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ICACT20220174 Question.1
Questioner: 201127091@fzu.edu.cn    2022-02-16 오후 11:50:45 		ICACT20220174 Answer.1
Answer by Auhor hieu.ln@ou.edu.vn   2022-02-16 오후 11:50:45
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The time complexity analysis of the RCBA algorithm is not given. complexity analysis of the RCBA algorithm can be seen in the Pseudocode of the algorithm. Based on the pseudocode and the schematic diagram of RCBA, we can easy calculate the complexity of the algorithm. Because the algorithm is real-time required, so far we focus more on the experimental results.
ICACT20220174 Question.2
Questioner: 201127091@fzu.edu.cn    2022-02-16 오후 11:54:12 		ICACT20220174 Answer.2
Answer by Auhor hieu.ln@ou.edu.vn   2022-02-16 오후 11:54:12
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This paper uses CloudSim as the simulation tool. Has it been tested on other tools such as CloudAnalyst, and what are the advantages of using CloudSim for this research? Actually, the CloudAnalyst is built on CloudSim, CloudSim is a library using JAVA to simulate cloud environments. This tool is world wide used for cloud researchers and cloud study. This cloudSim is A Framework For Modeling And Simulation Of Cloud Computing Infrastructures And Services,The Cloud Computing and Distributed Systems (CLOUDS) Laboratory, formerly GRIDS Lab, is a software research and development group within the School of Computing and Information Systems at the University of Melbourne, Australia.
ICACT20220174 Question.3
Questioner: 201127091@fzu.edu.cn    2022-02-16 오후 11:56:26 		ICACT20220174 Answer.3
Answer by Auhor hieu.ln@ou.edu.vn   2022-02-16 오후 11:56:26
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The size of the request is limited in the research model of this paper. Will it cause some other problems for the larger request? The size of our experiments are a bit limmited due to the complexity and flexibility of cloud environment. We want to test the small request and with its small variants. If we focus on lager requests, we need to do more enhancement, and it is also our future works.
ICACT20220174 Question.4
Questioner: tomayoon@ieee.org    2022-02-17 오전 12:00:16 		ICACT20220174 Answer.4
Answer by Auhor hieu.ln@ou.edu.vn   2022-02-17 오전 12:00:16
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First of all, thank you for the good research paper and presentation contents. I would like to know more about the research environment used in this study, and also in detail about the equipment & operating systems, development languages and software libraries you used. In this paper, we use CloudSim, a library built on JAVA langugae to simulate the cloud environments to have these experiments. CloudSim is A Framework For Modeling And Simulation Of Cloud Computing Infrastructures And Services, developed by School of Computing and Information Systems at the University of Melbourne, Australia. (http://cloudbus.org/intro.html). With cloudSim, you can simulate your cloud network with your configurations: datacenters, host config, vm configs.... Let’s take an example of AWS EC2 instance “t4g.micro” the configuration that it defines is vCPU 2 with consistent baseline compute availability of 10%, 1 GB RAM, up to 10 GB of EBS, and up to 5 Gbps of network bandwidth. Just like above the virtual machine configuration can be defined using a few lines of java code. The Virtual machine model behavior is implemented in Vm.java class. This class defines all the attributes like processing elements, RAM, Storage Size, Bandwidth, computation capacity, etc. The following snippet demonstrates how these attributes are initialized before the simulation process.
ICACT20220174 Question.5
Questioner: 201127091@fzu.edu.cn    2022-02-17 오전 12:03:20 		ICACT20220174 Answer.5
Answer by Auhor hieu.ln@ou.edu.vn   2022-02-17 오전 12:03:20
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Thank you for the good research paper and presentation contents.I would like to know more details about this research, I would be grateful if you could give the relevant youtube link. Our paper proposes an improvement using application of Naïve Bayes algorithm (based on Bayes theorem on probability theory to make judgments as well as classify data based on observed and statistical data) to improve the response time of VMs in the cloud, enhance the performance of cloud and cloud infrastructure. This new proposal is named as RCBA (Response Time Classification with Naive Bayes Algorithm). We simulated this proposed RCBA algorithm with the CloudSim engine and the result has improved from 4 popular load balancing algorithms: Round-Robin, FCFS, MaxMin and MinMin. the RCBA algorithm will use a loop to listen to all the Requests in the queue list of Requests sent to the load balancer (in this case, CloudRequests). Once this list is exhausted, it will no longer be distributed. In it, the algorithm uses the isLocated variable (logical type) to flag that the Request whether has been allocated or not. The first jump of the loop, the isLocated variable is set to false. Then, the algorithm calculates the new Response Time (predicted response time using Naïve Bayes), RT_new variable is to perform the Request in the current situation. This calculation is based on the historical data of previous requests RT1, RT2, … RTn where n is the number of requests that have been saved in the LB. Corresponding to each machine, we use the K-Means to cluster the situation of that VM, we get the VM_Cluster variable. The algorithm considers whether the virtual machine matches the predicted RT or not, through the isFitSituation(RT_new , VM_Cluster) function. If it is satisfied, it will allocate the request under consideration to that virtual machine AllocateRequestToVM(VM_Cluster, Request), and at the same time assign the variable isLoacated = true. If no matching virtual machine is found, the loop ends. At this point, the isLocated variable is still false, and now the Request has not been allocated. Therefore, the algorithm allocates this Request to the first VM which gets the nearest means, VM = VMList.getMinFromMean(). This allocation ensures that if any requests are predicted that are not in the data of the algorithm, they are still allocated and processed for the user. The historical data is always update after the completion of a request processing. We limit a number of requests depending on the requirement and the characteristic of the cloud users.