scholarly journals Cloud-based Network Virtualization in IoT with OpenStack

2022 ◽  
Vol 22 (1) ◽  
pp. 1-26
Author(s):  
Zakaria Benomar ◽  
Francesco Longo ◽  
Giovanni Merlino ◽  
Antonio Puliafito
Keyword(s):  
Cloud Computing ◽  
Overlay Networks ◽  
Virtual Machines ◽  
Cloud Model ◽  
Network Virtualization ◽  
Bare Metal ◽  
Infrastructure As A Service ◽  
Model Network ◽  
The Core ◽  
Geographically Distributed

In Cloud computing deployments, specifically in the Infrastructure-as-a-Service (IaaS) model, networking is one of the core enabling facilities provided for the users. The IaaS approach ensures significant flexibility and manageability, since the networking resources and topologies are entirely under users’ control. In this context, considerable efforts have been devoted to promoting the Cloud paradigm as a suitable solution for managing IoT environments. Deep and genuine integration between the two ecosystems, Cloud and IoT, may only be attainable at the IaaS level. In light of extending the IoT domain capabilities’ with Cloud-based mechanisms akin to the IaaS Cloud model, network virtualization is a fundamental enabler of infrastructure-oriented IoT deployments. Indeed, an IoT deployment without networking resilience and adaptability makes it unsuitable to meet user-level demands and services’ requirements. Such a limitation makes the IoT-based services adopted in very specific and statically defined scenarios, thus leading to limited plurality and diversity of use cases. This article presents a Cloud-based approach for network virtualization in an IoT context using the de-facto standard IaaS middleware, OpenStack, and its networking subsystem, Neutron. OpenStack is being extended to enable the instantiation of virtual/overlay networks between Cloud-based instances (e.g., virtual machines, containers, and bare metal servers) and/or geographically distributed IoT nodes deployed at the network edge.

scholarly journals SNMP for Cloud Environment Energy Efficiency

2021 ◽  
Author(s):  
Marta Chinnici ◽  
Asif Iqbal ◽  
ah lian kor ◽  
colin pattinson ◽  
eric rondeau
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Power Consumption ◽  
Empirical Evidence ◽  
Rapid Growth ◽  
Virtual Machines ◽  
Cloud Environment ◽  
Second Stage ◽  
The Core ◽  
Snmp Protocol

Abstract Cloud computing has seen rapid growth and environments are now providing multiple physical servers with several virtual machines running on those servers. Networks have grown larger and have become more powerful in recent years. A vital problem related to this advancement is that it has become increasingly complex to manage networks. SNMP is one standard which is applied as a solution to this management of networks problem. This work utilizes SNMP to explore the capabilities of SNMP protocol and its features for monitoring, control and automation of virtual machines and hypervisors. For this target, a stage-wise solution has been formed that obtains results of experiments from the first stage uses SNMPv3 and feed to the second stage for further processing and advancement. The target of the controlling experiments is to explore the extent of SNMP capability in the control of virtual machines running in a hypervisor, also in terms of energy efficiency. The core contribution based on real experiments is conducted to provide empirical evidence for the relation between power consumption and virtual machines.

scholarly journals Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Shyamala Loganathan ◽  
Saswati Mukherjee
Keyword(s):  
Cloud Computing ◽  
Job Scheduling ◽  
Virtual Machines ◽  
Cloud Model ◽  
Scheduling Algorithm ◽  
Private Cloud ◽  
Resource Monitoring ◽  
Efficient Resource ◽  
Efficient Data ◽  
Guaranteed Service

Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms.

scholarly journals Optimized Speculative Execution to Improve Performance of MapReduce Jobs on Virtualized Computing Environment

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Lei Yang ◽  
Yu Dai ◽  
Bin Zhang
Keyword(s):  
Cloud Computing ◽  
Response Time ◽  
Virtual Machines ◽  
Resource Provisioning ◽  
Speculative Execution ◽  
Computing Environment ◽  
Virtual Cluster ◽  
Improve Performance ◽  
The Core ◽  
Flexible Resource

Recently, virtualization has become more and more important in the cloud computing to support efficient flexible resource provisioning. However, the performance interference among virtual machines may affect the efficiency of the resource provisioning. In a virtualized environment, where multiple MapReduce applications are deployed, the performance interference can also affect the performance of the Map and Reduce tasks resulting in the performance degradation of the MapReduce jobs. Then, in order to ensure the performance of the MapReduce jobs, a framework for scheduling the MapReduce jobs with the consideration of the performance interference among the virtual machines is proposed. The core of the framework is to identify the straggler tasks in a job and back up these tasks to make the backed up one overtake the original tasks in order to reduce the overall response time of the job. Then, to identify the straggler task, this paper uses a method for predicting the performance interference degree. A method for scheduling the backing-up tasks is presented. To verify the effectiveness of our framework, a set of experiments are done. The experiments show that the proposed framework has better performance in the virtual cluster compared with the current speculative execution framework.

