scholarly journals Simulating Resource Management across the Cloud-to-Thing Continuum: A Survey and Future Directions

2020 ◽  
Vol 12 (6) ◽  
pp. 95
Author(s):  
Malika Bendechache ◽  
Sergej Svorobej ◽  
Patricia Takako Endo ◽  
Theo Lynn
Keyword(s):  
Cloud Computing ◽  
Resource Management ◽  
Research Area ◽  
Simulation Software ◽  
Future Research ◽  
Complex Environments ◽  
Future Directions ◽  
Infrastructure Performance ◽  
The Internet Of Things

In recent years, there has been significant advancement in resource management mechanisms for cloud computing infrastructure performance in terms of cost, quality of service (QoS) and energy consumption. The emergence of the Internet of Things has led to the development of infrastructure that extends beyond centralised data centers from the cloud to the edge, the so-called cloud-to-thing continuum (C2T). This infrastructure is characterised by extreme heterogeneity, geographic distribution, and complexity, where the key performance indicators (KPIs) for the traditional model of cloud computing may no longer apply in the same way. Existing resource management mechanisms may not be suitable for such complex environments and therefore require thorough testing, validation and evaluation before even being considered for live system implementation. Similarly, previously discounted resource management proposals may be more relevant and worthy of revisiting. Simulation is a widely used technique in the development and evaluation of resource management mechanisms for cloud computing but is a relatively nascent research area for new C2T computing paradigms such as fog and edge computing. We present a methodical literature analysis of C2T resource management research using simulation software tools to assist researchers in identifying suitable methods, algorithms, and simulation approaches for future research. We analyse 35 research articles from a total collection of 317 journal articles published from January 2009 to March 2019. We present our descriptive and synthetic analysis from a variety of perspectives including resource management, C2T layer, and simulation.

scholarly journals Simulating Resource Management across the Cloud-to-Thing Continuum

2020 ◽  
Author(s):  
Malika Bendechache ◽  
Sergej Svorobej ◽  
Patricia Takako Endo ◽  
Theo Lynn
Keyword(s):  
Cloud Computing ◽  
Resource Management ◽  
Research Area ◽  
Simulation Software ◽  
Future Research ◽  
Complex Environments ◽  
Journal Articles ◽  
Infrastructure Performance ◽  
The Internet Of Things

In recent years, there has been significant advancement in resource management mechanisms for cloud computing infrastructure performance in terms of cost, quality of service (QoS) and energy consumption. The emergence of the Internet of Things has led to the development of infrastructure that extends beyond centralised data centers from the cloud to the edge, the so-called cloud-to-thing continuum (C2T). This infrastructure is characterised by extreme heterogeneity, geographic distribution, and complexity, where the key performance indicators (KPIs) for the traditional model of cloud computing may no longer apply in the same way. Existing resource management mechanisms may not be suitable for such complex environments and therefore require thorough testing, validation and evaluation before even being considered for live system implementation. Similarly, previously discounted resource management proposals may be more relevant and worthy of revisiting. Simulation is a widely used technique in the development and evaluation of resource management mechanisms for cloud computing but is a relatively nascent research area for new C2T computing paradigms such as fog and edge computing. We present a methodical literature analysis of C2T resource management research using simulation software tools to assist researchers in identifying suitable methods, algorithms, and simulation approaches for future research. We analyse 35 research articles from a total collection of 317 journal articles published from January 2009 to March 2019. We present our descriptive and synthetic analysis from a variety of perspectives including resource management, C2T layer, and simulation.  

scholarly journals Moving to the Edge-Cloud-of-Things: Recent Advances and Future Research Directions

Electronics ◽  
2018 ◽  
Vol 7 (11) ◽  
pp. 309 ◽  
Author(s):  
Hind Bangui ◽  
Said Rakrak ◽  
Said Raghay ◽  
Barbora Buhnova
Keyword(s):  
Cloud Computing ◽  
Leading Edge ◽  
Cloud Services ◽  
Future Research ◽  
Research Directions ◽  
Iot Applications ◽  
Future Research Directions ◽  
Iot Devices ◽  
The Internet Of Things

