Resource allocation for fog computing based on software-defined networks

With the emergence of cloud computing as a processing backbone for internet of thing (IoT), fog computing has been proposed as a solution for delay-sensitive applications. According to fog computing, this is done by placing computing servers near IoT. IoT networks are inherently very dynamic, and their topology and resources may be changed drastically in a short period. So, using the traditional networking paradigm to build their communication backbone, may lower network performance and higher network configuration convergence latency. So, it seems to be more beneficial to employ a software-defined network paradigm to implement their communication network. In software-defined networking (SDN), separating the network’s control and data forwarding plane makes it possible to manage the network in a centralized way. Managing a network using a centralized controller can make it more flexible and agile in response to any possible network topology and state changes. This paper presents a software-defined fog platform to host real-time applications in IoT. The effectiveness of the mechanism has been evaluated by conducting a series of simulations. The results of the simulations show that the proposed mechanism is able to find near to optimal solutions in a very lower execution time compared to the brute force method

A Genetic Based Resource Management Algorithm Considering Energy Efficiency in Cloud Computing Systems

Cloud computing is a result of the continuing progress made in the areas of hardware, technologies related to the Internet, distributed computing and automated management. The Increasing demand has led to an increase in services resulting in the establishment of large-scale computing and data centers, in addition to high operating costs and huge amounts of electrical power consumption. Insufficient cooling systems and inefficient, causing overheating sources, shortening the life of the machine and too much carbon dioxide is produced. In this paper, we aim to improve system performance; Cloud Computing based on a decrease in migration of among virtual machines (VM), and reduce energy consumption to be able to manage resources to achieve optimal energy efficiency. For this reason, various techniques such as genetic algorithms (GAs), virtual machine migration and ways Dynamic voltage and frequency scaling (DVFS), and resize virtual machines to reduce energy consumption and fault tolerance are used. The main purpose of this article, the allocation of resources with the aim of reducing energy consumption in cloud computing. The results show that reduced energy consumption and hold down the rate of virtual machines breach of contract, reduces migration as well

Vehicular Networks: A Survey on Architecture, Communication Technologies and Applications

The Intelligent Transportation System (ITS) provides wireless and mobile communication between vehicles and infrastructure to improve the safety of transportation and make the journey more enjoyable. This system consists of many fixed and mobile nodes (Vehicles, Trains, Vessels, Air planes), Wireless and Wired Telecommunication Technologies to exchange information between mobile nodes or between mobile nodes and fixed stations. The most common transportation tools are cars. Vehicular Ad-hoc Networks as an Application of Mobile Ad-hoc Networks and one of the subsets of Intelligent Transportation System provides wireless Ad-hoc communication between vehicles. VANET is a mobile wireless technology which is designed to improve safety of transportation with exchanging real time data between vehicles and providing different services to the users. It has special characteristics like high mobility and provides a broad range of services to the users, so it has been emerged as one of the research interests in the field of computer and telecommunication networks. In This paper we present different aspects of ITS and VANET to help the researchers to understand the Architecture, Communication Technologies and Applications of these networks

Software defined fog platform

In recent years, the number of end users connected to the internet of things (IoT) has increased, and we have witnessed the emergence of the cloud computing paradigm. These users utilize network resources to meet their quality of service (QoS) requirements, but traditional networks are not configured to backing maximum of scalability, real-time data transfer, and dynamism, resulting in numerous challenges. This research presents a new platform of IoT architecture that adds the benefits of two new technologies: software-defined networking and fog paradigm. Software-defined networking (SDN) refers to a centralized control layer of the network that enables sophisticated methods for traffic control and resource allocation. So, fog paradigm allows for data to be analyzed and managed at the edge of the network, making it suitable for tasks that require low and predictable delay. Thus, this research provides an in-depth view of the platform organize and performance of its base ingredients, as well as the potential uses of the suggested platform in various applications

Improving Quality of Service Routing in Mobile Ad Hoc Networks Using OLSR

Mobile ad hoc networks (MANET) are constructed by mobile nodes without access point. Since MANET has certain constraints, including power shortages, an unstable wireless environment and node mobility, more power-efficient and reliable routing protocols are needed. The OLSR protocol is an optimization of the classical link state algorithm. OLSR introduces an interesting concept, the multipoint relays (MPRs), to mitigate the message overhead during the flooding process. Although very efficient by many points, it suffers from the drawbacks of not taking into account QoS metrics such as delay or bandwidth. To overcome this pitfall, some QOLSR solutions have been designed. IN this paper, we introduce an algorithm for MPRs selection based on Battery Capacity and Link Stability. Simulation results show that our proposed protocol is able to enhance throughput and improve end-to-end delay

Un nuevo algoritmo para el filtrado redundante de datos en redes integradas WSN y RFID

Las redes de sensores inalámbricos (WSN) y la identificación por radiofrecuencia (RFID) son tecnologías básicas que se emplean en entornos dinámicos descentralizados. En la red híbrida formada mediante la integración de RFID y WSN, los datos RFID se pueden utilizar aplicando protocolos WSN para comunicaciones de múltiples saltos. Sin embargo, los datos RFID contienen una duplicación excesiva, lo que aumenta el retraso temporal y el consumo de energía, lo que da como resultado un desperdicio de diferentes recursos. Existen cuatro arquitecturas de integración RFID-WSN populares: topología jerárquica RFID-sensor, topología de red RFID-sensor, topología de nodos de lectores-sensores y topología mixta. En este artículo, proponemos un nuevo plan para una red integrada WSN-RFID. Toda la red se divide en clústeres y se emplea el algoritmo de enrutamiento jerárquico de clústeres para enviar datos desde los nodos principales a la estación base. Además, proponemos dos algoritmos para superar los datos redundantes en la red híbrida. Nuestros resultados de simulación demuestran que el método propuesto reduce los datos redundantes y el tiempo de procesamiento en comparación con los métodos existentes