Smart Intermediate Data Transfer for MapReduce on Cloud Computing

2013 ◽  
Author(s):  
Tzu-Chi Huang ◽  
Kuo-Chih Chu ◽  
Yu-Ruei Rao
Keyword(s):  
Cloud Computing ◽  
Data Transfer ◽  
Intermediate Data

Advanced Data Storage Security System for Public Cloud

2020 ◽  
Vol 3 (2) ◽  
pp. 21-30
Author(s):  
Jitendra Kumar ◽  
Mohammed Ammar ◽  
Shah Abhay Kantilal ◽  
Vaishali R. Thakare
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Dynamic Capabilities ◽  
Data Transfer ◽  
Service Providers ◽  
Open Systems ◽  
Cloud Infrastructure ◽  
Great Loss ◽  
Security Issues ◽  
Data Auditing

Cloud is a collective term for a large number of developments and possibilities. Various data can be stored by the large amount of people onto the cloud storage facility without any bound of limitations as it provides tremendous space. Open systems like Android (Google Apps) still face many day- to-day security threats or attacks. With recent demand, cloud computing has raised security concerns for both service providers and consumers. Major issues like data transfer over wireless network across the globe have to be protected from unauthorized usage over the cloud as altered data can lead to great loss. In this regard, data auditing along with integrity, dynamic capabilities, and privacy preserving, and plays as an important role for preventing data from various cloud attacks which is considered in this work. The work also includes efficient auditor which plays a crucial role in securing the cloud environment. This paper presents a review on the cloud computing concepts and security issues inherent within the context of cloud computing and cloud infrastructure.

The Design of Power Security Defense System Based on Resource Pool Cloud Computing Technology

2020 ◽  
Vol 11 (1) ◽  
pp. 1-11
Author(s):  
Dang Nan
Keyword(s):  
Cloud Computing ◽  
System Analysis ◽  
Data Transfer ◽  
Automation System ◽  
Distributed Resources ◽  
Detection Technology ◽  
Automation Systems ◽  
Node Network ◽  
Node Protection ◽  
Power Dispatching Automation

In order to realize the power system defense security, this article puts forward the idea and method of constructing power dispatching automation systems with a cloud computing architecture and realizes the unified management of distributed resources with server virtualization technology. Real-time online migration of each module of the scheduling system is realized by using the in-memory data transfer technology. The multi-node network heartbeat detection technology is used to realize the complete monitoring of the server cluster. In the form of an independent disk array, the fault node is removed, and the service is restored automatically. The whole disaster reserve of the system is realized by means of remote resource mapping. System analysis results show that compared with traditional architecture, the service interruption probability of the new scheduling automation system is effectively reduced. Fault redundancy capacity in the station is increased from a key module 2 node to multi-node protection of all modules.

scholarly journals DM-MQTT: An Efficient MQTT Based on SDN Multicast for Massive IoT Communications

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3071 ◽  
Author(s):  
Jun-Hong Park ◽  
Hyeong-Su Kim ◽  
Won-Tae Kim
Keyword(s):  
Cloud Computing ◽  
Traffic Congestion ◽  
Data Exchange ◽  
Data Transfer ◽  
Edge Computing ◽  
Computing Paradigm ◽  
Transfer Delay ◽  
Network Usage ◽  
Iot Devices ◽  
Edge Networks

Edge computing is proposed to solve the problem of centralized cloud computing caused by a large number of IoT (Internet of Things) devices. The IoT protocols need to be modified according to the edge computing paradigm, where the edge computing devices for analyzing IoT data are distributed to the edge networks. The MQTT (Message Queuing Telemetry Transport) protocol, as a data distribution protocol widely adopted in many international IoT standards, is suitable for cloud computing because it uses a centralized broker to effectively collect and transmit data. However, the standard MQTT may suffer from serious traffic congestion problem on the broker, causing long transfer delays if there are massive IoT devices connected to the broker. In addition, the big data exchange between the IoT devices and the broker decreases network capability of the edge networks. The authors in this paper propose a novel MQTT with a multicast mechanism to minimize data transfer delay and network usage for the massive IoT communications. The proposed MQTT reduces data transfer delays by establishing bidirectional SDN (Software Defined Networking) multicast trees between the publishers and the subscribers by means of bypassing the centralized broker. As a result, it can reduce transmission delay by 65% and network usage by 58% compared with the standard MQTT.

