An Ensemble of Bacterial Foraging, Genetic, Ant Colony and Particle Swarm Approach eB-GAP: A Load Balancing Approach in Cloud Computing

2020 ◽  
Vol 13 ◽  
Author(s):  
Bhupesh Kumar Dewangan ◽  
Anurag Jain ◽  
Ram Narayan Shukla ◽  
Tanupriya Choudhury
Keyword(s):  
Load Balancing ◽  
Real Time ◽  
Virtual Machine ◽  
Service Level Agreement ◽  
Particle Swarm ◽  
Service Level ◽  
Ant Colony ◽  
Cloud Environment ◽  
Efficient Manner ◽  
Fitness Value

Background: In the cloud environment, satisfaction of service level agreement (SLA) is the prime objective. It can be achieved by providing services in minimum time in an efficient manner at the lowest cost by efficiently utilizing the resources. This will create a win-win situation for both consumer and service provider. Through literature analysis, it has been found that the procedure of resource optimization is quite costly and time-consuming. Objective: The research aim is to design and develop an efficient load-balancing technique for the satisfaction of service level agreement and the utilization of resources in an efficient manner. Methods: To achieve this, authors have proposed a new load-balancing algorithm named eB-GAP by picking the best features from Bacterial Foraging, Genetic, Particle-Swarm, and Ant-Colony algorithm. Based on the availability of resources and load on a virtual machine, a fitness value is assigned to all virtual machines. Results: A newly arrived task is mapped with the fittest virtual machine. Whenever a new task is mapped or left the system, the fitness value of the virtual machine is updated. In this manner, the system achieves the satisfaction of service level agreement, the balance of the load, and efficient utilization of resources. To test the proposed approach, the authors have used the real-time cloud environment of amazon web service. In this, waiting time, completion time, execution time, throughput, and cost have been computed in a real-time environment.

An Software Defined Network Based Secured Model for Malicious Virtual Machine Detection in Cloud Environment

2020 ◽  
Vol 17 (1) ◽  
pp. 526-530
Author(s):  
H. M. Anitha ◽  
P. Jayarekha
Keyword(s):  
Virtual Machine ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Service Level ◽  
Emerging Technology ◽  
Cloud Provider ◽  
Software Defined Network ◽  
Cloud Environment ◽  
Network Controller

Cloud computing is an emerging technology that offers the services to all the users as per their demand. Services are leveraged according to the Service level agreement (SLA). Service level agreement is monitored so that services are offered to the users without any problem and deprival. Software Defined Network (SDN) is used in order to monitor the trust score of the deployed Virtual Machines (VM) and Quality of Service (QoS) parameters offered. Software Defined Network controller is used to compute the trust score of the Virtual Machines and find whether Virtual Machine is malicious or trusted. Genetic algorithm is used to find the trusted Virtual Machine and release the resources allocated to the malicious Virtual Machine. This monitored information is intimated to cloud provider for further action. Security is enhanced by avoiding attacks from the malicious Virtual Machine in the cloud environment. The main objective of the paper is to enhance the security in the system using Software Defined Network based secured model.

Distance Aware VM allocation process to minimize energy consumption in cloud computing

2019 ◽  
Vol 12 ◽  
Author(s):  
Gurpreet Singh ◽  
Manish Mahajan ◽  
Rajni Mohana
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Research Work ◽  
Service Level Agreement ◽  
Service Level ◽  
Physical Machine ◽  
Allocation Process

BACKGROUND: Cloud computing is considered as an on-demand service resource with the applications towards data center on pay per user basis. For allocating the resources appropriately for the satisfaction of user needs, an effective and reliable resource allocation method is required. Because of the enhanced user demand, the allocation of resources has now considered as a complex and challenging task when a physical machine is overloaded, Virtual Machines share its load by utilizing the physical machine resources. Previous studies lack in energy consumption and time management while keeping the Virtual Machine at the different server in turned on state. AIM AND OBJECTIVE: The main aim of this research work is to propose an effective resource allocation scheme for allocating the Virtual Machine from an ad hoc sub server with Virtual Machines. EXECUTION MODEL: The execution of the research has been carried out into two sections, initially, the location of Virtual Machines and Physical Machine with the server has been taken place and subsequently, the cross-validation of allocation is addressed. For the sorting of Virtual Machines, Modified Best Fit Decreasing algorithm is used and Multi-Machine Job Scheduling is used while the placement process of jobs to an appropriate host. Artificial Neural Network as a classifier, has allocated jobs to the hosts. Measures, viz. Service Level Agreement violation and energy consumption are considered and fruitful results have been obtained with a 37.7 of reduction in energy consumption and 15% improvement in Service Level Agreement violation.

