cybersickness. In contrast, no significant differences in objective metrics, such as system performance and user completion time were observed. These results can support the creation of collective QoE metrics that model the group as a whole rather than each individual separately. As such, this work provides an important step to dynamically counteract any drops in group dynamics and performance by means of smart interventions in the transmission system and/or virtual environment. [ABSTRACT FROM AUTHOR]

In recent years, technologies have evolved towards social, universal and collaborative uses involving multiple users. However, methods and models from user centered design are focused on single-user design and do not take into account the impact of other users on intentions and behaviors to use the technology. The objective of this article is to provide paths of reflection on how to integrate a multi-user centered approach to existing user centered design methods and models. Each phase of user-centered design has been rethought to implement this new framework. Guidelines for moving from user experience to Multi-User eXperience (MUX) are provided. In the same way, we recommend adding a multi-user variable in the technology acceptance models to become the Multi-user Acceptance Model (MAM). User research and user testing have also been rethought to a multi-user reach and a multi-user testing. All these considerations are discussed, and lead to a proposal of a future Multi-user Centered Design (MCD) approach, specifically adapted to manage multi-user digital technology development projects. Finally, it is therefore necessary and important to direct research in the fields (acceptance, user experience, user research and user testing) to assist designers with the development of new methods of product design more respectful of social, environmental and collaborative values. [ABSTRACT FROM AUTHOR]

This study tackles the problem of increasing efficiency and scalability in deep neural network (DNN) systems by employing collaborative inference, an approach that is gaining popularity because to its ability to maximize computational resources. It involves splitting a pre-trained DNN model into two parts and running them separately on user equipment (UE) and edge servers. This approach is advantageous because it results in faster and more energy-efficient inference, as computation can be offloaded to edge servers rather than relying solely on UEs. However, a significant challenge of collaborative belief is the dynamic coupling of DNN layers, which makes it difficult to separate and run the layers independently. To address this challenge, we proposed a novel approach to optimize collaborative inference in a multi-agent scenario where a single-edge server coordinates the assumption of multiple UEs. Our proposed method suggests using an autoencoder-based technique to reduce the size of intermediary features and constructing tasks using the deep policy inference Q-inference network’s overhead (DPIQN). To optimize the collaborative inference, employ the Deep Recurrent Policy Inference Q-Network (DRPIQN) technique, which allows for a hybrid action space. The results of the tests demonstrate that this approach can significantly reduce inference latency by up to 56% and energy usage by up to 72% on various networks. Overall, this proposed approach provides an efficient and effective method for implementing collaborative inference in multi-agent scenarios, which could have significant implications for developing DNN systems. [ABSTRACT FROM AUTHOR]

Distance learning has become a popular learning channel today. However, while various distance learning tools are available, most of them only support a single platform, offer only the trainer’s perspective, and do not facilitate student-instructor interaction. As a result, distance learning systems tend to be inflexible and less effective. To address the limitations of existing distance learning systems, this study developed a cross-platform hands-on virtual lab within the Metaverse that enables multi-user participation and interaction for distance education. Four platforms, HTC VIVE Pro, Microsoft HoloLens 2, PC, and Android smartphone, are supported. The virtual lab allows trainers to demonstrate operation steps and engage with multiple trainees simultaneously. Meanwhile, trainees have the opportunity to practice their operational skills on their virtual machines within the Metaverse, utilizing their preferred platforms. Additionally, participants can explore the virtual environment and interact with each other by moving around within the virtual space, similar to a physical lab setting. The user test compares the levels of presence and usability in the hands-on virtual lab across different platforms, providing insights into the challenges associated with each platform within the Metaverse for training purposes. Furthermore, the results of the user test highlight the promising potential of the architecture due to its flexibility and adaptability. [ABSTRACT FROM AUTHOR]

