IMPROVING QoS OF VoWLAN VIA CROSS-LAYER BASED ADAPTIVE APPROACH

Voice over Internet Protocol (VoIP) is a technology that allows the transmission of voice packets over Internet Protocol (IP). Recently, the integration of VoIP and Wireless Local Area Network (WLAN), and known as Voice over WLAN (VoWLAN), has become popular driven by the mobility requirements ofusers, as well as by factor of its tangible cost effectiveness. However, WLAN network architecture was primarily designed to support the transmission of data, and not for voice traffic, which makes it lack ofproviding the stringent Quality ofService (QoS) for VoIP applications. On the other hand, WLAN operates based on IEEE 802.11 standards that support Link Adaptive (LA) technique. However, LA leads to having a network with multi-rate transmissions that causes network bandwidth variation, which hence degrades the voice quality. Therefore, it is important to develop an algorithm that would be able to overcome the negative effect of the multi-rate issue on VoIP quality. Hence, the main goal ofthis research work is to develop an agent that utilizes IP protocols by applying a Cross-Layering approach to eliminate the above-mentioned negative effect. This could be expected from the interaction between Medium Access Control (MAC) layer and Application layer, where the proposed agent adapts the voice packet size at the Application layer according to the change of MAC transmission data rate to avoid network congestion from happening. The agent also monitors the quality of conversations from the periodically generated Real Time Control Protocol (RTCP) reports. If voice quality degradation is detected, then the agent performs further rate adaptation to improve the quality. The agent performance has been evaluated by carrying out an extensive series ofsimulation using OPNET Modeler. The obtained results of different performance parameters are presented, comparing the performance ofVoWLAN that used the proposed agent to that ofthe standard network without agent. The results ofall measured quality parameters hav

IMPROVING QoS OF VoWLAN VIA CROSS-LAYER BASED ADAPTIVE APPROACH

Voice over Internet Protocol (VoIP) is a technology that allows the transmission of voice packets over Internet Protocol (IP). Recently, the integration of VoIP and Wireless Local Area Network (WLAN), and known as Voice over WLAN (VoWLAN), has become popular driven by the mobility requirements ofusers, as well as by factor of its tangible cost effectiveness. However, WLAN network architecture was primarily designed to support the transmission of data, and not for voice traffic, which makes it lack ofproviding the stringent Quality ofService (QoS) for VoIP applications. On the other hand, WLAN operates based on IEEE 802.11 standards that support Link Adaptive (LA) technique. However, LA leads to having a network with multi-rate transmissions that causes network bandwidth variation, which hence degrades the voice quality. Therefore, it is important to develop an algorithm that would be able to overcome the negative effect of the multi-rate issue on VoIP quality. Hence, the main goal ofthis research work is to develop an agent that utilizes IP protocols by applying a Cross-Layering approach to eliminate the above-mentioned negative effect. This could be expected from the interaction between Medium Access Control (MAC) layer and Application layer, where the proposed agent adapts the voice packet size at the Application layer according to the change of MAC transmission data rate to avoid network congestion from happening. The agent also monitors the quality of conversations from the periodically generated Real Time Control Protocol (RTCP) reports. If voice quality degradation is detected, then the agent performs further rate adaptation to improve the quality. The agent performance has been evaluated by carrying out an extensive series ofsimulation using OPNET Modeler. The obtained results of different performance parameters are presented, comparing the performance ofVoWLAN that used the proposed agent to that ofthe standard network without agent. The results ofall measured quality parameters hav

Smartphone Usage before and during COVID-19: A Comparative Study Based on Objective Recording of Usage Data

Most studies that claimed changes in smartphone usage during COVID-19 were based on self-reported usage data, e.g., that collected through a questionnaire. These studies were also limited to reporting the overall smartphone usage, with no detailed investigation of distinct types of apps. The current study investigated smartphone usage before and during COVID-19. Our study used a dataset from a smartphone app that objectively logged users’ activities, including apps accessed and each app session start and end time. These were collected during two periods: pre-COVID-19 (161 individuals with 77 females) and during COVID-19 (251 individuals with 159 females). We report on the top 15 apps used in both periods. The Mann–Whitney U test was used for the inferential analysis. The results revealed that the time spent on smartphones has increased since COVID-19. During both periods, emerging adults were found to spend more time on smartphones compared to adults. The time spent on social media apps has also increased since COVID-19. Females were found to spend more time on social media than males. Females were also found to be more likely to launch social media apps than males. There has also been an increase in the number of people who use gaming apps since the pandemic. The use of objectively collected data is a methodological strength of our study. Additionally, we draw parallels with the usage of smartphones in contexts similar to the COVID-19 period, especially concerning the limitations on social gatherings, including working from home for extended periods. Our dataset is made available to other researchers for benchmarking and future comparisons