scholarly journals Implementasi Data Center Untuk Penempatan Host Server Berbasis Private Cloud Computing

KREA-TIF ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 50
Author(s):  
Yuggo Afrianto ◽  
Ade Hendri Hendrawan
Keyword(s):  
Cloud Computing ◽  
Life Cycle ◽  
Data Center ◽  
Bare Metal ◽  
Network Development ◽  
Private Cloud ◽  
Infrastructure As A Service ◽  
Ibn Khaldun ◽  
Development Life Cycle ◽  
Private Cloud Computing

<p><em>private cloud computing dengan layanan Infrastructure as a Service (IaaS), yaitu tentang  layanan sumber daya komputasi yang di virtualisasikan pada kampus Universitas Ibn khaldun Bogor (UIKA)  dengan tujuan penggunan sumber daya komputasi tak terbatas sesuai dengan kebutuhan atau selalu bertambah sesuai dengan kebutuhan, pengguna dapat dengan mudah merubah dan merekonfigurasi sumber daya yang dikuasinya, sekaligus menjadi salah satu cara penghematan biaya penyedian sumber daya hardware server. Tujuan penelitian ini adalah menerapkan penempatan host server yang ada saat ini secara fisik menjadi berbasis virtualisasi. Metode penelitian yang digunakan adalah Network Development Life Cycle (NDLC) sebagai langkah-langkah dalam mendesain proses implementasi dan analisis. Hasil penelitian ini  adalah simtem layanan private cloud computing berbasis IaaS di data center kampus Universitas ibn khaldun (UIKA), dapat diterapkan menggunakan metode hypervisor native bare metal dan aplikasi proxmox. Hasil pengujian menyatakan bahwa data center berbasis IaaS secara sumber daya dapat menghemat, mengoptimalkan, dan pengelolaan sumberdaya dari kebutuhan layanan sistem infomasi yang harus di sediakan kampus UIKA. Berdasarkan uji usability menunjukkan aplikasi proxmox telah sesuai dengan kebutuhan manajemen yang ada pada administrator IT  kampus UIKA, yang memenuhi aspek Learnability, Efficiency, Memorability, Errors, dan Satisfaction.</em></p>

scholarly journals Taxonomy of resource allocation algorithms for inner IaaS cloud data centres

2013 ◽  
Author(s):  
Dang Minh Quan
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Virtual Machines ◽  
Computer Hardware ◽  
Infrastructure As A Service ◽  
Cloud Data ◽  
Cloud Infrastructures ◽  
Allocation Algorithms ◽  
Data Centres ◽  
Cloud User

Cloud computing has become more and more popular  with  the  widely  deployment  of  several  cloud infrastructures.  Infrastructure-as-a-service  (IaaS) Cloud  computing  replaces  bare  computer hardware. The cloud user  will use the virtual  machines (VMs)  to  fullfil  their  computing  requirements.  Among the  components  of  IaaS  cloud  software  stack,  the resource  allocation  module  is  very  important  as  it selects suitable VMs and the place to execute VMs. This paper  focuses  on  studying  and  classifying  algorithms used  in  the  resource  allocation  module.  The  issues  of how to apply those algorithms are also discussed.

Cloud Computing Resource Schedule Strategy Based on PSO Algorithm

2014 ◽  
Vol 513-517 ◽  
pp. 1332-1336 ◽  
Author(s):  
Ying Yidu Xiong ◽  
Yan Yan Wu
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Virtual Machines ◽  
Scheduling Algorithms ◽  
Pso Algorithm ◽  
Dynamic Adaptation ◽  
The Core ◽  
Schedule Strategy ◽  
Core Technology ◽  
Resource Schedule

Resource schedule Strategy is the core technology of cloud computing. PSO algorithm is one of dynamic adaptation resource scheduling algorithms to cloud computing. The virtual machines and the hosts can be scheduled reasonable by adjusting parameters. The resource can be scheduled quickly because of the dynamic trend calculation of PSO algorithm, to ensure real-time of the Cloud Calculation.

scholarly journals The Needs of Virtual Machines Implementation in Private Cloud Computing Environment

