Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
Browse
10 results
Search Results
Item A novel family genetic approach for virtual machine allocation(Elsevier B.V., 2015) Joseph, C.T.; Chandrasekaran, K.; Cyriac, R.The concept of virtualization forms the heart of systems like the Cloud and Grid. Efficiency of systems that employ virtualization greatly depends on the efficiency of the technique used to allocate the virtual machines to suitable hosts. The literature contains many evolutionary approaches to solve the virtual machine allocation problem, a broad category of which employ Genetic Algorithm. This paper proposes a novel technique to allocate virtual machines using the Family Gene approach. Experimental analysis proves that the proposed approach reduces energy consumption and the rate of migrations, and hence offers much scope for future research. © 2015 Published by Elsevier B.V.Item A Green Mechanism Design Approach to Automate Resource Procurement in Cloud(Elsevier, 2015) Ketankumar, D.C.; Verma, G.; Chandrasekaran, K.Cloud computing paradigm is emerging as the solution to all the infrastructure setup problems of IT industry. But the thriving demand of cloud infrastructure has increased the energy consumption of the data centers drastically. As the energy consumption of the data center rises, it leads us to high carbon emissions which are dangerous for the environment. In this paper, we propose a green cloud broker for resource procurement problem by considering the metrics of energy efficiency and environmental friendly operations of the cloud service provider. We use mechanism design methods to decide the allocation and payment for the submitted job dynamically. We perform experiments and show the results of comparisons of energy consumption and emission of greenhouse gases between the allocation decided by the proposed green cloud broker and a without taking the green metric into consideration. © 2015 The Authors.Item Energy Aware SLA with Classification of Jobs for Cloud Environment(Elsevier B.V., 2015) Joy, N.; Chandrasekaran, K.; Binu, A.The accelerated growth of the cloud eco-system is leading to the progress of new services, innovative ideas for the service replen- ishing and the newest interaction models both among the cloud providers and the customers which take advantage of the cloud resources. SLAs are one of the factors which allow for different interactions by keeping the objectives over privacy,QoS attributes and security constraints driving towards QoP attributes, the description of actions is needed in order to deliver the services ac- cording to the QoS attributes as expected by the customers. Energy aware SLAs extends the existing SLA agreements in order to include energy and carbon aware parameters. In this paper we propose an approach in order to relax certain jobs in a standardized way to obtain high energy consumption without disturbing the efficiency and availability of the system especially during the peak load times. The results for the above proposal are being discussed in this paper and were able to find that it is energy efficient. © 2015 The Authors.Item Analysis of MapReduce scheduling and its improvements in cloud environment(Institute of Electrical and Electronics Engineers Inc., 2015) D'Souza, S.; Chandrasekaran, K.MapReduce has become a prominent Parallel processing model used for analysing large scale data. MapReduce applications are increasingly being deployed in the cloud along with other applications sharing the same physical resources. In this scenario, efficient scheduling of MapReduce applications is of utmost importance. Also, MapReduce has to consider various other parameters like energy efficiency and meeting SLA goals besides achieving performance when executing jobs in cloud environments. In this work, we have classified MapReduce Scheduling as Cluster based Scheduling and Objective based Scheduling. We then summarize and analyse the different class of schedulers highlighting the strong points and limitations of each of the scheduling approaches. The Adaptive scheduling techniques provide dynamic resource management and meet performance goals. The Energy efficient scheduling techniques aim to cut data centre costs by using different approaches. Finally, we discuss the current challenges and future work. © 2015 IEEE.Item Monitoring and Management of Service Level Agreements in Cloud Computing(Institute of Electrical and Electronics Engineers Inc., 2015) Anithakumari, S.; Chandrasekaran, K.Cloud computing environment consists of various interactive entities like cloud service providers, cloud service brokers, cloud customers and end-users with different objectives and expectations. Service Level Agreements (SLAs) manage the relationship among cloud service providers and cloud consumers by defining the terms of the agreement for the participating entities and provide the basic ground for interactions among both the parties. In this work we proposed a framework to efficiently monitor and analyze the SLA parameters and tried to find out the possibility of occurrence of SLA violations. Also we implemented an adaptive resource allocation system by utilizing the results of predicted SLA violations. Our adaptive resource allocation system allocates