About: Cloud computing is a research topic. Over the lifetime, 156433 publications have been published within this topic receiving 1963602 citations. The topic is also known as: cloud platform & cloud.
TL;DR: Results revealed that DSOS outperforms Particle Swarm Optimization which is one of the most popular heuristic optimization techniques used for task scheduling problems and performs significantly better than PSO for large search spaces.
TL;DR: A quick introduction to cloud storage is given, which covers the key technologies in Cloud Computing and Cloud Storage, several different types of clouds services, and describes the advantages and challenges of Cloud Storage after the introduction of the Cloud Storage reference model.
Abstract: As an emerging technology and business paradigm, Cloud Computing has taken commercial computing by storm. Cloud computing platforms provide easy access to a company’s high-performance computing and storage infrastructure through web services. With cloud computing, the aim is to hide the complexity of IT infrastructure management from its users. At the same time, cloud computing platforms provide massive scalability, 99.999% reliability, high performance, and specifiable configurability. These capabilities are provided at relatively low costs compared to dedicated infrastructures. This article gives a quick introduction to cloud storage. It covers the key technologies in Cloud Computing and Cloud Storage, several different types of clouds services, and describes the advantages and challenges of Cloud Storage after the introduction of the Cloud Storage reference model.
TL;DR: Numerical results demonstrate that the optimized MEC system utilizing cooperation has significant performance improvement over systems without cooperation.
Abstract: This paper studies a mobile edge computing (MEC) system in which two mobile devices are energized by the wireless power transfer (WPT) from an access point (AP) and they can offload part or all of their computation-intensive latency-critical tasks to the AP connected with an MEC server or an edge cloud. This harvest-then-offload protocol operates in an optimized time-division manner. To overcome the doubly near-far effect for the farther mobile device, cooperative communications in the form of relaying via the nearer mobile device is considered for offloading. Our aim is to minimize the AP’s total transmit energy subject to the constraints of the computational tasks. We illustrate that the optimization is equivalent to a min–max problem, which can be optimally solved by a two-phase method. The first phase obtains the optimal offloading decisions by solving a sum-energy-saving maximization problem for given an energy transmit power. In the second phase, the optimal minimum energy transmit power is obtained by a bisection search method. Numerical results demonstrate that the optimized MEC system utilizing cooperation has significant performance improvement over systems without cooperation.
TL;DR: IoT and cloud computing are researched and addressed and cloud-compatible problems and computing techniques are addressed to promote the stable transition of IoT programs to the cloud.
Abstract: With the exponential growth of the Industrial Internet of Things (IIoT), multiple outlets are constantly producing a vast volume of data. It is unwise to locally store all the raw data in the IIoT devices since the energy and storage spaces of the end devices are strictly constrained. self-organization and short-range Internet of Things (IoT) networking also support outsourced data and cloud computing, independent of the distinctive resource constraint properties. For the remainder of the findings, there is a sequence of unfamiliar safeguards for IoT and cloud integration problems. The delivery of cloud computing is highly efficient, storage is becoming more and more current, and some groups are now altering their data from in house records Cloud Computing Vendors' hubs. Intensive IoT applications for workloads and data are subject to challenges while utilizing cloud computing tools. In this report, we research IoT and cloud computing and address cloud-compatible problems and computing techniques to promote the stable transition of IoT programs to the cloud.
TL;DR: In this paper, the authors describe the design, implementation and evaluation of OSA, a novel optical switching architecture for DCNs, which dynamically changes its topology and link capacities, thereby achieving unprecedented flexibility to adapt to dynamic traffic patterns.
Abstract: Data center networks (DCNs) form the backbone infrastructure of many large-scale enterprise applications as well as emerging cloud computing providers. This paper describes the design, implementation and evaluation of OSA, a novel Optical Switching Architecture for DCNs. Leveraging runtime reconfigurable optical devices, OSA dynamically changes its topology and link capacities, thereby achieving unprecedented flexibility to adapt to dynamic traffic patterns. Extensive analytical simulations using both real and synthetic traffic patterns demonstrate that OSA can deliver high bisection bandwidth (60%-100% of the non-blocking architecture). Implementation and evaluation of a small-scale functional prototype further demonstrate the feasibility of OSA.