The aim of this study is to investigate the relationship between no mobile phobia (nomophobia) which is defined as a modern fear of being unable to communicate through the mobile phone, and Fear of Missing Out (FOMO) which is known to be related with the problematic relationship with Social Networking Sites (SNSs), and play a critical role in the increased use of Social Networking Sites (SNS). The data were collected from a convenient sample of 538 university students via Nomophobia (NMP-Q) and FOMO Scales, The results show that a positive moderate level of relationship was found between Nomophobia and FOMO levels. The findings showed that FOMO level of university students predicts 41% of the total variance at the Nomophobia level. That is, when FOMO level increases, students’ nomophobia level can be predicted from data depicting the increase.

Cooperative applications for VANETs will require seamless communication between vehicle to infrastructure and vehicle to vehicle. IEEE 802.11p has been developed to facilitate this effort. However, in order to have seamless communication for these applications, it is necessary to look at handover as vehicles move between roadside units. Traditional models of handover used in normal mobile environments are unable to cope with the high velocity of the vehicle and the relatively small area of coverage with regard to vehicular environments. The Y-Comm framework has yielded techniques to calculate the time before vertical handover and the network dwell time for any given network topology. Furthermore, by knowing these two parameters, it is also possible to improve channel allocation and resource management in network infrastructure such as base stations, relays, and so on. In this article we explain our overall approach by describing the VANET Testbed and show that in vehicular environments it is necessary to consider a new handover model that is based on a probabilistic rather than a fixed coverage approach. Finally, we show a new performance model for proactive handover, which is then compared with traditional approaches.

A Wireless Sensor Network (WSN) is composed of distributed sensors with limited processing capabilities and energy restrictions. These unique attributes pose new challenges amongst which prolonging the WSN lifetime is one of the most important. Challenges are often tackled by a code-and-fix process that relies on low-level hardware and software information. Recently, the need of abstracting an implementation view into an architectural design is getting more realized. A clear separation of concerns is needed since hardware and software aspects are locked and tied down to specific types of nodes, hampering the possibility of reuse across projects and organizations. This means that exploiting the right level of abstraction, and keeping explicit (and separated) software and hardware architectural details will surely ease developers' job. In this paper we propose a modeling framework that allows developers to model separately the software architecture of the WSN, the low-level hardware specification of the WSN nodes and the physical environment where nodes are deployed in. The framework can use these models to generate executable code for analysis purposes. In this paper we focus on energy consumption analysis.

In recent years, there has been a huge trend towards running network intensive applications, such as Internet servers and Cloud-based service in virtual environment, where multiple virtual machines (VMs) running on the same machine share the machine's physical and network resources. In such environment, the virtual machine monitor (VMM) virtualizes the machine's resources in terms of CPU, memory, storage, network and I/O devices to allow multiple operating systems running in different VMs to operate and access the network concurrently. A key feature of virtualization is live migration (LM) that allows transfer of virtual machine from one physical server to another without interrupting the services running in virtual machine. Live migration facilitates workload balancing, fault tolerance, online system maintenance, consolidation of virtual machines etc. However, live migration is still in an early stage of implementation and its security is yet to be evaluated. The security concern of live migration is a major factor for its adoption by the IT industry. Therefore, this paper uses the X.805 security standard to investigate attacks on live virtual machine migration. The analysis highlights the main source of threats and suggests approaches to tackle them. The paper also surveys and compares different proposals in the literature to secure the live migration.

This paper investigates double-threshold-based energy detector for cooperative spectrum sensing mechanisms in cognitive wireless radio networks. We first propose a hybrid double-threshold-based energy detector (HDTED) to improve the sensing performance at secondary users (SUs) by exploiting both the local binary/energy decisions and global binary decisions feedback from the fusion center (FC). Significantly, we derive closed-form expressions and bounds for the probabilities of missed detection and false alarm considering a practical scenario where all channel links suffer from Rayleigh fading and background noise. The derived expressions not only show the improved performance achieved with the HDTED scheme but also enable us to analyze the impacts of the number of the SUs and the fading channels on the cooperative spectrum sensing performance. Furthermore, based on the derived bounds, we propose an optimal SU selection algorithm for forwarding the local decisions to the FC, which helps reduce the number of forwarding bits for a lower-complexity signaling. Finally, numerical results are provided to demonstrate the validity of the analytical findings.