Broker-based optimization of SLA negotiations in cloud computing

2021 ◽  
Vol 17 (2) ◽  
pp. 179-195
Author(s):  
Priyanka Bharti ◽  
Rajeev Ranjan ◽  
Bhanu Prasad
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Environment ◽  
Negotiation Strategies ◽  
Sla Negotiation ◽  
Conflicting Interests ◽  
The Impact

Cloud computing provisions and allocates resources, in advance or real-time, to dynamic applications planned for execution. This is a challenging task as the Cloud-Service-Providers (CSPs) may not have sufficient resources at all times to satisfy the resource requests of the Cloud-Service-Users (CSUs). Further, the CSPs and CSUs have conflicting interests and may have different utilities. Service-Level-Agreement (SLA) negotiations among CSPs and CSUs can address these limitations. User Agents (UAs) negotiate for resources on behalf of the CSUs and help reduce the overall costs for the CSUs and enhance the resource utilization for the CSPs. This research proposes a broker-based mediation framework to optimize the SLA negotiation strategies between UAs and CSPs in Cloud environment. The impact of the proposed framework on utility, negotiation time, and request satisfaction are evaluated. The empirical results show that these strategies favor cooperative negotiation and achieve significantly higher utilities, higher satisfaction, and faster negotiation speed for all the entities involved in the negotiation.

Towards A Virtual Machine Migration Algorithm Based On Multi-Objective Optimization

2017 ◽  
Vol 8 (3) ◽  
pp. 79-89 ◽  
Author(s):  
Xiang Chen ◽  
Jun-rong Tang ◽  
Yong Zhang
Keyword(s):  
Energy Consumption ◽  
Virtual Machine ◽  
Resource Competition ◽  
Service Level Agreement ◽  
Service Level ◽  
Multi Objective Optimization ◽  
Virtual Machine Migration ◽  
Multi Objective ◽  
Time Migration ◽  
Management Method

In the cloud computing, the virtual machine (VM) dynamical management method needs to consider VM resource re-configuration caused by system computation resource status changing and load fluctuation. Based on migration objectives as QoS (Quality of Service), resource competition and energy consumption, the VM migration time, migration objective node selection and VM placement strategies are designed in this work. The Multi-Criteria Decision-Making (MCDM) method is also introduced for migration destination host selection. Experiment results show that the multi-objective optimization management method with TOPSIS can achieve lower service-level agreement (SLA) violation rate, less energy consumption and better balance among different objectives.

Dynamic Management of Resources in Cloud Computing

2020 ◽  
Vol 8 (1) ◽  
pp. 65-81 ◽  
Author(s):  
Pradeep Kumar Tiwari ◽  
Sandeep Joshi
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Service Level Agreement ◽  
Service Level ◽  
Poor Quality ◽  
Migration Time ◽  
Load Imbalance ◽  
Management Of Resources ◽  
And Migration

It has already been proven that VMs are over-utilized in the initial stages and are underutilized in the later stages. Due to the random utilization of the CPU, resources are sometimes heavily loaded whereas other resources are idle. Load imbalance causes service level agreement (SLA) violations resulting in poor quality of service (QoS) aided by the imperfect management of resources. An effective load balancing mechanism helps to achieve balanced utilization, which maximizes the throughput, availability, and reliability and reduces the response and migration time. The proposed algorithm can effectively minimize the response and the migration time and maximize reliability, and throughput. This research also helps to understand the load balancing policies and analysis of other research works.

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