scholarly journals A Novel UDT-Based Transfer Speed-Up Protocol for Fog Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Zhijie Han ◽  
Weibei Fan ◽  
Jie Li ◽  
Miaoxin Xu
Keyword(s):  
Cloud Computing ◽  
Data Transfer ◽  
Evaluation Model ◽  
Fog Computing ◽  
Middle Layer ◽  
Transport Layer ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Data Transfer Protocol ◽  
Bit Error Ratio

Fog computing is a distributed computing model as the middle layer between the cloud data center and the IoT device/sensor. It provides computing, network, and storage devices so that cloud based services can be closer to IOT devices and sensors. Cloud computing requires a lot of bandwidth, and the bandwidth of the wireless network is limited. In contrast, the amount of bandwidth required for “fog computing” is much less. In this paper, we improved a new protocol Peer Assistant UDT-Based Data Transfer Protocol (PaUDT), applied to Iot-Cloud computing. Furthermore, we compared the efficiency of the congestion control algorithm of UDT with the Adobe’s Secure Real-Time Media Flow Protocol (RTMFP), based on UDP completely at the transport layer. At last, we built an evaluation model of UDT in RTT and bit error ratio which describes the performance. The theoretical analysis and experiment result have shown that UDT has good performance in IoT-Cloud computing.

scholarly journals Cloud Computing Cloud Computing in Remote Sensing : High Performance Remote Sensing Data Processing in a Big data Environment

2021 ◽  
Vol 16 (6) ◽  
Author(s):  
Yassine Sabri ◽  
Aouad Siham
Keyword(s):  
Remote Sensing ◽  
Cloud Computing ◽  
Data Processing ◽  
High Performance ◽  
Large Scale ◽  
Processing System ◽  
Remote Sensing Data ◽  
Cloud Service ◽  
Intermediate Data ◽  
High Level

Multi-area and multi-faceted remote sensing (SAR) datasets are widely used due to the increasing demand for accurate and up-to-date information on resources and the environment for regional and global monitoring. In general, the processing of RS data involves a complex multi-step processing sequence that includes several independent processing steps depending on the type of RS application. The processing of RS data for regional disaster and environmental monitoring is recognized as computationally and data demanding.Recently, by combining cloud computing and HPC technology, we propose a method to efficiently solve these problems by searching for a large-scale RS data processing system suitable for various applications. Real-time on-demand service. The ubiquitous, elastic, and high-level transparency of the cloud computing model makes it possible to run massive RS data management and data processing monitoring dynamic environments in any cloud. via the web interface. Hilbert-based data indexing methods are used to optimally query and access RS images, RS data products, and intermediate data. The core of the cloud service provides a parallel file system of large RS data and an interface for accessing RS data from time to time to improve localization of the data. It collects data and optimizes I/O performance. Our experimental analysis demonstrated the effectiveness of our method platform.

scholarly journals Storage and Communication Security in Cloud Computing Using a Homomorphic Encryption Scheme Based Weil Pairing

2020 ◽  
Vol 26 (1) ◽  
pp. 78-83
Author(s):  
Demet Cidem Dogan ◽  
Huseyin Altindis
Keyword(s):  
Cloud Computing ◽  
Elliptic Curve ◽  
Data Transfer ◽  
Homomorphic Encryption ◽  
Discrete Logarithm ◽  
Original Data ◽  
Bilinear Pairing ◽  
Encryption Scheme ◽  
Weil Pairing ◽  
Encrypted Data

With introduction of smart things into our lives, cloud computing is used in many different areas and changes the communication method. However, cloud computing should guarantee the complete security assurance in terms of privacy protection, confidentiality, and integrity. In this paper, a Homomorphic Encryption Scheme based on Elliptic Curve Cryptography (HES-ECC) is proposed for secure data transfer and storage. The scheme stores the data in the cloud after encrypting them. While calculations, such as addition or multiplication, are applied to encrypted data on cloud, these calculations are transmitted to the original data without any decryption process. Thus, the cloud server has only ability of accessing the encrypted data for performing the required computations and for fulfilling requested actions by the user. Hence, storage and transmission security of data are ensured. The proposed public key HES-ECC is designed using modified Weil-pairing for encryption and additional homomorphic property. HES-ECC also uses bilinear pairing for multiplicative homomorphic property. Security of encryption scheme and its homomorphic aspects are based on the hardness of Elliptic Curve Discrete Logarithm Problem (ECDLP), Weil Diffie-Hellman Problem (WDHP), and Bilinear Diffie-Helman Problem (BDHP).

