The impact of mobility patterns on the efficiency of data forwarding in MANETs

One of the most challenging requirements in cutting-edge Mobile Ad hoc Networks is the need for adaptive and efficient routing. Networks capable of adapting their behavior based on current conditions are often characterized as self-organizing networks, which are lately considered very promising for future applications. This work examines the impact of the different mobility properties on the performance of self-organizing networks. For that purpose, a simulator was developed to model different mobility patterns and study the way they affect the effectiveness of the well-known AODV routing protocol. Particularly, this paper focuses on the effect of the different mobility schemes on network topology and consequently to the overall network performance. The results reveal the tight correlations between node mobility characteristics and network metrics

Energy efficient network coding-based MAC for cooperative ARQ wireless networks

In this paper we introduce a network coding-aided energy efficient Medium Access Control (MAC) protocol that coordinates the transmissions among a set of relay nodes which act as helpers in cooperative Automatic Repeat reQuest-based (ARQ-based) wireless networks. Applying network coding techniques, we achieve to increase the energy efficiency of the network without compromising the system performance in terms of Quality of Service. Our proposed solution is evaluated by both analytical and simulation results. © 2012 Elsevier B.V. All rights reserved

Measurement and statistical analysis of asymmetric multipoint videoconference traffic in IP networks

The paper contributes results on the modeling of videoconferencing traffic over IP networks. The study is based on extensive data, gathered by tracing the actual packet exchange during a comprehensive set of realistic teleconferencing sessions over an asymmetric platform, in which commercial H.261-compliant terminal clients were communicating, through a Multipoint Control Unit (MCU) at 'continuous presence' mode. Analysis of the data suggests that the video traffic from the client terminals can always be represented at the frame level as a stationary stochastic process with an autocorrelation function of exponentially fast decay and a marginal frame size distribution of approximately Gamma form. The video traffic from the MCU to the clients is again stationary and with exponentially decaying correlations, while the corresponding marginal frame-size PDF has the form of an appropriately weighted sum of Gamma components, the number of terms in the sum always being equal to the number of conferring terminals. The paper discusses methods for correctly matching the parameters of the modeling components to the data and for combining these components into complete traffic models that have been proposed in the literature

Cooperative mobile high-speed and personal area networks for the provision of pervasive e-health services

The present paper studies the performance of a high-speed third-generation (3.5G) networking technology (Enhanced Uplink), in collaboration with well known personal area networks (i.e. Zigbee and Bluetooth) and wireless local area network (WLAN) technology, for delivering pervasive healthcare applications. The association of personal and local area networks along with the 3.5G network is a critical factor for successful development of pervasive e-health services perceived by end-users. In this paper, we propose a methodology for performance assessment based on the joint uplink transmission of voice, real-time video and biomedical data, such us electrocardiogram, vital signals and heart sounds. Various scenarios were concerned for point of care applications in real-time and near-real-time modes and in random locations, where no other system but 3.5G is available. The accomplishment of quality of service (QoS) was explored through the delay and the jitter of the networks' parameters, attributing the joint network system for best performance in the context of the desired e-health services. © 2011 IEEE

Metacognition in Autism Spectrum Disorder: Digital Technologies in Metacognitive Skills Training

Extensive research has been conducted regarding socio-emotional skills training in autism spectrum disorder (ASD). The latest autism research is now beginning to recognize the role of metacognitive deficits in ASD as well as the importance of metacognitive skills training in autism intervention. The purpose of the current review study is to shed light on the role of metacognition in ASD and identify assistive technologies that may compensate for metacognitive deficits in ASD. Specifically, we examine autism through the lens of the models of metacognition developed by (Drigas and Mitsea, 2020;2021). Following these metacognitive models, we identified digital technologies that have the significant potential to train metacognitive skills in people with ASD. These technologies include, among others,  robotics, virtual reality, mobile applications, digital serious games, coding digital games and robots. This review provides evidence that people with autism face important difficulties in almost all metacognitive domains. It also highlights that digital technologies are effective tools for training metacognitive skills in ASD. This study is one of the few studies that deal with autism as a disorder of metacognition and gives pointers for future experimental research regarding intervention strategies with the assistance of technologies