Cloud computing has significantly enhanced the growth of the Internet of Things (IoT) by ensuring and supporting the Quality of Service (QoS) of IoT applications. However, cloud services are still far from IoT devices. Notably, the transmission of IoT data experiences network issues, such as high latency. In this case, the cloud platforms cannot satisfy the IoT applications that require real-time response. Yet, the location of cloud services is one of the challenges encountered in the evolution of the IoT paradigm. Recently, edge cloud computing has been proposed to bring cloud services closer to the IoT end-users, becoming a promising paradigm whose pitfalls and challenges are not yet well understood. This paper aims at presenting the leading-edge computing concerning the movement of services from centralized cloud platforms to decentralized platforms, and examines the issues and challenges introduced by these highly distributed environments, to support engineers and researchers who might benefit from this transition.

scholarly journals QoE in IoT: a vision, survey and future directions

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Kaneez Fizza ◽  
Abhik Banerjee ◽  
Karan Mitra ◽  
Prem Prakash Jayaraman ◽  
Rajiv Ranjan ◽  
...  
Keyword(s):  
Autonomic Function ◽  
Rapid Evolution ◽  
Critical Factor ◽  
Poor Quality ◽  
Future Research ◽  
Future Directions ◽  
Iot Applications ◽  
The Internet Of Things

AbstractThe rapid evolution of the Internet of Things (IoT) is making way for the development of several IoT applications that require minimal or no human involvement in the data collection, transformation, knowledge extraction, and decision-making (actuation) process. To ensure that such IoT applications (we term them autonomic) function as expected, it is necessary to measure and evaluate their quality, which is challenging in the absence of any human involvement or feedback. Existing Quality of Experience (QoE) literature and most QoE definitions focuses on evaluating application quality from the lens of human receiving application services. However, in autonomic IoT applications, poor quality of decisions and resulting actions can degrade the application quality leading to economic and social losses. In this paper, we present a vision, survey and future directions for QoE research in IoT. We review existing QoE definitions followed by a survey of techniques and approaches in the literature used to evaluate QoE in IoT. We identify and review the role of data from the perspective of IoT architectures, which is a critical factor when evaluating the QoE of IoT applications. We conclude the paper by identifying and presenting our vision for future research in evaluating the QoE of autonomic IoT applications.

Examining Communication Technologies of IoT for Best QoS

2018 ◽  
pp. 264-276
Author(s):  
Jayashree K ◽  
Babu R ◽  
Chithambaramani R
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Cloud Service ◽  
Communication Technologies ◽  
Industry Sector ◽  
Cloud Service Providers ◽  
The Internet Of Things ◽  
Excessive Number ◽  
The Web

The Internet of Things (IoT) architecture has gained an increased amount of attention from academia as well as the industry sector as a significant methodology for the development of innovative applications and systems. Currently, the merging of this architecture with that of Cloud computing has been largely motivated by the need for various applications and infrastructures in IoT. In addition to this, the Cloud ascends as an eminent solution that would help solve various challenges that are faced by the IoT standard when varied physical devices. There are an excessive number of Cloud service providers the web along with many other services. Thus, it becomes critical to choose the provider who can be efficient, consistent, and suitable, and who can deliver the best Quality of Service (QoS). Thus, this chapter discusses QoS for cloud computing and IoT.

scholarly journals VNF Placement Optimization at the Edge and Cloud †

2019 ◽  
Vol 11 (3) ◽  
pp. 69 ◽  
Author(s):  
Aris Leivadeas ◽  
George Kesidis ◽  
Mohamed Ibnkahla ◽  
Ioannis Lambadaris
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Research Area ◽  
End Users ◽  
Network Function Virtualization ◽  
Future Research ◽  
Cloud Infrastructure ◽  
Network Function ◽  
Computing Paradigm ◽  
Network Functions

