Top PDF Serverless computing for the Internet of Things

Serverless computing for the Internet of Things

Serverless computing for the Internet of Things

Cloud-based services have evolved significantly over the years. Cloud computing models such as IaaS, PaaS and SaaS are serving as an alternative to traditional in-house infrastructure-based approach. Furthermore, serverless computing is a cloud computing model for ephemeral, stateless and event-driven applications that scale up and down instantly. In contrast to the infinite resources of cloud computing, the Internet of Things is the network of resource-constrained, hetero- geneous and intelligent devices that generate a significant amount of data. Due to the resource-constrained nature of IoT devices, cloud resources are used to pro- cess data generated by IoT devices. However, data processing in the cloud also has few limitations such as latency and privacy concerns. These limitations arise a requirement of local processing of data generated by IoT devices. A serverless platform can be deployed on a cluster of IoT devices using software containers to enable local processing of the sensor data. This work proposes a hybrid multi- layered architecture that not only establishes the possibility of local processing of sensor data but also considers the issues such as heterogeneity, resource constraint nature of IoT devices. We use software containers, and multi-layered architecture to provide the high availability and fault tolerance in our proposed solution. Keywords: IoT, Serverless computing, Fog computing, Docker
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Internet of Things and Integration with Cloud Computing

Internet of Things and Integration with Cloud Computing

Abstract- A fundamental understanding of the Internet of Things is that the data collection landscape has changed dramatically. Initially, ingested data in devices and storage caches were completely within the walls of the IT data center. At first, those walls gradually broke down as people started working from homes on their laptop and mobile devices which are connected to enterprises. Now we are seeing an explosion of devices in the field that need to connect and share data with the organizations. These devices, or things, need to share data with the same quality and performance regardless of whether they are in a remote corner of the world or in a metropolitan area. Enterprise data centers can’t be everywhere. Thus, the Internet of Things is the primary application for cloud computing. Cloud computing and Internet of Things are two very different technologies that are both already part of our day to day life. Their adoption and use are expected to be more and more pervasive, making them important components of the Future Internet. A novel paradigm where Cloud and IoT are merged together is foreseen as disruptive and as an enabler of a large number of application scenarios. This paper provides a brief overview of IoT, importance of reference model for IoT, challenges faced by IoT and IoT and cloud convergence to resolve those challenges.
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

The proliferation of smart Internet of Things (IoT) devices in our homes provides a level of convenience in our day-to-day activities but also raises key privacy concerns. There is an implicit concern among users that these devices storing important confidential information about the user (identity, credit-card details, family profile, house information) could someday go rogue leading to a doomsday question for user privacy. The general concern that, as technology gets smarter by the day, the level of privacy gets weaker, is already being reflected among users’ opinions today. With the array of smart sensors, assistants and perhaps robots invading the smart home consumer market, majority of users are already raising concerns on the need for constant monitoring (audio, video, indirect sensing) of the users. In a couple of recent patents [32], Google imagines devices that would get a lot more intrusive than what’s already available out there. We believe that it is only a matter of time before current day smart home technology deployments potentially hit the tipping point for privacy intrusion.
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Study of Internet of Things Using FOG Computing

Study of Internet of Things Using FOG Computing

The IoT promises to bring the connectivity to an earthly level, every home, vehicle, and workplace with smart, Internet-connected devices. But as dependence on our newly connected devices increases along with the benefits and uses of a growing technology, the consistency of the gateways that make the IoT a functional reality must increase and make uptime a near guarantee [3]. As every appliance light, door, piece of clothing etc. The Internet of Things is poised to apply major stresses to the current internet and data center infrastructure. Gardner predicts that the IoT may include 26 billion connected units by 2020.
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Internet of Things (IoT): The Most Up To Date Challenges, Architectures, Emerging Trends and Potential Opportunities

Internet of Things (IoT): The Most Up To Date Challenges, Architectures, Emerging Trends and Potential Opportunities

Internet of Things (IoT) is nowadays the most profound buzzword in Information Technology science. IoT is the evolution of Information Technology which aims to build a mutual infrastructure that integrates, connects and telecommunicates every „Things‟ (Objects) with each other on the face of the earth. This interconnected infrastructure provides humans with fully control of things. Projections and potential estimates about incomings of IoT are spectacular for future directions. IoT encompasses such a wide range of spectrum that its influences are anyone‟s guess. Not only the profits of IoT but also the forfeits and fears of IoT are unpredictable for yet. However, with the increase in research, academic studies and technological developments the atmosphere will be clear for IoT. This research paper proposes a novel comprehensive reference source for those who are interested in IoT, ubiquitous sensing, pervasive computing and smart objects. The paper explains IoT emergence and IoT history in detail, current IoT usage areas, the most up-to-date potential opportunities and future IoT directions, overall IoT architecture and well-liked architectures, security and privacy concerns about IoT. The latest ongoing IoT projects are discussed and the latest burning issues are presented. Critical and turning points of IoT are given in tabular. As compared to similar survey papers in the area, to the best of our knowledge contributions of this paper are unique.
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Internet of things

Internet of things

As trillions of things (objects) are connected to the Internet it is necessary to have an adequate architecture that permits easy connectivity, control, communications, and useful applications. How will these objects interact in and across applications? Many times, things or sets of things must be disjoint and protected from other devices. At other times it makes sense to share devices and information. One possible architectural approach for IoT is to borrow from the smartphone world. nes employ an approach where applications are implemented and made available from an appstore.
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A Pervasive Computing Model of Internet of Things based on Computing Area Network

