Topic
Cloud computing
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.
Papers published on a yearly basis
1 / 3
Papers
1 Dec 2012
TL;DR: How Internet of Things and Cloud computing can work together can address the Big Data issues is described and a prototype model for providing sensing as a service on cloud is proposed.
Abstract: Internet of Things (IoT) is a concept that envisions all objects around us as part of internet. IoT coverage is very wide and include variety of objects like smart phones, tablets, digital cameras, sensors, etc. Once all these devices are connected with each other, they enable more and more smart processes and services that support our basic needs, economies, environment and health. Such enormous number of devices connected to internet provides many kinds of services and produce huge amount of data and information. Cloud computing is a model for on-demand access to a shared pool of configurable resources (e.g. compute, networks, servers, storage, applications, services, and software) that can be easily provisioned as Infrastructure (IaaS), software and applications (SaaS). Cloud based platforms help to connect to the things (IaaS) around us so that we can access anything at any time and any place in a user friendly manner using customized portals and in built applications (SaaS). Hence, cloud acts as a front end to access Internet of Things. Applications that interact with devices like sensors have special requirements of massive storage to storage big data, huge computation power to enable the real time processing of the data, and high speed network to stream audio or video. In this paper, we describe how Internet of Things and Cloud computing can work together can address the Big Data issues. We also illustrate about Sensing as a service on cloud using few applications like Augmented Reality, Agriculture and Environment monitoring. Finally, we also propose a prototype model for providing sensing as a service on cloud.
326 citations
TL;DR: In this paper, the problem of joint computing, caching, communication, and control (4C) in big data MEC is formulated as an optimization problem whose goal is to jointly optimize a linear combination of the bandwidth consumption and network latency.
Abstract: The concept of Multi-access Edge Computing (MEC) has been recently introduced to supplement cloud computing by deploying MEC servers to the network edge so as to reduce the network delay and alleviate the load on cloud data centers. However, compared to the resourceful cloud, MEC server has limited resources. When each MEC server operates independently, it cannot handle all computational and big data demands stemming from users devices. Consequently, the MEC server cannot provide significant gains in overhead reduction of data exchange between users devices and remote cloud. Therefore, joint Computing, Caching, Communication, and Control (4C) at the edge with MEC server collaboration is needed. To address these challenges, in this paper, the problem of joint 4C in big data MEC is formulated as an optimization problem whose goal is to jointly optimize a linear combination of the bandwidth consumption and network latency. However, the formulated problem is shown to be non-convex. As a result, a proximal upper bound problem of the original formulated problem is proposed. To solve the proximal upper bound problem, the block successive upper bound minimization method is applied. Simulation results show that the proposed approach satisfies computation deadlines and minimizes bandwidth consumption and network latency.
325 citations
8 Nov 2010
TL;DR: This paper puts forth a novel vision, namely that advances in vehicular networks, embedded devices, and cloud computing can be used to form what the authors may call Vehicular Cloud Computing, VC2 for short.
Abstract: The past decade has witnessed a growing interest in vehicular networking and its myriad potential applications. The initial view of practitioners and researchers was that radio-equipped vehicles could keep the drivers informed about potential safety risks and increase their awareness of road conditions. The view then expanded to include access to the Internet and associated services. More recently, the availability of bandwidth has seen vehicular peer-to-peer networking and multimedia content delivery.This paper puts forth a novel vision, namely that advances in vehicular networks, embedded devices, and cloud computing can be used to form what we may call Vehicular Cloud Computing, VC2 for short. In VC2, the underutilized vehicles resources such as computing power, Internet connectivity and storage can be shared between drivers or rented over the Internet to various customers, very much like usual cloud resources are.
324 citations
TL;DR: A new cryptographic primitive called attribute-based encryption scheme with outsourcing key-issuing and outsourcing decryption, which can implement keyword search function (KSF-OABE) and is proved secure against chosen-plaintext attack (CPA).
Abstract: Cloud computing becomes increasingly popular for data owners to outsource their data to public cloud servers while allowing intended data users to retrieve these data stored in cloud. This kind of computing model brings challenges to the security and privacy of data stored in cloud. Attribute-based encryption (ABE) technology has been used to design fine-grained access control system, which provides one good method to solve the security issues in cloud setting. However, the computation cost and ciphertext size in most ABE schemes grow with the complexity of the access policy. Outsourced ABE (OABE) with fine-grained access control system can largely reduce the computation cost for users who want to access encrypted data stored in cloud by outsourcing the heavy computation to cloud service provider (CSP). However, as the amount of encrypted files stored in cloud is becoming very huge, which will hinder efficient query processing. To deal with above problem, we present a new cryptographic primitive called attribute-based encryption scheme with outsourcing key-issuing and outsourcing decryption, which can implement keyword search function (KSF-OABE). The proposed KSF-OABE scheme is proved secure against chosen-plaintext attack (CPA). CSP performs partial decryption task delegated by data user without knowing anything about the plaintext. Moreover, the CSP can perform encrypted keyword search without knowing anything about the keywords embedded in trapdoor.
324 citations
TL;DR: A perfect combination of cloud computing and internet of things can promote fast development of agricultural modernization, realize smart agriculture and effectively solve the issues concerning agriculture, countryside and farmers.
Abstract: Issues concerning agriculture, countryside and farmers have been always hindering China’s development. The only solution to these three problems is agricultural modernization. However, China's agriculture is far from modernized. The introduction of cloud computing and internet of things into agricultural modernization will probably solve the problem. Based on major features of cloud computing and key techniques of internet of things, cloud computing, visualization and SOA technologies can build massive data involved in agricultural production. Internet of things and RFID technologies can help build plant factory and realize automatic control production of agriculture. Cloud computing is closely related to internet of things. A perfect combination of them can promote fast development of agricultural modernization, realize smart agriculture and effectively solve the issues concerning agriculture, countryside and farmers.
323 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2026 | 91 |
| 2025 | 9,873 |
| 2024 | 13,154 |
| 2023 | 16,155 |
| 2022 | 25,943 |
| 2021 | 12,056 |