Network Function Virtualization (NFV) has revolutionized the way network services are offered to end users. Individual network functions are decoupled from expensive and dedicated middleboxes and are now provided as software-based virtualized entities called Virtualized Network Functions (VNFs). NFV is often complemented with the Cloud Computing paradigm to provide networking functions to enterprise customers and end-users remote from their premises. NFV along with Cloud Computing has also started to be seen in Internet of Things (IoT) platforms as a means to provide networking functions to the IoT traffic. The intermix of IoT, NFV, and Cloud technologies, however, is still in its infancy creating a rich and open future research area. To this end, in this paper, we propose a novel approach to facilitate the placement and deployment of service chained VNFs in a network cloud infrastructure that can be extended using the Mobile Edge Computing (MEC) infrastructure for accommodating mission critical and delay sensitive traffic. Our aim is to minimize the end-to-end communication delay while keeping the overall deployment cost to minimum. Results reveal that the proposed approach can significantly reduce the delay experienced, while satisfying the Service Providers’ goal of low deployment costs.

scholarly journals A Comprehensive Survey on Resource Management in Internet of Things

2020 ◽  
Vol 4 ◽  
pp. 27-43
Author(s):  
Lokesh B Bhajantri ◽  
Gangadharaiah S.
Keyword(s):  
Resource Management ◽  
Internet Of Things ◽  
Resource Discovery ◽  
Future Research ◽  
The Internet ◽  
Management Processes ◽  
Efficient Resource ◽  
Comprehensive Survey ◽  
The Individual ◽  
The Internet Of Things

Efficient resource management is a challenging task in distributed systems, such as the Internet of Things, fog, edge, and cloud computing. In this work, we present a broad overview of the Internet of Things ecosystem and of the challenges related to managing its resources. We also investigate the need for efficient resource management and the guidelines given/suggested by Standard Development Organizations. Additionally, this paper contains a comprehensive survey of the individual phases of resource management processes, focusing on resource modeling, resource discovery, resource estimation, and resource allocation approaches based on performance parameters or metrics, as well as on architecture types. This paper presents also the architecture of a generic resource management enabler. Furthermore, we present open issues concerning resource management, pointing out the directions of future research related to the Internet of Things.

scholarly journals Commentary: Race and Ethnicity in Biomedical Research – Classifications, Challenges, and Future Directions

2018 ◽  
Vol 28 (4) ◽  
pp. 561-564 ◽  
Author(s):  
Dame Idossa ◽  
Narjust Duma ◽  
Katerina Chekhovskiy ◽  
Ronald Go ◽  
Sikander Ailawadhi
Keyword(s):  
Biomedical Research ◽  
Race And Ethnicity ◽  
The United States ◽  
Future Research ◽  
Future Directions ◽  
Data Collection Process ◽  
Large Databases ◽  
Future Research Directions ◽  
Racial Ethnic

The use of race and ethnicity in biomedical research has been a subject of debate for the past three decades. Initially the two ma­jor race categories were: White and Black, leaving other minorities uncounted or inap­propriately misclassified. As the science of health disparities evolves, more sophisticat­ed and detailed information has been add­ed to large databases. Despite the addition of new racial classifications, including multi-racial denominations, the quality of the data is limited to the data collection process and other social misconceptions. Although race is viewed as an imposed or ascribed status, ethnicity is an achieved status, making it a more challenging variable to include in biomedical research. Ambiguity between race and ethnicity often exists, ultimately affecting the value of both variables. To bet­ter understand specific health outcomes or disparities of groups, it is necessary to col­lect subgroup-specific data. Cultural percep­tions and practices, health experiences, and susceptibility to disease vary greatly among broad racial-ethnic groups and requires the collection of nuanced data to understand. Here, we provide an overview of the clas­sification of race and ethnicity in the United States over time, the existing challenges in using race and ethnicity in biomedical re­search and future research directions. Ethn Dis. 2018;28(4):561-564; doi:10.18865/ed.28.4.561.

scholarly journals Cyber Resilience and Incident Response in Smart Cities: A Systematic Literature Review

Smart Cities ◽  
2020 ◽  
Vol 3 (3) ◽  
pp. 894-927
Author(s):  
Gabriela Ahmadi-Assalemi ◽  
Haider Al-Khateeb ◽  
Gregory Epiphaniou ◽  
Carsten Maple
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Smart Cities ◽  
Scientific Evidence ◽  
Simulation Software ◽  
Incident Response ◽  
Natural Ecosystems ◽  
Future Directions ◽  
Smart Healthcare ◽  
The Internet Of Things

