The Glasgow raspberry pi cloud: a scale model for cloud computing infrastructures

Data Centers (DC) used to support Cloud services often consist of tens of thousands of networked machines under a single roof. The significant capital outlay required to replicate such infrastructures constitutes a major obstacle to practical implementation and evaluation of research in this domain. Currently, most research into Cloud computing relies on either limited software simulation, or the use of a testbed environments with a handful of machines. The recent introduction of the Raspberry Pi, a low-cost, low-power single-board computer, has made the construction of a miniature Cloud DCs more affordable. In this paper, we present the Glasgow Raspberry Pi Cloud (PiCloud), a scale model of a DC composed of clusters of Raspberry Pi devices. The PiCloud emulates every layer of a Cloud stack, ranging from resource virtualisation to network behaviour, providing a full-featured Cloud Computing research and educational environment

Introduction to the Computation Offloading from Mobile Devices to the Edge of Mobile Network

This paper introduces the concept of Small Cell Cloud (SCC) composed of multiple Cloud-enabled Small Cells (CeSCs), which provide radio connection for mobile User Equipment (UE) such as smart-phones or wearables such as smart glasses. Moreover, CeSCs host computations offloaded from UEs in a way similar to centralized cloud, yet different in its proximity to users. Proposed client-server architecture of SCC con-veys mechanisms for moving offloaded computations from the UEs to CeSCs. Real-life implementation of the SCC architecture relies on custom-developed Of-floading Framework which is responsible for low-level communication between the UE and the SCC. The Of-floading Framework is accompanied by an Augmented Reality (AR) app, which employs intensive computa-tions for discovery of places of interest. Such app is latency-sensitive, a criterion which makes computation offloading beneficial due to its ability to decrease la-tency. The combination of the O˜oading Framework and the AR app makes up an SCC testbed used for fur-ther performance evaluation. Numerous measurements are carried out to examine the impact of various pa-rameters. Based on Proof-of-concept implementation and thorough measurements, it has been revealed that computation offloading can decrease overall latency as much as to 47 % and energy consumption on the UE side to 56

Will SDN be part of 5G?

For many, this is no longer a valid question and the case is considered settled with SDN/NFV (Software Defined Networking/Network Function Virtualization) providing the inevitable innovation enablers solving many outstanding management issues regarding 5G. However, given the monumental task of softwarization of radio access network (RAN) while 5G is just around the corner and some companies have started unveiling their 5G equipment already, the concern is very realistic that we may only see some point solutions involving SDN technology instead of a fully SDN-enabled RAN. This survey paper identifies all important obstacles in the way and looks at the state of the art of the relevant solutions. This survey is different from the previous surveys on SDN-based RAN as it focuses on the salient problems and discusses solutions proposed within and outside SDN literature. Our main focus is on fronthaul, backward compatibility, supposedly disruptive nature of SDN deployment, business cases and monetization of SDN related upgrades, latency of general purpose processors (GPP), and additional security vulnerabilities, softwarization brings along to the RAN. We have also provided a summary of the architectural developments in SDN-based RAN landscape as not all work can be covered under the focused issues. This paper provides a comprehensive survey on the state of the art of SDN-based RAN and clearly points out the gaps in the technology.Comment: 33 pages, 10 figure

Running Genetic Algorithms in the Edge: A First Analysis

Nowadays, the volume of data produced by different kinds of devices is continuously growing, making even more difficult to solve the many optimization problems that impact directly on our living quality. For instance, Cisco projected that by 2019 the volume of data will reach 507.5 zettabytes per year, and the cloud traffic will quadruple. This is not sustainable in the long term, so it is a need to move part of the intelligence from the cloud to a highly decentralized computing model. Considering this, we propose a ubiquitous intelligent system which is composed by different kinds of endpoint devices such as smartphones, tablets, routers, wearables, and any other CPU powered device. We want to use this to solve tasks useful for smart cities. In this paper, we analyze if these devices are suitable for this purpose and how we have to adapt the optimization algorithms to be efficient using heterogeneous hardware. To do this, we perform a set of experiments in which we measure the speed, memory usage, and battery consumption of these devices for a set of binary and combinatorial problems. Our conclusions reveal the strong and weak features of each device to run future algorihms in the border of the cyber-physical system.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. This research has been partially funded by the Spanish MINECO and FEDER projects TIN2014-57341-R (http://moveon.lcc.uma.es), TIN2016-81766-REDT (http://cirti.es), TIN2017-88213-R (http://6city.lcc.uma.es), the Ministry of Education of Spain (FPU16/02595

Graphene etch mask for silicon

In this thesis, an alternative future use for graphene will be explored. Graphene, a popular two-dimensional material of remarkable electrical properties, has been thought to be a successor to current day microelectronic materials. With the many challenges posed by the manufacture of conventional devices from graphene, other adaptations for its properties are sought in the work that follows. Chiefly, its mechanical and chemical strength as an etch mask for silicon is tested.We attempt to present the progress toward a working model of a graphene etch mask. The influence of the mask geometry, etch method, etch conditions, substrate quality and other factors will be explored to present a clear understanding of methodology and requirements for carrying out the process. Along the way, other aspects of the project such as the growth and transfer of graphene, which are not the focus but extremely crucial to the results, will be elucidated as required. Possible future directions will also be presented to provide a notion of where the idea can head

Microservices Architecture Enables DevOps: an Experience Report on Migration to a Cloud-Native Architecture

This article reports on experiences and lessons learned during incremental migration and architectural refactoring of a commercial mobile back end as a service to microservices architecture. It explains how the researchers adopted DevOps and how this facilitated a smooth migration

End-to-End Privacy for Open Big Data Markets

The idea of an open data market envisions the creation of a data trading model to facilitate exchange of data between different parties in the Internet of Things (IoT) domain. The data collected by IoT products and solutions are expected to be traded in these markets. Data owners will collect data using IoT products and solutions. Data consumers who are interested will negotiate with the data owners to get access to such data. Data captured by IoT products will allow data consumers to further understand the preferences and behaviours of data owners and to generate additional business value using different techniques ranging from waste reduction to personalized service offerings. In open data markets, data consumers will be able to give back part of the additional value generated to the data owners. However, privacy becomes a significant issue when data that can be used to derive extremely personal information is being traded. This paper discusses why privacy matters in the IoT domain in general and especially in open data markets and surveys existing privacy-preserving strategies and design techniques that can be used to facilitate end to end privacy for open data markets. We also highlight some of the major research challenges that need to be address in order to make the vision of open data markets a reality through ensuring the privacy of stakeholders.Comment: Accepted to be published in IEEE Cloud Computing Magazine: Special Issue Cloud Computing and the La