scholarly journals From Networked Robotics to Cloud and Big Data Supercharged Robotics: A Survey and Analysis

2021 ◽  
Author(s):  
Muhammed Tawfiq Chowdhury ◽  
Feng Yan
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Dominant Factor ◽  
Multiple Robots ◽  
Networked Robots ◽  
Survey Paper ◽  
Cloud Robotics ◽  
Networked Robotics ◽  
Processing Power ◽  
Cloud Servers

Abstract In recent years, with the prosperity of big data and cloud computing, robotics is evolving from conventional networked robotics to internet-scale connected, big data driven, and cloud resources supercharged multi-robot systems. In this survey paper, we present a survey of an advancing, pioneering, and multi-disciplinary field of research at the intersection of wireless sensor networks (WSN), robotics and big data. We discuss the concepts of networked robots. Networked robots refer to multiple robots working together in coordination with different types of embedded computers, sensors, and human users. Networked robotics allows multiple robots and supporting entities to execute tasks that are well beyond the capabilities of a single robot. The recent initiation of cloud technologies is opening new prospects for the provisioning of advanced robotic services based on the cooperation of some connected robots, smart environments and devices powered by the huge computational and storage capability of the cloud servers. We have recently witnessed the emergence of cloud computing on one hand and robotics platforms on the other hand. These two areas have been merging and resulting in the cloud robotics model to offer more distant services. Since networked robots require high computational and processing power, big data is becoming a dominant factor in networked and cloud robotics. This survey paper elaborates the primary concepts of networked and cloud robotics, their applications, challenges as well as the importance of big data in robotics, particularly, networked and cloud robotics and the noteworthy works in these areas.

Big Data in Massive Parallel Processing

2018 ◽  
pp. 276-302 ◽  
Author(s):  
Vijayalakshmi Saravanan ◽  
Anpalagan Alagan ◽  
Isaac Woungang
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Storage ◽  
Mobile Phones ◽  
Scientific Data ◽  
Computational Power ◽  
Data Intensive ◽  
Heterogeneous Devices ◽  
Processing Power ◽  
Massive Parallel Processing

With the advent of novel wireless technologies and Cloud Computing, large volumes of data are being produced from various heterogeneous devices such as mobile phones, credit cards, and computers. Managing this data has become the de-facto challenge in the current Information Systems. According to Moore's law, processor speeds are no longer doubling, the processing power also continuing to grow rapidly which leads to a new scientific data intensive problem in every field, especially Big Data domain. The revolution of Big Data lies in the improved statistical analysis and computational power depend on its processing speed. Hence, the need to put massively multi-core systems on the job is vital in order to overcome the physical limits of complexity and speed. It also arises with many challenges such as difficulties in capturing massive applications, data storage, and analysis. This chapter discusses some of the Big Data architectural challenges in the perspective of multi-core processors.

scholarly journals Research on Big data Security privacy Protection based on cloud Computing

2021 ◽  
Vol 2083 (4) ◽  
pp. 042077
Author(s):  
Tongtong Xu ◽  
Lei Shi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Storage ◽  
Data Security ◽  
Privacy Protection ◽  
Data Privacy ◽  
Cloud Services ◽  
Security Mechanism ◽  
Computing Platform ◽  
Cloud Servers

Abstract Cloud computing is a new way of computing and storage. Users do not need to master professional skills, but can enjoy convenient network services as long as they pay according to their own needs. When we use cloud services, we need to upload data to cloud servers. As the cloud is an open environment, it is easy for attackers to use cloud computing to conduct excessive computational analysis on big data, which is bound to infringe on others’ privacy. In this process, we inevitably face the challenge of data security. How to ensure data privacy security in the cloud environment has become an urgent problem to be solved. This paper studies the big data security privacy protection based on cloud computing platform. This paper starts from two aspects: implicit security mechanism and display security mechanism (encryption mechanism), so as to protect the security privacy of cloud big data platform in data storage and data computing processing.

