scholarly journals Load Aware Hotspot Selection for SLA Improvement in Cloud Computing and Protect Environment by Reduction In CO2 Emissions

2021 ◽  
Vol 889 (1) ◽  
pp. 012028
Author(s):  
A.P Vaneet Kumar ◽  
Balkrishan Jindal
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Virtual Machines ◽  
Everyday Objects ◽  
Proposed Model ◽  
Classical Models ◽  
Computer Based ◽  
Selection For ◽  
Cloud Users ◽  
Vm Consolidation

Abstract Internet of Things (IoT) is a leading concept that envisions everyday objects around us as a part of internet. In order to accomplish this attribution, cloud computing provides a pathway to deliver all the promises with IoT enabled devices. The outbreak of COVID-19 coronavirus, namely SARS-CoV-2, acts as feather to the cap for the growth of Cloud users. With the increasing traffic of applications on cloud computing infrastructure and the explosion in data center sizes, QoS along with energy efficiency to protect environment, reducing CO2 emissions is need of the hour. This strategy is typically achieved using Three Layer upper Threshold (TLTHR) policy to analyze and perform VM consolidation. The proposed model controls number of migrations by placement of virtual machines, based on VMs and their utilization capacity on host. The efficacy of the proposed technique is exhibited by comparing it with other baseline algorithms using computer based simulation. Hence better QoS and energy efficiency has been obtained than other classical models.

scholarly journals VM Consolidation Plan for Improving the Energy Efficiency of Cloud

2021 ◽  
Vol 21 (3) ◽  
pp. 145-159
Author(s):  
Satveer ◽  
Mahendra Singh Aswal
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Service Level ◽  
Sla Violation ◽  
Dynamic Consolidation ◽  
Cloud Datacenter ◽  
Cloud Users ◽  
Vm Consolidation

Abstract Achieving energy-efficiency with minimal Service Level Agreement (SLA) violation constraint is a major challenge in cloud datacenters owing to financial and environmental concerns. The static consolidation of Virtual Machines (VMs) is not much significant in recent time and has become outdated because of the unpredicted workload of cloud users. In this paper, a dynamic consolidation plan is proposed to optimize the energy consumption of the cloud datacenter. The proposed plan encompasses algorithms for VM selection and VM placement. The VM selection algorithm estimates power consumption of each VM to select the required VMs for migration from the overloaded Physical Machine (PM). The proposed VM allocation algorithm estimates the net increase in Imbalance Utilization Value (IUV) and power consumption of a PM, in advance before allocating the VM. The analysis of simulation results suggests that the proposed dynamic consolidation plan outperforms other state of arts.

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 A Threshold-based Tournament Resource Allocation in Cloud Computing Environment

2021 ◽  
pp. 1-13
Author(s):  
I. P. Oladoja ◽  
O. S. Adewale ◽  
S. A. Oluwadare ◽  
E. O. Oyekanmi
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Selection Probability ◽  
Cloud Computing Environment ◽  
High Resource ◽  
Performance Requirements ◽  
Tournament Selection ◽  
Computing Environments ◽  
Cloud Users

Cloud computing environments provide an apparition of infinite computing resources to cloud users so that they can increase or decrease resource consumption rate according to their demands. In the Cloud, computing resources need to be allocated and scheduled in a way that providers can achieve high resource utilization and users can meet their applications’ performance requirements with minimum expenditure. Due to these different intentions, there is the need to develop a scheduling algorithm to outperform appropriate allocation of tasks on resources. The paper focuses on the resource optimization using a threshold-based tournament selection probability for virtual machines used in the execution of tasks. The proposed approach was designed to create metatask and the proposed algorithm used was Median-Based improved Max-Min algorithm. The experimental results showed that the algorithm had better performance in terms of makespan, utilization of resources and throughput. The load balance of tasks was also fairly distributed on the two datacenters.

scholarly journals Enhance the Security of Data Storage and Retrieval in Cloud Computing Through Authentication Based Encryption

2019 ◽  
Vol 8 (4) ◽  
pp. 11927-11931
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Virtual Machines ◽  
Public Key ◽  
Sensitive Data ◽  
Cloud Data ◽  
Finger Print ◽  
Additional Level ◽  
Cloud Users ◽  
Cloud User

The digital computing infrastructure is rapidly moving towards cloud based architecture. The protection of data is becoming a difficult task in the current scenario as more and more confidential and sensitive data is stored in cloud environment and transmitted between cloud users. In a cloud computing environment, the entire data reside over a set of networked resources of remote servers and locations. These data has been accessed by unauthorized cloud users through virtual machines. To provide additional level of cloud data security, Biometric based authentication with encryption using public key cryptography is proposed in this paper. The proposed model Authentication Based Encryption (ABE) helps to enhance the security of data as well as the authentication of cloud user. The sensitive data is initially encrypted and then stored secretly with biometric finger print image. The resultant image is transmitted through the in-secured channel. However to avoid unauthorized access, the image is decomposed and stored in cloud separately as encrypted message and finger print. Before beginning the decryption process, the finger print of the cloud user is being compared with the stored image for authentication. If the match is found, the encrypted data is decrypted by the authenticated cloud user. Otherwise access to the data is denied to ensure security. Thus, the proposed framework provides an additional level of protection to public key algorithm with authentication

scholarly journals Fog-based Spider Web Algorithm to Overcome Latency in Cloud Computing

