A Case Study of Edge Computing Implementations: Multi-access Edge Computing, Fog Computing and Cloudlet

With the explosive growth of intelligent and mobile devices, the current centralized cloud computing paradigm is encountering difficult challenges. Since the primary requirements have shifted towards implementing real-time response and supporting context awareness and mobility, there is an urgent need to bring resources and functions of centralized clouds to the edge of networks, which has led to the emergence of the edge computing paradigm. Edge computing increases the responsibilities of network edges by hosting computation and services, therefore enhancing performances and improving quality of experience (QoE). Fog computing, multi-access edge computing (MEC), and cloudlet are three typical and promising implementations of edge computing. Fog computing aims to build a system that enables cloud-to-thing service connectivity and works in concert with clouds, MEC is seen as a key technology of the fifth generation (5G) system, and Cloudlet is a micro-data center deployed in close proximity. In terms of deployment scenarios, Fog computing focuses on the Internet of Things (IoT), MEC mainly provides mobile RAN application solutions for 5G systems, and cloudlet offloads computing power at the network edge. In this paper, we present a comprehensive case study on these three edge computing implementations, including their architectures, differences, and their respective application scenario in IoT, 5G wireless systems, and smart edge. We discuss the requirements, benefits, and mechanisms of typical co-deployment cases for each paradigm and identify challenges and future directions in edge computing

Airborne Directional Networking: Topology Control Protocol Design

This research identifies and evaluates the impact of several architectural design choices in relation to airborne networking in contested environments related to autonomous topology control. Using simulation, we evaluate topology reconfiguration effectiveness using classical performance metrics for different point-to-point communication architectures. Our attention is focused on the design choices which have the greatest impact on reliability, scalability, and performance. In this work, we discuss the impact of several practical considerations of airborne networking in contested environments related to autonomous topology control modeling. Using simulation, we derive multiple classical performance metrics to evaluate topology reconfiguration effectiveness for different point-to-point communication architecture attributes for the purpose of qualifying protocol design elements

Simulation-Based Learning via Cisco Packet Tracer to Enhance the Teaching of Computer Networks

Teaching and learning computer networks is a crucial part of a computing undergraduates’ education. However, it is an abstract topic with theory that can be challenging for students to comprehend. Simulation-based learning can be used as a teaching tool to enhance networking-based lecture topics and help students more easily understand and visualise how it really works in a safe, user-friendly environment. One such simulation tool, Cisco Packet Tracer, can be used to good effect, and this paper reports on the practical implementation of the tool as identified in existing literature. Additionally, this paper discusses how Packet Tracer was utilised as part of a UK based first year undergraduate module ’Computers and Security’, and details the content of nine practical sessions, whilst also identifying the main benefits and challenges of their implementation from a practitioner’s perspective. It was found that while Packet Tracer can be an additional benefit to augment the teaching of networking concepts, there are limitations and challenges which educators must be aware of if implementing the tool. The paper therefore concludes with providing recommendations which should help educators and curriculum designers in creating and delivering more effective and interactive networking sessions

IEEE 802.15.4 MAC Protocol Study and Improvement

IEEE 802.15.4 is a standard used for low rate personal area networks (PANs). It offers device level connectivity in applications with limited ower and relaxed throughput requirements. Devices with IEEE 802.15.4 technology can be used in many potential applications, such as home networking, industry/environments monitoring, healthcare equipments, etc, due to its extremely low power features. Although the superframe beacons play the key role in synchronizing channel access in IEEE 802.15.4, they are sources for energy inefficiency. This research focuses on exploring how to optimize the beacons, and designing novel schemes to distribute the information that are supposed to be delivered to a subset of PAN devices. In this work, an acknowledgement based scheme is proposed to reduce the energy consumption in the distribution of guaranteed time slot (GTS) descriptors. Based on the observation that the superframe beacon frame has global impact on all PAN devices, an energy-efficient channel reservation scheme is presented to deliver the information (GTS descriptors and pending addresses). In addition, the problem of channel underutilization is studied in the contention free period. To address the problem, a new GTS allocation scheme is proposed to improve the bandwidth utilization

A Virtual University Infrastructure For Orthopaedic Surgical Training With Integrated Simulation

This thesis pivots around the fulcrum of surgical, educational and technological factors. Whilst there is no single conclusion drawn, it is a multidisciplinary thesis exploring the juxtaposition of different academic domains that have a significant influence upon each other. The relationship centres on the engineering and computer science factors in learning technologies for surgery. Following a brief introduction to previous efforts developing surgical simulation, this thesis considers education and learning in orthopaedics, the design and building of a simulator for shoulder surgery. The thesis considers the assessment of such tools and embedding into a virtual learning environment. It explains how the performed experiments clarified issues and their actual significance. This leads to discussion of the work and conclusions are drawn regarding the progress of integration of distributed simulation within the healthcare environment, suggesting how future work can proceed

Realtime reservoir characterization and beyond: cyber-infrastructure tools and technologies

The advent of the digital oil _x000C_eld and rapidly decreasing cost of computing creates opportunities as well as challenges in simulation based reservoir studies, in particular, real-time reservoir characterization and optimization. One challenge our e_x000B_orts are directed toward is the use of real-time production data to perform live reservoir characterization using high throughput, high performance computing environments. To that end we developed the required tools of parallel reservoir simulator, parallel ensemble Kalman _x000C_lter and a scalable work ow manager. When using this collection of tools, a reservoir modeler is able to perform large scale reservoir management studies in short periods of time. This includes studies with thousands of models that are individually complex and large, involving millions of degrees of freedom. Using parallel processing, we are able to solve these models much faster than we otherwise would on a single, serial machine. This motivated the development of a fast parallel reservoir simulator. Furthermore, distributing those simulations across resources leads to a smaller total time to completion by making use of distributed processing. This allows the development of a scalable high throughput work ow manager. Finally, with thousands of models, each with millions of degrees of freedom, we end up with a super uity of model parameters. This translates directly to billions of degrees of freedom in the reservoir study. To be able to use the ensemble Kalman _x000C_lter on these models, we needed to develop a parallel implementation of the ensemble Kalman _x000C_lter. This thesis discusses the enabling tools and technologies developed to address a speci _x000C_c problem: how to accurately characterize reservoirs, using large numbers of complex detailed models. For these characterization studies to be helpful in making production decisions, the time to solution must be feasible. To that end, our work is focused on developing and extending these tools, and optimizing their performance