Examining Data Lake Design Principle for Cloud Computing Technology and IoT

2018 ◽  
pp. 228-250
Author(s):  
Deepak Saini ◽  
Jasmine Saini
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Design Principle ◽  
Business Value ◽  
Computing Technology ◽  
Multiple Systems ◽  
Good Design ◽  
The World ◽  
Data Files ◽  
Cloud Servers

In the Cloud-based IoT systems, the major issue is handling the data because IoT will deliver an abundance of data to the Cloud for computing. In this situation, the cloud servers will compute the big data and try to identify the relevant data and give decisions accordingly. In the world of big data, it is a herculean task to manage inflow, storage, and exploration of millions of data files and the volume of information coming from multiple systems. The growth of this information calls for good design principles so that it can leverage the different big data tools available in the market today. From the information consumption standpoint, business users are exploring new insights from the big data that can uncover potential business value. Data lake is a technology framework that helps to solve this big data challenge.

scholarly journals Smarter Round Robin Scheduling Algorithm for Cloud Computing and Big Data

2018 ◽  
Vol Special Issue on Scientific... ◽  
Author(s):  
Hicham GIBET TANI ◽  
Chaker EL AMRANI
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Scheduling Algorithm ◽  
Growth Management ◽  
Power Scheduling ◽  
Processing Power ◽  
Business Market ◽  
High Efficient ◽  
Exploitation Model ◽  
Computing Models

Cloud Computing and Big Data are the upcoming Information Technology (IT) computing models. These groundbreaking paradigms are leading IT to a new set of rules that aims to change computing resources delivery and exploitation model, thus creating a novel business market that is exponentially growing and attracting more and more investments from both providers and end users that are looking forward to make profits from these innovative models of computing. In the same context, researchers and investigators are wrestling time in order to develop, test and optimize Cloud Computing and Big Data platforms, whereas several studies are ongoing to determine and enhance the essential aspects of these computing models especially compute resources allocation. The processing power scheduling is crucial when it comes to Cloud Computing and Big Data because of the data growth management and delivery design proposed by these new computing models, that requires faster responses from platforms and applications. Hence originates the importance of developing high efficient scheduling algorithms that are compliant with these computing models platforms and infrastructures requirement. Cloud Computing et Big Data sont les prochains modèles informatiques. Ces paradigmes révolutionnaires conduisent l'informatique à un nouveau jeu de règles qui vise à changer la livraison des ressources informatiques et le modèle d'exploitation, créant ainsi un monde d'affaires nouveau qui croît de façon exponentielle et attire de plus en plus d'investissements des fournisseurs et des utilisateurs finaux qui attendent Amener profit de ces modèles innovants de l'informatique. Dans le même contexte, les chercheurs combattent pour développer, tester et optimiser les plates-formes Cloud Computing et Big Data, alors que plusieurs études sont en cours pour déterminer et améliorer les aspects essentiels de ces modèles informatiques, en particulier l'allocation des ressources. La planification de la puissance de traitement est cruciale quand il s'agit de Cloud Computing et Big Data en raison de la gestion de la croissance des données et la conception de livraison proposée par ces nouveaux modèles informatiques, qui nécessite des réponses plus rapides des plates-formes et des applications. D'où l'origine de l'importance de développer des algorithmes d'ordonnancement efficaces qui sont conformes à ces plates-formes de modèles informatiques et aux exigences d'infrastructure.

scholarly journals ELASTIC CLOUD COMPUTING APPROACH FOR BIG DATA ANALYTICS

2019 ◽  
Vol 2019 (02) ◽  
pp. 87-96
Author(s):  
Suma V
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analytics ◽  
Information Technologies ◽  
Big Data Analytics ◽  
Resource Provisioning ◽  
Network Bandwidth ◽  
Processing Power ◽  
Industrial Operations ◽  
Computing Approach

The latest developments in the communication and the information technologies have turned out to be the foundation for the emergence of the industrial developments and progress in the business causing digital transformation in the industrial and the business operations. The clubbing of the internet and the information technology along with the tangible things that are the responsible for the industrial operations, generate a huge set of data that requires enormous network bandwidth, high processing power and accessible resolutions. So the paper presents the elastic cloud computing approach to bring down the complexities in deploying, cost of the groundwork and maintenance and provide an automated resource provisioning according to the demands. This method increases the amount of the computing power available, network properties and the storage. The experimental results for the novel elastic approach for the big data analytics is obtained by the simulation through MATLAB in terms response time, processing power and cost.

