Modelling network memory servers with parallel processors, break-downs and repairs.

This paper presents an analytical method for the performability evaluation of a previously reported network memory server attached to a local area network. To increase the performance and availability of the proposed system, an additional server is added to the system. Such systems are prone to failures. With this in mind, a mathematical model has been developed to analyse the performability of the proposed system with break-downs and repairs. Mean queue lengths and the probability of job losses for the LAN feeding the network memory server is calculated and presented

The aptness of tangible user interfaces for explaining abstract computer network principles

The technological deployment of Tangible User Interfaces (TUI) with their intrinsic ability to interlink the physical and digital domains, have steadily gained interest within the educational sector. As a concrete example of Reality Based Interaction, such digital manipulatives have been successfully implemented in the past years to introduce scientific and engineering concepts at earlier stages throughout the educational cycle. With difference to literature, this research investigates the suitability and effectiveness of implementing a TUI system to enhance the learning experience in a higher education environment. The proposal targets the understanding of advanced computer networking principles by the deployment of an interactive table-top system. Beyond the mere simulation and modelling of networking topologies, the design presents students the ability to directly interact with and visualise the protocol execution, hence augmenting their ability to understand the abstract nature of such algorithms. Following deployment of the proposed innovate prototype within the delivery of a university undergraduate programme, the quantitative effectiveness of this novel methodology will be assessed from both a teaching and learning perspective on its ability to convey the abstract notions of computer network principles

LearnQoS: a learning approach for optimizing QoS over multimedia-based SDNs

As video-based services become an integral part of the end-users’ lives, there is an imminent need for increase in the backhaul capacity and resource management efficiency to enable a highly enhanced multimedia experience to the endusers. The next-generation networking paradigm offers wide advantages over the traditional networks through simplifying the management layer, especially with the adoption of Software Defined Networks (SDN). However, enabling Quality of Service (QoS) provisioning still remains a challenge that needs to be optimized especially for multimedia-based applications. In this paper, we propose LearnQoS, an intelligent QoS management framework for multimedia-based SDNs. LearnQoS employs a policy-based network management (PBNM) to ensure the compliance of QoS requirements and optimizes the operation of PBNM through Reinforcement Learning (RL). The proposed LearnQoS framework is implemented and evaluated under an experimental setup environment and compared with the default SDN operation in terms of PSNR, MOS, throughput and packet loss

On demand multicast routing in wireless sensor networks

The wireless networking environment presents imposing challenges to the study of broadcasting and multicasting problems. Developing an algorithm to optimize communication amongst a group of spatially distributed sensor nodes in a WSN (Wireless Sensor Network) has been met with a number challenges due to the characterization of the sensor node device. These challenges include, but are not limited to: energy, memory, and throughput constraints. The traditional approach to overcome these challenges have emphasised the development of low power electronics, efficient modulation, coding, antenna design etc., it has been recognised that networking techniques can also have a strong impact on the energy efficiency of such systems. A variety of networking based approaches to energy efficiency are possible. One of the well-known approaches is to apply clustering techniques to effectively establish an ordered connection of sensor nodes whilst improving the overall network lifetime. This paper proposes an improved clustering based multicast approach that allows any cluster head to be a multicast source with an unlimited number of subscribers, to optimize group communication in WSNs whilst ensuring sensor nodes do not deprecate rapidly in energy levels. We review several clustering approaches and examine multicast versus broadcast communication in WSNs

Social networks users: fear of missing out in preservice teachers

As mobile computing and smartphones become an integrated part of our lives, the time individuals spend on social networks has significantly increased. Moreover, a link has been established between the uncontrolled use of social networks to the development of undesirable habits and behaviors including addictions. One such behavior, namely, fear of missing out (FOMO) is of particular interest and concern especially because of the widespread use of smartphones and computers, and thereby extensive use of social networks by the younger generation. This study establishes the relationships between FOMO and various social networks in an attempt to identify the problematic use of social media in Turkey and discover variables relevant to FOMO. The main objective of the study is to examine the prevalence of FOMO in preservice teachers. A total number of 363 preservice teachers on various academic courses were employed for the purpose of this study. The design was a survey which utilized a standardized questionnaire on FOMO together with a demographic questionnaire to explore the impact of the usage of smartphones and social networks by preservice teachers. The data were analyzed using descriptive statistics, independent samples t-tests, and analysis of variance (ANOVA). The overall findings of the study showed that the spread of FOMO amongst preservice teachers is at intermediate level. Significant differences were also found between groups based on gender, age, and usage of social networks. Furthermore, data from males were indicative of higher FOMO levels than female preservice teachers and again, under 21s were found to have higher levels of FOMO compared to the other age groups. A significant relationship was reported between being online on social networks throughout the day and active use of social media over seven hours, and FOMO. Furthermore, preservice teachers using Twitter, Instagram, Swarm, or Snapchat have increased levels of FOMO. Implications are discussed within current models

Policy-based QoS management framework for software-defined networks

With the emerging trends of virtualization of cloud computing and big data applications, network management has become a challenging problem for optimizing the network state while satisfying the applications’ Quality of Service (QoS) requirements. This paper proposes a policy-based management framework over Software-Defined Networks (SDN) for QoS provisioning. The proposed approach monitors the QoS parameters of the active flows and dynamically enforces new decisions on the underlying SDN switches to adapt the network state to the current demanded high-level policies. Moreover, the proposed solution makes use of Neural Networks to identify the violating flows causing the network congestion. Upon detection of a policy violation two route management techniques are implemented, such as: rerouting and rate limiting. The proposed framework was implemented and evaluated within an experimental test bed setup. The results indicate that the proposed PBNM-based SDN framework enables QoS provisioning and outperforms the default SDN in terms of throughput, packet loss rate and latency

On the performance, availability and energy consumption modelling of clustered IoT systems

Wireless sensor networks (WSNs) form a large part of the ecosystem of the Internet of Things (IoT), hence they have numerous application domains with varying performance and availability requirements. Limited resources that include processing capability, queue capacity, and available energy in addition to frequent node and link failures degrade the performance and availability of these networks. In an attempt to efficiently utilise the limited resources and to maintain the reliable network with efficient data transmission; it is common to select a clustering approach, where a cluster head is selected among the diverse IoT devices. This study presents the stochastic performance as well as the energy evaluation model for WSNs that have both node and link failures. The model developed considers an integrated performance and availability approach. Various duty cycling schemes within the medium-access control of the WSNs are also considered to incorporate the impact of sleeping/idle states that are presented using analytical modeling. The results presented using the proposed analytical models show the effects of factors such as failures, various queue capacities and system scalability. The analytical results presented are in very good agreement with simulation results and also present an important fact that the proposed models are very useful for identification of thresholds between WSN system characteristics