scholarly journals A Newly Proposed Prospective and Robust Computer Networking Model Architecture Based on the Infrastructure of Cloud Computing Contrivance

2021 ◽  
Vol 9 (9) ◽  
pp. 331-337
Author(s):  
Shivankur Thapliyal
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Data Transfer ◽  
Data Communication ◽  
Computer Networking ◽  
Significant Feature ◽  
Security Measures ◽  
Computational Costs ◽  
Cloud Networking ◽  
Access Data

Abstract: Computer Networking Play’s a major role for data communication or data sharing and data transmissions from one location to another, which are geographically differ, but in today’s scenario where the main and primary major concerns are not to data transfer but also utilize all resources with greater efficiency and also preserves the confidentiality and integrity of the messages with respect to speed and time with lower Bandwidth and also consume a very low computational costs with low power supply and redirect to optimality. Cloud Computing also play’s a significant role to access data at geographically different locations. So In this paper we create a fusion of Computer Networking Architecture and Cloud Computing Architecture and released a very much superior fundamentally strong Cloud computing based Computer Networking model, which works on the concepts of ‘Virtualization’. Because when the number of hardware components (Servers) drastically increases all factors which are responsible to make possible networking among nodes are also consume each resources at extreme level, and networking becomes complex and slow, that’s why we used the concept of Virtual Machine. In this paper we proposed a Computer Networking model using the concepts of Cloud Computing. This model also suitable for data transmission but also take concern the most significant feature of Computer Networking, which is Data Security. This model also used some Proxy servers/ firewalls to take concern some security mechanisms. In this paper we also proposed Communication Oriented model among the Intercluster domains that how one node which belongs to another CLOUD cluster make possible communication among other InterCLOUD clusters with respect to data security measures. In this paper we proposed three models related to this networking model, which is CLOUD Networking Infrastructure, Connection Oriented model, Communication Oriented model. The detailed description of all three models are in the upcoming sections of this paper. Keywords: Cloud computing based computer networking model, A virtual model for computer networking, Computer Networking model based on virtualization, Virtualization based computer networking model.

scholarly journals Cloud bursting galaxy: federated identity and access management

2019 ◽  
Vol 36 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Vahid Jalili ◽  
Enis Afgan ◽  
James Taylor ◽  
Jeremy Goecks
Keyword(s):  
Cloud Computing ◽  
High Speed ◽  
Large Scale ◽  
Best Practice ◽  
Data Transfer ◽  
Data Access ◽  
Web Security ◽  
Biomedical Data ◽  
Authentication And Authorization ◽  
Computing Platforms

Abstract Motivation Large biomedical datasets, such as those from genomics and imaging, are increasingly being stored on commercial and institutional cloud computing platforms. This is because cloud-scale computing resources, from robust backup to high-speed data transfer to scalable compute and storage, are needed to make these large datasets usable. However, one challenge for large-scale biomedical data on the cloud is providing secure access, especially when datasets are distributed across platforms. While there are open Web protocols for secure authentication and authorization, these protocols are not in wide use in bioinformatics and are difficult to use for even technologically sophisticated users. Results We have developed a generic and extensible approach for securely accessing biomedical datasets distributed across cloud computing platforms. Our approach combines OpenID Connect and OAuth2, best-practice Web protocols for authentication and authorization, together with Galaxy (https://galaxyproject.org), a web-based computational workbench used by thousands of scientists across the world. With our enhanced version of Galaxy, users can access and analyze data distributed across multiple cloud computing providers without any special knowledge of access/authorization protocols. Our approach does not require users to share permanent credentials (e.g. username, password, API key), instead relying on automatically generated temporary tokens that refresh as needed. Our approach is generalizable to most identity providers and cloud computing platforms. To the best of our knowledge, Galaxy is the only computational workbench where users can access biomedical datasets across multiple cloud computing platforms using best-practice Web security approaches and thereby minimize risks of unauthorized data access and credential use. Availability and implementation Freely available for academic and commercial use under the open-source Academic Free License (https://opensource.org/licenses/AFL-3.0) from the following Github repositories: https://github.com/galaxyproject/galaxy and https://github.com/galaxyproject/cloudauthz.

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