In a smart home environment, multiple users can access a single smart device simultaneously. Moreover, these multiple users may have conflicting demands at a time; that is, one user’s demands differ from another for the same device based on the role of users and environmental factors. Therefore, existing single-user access control systems cannot handle such conflicting and dynamically changing demands, considering both roles and environmental factors in the multi-user smart home environment. Considering this issue, we proposed a Smart Access Control and Authorization framework (SAAC). It is a multi-user access control solution that has four modules, namely, a user interaction module, a backend server module, a policy manager module, and a policy execution module. The user interaction module collects user data and resource policies, which are processed by the backend server and forwarded to the policy manager. The policy manager resolves conflicts and generates final policies, which are stored in the backend server for enforcement by the policy execution module. The finalized policies are shared with the backend server module and saved there till needed for execution by the policy execution module to enforce the access control decision. We have implemented a proof of concept of the proposed framework on VS Code using the Casbin library. The performance evaluation results show our framework’s effectiveness and efficiency with lower computational complexity requirements than existing methods. Finally, we performed a security analysis of the proposed model based on the STRIDE model that confirms its robustness against access control attacks.

In recent years, the remarkable advancement of WiFi sensing technologies has opened new frontiers in human activity recognition, enabling innovative solutions that transcend traditional methods and improve the capabilities of intelligent environments. Individual dynamic movements such as walking, sitting, standing, and running, as well as more complex interactions such as sports activities, are all examples of human activity. WiFi sensing has emerged as a powerful tool for human activity recognition; however, certain restrictions persist, especially when sensing activities involving multiple users across different locations. These limitations highlight the need for innovative techniques to address the intricacies of multi-user scenarios and environmental effects, ensuring the robustness and accuracy of WiFi-based sensing systems. To address multi-user effects in WiFi signals, we propose a few layering LSTM deep learning models with Raspberry Pi for edge computing solutions. The method leverages the decomposition of Channel State Information (CSI) signals through Independent Component Analysis (ICA) and Continuous Wavelet Transform (CWT). The integration of signal decomposition and deep learning holds promise for advancing WiFi sensing systems’ accuracy, reliability, and real-time capabilities in complex environments and multi-user scenarios. Experimental findings prove the system’s ability to handle complex activities with high classification accuracy. Furthermore, the system displays a remarkable ability to classify complex activities. By leveraging the power of deep learning, the model learns intricate patterns and relationships within the decomposed CSI signals, enabling it to distinguish between diverse activities with high accuracy.

In this paper, we designed and implemented a multi-antenna configured secure millimeter-wave (mmWave) CP-less multi-user orthogonal chirp division multiplexing (OCDM) transceiver. The proposed simulated system emphasizes more applicable performance metrics for a typically assumed case of four users and a passive eavesdropper for audio data transmission. We introduce a four-dimensional hyperchaotic system-based encryption algorithm to enhance physical layer security (PLS). In addition, low-density parity check (LDPC), TURBO, ( $3, 2$ ) single parity check (SPC), and repeat and accumulate (RA) channel coding with Cholesky decomposition-based zero-forcing (CD-ZF) and minimum mean square error (MMSE) signal detection techniques for a better bit error rate (BER) were also implemented. The simulation results signify the effectiveness of the proposed system in terms of PLS enhancement with low correlation coefficients (14.62%, 7.61%, 13.61%, and 15.39% for users 1, 2, 3, and 4, respectively), an achievable secrecy rate with a low signal-to-interference and noise ratio (SINR) of the passive eavesdropper, an achievable out-of-band (OOB) power emission of 341 dB, an estimated average short-time Fourier transform (STFT) spectral power difference of 7.68 dB and estimated peak-to-average power ratios (PAPRs) ranging from 7 to 7.5 dB at a complementary cumulative distribution function (CCDF) of $1\times 10^{-3}$ for different ground transmitting channels. At an identical signal-to-noise ratio (SNR) of 17 dB, all four users achieved a bit error rate of $1\times 10^{-4}$ under RA channel coding, CD-ZF, and 16-QAM (quadrature amplitude modulation) digital modulation.

