Analysis of a trunk reservation policy in the framework of fog computing

We analyze in this paper a system composed of two data centers with limited capacity in terms of servers. When one request for a single server is blocked at the first data center, this request is forwarded to the second one. To protect the single server requests originally assigned to the second data center, a trunk reservation policy is introduced (i.e., a redirected request is accepted only if there is a sufficient number of free servers at the second data center). After rescaling the system by assuming that there are many servers in both data centers and high request arrival rates, we are led to analyze a random walk in the quarter plane, which has the particularity of having non constant reflecting conditions on one boundary of the quarter plane. Contrary to usual reflected random walks, to compute the stationary distribution of the presented random walk, we have to determine three unknown functions, one polynomial and two infinite generating functions. We show that the coefficients of the polynomial are solutions to a linear system. After solving this linear system, we are able to compute the two other unknown functions and the blocking probabilities at both data centers. Numerical experiments are eventually performed to estimate the gain achieved by the trunk reservation policy

A Taxonomy for Management and Optimization of Multiple Resources in Edge Computing

Edge computing is promoted to meet increasing performance needs of data-driven services using computational and storage resources close to the end devices, at the edge of the current network. To achieve higher performance in this new paradigm one has to consider how to combine the efficiency of resource usage at all three layers of architecture: end devices, edge devices, and the cloud. While cloud capacity is elastically extendable, end devices and edge devices are to various degrees resource-constrained. Hence, an efficient resource management is essential to make edge computing a reality. In this work, we first present terminology and architectures to characterize current works within the field of edge computing. Then, we review a wide range of recent articles and categorize relevant aspects in terms of 4 perspectives: resource type, resource management objective, resource location, and resource use. This taxonomy and the ensuing analysis is used to identify some gaps in the existing research. Among several research gaps, we found that research is less prevalent on data, storage, and energy as a resource, and less extensive towards the estimation, discovery and sharing objectives. As for resource types, the most well-studied resources are computation and communication resources. Our analysis shows that resource management at the edge requires a deeper understanding of how methods applied at different levels and geared towards different resource types interact. Specifically, the impact of mobility and collaboration schemes requiring incentives are expected to be different in edge architectures compared to the classic cloud solutions. Finally, we find that fewer works are dedicated to the study of non-functional properties or to quantifying the footprint of resource management techniques, including edge-specific means of migrating data and services.Comment: Accepted in the Special Issue Mobile Edge Computing of the Wireless Communications and Mobile Computing journa

FOG-орієнтована інтелектуальна мережа для IoT-керованих розумних домівок

Темою магістерської дисертації є дослідження можливостей підвищення функціональності FOG-орієнтованої інтелектуальної мережі для IoT-керованих розумних домівок. Робота містить 75 сторінок, зокрема 11 ілюстрацій, 2 таблиці та 24 джерела інформації. Тема магістерської дисертації є актуальною, так як через зростаючі вимоги кінцевого користувача до якості передачі інформації провайдери телекомунікаційних послуг змушені приділяти велику увагу підвищенню надійності мереж. Мета магістерської роботи полягає в пошуку балансу в продуктивності пристроїв у локальній мережі та хмарі, зменшуючи при цьому передачу даних до хмари. Об’єктом дослідження є мережа змодельована як непрямий графік, що представляє FOG вузли у вигляді сітчастої мережі При виконанні роботи застосовувалося моделювання у пакеті програмного забезпечення Matlab 2018b для встановлення FOG вузлів з різними можливостями, отже, FOG вузли будуть відрізнятися за рівнем обслуговування. У дисертації була запропонована методика координації між окремими FOG вузлами для ефективного обходження підозрілих/скомпрометованих FOG вузлів в FOG-орієнтованій інтелектуальній мережі для IoT-керованих розумних домівок.The topic of the master's dissertation is the study of the possibilities of improving the functionality of FOG-oriented intelligent network for IoT-controlled smart homes. The work contains 75 pages, including 11 illustrations, 2 tables and 24 sources of information. The topic of the master's dissertation is relevant, as due to the growing demands of the end user to the quality of information transmission, telecommunications service providers are forced to pay much attention to improving the reliability of networks. The purpose of the master's thesis is to find a balance in the performance of devices in the local network and the cloud, while reducing data transmission to the cloud. The object of study is a network modeled as an indirect graph, representing FOG nodes in the form of a network The work used modeling in the Matlab 2018b software package to install FOG nodes with different capabilities, therefore, FOG nodes will differ in the level of service. In the dissertation, the technique of coordination between separate FOG nodes for effective handling of suspicious / compromised FOG nodes in FOG-oriented intelligent network for IoT-controlled smart homes was offered

Fog Computing

Everything that is not a computer, in the traditional sense, is being connected to the Internet. These devices are also referred to as the Internet of Things and they are pressuring the current network infrastructure. Not all devices are intensive data producers and part of them can be used beyond their original intent by sharing their computational resources. The combination of those two factors can be used either to perform insight over the data closer where is originated or extend into new services by making available computational resources, but not exclusively, at the edge of the network. Fog computing is a new computational paradigm that provides those devices a new form of cloud at a closer distance where IoT and other devices with connectivity capabilities can offload computation. In this dissertation, we have explored the fog computing paradigm, and also comparing with other paradigms, namely cloud, and edge computing. Then, we propose a novel architecture that can be used to form or be part of this new paradigm. The implementation was tested on two types of applications. The first application had the main objective of demonstrating the correctness of the implementation while the other application, had the goal of validating the characteristics of fog computing.Tudo o que não é um computador, no sentido tradicional, está sendo conectado à Internet. Esses dispositivos também são chamados de Internet das Coisas e estão pressionando a infraestrutura de rede atual. Nem todos os dispositivos são produtores intensivos de dados e parte deles pode ser usada além de sua intenção original, compartilhando seus recursos computacionais. A combinação desses dois fatores pode ser usada para realizar processamento dos dados mais próximos de onde são originados ou estender para a criação de novos serviços, disponibilizando recursos computacionais periféricos à rede. Fog computing é um novo paradigma computacional que fornece a esses dispositivos uma nova forma de nuvem a uma distância mais próxima, onde “Things” e outros dispositivos com recursos de conectividade possam delegar processamento. Nesta dissertação, exploramos fog computing e também comparamos com outros paradigmas, nomeadamente cloud e edge computing. Em seguida, propomos uma nova arquitetura que pode ser usada para formar ou fazer parte desse novo paradigma. A implementação foi testada em dois tipos de aplicativos. A primeira aplicação teve o objetivo principal de demonstrar a correção da implementação, enquanto a outra aplicação, teve como objetivo validar as características de fog computing

Analysis of an offloading scheme for data centers in the framework of fog computing

International audienceIn the context of fog computing, we consider a simple case when data centersinstalled at the edge of the network are backed up by a central (bigger) datacenter. The system considered precisely comprises two data centers in parallel.We assume that if a request arrives at an overloaded data center, it isforwarded to the other data center with a given probability. Both data centersare assumed to have a large number of servers (rescaling of the system) andthat traffic to one of them is causing saturation so that the other data centermay help to cope with this saturation regime by reducing the rejection ofrequests. Our aim here is to qualitatively estimate the gain achieved by thecollaboration of the two data centers. After proving some convergence results,related to the scaling limits of loss systems, for the process describing thenumber of free servers at both data centers, we show that the performance ofthe system can be expressed in terms of the invariant distribution of a randomwalk in the quarter plane. By using and developing existing results in thetechnical literature, explicit formulas for the blocking rates of such a systemare derived