2020 ◽  
pp. 1781-1790
Author(s):  
ABDUL RASHID DAR ◽  
D Ravindran ◽  
Shahidul Islam
Keyword(s):  
Cloud Computing ◽  
Web Applications ◽  
Virtual Machines ◽  
Fog Computing ◽  
Network Reduction ◽  
Spider Web ◽  
Network Bandwidth ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Cloud Users

The cloud-users are getting impatient by experiencing the delays in loading the content of the web applications over the internet, which is usually caused by the complex latency while accessing the cloud datacenters distant from the cloud-users. It is becoming a catastrophic situation in availing the services and applications over the cloud-centric network. In cloud, workload is distributed across the multiple layers which also increases the latency. Time-sensitive Internet of Things (IoT) applications and services, usually in a cloud platform, are running over various virtual machines (VM’s) and possess high complexities while interacting. They face difficulties in the consolidations of the various applications containing heterogenetic workloads. Fog computing takes the cloud computing services to the edge-network, where computation, communication and storage are within the proximity to the end-user’s edge devices. Thus, it utilizes the maximum network bandwidth, enriches the mobility, and lowers the latency. It is a futuristic, convenient and more reliable platform to overcome the cloud computing issues. In this manuscript, we propose a Fog-based Spider Web Algorithm (FSWA), a heuristic approach which reduces the delays time (DT) and enhances the response time (RT) during the workflow among the various edge nodes across the fog network. The main purpose is to trace and locate the nearest f-node for computation and to reduce the latency across the various nodes in a network. Reduction of latency will enhance the quality of service (QoS) parameters, smooth resource distribution, and services availability. Latency can be an important factor for resource optimization issues in distributed computing environments. In comparison to the cloud computing, the latency in fog computing is much improved.

scholarly journals Elastic Technique for Load Balancing in Cloud Computing

2020 ◽  
Vol 8 (6) ◽  
pp. 1123-1127
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Service Level ◽  
Advanced Technology ◽  
Service Provisioning ◽  
Web Traffic ◽  
Cloud Environments ◽  
Cloud Users

The cloud computing is the architecture that is decentralized in nature due to which various issues in the network get raised which reduces its efficiency. The exchange of data over the network is also continuously increasing. New advanced technology, cloud computing is becoming popular because of providing the above services beneficially. Other vital technologies like virtualization and scalability by designing virtual machines in cloud computing. In cloud computing, web traffic and service provisioning are increasing day by day, so load balancing is becoming a big research issue in cloud computing. Cloud Computing is a new propensity emerging in the IT environment within huge requirements of infrastructure and resources. The load Balancing technique for cloud computing is a vital aspect of the cloud computing environment. Peerless Load balancing scheme ensures splendid resource utilization by provisioning resources to cloud users on-demand services basis in a pay-as-you-use manner. The technique of Load Balancing may further support prioritizing requests of users/clients by applying appropriate scheduling criteria. This paper presents various load balancing schemes in different cloud environments based on requirements specified in the Service Level Agreement (SLA).

A Cloud-Based Environment for Collaborative Resources Management

2014 ◽  
Vol 4 (4) ◽  
pp. 7-31 ◽  
Author(s):  
Anna Goy ◽  
Giovanna Petrone ◽  
Marino Segnan
Keyword(s):  
Cloud Computing ◽  
Web 2.0 ◽  
Interaction Model ◽  
Controlled Experiments ◽  
Collaborative Environments ◽  
Resources Management ◽  
Digital Devices ◽  
Heterogeneous Objects ◽  
Proposed Model ◽  
Cloud Users

The interaction between users and digital devices has deeply changed in the last decades. In particular, the so called desktop metaphor relied on assumptions which have been modified by the rise of new paradigms, such as Web 2.0 and Cloud Computing. This paper discusses the limits of the desktop metaphor and proposes a new interaction model, TablePlusPlus (T++), aimed at providing Web and Cloud users with interaction mechanisms fulfilling their needs, i.e., the possibility of handling activity contexts, collaborating with other users, and homogeneously managing heterogeneous objects. T++ tables provide a context-based environment which enables a homogeneous treatment of heterogeneous content items, enhanced by a table-level annotation mechanism supporting an abstract view over resources, which is missing in standard current desktop and collaborative environments. In order to evaluate the effectiveness of the proposed model, this work developed a prototype and tested it in two controlled experiments, whose results are definitely encouraging.

