Showing papers in "Pervasive and Mobile Computing in 2021"

TL;DR: In this paper, the authors investigate the effects of app design choices and individual differences on COVID-19 contact-tracing app adoption intentions and find that individual differences such as prosocialness, risk perceptions, general privacy concerns, technology readiness, and demographic factors played a more important role than app design decisions such as decentralized design vs. centralized design, location use, app providers, and the presentation of security risks.

TL;DR: In this article, the authors proposed a new hybrid algorithm named ACO integrated Glowworm Swarm Optimization (ACI-GSO), which is the hybridization of (GSO) and (ACO) algorithms.

TL;DR: A sub-optimal algorithm based on the hybrid of genetic algorithm and particle swarm optimization is designed to solve the task offloading problem as a mixed-integer nonlinear program (MINLP), which is NP-hard.

TL;DR: In this paper, the authors proposed a new energy-aware CH selection framework by hierarchical routing in WSN via a hybrid optimization algorithm, where the selection of CH is carried out under the consideration of energy, distance, delay and Quality of Service (QoS) as well.

TL;DR: Evaluation of OmniCells++ in two realistic testbeds using different Android phones with different form factors and cellular radio hardware shows that it can achieve a consistent median localization accuracy when tested on different phones, better than the state-of-the-art indoor cellular-based systems by at least 148%.

TL;DR: In this article, a new behavioural method for Android malware detection and classification is proposed, where the Android malware dataset is decompiled to identify the suspicious API classes/methods and generated an encoded list.

TL;DR: The design and implementation of WiNar is presented, a WiFi RTT-based indoor location determination system that combines the advantages of both fingerprint and ranging-based techniques to overcome the different challenges of indoor environments and is also robust to heterogeneous devices.

TL;DR: A blockchain-based trust management mechanism (BBTM) is proposed in this article, where the trustworthiness of sensor nodes will be evaluated by the mobile edge nodes, which can create smart contracts for trust computation and verify the computation process.

TL;DR: In this article, a framework of blockchain-enabled Internet of Medical Things (IoMT) is proposed to tackle the privacy, security, and interoperability issues of IoMT by introducing blockchain to incumbent IoMT systems.

TL;DR: The experimental results show that the optimal deployment and allocation strategy for deploying edge servers in Ultra-dense network can minimize the cost of deployment and guarantee mobile users’ requirements on offloaded tasks’ completion time.

TL;DR: Li et al. as discussed by the authors proposed a new blockchain-based identity management system for smart industry, which provides non-transferability through a freshly computed hidden biometric attribute, which is generated using a secure fuzzy extractor during each authentication.

TL;DR: Results show that the proposed precoding technique in conjunction with the machine learning algorithm based on a decision tree model that uses empirical data collected from the network can identify the status of cells and suitable self-healing procedures can be triggered to recover the cell accordingly.

TL;DR: SPIDERS + is a low-cost, wireless, glasses-based platform for continuous in-situ monitoring of user’s facial expressions (apparent emotions) and real emotions, and includes optional contact-based sensors such as photoplethysmography and multi-channel electroencephalogram (EEG) to monitor other bio-signals.

TL;DR: A Self Organizing Feature Map is designed to manage MCS-based data for planning of the autonomous mobile assessment centers to enable early detection of infected cases based upon MCS data acquired through smart devices via wireless communications such as Wifi, LTE and 5G.

TL;DR: This work formulated a bi-objective optimization problem that jointly minimizes the overall energy consumption and the penalty function while allocating the local processing frequencies for the SMDs, their transmit powers and the radio resources allocated by the Base Station (BS).

TL;DR: This paper proposes an approach for service discovery and selection in the IoT using Ant Colony Optimization (ACO), and shows high performance in term of accuracy and a longer network lifetime for the discovery andselection phases respectively, as well as a short period of time for both phases.

TL;DR: In this article, a keystroke recognition system for classifying numeric keyboard inputs on smartphones, which consists of a transmitter (e.g., a WiFi router) and a receiver (i.e., a desktop computer with a Commercial Off-The-Shelf (COTS) WiFi NIC), was proposed.

TL;DR: In this paper, the authors proposed distributed algorithms whereby the compute nodes measure the network proximity to each other, and self-organize into a hierarchical or a flat structure accordingly, and implement these algorithms on geographically distributed compute nodes, and they experiment with image processing and smart city use cases.

TL;DR: In this paper, the authors compared the performance of four range-free (RF) localization algorithms that use a mobile anchor (MA) and compared the compared algorithms in which, instead of using the observed or the manufacturer radii, the actual measured distances between the MA and the ground device are used.

TL;DR: The comparative simulations were carried out with state-of-the-art methodologies, which demonstrated the dominance of the presented model in terms of Data assessment efficacy, Statistical classification analysis, Decision-making efficiency, Reliability, and Stability.

TL;DR: In this article, the authors consider the use of machine learning models to evaluate different feature sets that can be extracted from the received BLE signal, and assess the performance gain as more features are introduced in these models.

TL;DR: In this article, an edge-based data conflict resolution approach for IoT is presented to tackle the issues of uncertain, imperfect, and conflicting data in the IoT data collection and data fusion.

TL;DR: An Intelligent Charging scheme Maximizing the Quality Utility (ICMQU) is proposed to design the charging path for the mobile charger, which considers not only the utility of the data collected from the environment, but also the impact of sensing nodes with different quality.

TL;DR: In this paper, the authors propose an OpenStack-based platform that implements a fog service as a container and migrates the latter to support device mobility, following the device route, permitting to maintain proximity and preserve low latency.

TL;DR: This paper describes both temporal and spatial approaches, the methods to select various hyperparameters, and a workflow to combine these two methodologies and provide comparative results illustrate that the average precision of temporal methods using long-short temporal memory networks to predict impending failures in the next ten days was 84 percent.

TL;DR: This article proposes a mutual privacy-preserving authentication protocol based on elliptic curve cryptography (ECC) to achieve efficiency in resource consumption and protect the privacy of involved devices.

TL;DR: In this article, a two-layer model framework is proposed to classify Byzantine attackers in a CRN, where the first layer, Processing layer, uses Hidden Markov Model (HMM) to get a probabilistic relationship between the PU's states and the SUs' sensing reports.

TL;DR: The Congestion Propagation Modeling Algorithm (CPMA) presented in this article is the first to be able to determine the expected value of propagation times for any propagation pattern as well as propagation probabilities using Markov chains.

TL;DR: A novel health and sleep nursing assistant called “Helena” for real-time, contactless, and non-invasive monitoring that can be mounted on a bed frame to continuously monitor sleep activities, vital signs, and falls from bed in a pervasive computing manner.

TL;DR: In this paper, the authors investigate how cloudlets can be transported by unmanned autonomous vehicles (UAV)s to provide computation support on the edge, and they develop a novel UAV-based system that enables the dynamic deployment of an edge computing infrastructure through the cooperation of multiple UAVs carrying cloudlets.