{"title":"An Improved Model for Live Migration in Data Centre Simulators","authors":"Vincenzo De Maio, G. Kecskeméti, R. Prodan","doi":"10.1145/2996890.2996892","DOIUrl":"https://doi.org/10.1145/2996890.2996892","url":null,"abstract":"Due to the difficulty of employing real data centres' infrastructure for assessing the effectiveness of energy-aware algorithms, many researchers resort to use simulation tools. These tools require precise and detailed models for virtualized data centres in order to deliver accurate results. In recent years, many models have been proposed, but most of them either do not consider energy consumption related to virtual machine (VM) migration or do not investigate some of the energy impacting components (e.g. CPU, network, storage). We propose a new model for data centre energy consumption that takes into account the previously omitted components and provides more accurate energy consumption predictions compared to other state-of-the-art solutions. We evaluate our model's accuracy in a comprehensive set of scenarios implemented in the combined GroudSim/DISSECT-CF simulator. With the use of these scenarios, we present a comparative analysis of our model with a similar state-of-the-art simulator. Our analysis revealed a significant improvement in accuracy (up to 42.5%) in the modelled energy consumption compared to a similar state-of-the-art simulator.","PeriodicalId":350701,"journal":{"name":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115948013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"TCloud: A Transparent Framework for Public Cloud Service Comparison","authors":"B. Muhammad-Bello, M. Aritsugi","doi":"10.1145/2996890.3007864","DOIUrl":"https://doi.org/10.1145/2996890.3007864","url":null,"abstract":"Whilst there are many attributes that need to be considered for cloud service selection, performance remains one of the most crucial aspects. Thus, we argue for a transparent cloud provider comparison framework in this study. We initiate the development of TCloud: a transparent framework for public cloud service comparison. Our framework helps prospective cloud users to decipher public cloud benchmarking data and appraise the performance of public cloud services relative to their performance goals. We carried out experiments on the real public cloud environment to implement our framework and demonstrated how prospective cloud users can use the TCloud framework in understanding how well virtualized public cloud resources meet their application requirements. Unlike previous studies, the TCloud framework presents a more realistic method of appraising the performance of virtualized resources in the public cloud. TCloud is unique in the sense that it collates public cloud benchmarking data and correlates the observed performance metrics to prospective cloud users' actual application workload requirements.","PeriodicalId":350701,"journal":{"name":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125466661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Handling the Uncertainty in Resource Performance for Executing Workflow Applications in Clouds","authors":"H. M. Fard, S. Ristov, R. Prodan","doi":"10.1145/2996890.2996902","DOIUrl":"https://doi.org/10.1145/2996890.2996902","url":null,"abstract":"Execution of workflow applications in Cloud environments involves many uncertainties because of elastic resource provisioning and unstable performance of multitenant virtual machines (VM) instances over time. These uncertainties are usually either neglected by existing researches, or modeled with some probability distribution function. To address this gap, we extend a multi-objective workflow scheduling algorithm (MOHEFT) in two directions: (1) to deal with the dynamic nature of Cloud environments offering a potentially infinite amount of on-demand resources, and (2) to consider robustness as an objective that mitigates the variability in VM performance over time. Our new robust model, called R-MOHEFT, considers uncertainty in processing times of workflow activities without a precise estimation or known distribution function within an uncertainty interval. We approach this scheduling problem as a three-objective optimisation that considers makespan, monetary cost, and robustness as simultaneous objectives of a commercial Cloud environment. Our new algorithm is able to estimate the Pareto optimal set of scheduling solutions that resist against fluctuations in processing times three times better than its MOHEFT predecessor, with a tradeoff of only 15% worse Pareto frontier. R-MOHEFT's hypervolume suffers by only 5% to 16%, compared to the MOHEFT's drawback of 38% to surprisingly 87%, when the processing time fluctuates up to its double value.","PeriodicalId":350701,"journal":{"name":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126709870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Reverse Replication of Virtual Machines (rRVM) for Low Latency and High Availability Services","authors":"Muyang He, Shaoning Pang, Denis Lavrov, Ding Lu, Yuan Zhang, A. Sarrafzadeh","doi":"10.1145/2996890.2996894","DOIUrl":"https://doi.org/10.1145/2996890.2996894","url":null,"abstract":"Virtualization supplies a straightforward approach to high availability through iterative replications of virtual machine (VM) checkpoints that encapsulate the protected services. Unfortunately, traditional VM replication solutions suffer from deficiencies in either response latency or state recovery consistency, which constrains the adoption of VM replication in production. In this paper, we extend the function of the secondary host to be the primary recipient of network requests so that the state of the primary VM (PVM) is retained by the secondary host in the form of network packets. In doing this, we redesign the typical consistency model and network architecture for virtual machine replication. Specifically, the secondary host is set for network redirection and packets recording. Should the primary host fail, the recorded packets are used to recreate the state on the secondary host. Experiments in this research demonstrate simultaneously strong recovery consistency and low response latency in our real-time fault tolerance system. We name the system reverse replication of virtual machines (rRVM).","PeriodicalId":350701,"journal":{"name":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","volume":"09 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115293350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. H. Nunes, J. C. Estrella, A. Delbem, Charith Perera, S. Reiff-Marganiec
{"title":"The Effects of Relative Importance of User Constraints in Cloud of Things Resource Discovery: A Case Study","authors":"L. H. Nunes, J. C. Estrella, A. Delbem, Charith Perera, S. Reiff-Marganiec","doi":"10.1145/2996890.3007867","DOIUrl":"https://doi.org/10.1145/2996890.3007867","url":null,"abstract":"Over the last few years, the number of smart objects connected to the Internet has grown exponentially in comparison to the number of services and applications. The integration between Cloud Computing and Internet of Things, named as Cloud of Things, plays a key role in managing the connected things, their data and services. One of the main challenges in Cloud of Things is the resource discovery of the smart objects and their reuse in different contexts. Most of the existent work uses some kind of multi-criteria decision analysis algorithm to perform the resource discovery, but do not evaluate the impact that the user constraints has in the final solution. In this paper, we analyse the behaviour of the SAW, TOPSIS and VIKOR multi-objective decision analyses algorithms and the impact of user constraints on them. We evaluated the quality of the proposed solutions using the Pareto-optimality concept.","PeriodicalId":350701,"journal":{"name":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","volume":"315 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115833838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}