scholarly journals A Methodology Based on Computational Patterns for Offloading of Big Data Applications on Cloud-Edge Platforms

2020 ◽  
Vol 12 (2) ◽  
pp. 28
Author(s):  
Beniamino Di Martino ◽  
Salvatore Venticinque ◽  
Antonio Esposito ◽  
Salvatore D’Angelo

Internet of Things (IoT) is becoming a widespread reality, as interconnected smart devices and sensors have overtaken the IT market and invaded every aspect of the human life. This kind of development, while already foreseen by IT experts, implies additional stress to already congested networks, and may require further investments in computational power when considering centralized and Cloud based solutions. That is why a common trend is to rely on local resources, provided by smart devices themselves or by aggregators, to deal with part of the required computations: this is the base concept behind Fog Computing, which is becoming increasingly adopted as a distributed calculation solution. In this paper a methodology, initially developed within the TOREADOR European project for the distribution of Big Data computations over Cloud platforms, will be described and applied to an algorithm for the prediction of energy consumption on the basis of data coming from home sensors, already employed within the CoSSMic European Project. The objective is to demonstrate that, by applying such a methodology, it is possible to improve the calculation performances and reduce communication with centralized resources.

2018 ◽  
Vol 6 (4) ◽  
pp. 39-47 ◽  
Author(s):  
Reuben Ng

Cloud computing adoption enables big data applications in governance and policy. Singapore’s adoption of cloud computing is propelled by five key drivers: (1) public demand for and satisfaction with e-government services; (2) focus on whole-of-government policies and practices; (3) restructuring of technology agencies to integrate strategy and implementation; (4) building the Smart Nation Platform; (5) purpose-driven cloud applications especially in healthcare. This commentary also provides recommendations to propel big data applications in public policy and management: (a) technologically, embrace cloud analytics, and explore “fog computing”—an emerging technology that enables on-site data sense-making before transmission to the cloud; (b) promote regulatory sandboxes to experiment with policies that proactively manage novel technologies and business models that may radically change society; (c) on the collaboration front, establish unconventional partnerships to co-innovate on challenges like the skills-gap—an example is the unprecedented partnership led by the Lee Kuan Yew School of Public Policy with the government, private sector and unions.


2021 ◽  
Vol 2021 ◽  
pp. 1-30
Author(s):  
Sita Rani ◽  
Aman Kataria ◽  
Vishal Sharma ◽  
Smarajit Ghosh ◽  
Vinod Karar ◽  
...  

Internet of Things (IoT) is the utmost assuring framework to facilitate human life with quality and comfort. IoT has contributed significantly to numerous application areas. The stormy expansion of smart devices and their credence for data transfer using wireless mechanics boost their susceptibility to cyberattacks. Consequently, the cybercrime rate is increasing day by day. Hence, the study of IoT security threats and possible corrective measures can benefit researchers in identifying appropriate solutions to deal with various challenges in cybercrime investigation. IoT forensics plays a vital role in cybercrime investigations. This review paper presents an overview of the IoT framework consisting of IoT architecture, protocols, and technologies. Various security issues at each layer and corrective measures are also discussed in detail. This paper also presents the role of IoT forensics in cybercrime investigation in various domains like smart homes, smart cities, automated vehicles, and healthcare. The role of advanced technologies like artificial intelligence, machine learning, cloud computing, edge computing, fog computing, and blockchain technology in cybercrime investigation is also discussed. Lastly, various open research challenges in IoT to assist cybercrime investigation are explained to provide a new direction for further research.


2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Aymen Abdullah Alsaffar ◽  
Hung Phuoc Pham ◽  
Choong-Seon Hong ◽  
Eui-Nam Huh ◽  
Mohammad Aazam

Despite the wide utilization of cloud computing (e.g., services, applications, and resources), some of the services, applications, and smart devices are not able to fully benefit from this attractive cloud computing paradigm due to the following issues: (1) smart devices might be lacking in their capacity (e.g., processing, memory, storage, battery, and resource allocation), (2) they might be lacking in their network resources, and (3) the high network latency to centralized server in cloud might not be efficient for delay-sensitive application, services, and resource allocations requests. Fog computing is promising paradigm that can extend cloud resources to edge of network, solving the abovementioned issue. As a result, in this work, we propose an architecture of IoT service delegation and resource allocation based on collaboration between fog and cloud computing. We provide new algorithm that is decision rules of linearized decision tree based on three conditions (services size, completion time, and VMs capacity) for managing and delegating user request in order to balance workload. Moreover, we propose algorithm to allocate resources to meet service level agreement (SLA) and quality of services (QoS) as well as optimizing big data distribution in fog and cloud computing. Our simulation result shows that our proposed approach can efficiently balance workload, improve resource allocation efficiently, optimize big data distribution, and show better performance than other existing methods.


Author(s):  
Manbir Sandhu ◽  
Purnima, Anuradha Saini

Big data is a fast-growing technology that has the scope to mine huge amount of data to be used in various analytic applications. With large amount of data streaming in from a myriad of sources: social media, online transactions and ubiquity of smart devices, Big Data is practically garnering attention across all stakeholders from academics, banking, government, heath care, manufacturing and retail. Big Data refers to an enormous amount of data generated from disparate sources along with data analytic techniques to examine this voluminous data for predictive trends and patterns, to exploit new growth opportunities, to gain insight, to make informed decisions and optimize processes. Data-driven decision making is the essence of business establishments. The explosive growth of data is steering the business units to tap the potential of Big Data to achieve fueling growth and to achieve a cutting edge over their competitors. The overwhelming generation of data brings with it, its share of concerns. This paper discusses the concept of Big Data, its characteristics, the tools and techniques deployed by organizations to harness the power of Big Data and the daunting issues that hinder the adoption of Business Intelligence in Big Data strategies in organizations.


Author(s):  
Jonatan Enes ◽  
Guillaume Fieni ◽  
Roberto R. Exposito ◽  
Romain Rouvoy ◽  
Juan Tourino

Sign in / Sign up

Export Citation Format

Share Document