Problematic internet usage: the impact of objectively Recorded and categorized usage time, emotional intelligence components and subjective happiness about usage

Most research on Problematic Internet Usage (PIU) relied on self-report data when measuring the time spent on the internet. Self-reporting of use, typically done through a survey, showed discrepancies from the actual amount of use. Studies exploring the association between trait emotional intelligence (EI) components and the subjective feeling on technology usage and PIU are also limited. The current cross-sectional study aims to examine whether the objectively recorded technology usage, taking smartphone usage as a representative, components of trait EI (sociability, emotionality, well-being, self-control), and happiness with phone use can predict PIU and its components (obsession, neglect, and control disorder). A total of 268 participants (Female: 61.6%) reported their demographic and completed a questionnaire that included Problematic Internet Usage Questionnaire short form (PIUQ–SF–6), Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), level of happiness with the amount and frequency of smartphone use, and living conditions (whether alone or with others). Their smartphone usage was objectively recorded through a dedicated app. A series of one-way ANOVA revealed no significant difference in PIU for different living conditions and a significant difference in the subjective level of happiness with phone usage (F (3, 264) = 7.55, p \u3c .001), as well as of the frequency of usage where the unhappy group had higher PIU (F (3, 264) = 6.85, p \u3c .001). Multiple linear regression analysis showed that happiness with phone usage (β = −.17), the actual usage of communication (β = .17), social media (β = .19) and gaming apps (β = .13), and trait EI component of self-control (β = −.28) were all significant predictors of PIU. Moreover, gender, age, and happiness with the frequency of phone usage were not significant predictors of PIU. The whole model accounted for the total variance of PIU by 32.5% (Adjusted R2 = .287). Our study contributes to the literature by being among the few to rely on objectively recorded smartphone usage data and utilizing components of trait EI as predictors

Need for Affect, Problematic Social Media Use and the Mediating Role of Fear of Missing Out in European and Arab Samples

Purpose: The growing awareness and concern about the excessive use of social media have led to an increasing number of studies investigating the underlying factors contributing to this behavior. In the literature, it is discussed that problematic social media use (PSMU) can impact individuals’ mental health and well-being. Drawing on the Interaction of Person-Affect-Cognition-Execution (I-PACE) model, this study aimed to examine the association between the need for affect (affect approach and affect avoidance) and PSMU (operationalized via the social media disorder scale), as well as the mediating role of fear of missing out (FoMO) in that relation. Participants and Methods: Data were collected via an online survey from 513 participants in European and Arabic countries. Regression and mediation analyses were conducted to explore the relationships between affect approach, affect avoidance, FoMO, and PSMU. Results: Regression analysis results indicated that both affect approach and affect avoidance as part of the need for affect construct significantly predicted PSMU in both cultural contexts. Mediation analysis showed that FoMO partially mediated the relationship between affect approach and PSMU in the Arab sample but not in the European sample. Beyond this, FoMO partially mediated the relationship between affect avoidance and PSMU in both cultural samples. Conclusion: The present study indicates that managing emotions could be an effective strategy to combat PSMU. In line with this and against the background of the data business model behind social media companies, we deem it to be of importance to minimize triggers related to FoMO in the design of social media platforms (for example, push notifications). This might be particularly relevant for individuals with a high inclination towards affect approach and affect avoidance

On the association between personality, fear of missing out (FoMO) and problematic social media use tendencies in European and Arabian samples

Recent meta-analytical evidence indicates a mild association between higher neuroticism and lower conscientiousness scores and a tendency towards problematic social media use (PSMU). However, fear of missing out (FoMO) has emerged as a critical variable in understanding the positive link between neuroticism and PSMU. Given the replication crisis in psychology, this study aimed to reinvestigate personality-PSMU associations and, crucially, the less-studied FoMO mediation effect. To ensure generalizability of the findings, we recruited two diverse samples with European and Arabian backgrounds. The results revealed a significant total effect of neuroticism on PSMU for both cultural groups, with the European sample demonstrating a fully mediated effect via FoMO, whereas the Arab sample showed a partially mediated effect via FoMO, along with a significant direct effect. This study contributes to the existing literature by highlighting the importance of FoMO as a mediator between neuroticism and PSMU and some minor potential cultural differences in this association