scholarly journals A Heuristic Research of the Designing and Evaluation of Energy Efficiency using Dynamic VM Consolidation in Green Cloud Data Centres

2019 ◽  
Vol 8 (6S4) ◽  
pp. 1532-1540
Keyword(s):  
Carbon Dioxide ◽  
Energy Efficiency ◽  
Quality Of Service ◽  
Virtual Machines ◽  
Web Based ◽  
Cloud Data ◽  
The Earth ◽  
Data Centres ◽  
Vm Consolidation

Allotted computing is a blasting innovation that tenders effective assets, and smooth accessibility through web based processing. however, the growing wishes of clients for such administrations are convincing the cloud professional corporations to send huge portions of strength hungry server farms which element awful effect to the earth with the aid of the usage of plenteous Carbon Dioxide discharge. To limit control usage and strengthen the quality of service (QoS) inside the server farm assesses the strength usage in an assortment of plans in IaaS of dispensed computing situation. Dynamic Virtual Machines’ Consolidation and Placement(DVMCP) is an in a position strategies for enhancing using assets and proficient power usage in Cloud DataCenters. in this exploration, we proposed a calculation, Energy Conscious Greeny Cloud Dynamic (ECGCD) set of rules that accomplishes live VM relocation that is turning off the inert has or located it to lowcontrol mode (i.e., rest or hibernation),that builds up power productivity and succesful usage of property in the dynamic hosts. The take a look at stop result confirmations with duplicate that, the proposed calculation achieves good sized diploma of lower in electricity usage in correlation with the modern-day-day VM combination calculations.

scholarly journals Privacy Preserving Auction Based Virtual Machine Instances Allocation Scheme for Cloud Computing Environment

2017 ◽  
Vol 7 (5) ◽  
pp. 2645
Author(s):  
Suneeta Mohanty ◽  
Prasant Kumar Pattnaik ◽  
G. B. Mund
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Cloud Service ◽  
Computing Environment ◽  
Cloud Service Provider ◽  
Cloud Computing Environment ◽  
The Individual ◽  
Cloud Users ◽  
Yao’S Protocol

<p>Cloud Computing Environment provides computing resources in the form of Virtual Machines (VMs), to the cloud users through Internet. Auction-based VM instances allocation allows different cloud users to participate in an auction for a bundle of Virtual Machine instances where the user with the highest bid value will be selected as the winner by the auctioneer (Cloud Service Provider) to gain more. In this auction mechanism, individual bid values are revealed to the auctioneer in order to select the winner as a result of which privacy of bid values are lost. In this paper, we proposed an auction scheme to select the winner without revealing the individual bid values to the auctioneer to maintain privacy of bid values. The winner will get the access to the bundle of VM instances. This  scheme relies on a set of cryptographic protocols including Oblivious Transfer (OT) protocol and Yao’s protocol to maintain privacy of bid values.</p>

scholarly journals Energy Efficient and VM Consolidation Framework using Improved Spider Monkey Optimization Algorithm

2021 ◽  
Vol 10 (3) ◽  
pp. 21-26
Author(s):  
Kethavath Prem Kumar ◽  
◽  
Thirumalaisamy Ragunathan ◽  
Devara Vasumathi ◽  
◽  
...  
Keyword(s):  
Cloud Computing ◽  
Energy Efficient ◽  
Data Centers ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Service Level ◽  
Energy Usage ◽  
Energy Efficient Computing ◽  
Spider Monkey Optimization ◽  
Vm Consolidation

Cloud Computing is rapidly being utilized to operate informational technological services by outstanding technologies for a variety of benefits, including dynamically improved resources planning and a new service delivery method. The Cloud computing process is occurred by allowing the client devices for data access through the internet from a remote server, computers, and the databases. An internet connection is linked among the front end users such as client device, network, browser, and software application with the back end that constitutes of servers, computers, and database. For satisfying the demands of the Service Level Agreement (SLA), providers of cloud service should reduce the usage of energy. Capacity reservations oriented system is available by clouds’ providers to permit users for customizing Virtual Machines (VMs) having specified age and geographic resources, reduces the amount to be paid for cloud services. To overcome the aforementioned issue, an Improved Spider Monkey Optimization (ISMO) approach is proposed for cloud center optimization. The VM consolidation architecture based on the proposed ISMO algorithm decreases energy usage while attempting to prevent Service Level Agreement breaches. The accessibility of hosts or virtual machines (VMs) for task performance is measured by fitness. If the number of tasks to be handled increases the hosts of VMs available at right state. The proposed VM consolidation architecture decreases energy usage while also attempting to prevent Service Level Agreement breaches and also provide energy-efficient computing in data centers. The proposed approach may be utilized to provide energy-efficient computing in data centers. The energy efficiency of the proposed ISMO method is achieved 28266 whereas, the existing algorithm showed an energy efficiency of 6009 and 10001.

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