The demand for ultra-reliable low-latency communications (URLLC) has led to the adoption of grant-free (GF) access techniques by the 5G NR, with the goal of reducing uplink access time. When GF access is employed, the base station (BS) preallocates multiple transmission opportunities (TOs) that can be utilized by the user equipment (UE) as needed. However, this approach results in inefficient resource utilization as unused TOs are wasted. To overcome this inefficiency, the 5G NR allows the assignment of configured grants (CG) to a group of UEs instead of a single one. This development has led research into group-based CG (GCG) schemes, whose reliance on shared resources can result in collisions. The collisions can be prevented by the use of stop-and-wait IR-HARQ schemes. Nevertheless, the delay caused by feedback latency is also undesirable as it severely affects latency performance. This work proposes two new IR-HARQ GCG schemes to efficiently handle feedback latency. The first one is able to eliminate the feedback latency overhead and is proven to simultaneously achieve the latency of a one-shot transmission and the energy efficiency of IR-HARQ, even in the presence of non-instantaneous feedback signaling. The second one features both a feedback latency protection mechanism, similar to the first scheme, and a mechanism specifically designed to further reduce latency. The performance of the proposed schemes is compared with scenarios where each UE uses either an individual one-shot or an IR-HARQ scheme. These comparisons encompass scenarios with either power or energy constraints. The results have shown that the second scheme always outperforms the IR-HARQ scheme and that it is able to outperform the one-shot scheme on a wide interval of feedback latency values, achieving a lower latency both for power and energy constrained cases.

Integrated access and backhaul (IAB) networks operating in full-duplex (FD) mode at millimeter wave frequencies have been actively investigated in the context of future-generation communications networks. However, conventional analog cancellation techniques cannot adequately mitigate the self-interference resulting from the FD operation and the multi-user interference. Hence, in this paper, we consider a multi-cell, multi-user IAB network and jointly design the beamforming and combining matrices to maximize the network’s weighted sum rate. Given the non-convex nature of the problem, we reformulate it using weighted minimum-mean-square-error (WMMSE) and extended fractional programming (FP) techniques followed by a block coordinate descent (BCD) approach. Extensive simulation results validate the superior performance of our proposed algorithms. Specifically, the WMMSE and FP methods can achieve 50 bits/sec/Hz higher than the benchmark scheme for a network employing three cells with two uplink and two downlink users per cell.

Photon counting has been proven to possess excellent signal detection capabilities at low power levels and has extensive potential applications in sixth-generation (6G) communications. However, the inherent dependency between the signal and noise complicates system analysis, and optimizing achievable rates in photon-counting visible light communication (VLC) systems remains unresolved. This paper introduces a new method aimed at minimizing multi-user interference (MUI) through a zero-forcing (ZF) scheme and maximizing the weighted sum rate of the proposed downlink multi-user photon-counting multiple-input multiple-output (MU-PhC-MIMO) VLC system by solving an optimization problem. The key point lies in our utilization of the ZF approach to derive a reasonable asymptotic approximation expression for the weighted sum rate. Subsequently, we use variable substitution and methods like successive convex approximation (SCA) to iteratively convexify the non-convex optimization problem and maximize the weighted sum rate under the ZF form. Compared to other algorithms, this approach can save 2.5 dB of transmission power to achieve the same system-weighted sum rate and significantly outperforms the repetition coding scheme at sufficient transmission power. [ABSTRACT FROM AUTHOR]

Understanding how individuals focus and perform visual searches during collaborative tasks can help improve user engagement. Eye tracking measures provide informative cues for such understanding. This article presents A-DisETrac, an advanced analytic dashboard for distributed eye tracking. It uses off-the-shelf eye trackers to monitor multiple users in parallel, compute both traditional and advanced gaze measures in real-time, and display them on an interactive dashboard. Using two pilot studies, the system was evaluated in terms of user experience and utility, and compared with existing work. Moreover, the system was used to study how advanced gaze measures such as ambient-focal coefficient K and real-time index of pupillary activity relate to collaborative behavior. It was observed that the time a group takes to complete a puzzle is related to the ambient visual scanning behavior quantified and groups that spent more time had more scanning behavior. User experience questionnaire results suggest that their dashboard provides a comparatively good user experience. [ABSTRACT FROM AUTHOR]