2015 ◽  
Vol 6 (4) ◽  
pp. 525
Author(s):  
Edy Kristianto
Keyword(s):  
Cloud Computing ◽  
Information And Communication Technology ◽  
Communication Technology ◽  
Virtual Machines ◽  
Computing Environment ◽  
Infrastructure As A Service ◽  
Cloud Computing Environment ◽  
Information And Communication ◽  
Private Cloud Computing ◽  
The Internet Of Things

The Internet of Things (IOT) becomes the purpose of the development of information and communication technology. Cloud computing has a very important role in supporting the IOT, because cloud computing allows to provide services in the form of infrastructure (IaaS), platform (PaaS), and Software (SaaS) for its users. One of the fundamental services is infrastructure as a service (IaaS). This study analyzed the requirement that there must be based on a framework of NIST to realize infrastructure as a service in the form of a virtual machine to be built in a cloud computing environment.

scholarly journals On dynamic performance estimation of fault-prone Infrastructure-as-a-Service clouds

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771771851 ◽  
Author(s):  
Wanbo Zheng ◽  
Yuandou Wang ◽  
Yunni Xia ◽  
Quanwang Wu ◽  
Lei Wu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Analytical Approach ◽  
Virtual Machines ◽  
Dynamic Performance ◽  
Rejection Rate ◽  
Performance Estimation ◽  
Variable Load ◽  
Infrastructure As A Service ◽  
Trend Prediction ◽  
Prediction Approach

The cloud computing paradigm enables elastic resources to be scaled at run time satisfy customers’ demand. Cloud computing provisions on-demand service to users based on a pay-as-you-go manner. This novel paradigm enables cloud users or tenant users to afford computational resources in the form of virtual machines as utilities, just like electricity, instead of paying for and building computing infrastructures by their own. Performance usually specified through service level agreement performance commitment of clouds is one of key research challenges and draws great research interests. Thus, performance issues of cloud infrastructures have been receiving considerable interest by both researchers and practitioners as a prominent activity for improving cloud quality. This work develops an analytical approach to dynamic performance modeling and trend prediction of fault-prone Infrastructure-as-a-Service clouds. The proposed analytical approach is based on a time-series and stochastic-process-based model. It is capable of predicting the expected system responsiveness and request rejection rate under variable load intensities, fault frequencies, multiplexing abilities, and instantiation processing times. A comparative study between theoretical and measured performance results through a real-world campus cloud is carried out to prove the correctness and accuracy of the proposed prediction approach.

scholarly journals A REVIEW ON TASK ALLOCATION PERFORMANCE ISSUES IN CLOUD ENVIRONMENT

2017 ◽  
Vol 16 (3) ◽  
pp. 6225-6232
Author(s):  
Kavita Redishettywar ◽  
Prof. Rafik Juber Thekiya
Keyword(s):  
Cloud Computing ◽  
Task Allocation ◽  
Virtual Machines ◽  
Bottom Layer ◽  
Computer Hardware ◽  
Cloud Environment ◽  
Core Concept ◽  
The Core ◽  
Load Imbalance ◽  
Cloud Server

Cloud computing is an emerging paradigm in the computer industry where the computing is moved to a cloud of computers. It has become one of the buzz words of the industry. The core concept of cloud computing is, quite simply, that the vast computing resources that we need will reside somewhere out there in the cloud of computers and we’ll connect to them and use them as and when needed. Computing can be described as any activity of using and/or developing computer hardware and software. It includes everything that sits in the bottom layer, i.e. everything from raw compute power to storage capabilities. Cloud computing ties together all these entities and delivers them as a single integrated entity under its own sophisticated management. Load balancing is a mechanism that distributes the dynamic workload equally across over the nodes or virtual machines within the whole cloud server to avoid a state of conflict wherever some virtual machines are measured as heavily loaded whereas others nodes or hosts are measured as idle or doing very little work. It helps to realize a high client satisfaction and resource utilization magnitude relation, consequently increasing the performance and resource utility of the system. It additionally makes sure that each computing resource in the cloud server is distributed with efficiently and fairly among all the requests of the client. It additionally prevents bottlenecks of the system which can occur because of load imbalance.

scholarly journals Virtual machines migration game approach for multi-tier application in infrastructure as a service cloud computing

IET Networks ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 326-337
Author(s):  
Khiet Thanh Bui ◽  
Hung Dac Ho ◽  
Tran Vu Pham ◽  
Hung Cong Tran
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Infrastructure As A Service ◽  
Service Cloud
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