Cross-Layer Monitoring in Cloud Computing

2012 ◽  
pp. 328-348 ◽  
Author(s):  
Jose M. Alcaraz Calero ◽  
Benjamin König ◽  
Johannes Kirschnick
Keyword(s):  
Cloud Computing ◽  
Future Research ◽  
Cross Layer ◽  
Distributed Monitoring ◽  
Research Directions ◽  
Future Research Directions ◽  
Monitoring Architecture

This book chapter describes the different aspects related to designing a suitable monitoring architecture for Cloud Computing, aiming to support cross-layer monitoring across all layers available in the Cloud stack. For this purpose, the importance of monitoring services in Cloud scenarios is outlined, followed by a comprehensible analysis of a wide set of distributed monitoring solutions. After that, the particular requirements related to cross-layer monitoring for Cloud Computing architectures are identified and explained. Then, diverse aspects which may fit a monitoring architecture for fulfilling such requirements are explained. Finally, some future research directions and conclusions are highlighted.

Throughput Dependence on SNR in IEEE802.11 WLAN Systems

2019 ◽  
pp. 1307-1323
Author(s):  
Ikponmwosa Oghogho
Keyword(s):  
High Throughput ◽  
Signal To Noise Ratio ◽  
Physical Layer ◽  
Future Research ◽  
Cross Layer ◽  
Signal To Noise ◽  
Research Directions ◽  
Data Rates ◽  
Research Findings ◽  
Future Research Directions

This chapter seeks to present the dependence of throughput on signal to noise ratio (SNR) in IEEE802.11 WLAN systems. High throughput and low delays are presented as the requirements for indicating good performance of WLAN systems. The multiple communication data rates specified by the physical layer of IEEE802.11 WLANs which vary depending on the SNR observed is shown to appreciably influence the throughput experienced by the users. Cross-layer modelling principles which simplifies the process of estimating the dependence of throughput on SNR is presented. Recent research findings which apply cross-layer modelling principles to model the dependence of throughput on SNR only is presented along with future research directions.

Cloud and Mobile

2016 ◽  
pp. 1-20 ◽  
Author(s):  
Antonio Miguel Rosado da Cruz ◽  
Sara Paiva
Keyword(s):  
Cloud Computing ◽  
Mobile Computing ◽  
Mobile Devices ◽  
Mobile Apps ◽  
Mobile Technologies ◽  
Future Research ◽  
Mobile Cloud ◽  
Research Projects ◽  
Research Directions ◽  
Future Research Directions

Mobile computing and Cloud computing are two of the most growing technologies in number of users, practitioners and research projects. This chapter surveys mobile technologies and applications, along with cloud computing technologies and applications, presenting their evolution and characteristics. Then, building on mobile devices limitations and mobile apps increasing need of resources, and on the cloud computing ability to overcome those limitations, the chapter presents mobile cloud computing, and characterizes it by addressing approaches to augment mobile devices capabilities. The chapter is settled after some views about future research directions and some concluding remarks.

Unit of Analysis in Digitally-Enabled Electronic Procurement Research

2020 ◽  
pp. 83-103
Author(s):  
Md Mahbubur Rahim ◽  
Maryam Jabberzadeh ◽  
Nergiz Ilhan
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Critical Issue ◽  
Future Research ◽  
Research Directions ◽  
Research Issues ◽  
Unit Of Analysis ◽  
Electronic Procurement ◽  
Future Research Directions ◽  
Methodological Concern

E-procurement systems that have been in place for over a decade have begun incorporating digital tools like big data, cloud computing, internet of things, and data mining. Hence, there exists a rich literature on earlier e-procurement systems and advanced digitally-enabled e-procurement systems. Existing literature on these systems addresses many research issues (e.g., adoption) associated with e-procurement. However, one critical issue that has so far received no rigorous attention is about “unit of analysis,” a methodological concern of importance, for e-procurement research context. Hence, the aim of this chapter is twofold: 1) to discuss how the notion of “unit of analysis” has been conceptualised in the e-procurement literature and 2) to discuss how its use has been justified by e-procurement scholars to address the research issues under investigation. Finally, the chapter provides several interesting findings and outlines future research directions.

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 Data Placement in Era of Cloud Computing: a Survey, Taxonomy and Open Research Issues

2019 ◽  
Vol 20 (2) ◽  
pp. 377-398 ◽  
Author(s):  
Avinash Kaur ◽  
Pooja Gupta ◽  
Manpreet Singh ◽  
Anand Nayyar
Keyword(s):  
Cloud Computing ◽  
Workflow Management ◽  
Data Placement ◽  
Future Research ◽  
Research Directions ◽  
Research Issues ◽  
Cloud Computing Environment ◽  
Factors Affecting ◽  
Complete Survey ◽  
Future Research Directions

In cloud computing, data placement is a critical operation performed as part of workflow management and aims to find the best physical machine to place the data. It has direct impact on performance, cost and execution time of workflows. Number of data placement algorithms is designed in cloud computing environment that aimed to improve various factors affecting the workflows and their execution including the movement of data among data centers. This paper provides a complete survey and analyses of existing data placement schemes proposed in literature for cloud computing. Further, it classifies data placement schemes based on their assess capabilities and objectives. Further objectives and properties of data placement schemes are compared. Finally future research directions are provided with concluding remarks.

scholarly journals Recent Advances and Future Research Directions in Edge Cloud Framework

2019 ◽  
Vol 9 (2) ◽  
pp. 439-444 ◽  
Keyword(s):  
Cloud Computing ◽  
Service Time ◽  
Response Times ◽  
Edge Computing ◽  
Future Research ◽  
Simulation Environment ◽  
Research Directions ◽  
Great Idea ◽  
Cloud Framework ◽  
Future Research Directions

Recent years have shown the explosive emergence of Cloud computing in the industry and it is now the need of the hour. It is a great idea to go to utilize 5G remote advancement and man-made thinking to engage speedier response times, lower latency, improved upkeep in figuring. The cloud has at no other time been so essential to the undertaking beforehand. This is where Edge Computing came into picture — seen as an expansion to the cloud, yet interesting in a couple of crucial ways. Empowering data to be taken care of, explored and moved at the edge of the framework, edge enlisting will enable undertakings to gather and assessments data closer to where it is taken care of, consistently, without idleness. Thus it can take into consideration snappy substance conveyance and information preparing that ought to be the eventual fate of registering. In this paper we will extensively study the necessity of Edge Cloud simulation environment and simulate it through EdgeCloudSim. We find that the utilization based, fuzzy competitor based and hybrid based methodologies incline toward offloading the assignments to the edge, so they give better outcomes whereas the average service time of the Fuzzy-Based methodology is least in contrast with the others

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