The world is experiencing a rapid growth of smart cities accelerated by Industry 4.0, including the Internet of Things (IoT), and enhanced by the application of emerging innovative technologies which in turn create highly fragile and complex cyber–physical–natural ecosystems. This paper systematically identifies peer-reviewed literature and explicitly investigates empirical primary studies that address cyber resilience and digital forensic incident response (DFIR) aspects of cyber–physical systems (CPSs) in smart cities. Our findings show that CPSs addressing cyber resilience and support for modern DFIR are a recent paradigm. Most of the primary studies are focused on a subset of the incident response process, the “detection and analysis” phase whilst attempts to address other parts of the DFIR process remain limited. Further analysis shows that research focused on smart healthcare and smart citizen were addressed only by a small number of primary studies. Additionally, our findings identify a lack of available real CPS-generated datasets limiting the experiments to mostly testbed type environments or in some cases authors relied on simulation software. Therefore, contributing this systematic literature review (SLR), we used a search protocol providing an evidence-based summary of the key themes and main focus domains investigating cyber resilience and DFIR addressed by CPS frameworks and systems. This SLR also provides scientific evidence of the gaps in the literature for possible future directions for research within the CPS cybersecurity realm. In total, 600 papers were surveyed from which 52 primary studies were included and analysed.

scholarly journals Security Measurement in Industrial IoT with Cloud Computing Perspective: Taxonomy, Issues, and Future Directions

2020 ◽  
Vol 2020 ◽  
pp. 1-31 ◽  
Author(s):  
Sahar Shah ◽  
Mahnoor Khan ◽  
Ahmad Almogren ◽  
Ihsan Ali ◽  
Lianwen Deng ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Literature Review ◽  
Optimal Algorithm ◽  
Cloud Security ◽  
Wireless Channel ◽  
Security And Privacy ◽  
Future Research ◽  
Future Directions ◽  
Cloud Models ◽  
Industrial Iot

In recent years, cloud computing has gained massive popularity in information technology and the industrial Internet of things. It provides facilities to the users over the wireless channel. Many surveys have been carried out in cloud security and privacy. The existing survey papers do not specify the classifications on the basis of cloud computing components. Therefore, they fail to provide the techniques with their specialities as well as the previously available literature review is outdated. This paper presents the security for cloud computing models with a new aspect. Unlike the previously existing surveys, the literature review of this paper includes the latest research papers in the field of cloud security. Also, different classifications are made for cloud computing security on the basis of different cloud components that are used to secure the cloud models. Furthermore, a total of eleven (11) classifications are considered, which includes cloud components to secure the cloud systems. These classifications help the researchers to find out the desired technique used in a specific component to secure the cloud model. Moreover, the shortcoming of each component enables the researchers to design an optimal algorithm. Finally, future directions are given to highlight future research challenges that give paths to researchers.

scholarly journals Study of the Most Valuable Researcher: Bibliometric Indicators and Collaboration Networks

2021 ◽  
pp. 117-136
Author(s):  
Camilo Peña Ramírez ◽  
Leonardo Concha ◽  
Eric Forcael ◽  
Gonzalo Garcés
Keyword(s):  
Research Area ◽  
Scientific Production ◽  
Collaborative Networks ◽  
Future Research ◽  
Bibliometric Indicators ◽  
Collaboration Networks ◽  
Academic Unit ◽  
The University ◽  
Bibliometric Studies

This work seeks to find the Most Valuable Researcher (MVR) within the academics of Faculties of Engineering and Business of a University in Chile, applying bibliometric indicators and collaboration networks. The methodology consisted in reviewing the literature referring to similar bibliometric studies from open databases, such as SciELO and Google Scholar. As a result of the study, a model was proposed based on the main bibliometric indicators used, with it was possible to filter the researchers from both faculties and establish a ranking with those academics with the best results and the current situation facing the research in each unit. This ranking indicates the standard that the most valuable researchers have, identifying that the variable “collaborative networks” has a direct relationship with the productivity of researchers and, also, the existence of correlations with indicators of network grade, co-authorship, and research area. This work seeks to deliver recommendations on the quantity and quality of scientific production within the University. Future research should include other databases and expand the scope by region, country, and area of expertise, and consider other factors such as the age of the researcher, forms of citation, and characteristics by area of knowledge, as well as deepen the concept of MVR, and its virtuous effect on the productivity of an academic unit.

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