computing resources to cloud applications and tries to reduce the occurrence of SLA violations, by allocating additional resources on the detection of possibility of occurrence of a violation. The experimental studies show that our proposed system works well in private cloud computing environment and gives more efficient results. © 2015 IEEE.Item Optimization-Aware scheduling in cloud computing(Association for Computing Machinery acmhelp@acm.org, 2016) Binu, A.; George, N.; Chandrasekaran, K.Cloud computing allows delivery of computational resources via internet. Some of the computational resources include signals, codes and physical resources. Cloud users require computational resources for execution of their tasks. The computational elements, when thoroughly assigned to the cloud users according to requirement facilitate an efficient scheduling mechanism. The efficiency is dependent on the parameters chosen to promote the assignment of task to resources. Here, computational cost is chosen as the optimization factor, and the solution with the least cost is selected as the best assignment. A Cuckoo Search inspired technique is used, and task assignment to resources is done by validating the solution with the least value of cost. © 2016 ACM.Item Negotiation and monitoring of service level agreements in cloud computing services(Springer Verlag service@springer.de, 2017) Anithakumari, S.; Chandrasekaran, K.SLAs are so significant in cloud computing because it establishes agreements between the cloud service providers and cloud consumers, about the quality of the providing service. SLA monitoring is the only available provision to check whether the agreed parties are following the agreement terms or not. A multistep SLA negotiation, which contains the selection of apt cloud service provider and the negotiation with the selected provider, is proposed here. An efficient SLA negotiation algorithm is also included in this negotiation method. Experimental evaluation shows that the proposed method is more efficient in resource allocation and it gives more revenue to the cloud providers. © Springer Science+Business Media Singapore 2017.Item Comparative study of simulation tools and challenging issues in cloud computing(Springer Verlag service@springer.de, 2018) Shishira, S.R.; Kandasamy, A.; Chandrasekaran, K.Resource Scheduling lays a key role in large-scale cloud applications. It is difficult for the developers to do an extensive research on all the issues in real time as it requires infrastructure which is beyond the control, also network condition cannot be predicted. Hence simulations are used which imitates the real time environment. There are various simulators developed for the research as it is difficult to maintain the infrastructure on premise. Thus to understand the tools in deep, we focused on five open source tools such as Cloudsim, CloudAnalyst, iCancloud, Greencloud and CloudSched. The above mentioned tools are compared based on the respective architecture, the process of simulation, structural elements and performance parameters. In the paper, we have also discussed some of the challenging issues among the tools for further research. © Springer Nature Singapore Pte Ltd. 2018.Item Adaptive resource allocation in interoperable cloud services(Springer Verlag, 2019) Anithakumari, S.; Chandrasekaran, K.Interoperable cloud computing is the one in which the services or resources of one cloud can be accessed by another cloud. The implementation of interoperable cloud architecture is a challenging one because various characteristics of the cloud computing environment need to be considered for its achievement. The aim of this work is to implement interoperable cloud computing with the awareness of service-level agreements and to provide adequate resources when shortage of resources occurs at one cloud while providing the agreed services to the user. To achieve this, we proposed a methodology of interoperability-based flexible resource management. Initially, the SLA templates of private and public cloud are mapped using the Soft TF-IDF metric with case-based reasoning (CBR) approach. Then, based on the mapped SLAs, different clusters of cloud providers are formed with the help of K-means clustering technique. And finally, if one of the cloud in a cluster faces the problem of resource shortage, the flexible resource allocation is provided through the adaptive dimensional search algorithm. © Springer Nature Singapore Pte Ltd. 2019.Item Allocation of cloud resources in a dynamic way using an sla-driven approach(Springer Verlag service@springer.de, 2019) Anithakumari, S.; Chandrasekaran, K.Cloud computing provides a wide access to complex applications running on virtualized hardware with its support for elastic resources that are available in an on-demand manner. In cloud environment, multiple users can request resources simultaneously and so it has to be made available to them in an efficient manner. For the efficient utilization, these computing resources can be dynamically configured according to varying workload. Here in this paper, we proposed an efficient resource management system to allocate elastic resources dynamically according to dynamic workload. © 2019, Springer Nature Singapore Pte Ltd.