A Pervasive Computing Model of Internet of Things based on Computing Area Network

B. CAN-CSM computing area network system model As is shown in Fig.1, the pervasive computing framework of internet of things can be divided into three levels. In the ubiquitous computing environments of internet of things, DCS can cope with the needs of the body to migrate to different computing environments, which require different equipments to form an environment computing system. The body needs to complete the DCS services include computing, display, input and output, control processing functions and so on. In this paper, in aspect of DCS storage, migration and coordination of implementation, a control system model algorithm of regional network computing is proposed, called CAN-CSM (Computing Area Network- Control System Model). As the core implementation and virtual compute nodes, it make the pervasive computing architecture of internet of things have a very good flexibility and scalability, which described in Figure 2. PU means processing unit, CU for the memory cell, IO for the input output unit, MCU for the micro-control unit.
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

Despite the prevalence of new technologies and online learning-related research, and, despite substantial interests for using mobile devices to support learning, little is known of English Learners’ (ELs) literacy activities on mobile phones. Social networking and learning in online spaces have been a popular topic among many language and literacy educators and researchers for years (Belcher, 1999; Black, 2009; Nelson & Temple, 2011). Now, technology- mediated learning, which was once reliant on computer-assisted online spaces, is moving towards mobile phones. Language learners now interact in a mobile world by using various applications and nearly unlimited online access. Most of the studies related to mobile learning were done with technological evaluations (Petrova & Li, 2009). However, only limited research has been done on ELs’ actual mobile phone language learning and literacy practices in and out of school. Rather, most of the published studies are reviews of existing tools and how they can help learners, not necessarily English learners. Godwin-Jones (2008) reviewed online writing tools to examine what features they have and how they can assist learners. His research clearly shows that emerging technologies provide an opportunity for ELs’ self-development of writing skills using various tools--including Google. He argued that the new challenge for language teachers is the issue of how they can help students extend their Internet world beyond their first language and provide appropriate instruction and tools for students’ self-development in that environment. Literacy practices include what students do and most importantly how they use their
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

In Vasquez’s (2014b) research in her kindergarten class, influenced by the Reggio Emilia approach (Forman & Frye, 2012), the children examined the topic of gender equity through a multimodal exploration of rain forests, which included song, dance, letter writing, and the production of a play. In one of the books the class read during their rain forest study, an image depicted a man cooking food on an outdoor fire, which prompted one of the children to ask why a man was cooking instead of a woman (Vasquez, 2014b). The child’s question led to Vasquez facilitating an interrogation of gender representation in other texts. The children considered such things as gender roles and how power or weakness was associated with gender in those texts. The children also considered who was telling each story and why. Although gender equity was a topic raised during rain forest study, it permeated the wider curriculum throughout the year. For example, at another point in the year, gender equity was taken up again in discussions about advertisements for Halloween costumes. The children considered the types of costumes worn by boys versus girls, the cost of these costumes, and representations of power. As a result of this study, children troubled the messages about traditional gender roles in the advertisements by designing their costumes that reflected counter-narratives.
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

Through the examination of storytelling, this research seeks to gain a deeper understanding of the relationship between identity and place through examining African memory in African Ame[r]

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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

This study is designed to investigate paleoenvironmental changes in tropical East Africa through the examination of multi-proxy data, the primary being fungal spores, from Kapkanyar Swam[r]

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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

Several search terms were used to provide information about physical activity and African American women: African American women, Black women, consequences of physical inactivity, physic[r]

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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

There is a significant negative effect of grade, indicating that middle schools teachers are less likely to remain in teaching beyond five years than elementary and high school educators[r]

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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

The pupil placement plan that allowed schools to select a few “token” students and place them strategically throughout the district was the reason for Rosalyn’s transfer, over everybody else, including her best friends. For Rosalyn, the greatest burden was the loss of those significant relationships. She initially had difficulty reconciling the fact that she was the only one chosen, especially since the plan was for all of her network of friends to transfer together. After all, they were the reason she applied in the first place, “I missed out on my friends because at Murphy High, there were no friendships to be made. They weren’t friendly. I missed out on social things that I would have done being at my own school.” Rosalyn knew she was taking on a courageous feat, and it did not take long for her to realize the students were being used by the school system as a way to avoid the full desegregation of schools. Rather than give up, Rosalyn decided to take it all in stride and prove that she was just as smart, talented, and belonged there just as much as anyone.
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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

1 List of Tables Table 1: Sociodemographic Characteristics of Study Population Table 2: Emerging Themes and Subthemes from both MBAT and “iQuit” Mindfully Table 3: Mindfulness Practice A[r]

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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

While Chapter 2 is an example of a correlation study, in Chapter 3 we directly tested the role of gut dysbiosis by exploring the effects of treatments that affect gut microbial compositi[r]

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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

The overall study centers second-generation East African women concerning their digital media practices and how they re-cultivated homeplace through work around cultural identity, memory[r]

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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

The research questions that guide the study are 1 how the inclusive strategies I have found in my art classroom can be utilized to create an inclusive art museum setting, 2 how we can ap[r]

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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

Visual arts with refugee children: gives an overview of the issues facing refugee children, the significance of using the visual arts in supporting the development of young refugees, and[r]

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Collaborative Edge Computing in Mobile Internet of Things

Collaborative Edge Computing in Mobile Internet of Things

ABSTRACT INFLUENCES OF MATERNAL OBESITY ON INDUCTION OF LABOR REQUIRING CERVICAL RIPENING by JESSICA ANN ELLIS Statement of the Problem Although obese women are less likely to initiate s[r]

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