We consider a multiple access channel (MAC) problem where several users communicate with a base station and in which the users may have different applications or communication purposes for using the network, which is reflected via associated communication metrics. Specifically, we use throughput as the metric to reflect regular data transmission purposes, and latency, modeled by the inverse throughput, is used to reflect data transmission speed as another metric. The problem is formulated as a non-zero sum game. The equilibrium is derived in closed form. Stability in communication for such a heterogeneous network is established by proving the uniqueness of the equilibrium, except for particular cases where stability still can be maintained via cooperation of users with throughput metric or their switching to latency metric.

To solve the channel acquisition overhead problem of frequency division duplex massive MIMO, for the typical scenario of zero-forcing (ZF) precoding at the base station with users’ quality of service guarantee, a supervisory mechanism for the signal-to-interference-and-noise ratio (SINR) was introduced, and a multi-user antenna-by-antenna interleaved training scheme was designed.Then, considering the additional time overhead introduced by the interleaved training, a multi-user interleaved training scheme based on antenna grouping was designed.Closed-form expressions of the average training length, transmission success rate, and average effective sum spectrum efficiency were derived for the proposed schemes.Theoretical and simulation results reveal the impact of transmit power, SINR threshold, user number, group length, and the error level of channel on the performance of the proposed schemes, and demonstrate that the proposed schemes significantly reduce the pilot overhead and improve the transmission success rate compared to the full and partial training.

The quantum entanglement distribution network, serviced as the communication infrastructure which distributes quantum information among remote users, enables many applications beyond the reach of classical networks. Recently, the applications such as quantum key distribution and quantum secure direct communication, have been successfully demonstrated in the quantum entanglement distribution network. In this article, we propose a multi-user round-trip quantum clock synchronization (QCS) scheme in the quantum network, which can be implemented with one single entangled photon source located at the server. The server distributes the entangled photons to remote multiple users with the wavelength division multiplexing strategy, and each user feeds partial received photons back to the server. The clock difference between the server and each user is calculated from the one-way and round-trip propagation times, which are determined according to the time correlation of entangled photons. Afterwards, the demonstration has been conducted between the server and a user over a 75-km-long fiber link, where the measured clock difference uncertainty is 4.45 ps, and the time deviation is 426 fs with an average time of 4000 s. Furthermore, the proposed QCS scheme is linearly scalable to many users, with respect to user hardware and number of deployed fibers. [ABSTRACT FROM AUTHOR]

Symmetric Searchable Encryption (SSE), as an ideal primitive, can ensure data privacy while supporting retrieval over encrypted data. However, existing multi-user SSE schemes require the data owner to share the secret key with all query users or always be online to generate search tokens. While there are some solutions to this problem, they have at least one weakness, such as non-supporting conjunctive query, result decryption assistance of the data owner, and unauthorized access. To solve the above issues, we propose an Owner-free Distributed Symmetric searchable encryption supporting Conjunctive query (ODiSC). Specifically, we first evaluate the Learning-Parity-with-Noise weak Pseudorandom Function (LPN-wPRF) in dual-cloud architecture to generate search tokens with the data owner free from sharing key and being online. Then, we provide fine-grained conjunctive query in the distributed architecture using additive secret sharing and symmetric-key hidden vector encryption. Finally, formal security analysis and empirical performance evaluation demonstrate that ODiSC is adaptively simulation-secure and efficient. [ABSTRACT FROM AUTHOR]