Binary Integer Programming Approach to Optimal Content Placement in Cloud-based Content Delivery Networks

2021 ◽  
Author(s):  
Nay Myo Sandar
Keyword(s):  
Cloud Computing ◽  
Integer Programming ◽  
Content Delivery ◽  
Binary Integer Programming ◽  
Content Delivery Networks ◽  
Processing Power ◽  
Content Placement ◽  
Cloud Servers ◽  
Delivery Networks ◽  
Origin Server

Over the last decades, Content Delivery Networks (CDNs) have been developed to overcome the limitation of user perceived latency by replicating contents from origin server to its content servers around the globe close to clients. As some contents occupy most of the storage capacity and processing power in traditional private content servers, cloud computing can provide a pool of storage and processing power resources for caching contents. By adopting cloud computing to CDN, the content provider can use the cloud infrastructure by distributing the contents to cloud servers which will then deliver to near clients. In this paper, we propose a cloud-based CDN framework designed by two schemes 1) UDP/TCP-based content distribution from origin server to cloud servers and 2) SDN-based cloud server coordination. In addition, we also formulate the optimal content placement problem using binary integer programming to minimize the total cost of renting resources including storage, processing power, and network bandwidth in cloud providers for hosting contents from origin server. Then, the optimal solution obtained from binary integer programming is evaluated by greedy algorithm and simulations. The proposed framework helps content provider to offer high quality of services to clients while minimizing the cost of rented cloud resources.

scholarly journals A Comprehensive Survey of Recent Trends in Cloud Robotics Architectures and Applications

Robotics ◽  
2018 ◽  
Vol 7 (3) ◽  
pp. 47 ◽  
Author(s):  
Olimpiya Saha ◽  
Prithviraj Dasgupta
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Large Scale ◽  
Future Research ◽  
Survey Paper ◽  
Cloud Robotics ◽  
Internet Resources ◽  
Learning Capabilities ◽  
Comprehensive Survey ◽  
Active Research

Cloud robotics has recently emerged as a collaborative technology between cloud computing and service robotics enabled through progress in wireless networking, large scale storage and communication technologies, and the ubiquitous presence of Internet resources over recent years. Cloud computing empowers robots by offering them faster and more powerful computational capabilities through massively parallel computation and higher data storage facilities. It also offers access to open-source, big datasets and software, cooperative learning capabilities through knowledge sharing, and human knowledge through crowdsourcing. The recent progress in cloud robotics has led to active research in this area spanning from the development of cloud robotics architectures to its varied applications in different domains. In this survey paper, we review the recent works in the area of cloud robotics technologies as well as its applications. We draw insights about the current trends in cloud robotics and discuss the challenges and limitations in the current literature, open research questions and future research directions.

Challenges and Cloud Computing Environments Towards Big Data

2014 ◽  
pp. 203-208
Author(s):  
Kiran Kumar S V N Madupu
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Big Data ◽  
Technology Development ◽  
Computing Environments ◽  
Modern Technologies

Big Data has terrific influence on scientific discoveries and also value development. This paper presents approaches in data mining and modern technologies in Big Data. Difficulties of data mining as well as data mining with big data are discussed. Some technology development of data mining as well as data mining with big data are additionally presented.

Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

2017 ◽  
Vol 7 (7) ◽  
pp. 137
Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Large Data ◽  
Workflow Scheduling ◽  
Cloud Environment ◽  
Computing Environment ◽  
Scientific Application ◽  
Cloud Computing Environment ◽  
Flow Of Information

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.

Issues in security and privacy of big data

2018 ◽  
Vol 7 (12) ◽  
pp. 1
Author(s):  
Shaveta Bhatia
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Approximate Method ◽  
Biomedical Research ◽  
Cyber Security ◽  
Data Science ◽  
Third Party ◽  
Security And Privacy ◽  
Security Threats ◽  
The Third

 The epoch of the big data presents many opportunities for the development in the range of data science, biomedical research cyber security, and cloud computing. Nowadays the big data gained popularity.  It also invites many provocations and upshot in the security and privacy of the big data. There are various type of threats, attacks such as leakage of data, the third party tries to access, viruses and vulnerability that stand against the security of the big data. This paper will discuss about the security threats and their approximate method in the field of biomedical research, cyber security and cloud computing.

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