PWRR Algorithm for Video Streaming Process Using Fog Computing

يُعد بث الفيديو أكثر الوسائط شيوعًا التي يستخدمها الأشخاص على الإنترنت اليوم ويستهلك الكثير من عمليات نقل الإنترنت. يتم استخدام كمية هائلة من استخدام الإنترنت لتدفق الفيديو الذي ينفق ما يقرب من 70٪ من الإنترنت اليوم. ومع ذلك ، توجد قيود على الوسائط التفاعلية ممثلة في زيادة استخدام النطاق الترددي وتأخره ، مثل بث الفيديو المباشر الذي يتطلب الإرسال في الوقت الفعلي. تستخدم تقنيات حوسبة الضباب للتخفيف من حدة هذه المشكلات من خلال توفير استجابة عالية في الوقت الحقيقي وموارد حاسوبية قريبة من العميل عند حدود الشبكة ، والضباب عبارة عن طبقة وسيطة بين السحابة والمستخدم النهائي ، تقترح هذه الورقة خوارزمية Weighted Round Robin (PWRR) ذات الأولوية لجدولة عمليات التدفق في بنية الضباب لإعطاء استباقية لبث طلب فيديو مباشر لتقديم وقت استجابة أقل للغاية وتواصل في الوقت الفعلي. تعرض نتائج تجربة PWRR في البنية المقترحة لتدفق الفيديوعبر حوسبة الضباب ، تقليل وقت الاستجابة ونوعية جيدة لطلبات الفيديو المباشرة التي تم تحقيقها مع تغييرات النطاق الترددي بالاضافة الى تلبية كل طلبات الاخرى للزبائن في نفس الوقت.       The most popular medium that being used by people on the internet nowadays is video streaming.  Nevertheless, streaming a video consumes much of the internet traffics. The massive quantity of internet usage goes for video streaming that disburses nearly 70% of the internet. Some constraints of interactive media might be detached; such as augmented bandwidth usage and lateness. The need for real-time transmission of video streaming while live leads to employing of Fog computing technologies which is an intermediary layer between the cloud and end user. The latter technology has been introduced to alleviate those problems by providing high real-time response and computational resources near to the client at the network boundary. The present research paper proposes priority weighted round robin (PWRR) algorithm for streaming operations scheduling in the fog architecture. This will give preemptive for streaming live video request to be delivered in a very short response time and real-time communication. The results of experimenting the PWRR in the proposed architecture display a minimize latency and good quality of live video requests which has been achieved with bandwidth changes as well as meeting all other clients requests at the same tim

Past, Present, and Future of EEG-Based BCI Applications

An electroencephalography (EEG)-based brain–computer interface (BCI) is a system that provides a pathway between the brain and external devices by interpreting EEG. EEG-based BCI applications have initially been developed for medical purposes, with the aim of facilitating the return of patients to normal life. In addition to the initial aim, EEG-based BCI applications have also gained increasing significance in the non-medical domain, improving the life of healthy people, for instance, by making it more efficient, collaborative and helping develop themselves. The objective of this review is to give a systematic overview of the literature on EEG-based BCI applications from the period of 2009 until 2019. The systematic literature review has been prepared based on three databases PubMed, Web of Science and Scopus. This review was conducted following the PRISMA model. In this review, 202 publications were selected based on specific eligibility criteria. The distribution of the research between the medical and non-medical domain has been analyzed and further categorized into fields of research within the reviewed domains. In this review, the equipment used for gathering EEG data and signal processing methods have also been reviewed. Additionally, current challenges in the field and possibilities for the future have been analyzed

Edge/Fog Computing Technologies for IoT Infrastructure

The prevalence of smart devices and cloud computing has led to an explosion in the amount of data generated by IoT devices. Moreover, emerging IoT applications, such as augmented and virtual reality (AR/VR), intelligent transportation systems, and smart factories require ultra-low latency for data communication and processing. Fog/edge computing is a new computing paradigm where fully distributed fog/edge nodes located nearby end devices provide computing resources. By analyzing, filtering, and processing at local fog/edge resources instead of transferring tremendous data to the centralized cloud servers, fog/edge computing can reduce the processing delay and network traffic significantly. With these advantages, fog/edge computing is expected to be one of the key enabling technologies for building the IoT infrastructure. Aiming to explore the recent research and development on fog/edge computing technologies for building an IoT infrastructure, this book collected 10 articles. The selected articles cover diverse topics such as resource management, service provisioning, task offloading and scheduling, container orchestration, and security on edge/fog computing infrastructure, which can help to grasp recent trends, as well as state-of-the-art algorithms of fog/edge computing technologies