In this paper, low complexity rate and power optimization schemes operating in the spatial and frequency domains are proposed in a cognitive radio (CR) setting involving multi-user multiple-input-multiple-output-orthogonal frequency division multiplexing (MU-MIMO-OFDM). Under the assumption of a perfect secondary channel state information (CSI) at the receiver, the presented architectures encompass two main stages. In the first one, spatial power waterfilling-like method is performed per each MIMO subchannel pertaining to each subcarrier of each secondary user (SU). The resulting allocated power per each eigen-channel is considered as the power budget in the second stage. In this latter, stochastic algorithm-based approach wherein the transmit parameters per each subcarrier of each SU are adapted such that to maximize the achievable sum-rate capacity of the SUs. Three different schemes are introduced in this work. First, the derivation of the continuous rate MU-MIMO-OFDM-CR version, referred to as C-MU-MIMO-OFDM-CR is presented. Obviously, this proposition is theoretical and is taken as a benchmark for the two remaining counterparts. The second proposition we called discrete-rate MU-MIMO-OFDM-CR, and briefly designated as D-MU-MIMO-OFDM-CR which is to round the provided allocated rate. Finally, the third modified solution, denoted as P-D-MU-MIMO-OFDM-CR proceeds in a similar way as the D-MU-MIMO-OFDM-CR alternative, but superimposes the non/over-used amount of power to the power budget in next iteration. The simulation results show that, compared to the discrete rate D-MU-MIMO-OFDM-CR solution, the P-D-MU-MIMOOFDM-CR approach exhibits an approximate power gain of 1 dB when the SNR level is low, and of 5 dB at high SNR range. [ABSTRACT FROM AUTHOR]

This study introduces a virtual reality (VR)-based remote hair design training system that addresses the limitations of physical presence. By leveraging virtual environments and eliminating the need for tangible tools, this system allows hairstylists and learners to collaborate and master hair-design techniques from a distance. In this approach, a section of a user's hair was derived from their photograph, and during the training, the most compatible 3D hair model was integrated with the user's 3D avatar using the recommended matching procedure. This aligned hairstyle was subsequently incorporated into a 3D model for hair simulation. Further, VR HMD interaction mapping was used for hair cutting and styling. A collaborative environment for hair design has been crafted, enabling multiple participants to partake in remote hairstyle education. This system offers cost-effective training, enhances cooperative learning, and aligns with the requirements of contact-free education. In essence, this research has transformed remote hair design training with immersive VR technology. To verify the system's accuracy, tests were conducted, and the results showcased enhancements in the matching procedure. [ABSTRACT FROM AUTHOR]

Copyright of Journal on Communication / Tongxin Xuebao is the property of Journal on Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Data outsourcing has become more and more popular due to its low cost and flexibility. However, there is a problem that the cloud server used to store data is partially trusted. Searchable encryption is an efficient technology that is devoted to helping people conduct accurate searches without leaking information. Nonetheless, most existing schemes cannot support dynamic updates or meet the privacy requirements of all users. There have been some experiments to solve these issues by implementing a dynamically searchable asymmetric encryption scheme. This paper proposes an efficient searchable encryption scheme based on the Authenticator Bloom Filter (ABF). The solution can support dynamic updates and multiple users and meet forward and backward security. This paper uses an ABF to improve the efficiency of searches and updates while playing a significant role in dynamic updates. This paper designs a new token encryption scheme and file set encryption scheme, which not only helps users reduce time in searches and updates but also supports multi-user modes. Experiments show that the proposed scheme takes less time in searching and updating algorithms, especially when the keyword does not exist. The solution also takes into account the problem of history storage when updating, which reduces the unnecessary consumption of memory and avoids multiple storage states for the same file.

Interactive, multi-user experiences are meant to define the present and future of Virtual Reality (VR). Such immersive experiences will typically consist of remote collaborations where content is streamed and/or synchronized over a network connection. Thus, real-time collaboration will be key. In this light, the responsiveness of the system and the network will define the overall experience. As such, understanding the effect of network distortions, especially related to time delay, on end-user’s perception (in terms of Quality-of-Experience (QoE)), performance, and collaboration becomes crucial. The existing literature, however, has mostly focused on network requirements from a system point-of-view, where the key performance parameters are only provided in the form of Quality-of-Service (QoS) parameters (such as end-to-end latency). However, the translation of these network impairments to the end-user experience is often omitted. The purpose of this paper is to fill the gap by providing a thorough investigation of the impact of latency on the perception of users while performing collaborative tasks in multi-user VR. To this end, an experimental framework was designed, developed, and tested. It is based on a multi-device synchronizing architecture, enabling two simultaneous users to work together in a gamified virtual environment. The developed test environment also allows for the identification of the most prominent network requirements and objective analysis for each traffic link. To experimentally investigate the impact of latency on user perception, a user study was conducted. Participants were paired and asked to perform the collaborative task under different latency-prone scenarios. The results show that users are able to easily distinguish between distorted and non-distorted network configurations. However, making a distinction between different manifestations of latency is much less straightforward. Moreover, factors such as the user’s role in the experience and the required task, and the level of interactivity and movement have an important influence on the subjective level of perception, the strength of the user’s preferences, and the occurrence of cybersickness. In contrast, no significant differences in objective metrics, such as system performance and user completion time were observed. These results can support the creation of collective QoE metrics that model the group as a whole rather than each individual separately. As such, this work provides an important step to dynamically counteract any drops in group dynamics and performance by means of smart interventions in the transmission system and/or virtual environment.

This paper presents research on the physical layer security performance of a multi-user mixed RF/FSO system based on optimal user interference. In this system model, the RF link experiences Rayleigh fading, and the FSO link follows the Fischer–Snedecor F distribution. The system adopts a double-hop-decode-and-forward (DF) relay scheme. We also consider the effect of directivity errors in the FSO link and assume the presence of an illegal eavesdropper with a single antenna near the RF link. The source node controls the energy collection and information forwarding using a multi-user structure based on simultaneous wireless information and power transfer (SWIPT). We select the optimal user to jam the eavesdropper's communication. We derive closed-form expressions for the mixed RF/FSO communication system's secrecy outage probability (SOP) and average secrecy capacity (ASC). Monte Carlo simulations are performed to verify the accuracy of these expressions. By formulating and simulating the simulation system, the impact of various important factors on the mixed system's physical layer security (PLS) is analyzed. The analysis indicates that increasing the number of antennas and interference signal-to-noise ratio (SNR) of the optimal user, the time allocation factor and energy conversion efficiency, and the improvement in the quality of atmospheric channels with improved weather will significantly enhance this system's PLS. [ABSTRACT FROM AUTHOR]

Vehicles are getting equipped in technology, communication between vehicle and the user is getting better. The vehicular network is an emerging technology to provide mobile users with the flexibility to use various services such as entertainment and navigation on wheels. The users are served with data related to their travel in terms of road map, weather updates, traffic congestions, radio services, social network applications and place of interest. The data communication takes place with the help of Smart On-board Unit (SOBU) present on the vehicle. There is a requirement of compound data computations with firm latency. Vehicle Edge computing (VEC) is the emerging technology that has serves at the edge in the neighbourhood of vehicle that enables data offloading. There will be much of energy consumption and latency resulting from offloading and computations. In this paper smart offloading scheme is proposed that will efficiently harvest the energy and reduce the energy consumption problem. As a performance statistic, the execution cost is used, which accounts for both execution delay and task failure. And also, the offloading scheme is analyzed for single user and multiuser by simulations and the results are compared graphically for battery energy level, average execution cost and channel mode select parameters respectively. The factors affecting both Single-user and multi-user computation are identified from the results. Experimental results show that offloading schemes proposed for single user and multi user work better than the other state-of-the-art algorithms for vehicular networks. This single-user analysis will be a benchmark for developing auto pilot vehicle for people with special needs and multi-user analysis will help in developing to all kinds of Electric Vehicle communication. [ABSTRACT FROM AUTHOR]

Existing quantum private query (QPQ) proposals are mostly for single-user scenarios, while recent multi-user proposals assume the existence of a semi-trusted server and only consider the retrieval of the items of common interest. To address these limitations, here we propose a semi-device independent multi-user QPQ scheme exploiting the verification of distributed multipartite GHZ states and the self-testing of a specific class of POVM operators used by the clients. Our scheme allows each user to retrieve different items simultaneously while keeping their choices confidential and also enables the users to retrieve optimal raw key bits during oblivious key generation phase. Additionally, we perform a formal evaluation of the security concerns and are able to determine the maximum likelihood of cheating for both the server and users. [ABSTRACT FROM AUTHOR]

The ultra-reliable low-latency communications (URLLC) tight latency requirements paired with transmission of small payload packets motivates the development of techniques that reduce or eliminate the need for dynamic scheduling. This justifies the study of grant free (GF) leveraged techniques in order to reduce both the latency and control signaling overhead. Previous works considered preallocating resources not only for the first transmission, but also for all possible IR-HARQ transmissions, effectively reducing the scheduling latency and control signaling overhead. However, this has several drawbacks, as it translates into wasted resources. To address these issues, we propose a group-based preallocation method combined with IR-HARQ. Initially, a pool of preallocated resources is assigned to a group of users, which then cooperatively use IR-HARQ feedback signals to distribute, on the fly, the resources amongst them without collisions. The proposed method has two phases: a preallocation phase that takes place once at the group formation stage and a transmission phase which happens at each uplink transmission. The transmission parameters for all possible transmission scenarios are selected at the preallocation stage, with the goal of reducing the latency under reliability and energy constraints. The transmission parameters are obtained through a constrained latency optimization procedure, which considers the stochastic nature of the underlying process. We prove that, asymptotically, the proposed scheme is able to reduce the latency, at least, down to the average latency of any single user (SU) HARQ. The numerical results show that the latency and resources wastage is significantly reduced comparatively to single user IR-HARQ with preallocated resources.

In this work, frequency selective hybrid precoders and combiners are designed for a millimeter wave (mmWave) multiuser (MU) multiple-input-multiple-output (MIMO) downlink underlay cognitive radio network (CRN) utilizing multiple radio frequency (RF) chains and uniform rectangular planar arrays (URPAs) both at the CR base station (CBS) and the secondary users (SUs). The proposed designs maximize the downlink spectral efficiency (SE) of the secondary users, while keeping the interference introduced to the primary user within a prescribed threshold. In the first phase, considering only the channel knowledge at each subcarrier, a novel blind hybrid MMSE-RC (minimum mean squared error-receiver combiner) design is determined using the modified simultaneous orthogonal matching pursuit (MSOMP). Further, employing feedback for each SU’s effective channel, a two-stage decoupled strategy is developed for hybrid transmit precoder (TPC) design, wherein the RF and stage-1 BB-TPC are designed in the first step relying on a capacity-optimal fully digital (FD)-TPC approximation problem followed by the stage-2 BB-TPC design using a low-complexity ZF approach with the goal of mitigating the MUI. Towards this, a novel Modified Alternating Minimization-Zeroforcing (MAM-ZF) algorithm is proposed to compute the hybrid-TPC weights. Furthermore, a low complexity alternating minimization-zeroforcing (LAM-ZF)-based precoding algorithm is also proposed towards the same. Finally, a per-subcarrier optimal power loading solution is derived in closed-form with the objective of maximizing the sum SE while satisfying the interference and transmit power budget limitations. Our simulation findings show that the proposed schemes outperform other state-of-the-art techniques and achieve a spectral efficiency comparable to that achieved by fully-digital beamforming, while requiring a significantly fewer number of RF chains.