2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)最新文献

{"title":"IEEE CloudCom 2022 Technical Program Committee","authors":"","doi":"10.1109/cloudcom55334.2022.00010","DOIUrl":"https://doi.org/10.1109/cloudcom55334.2022.00010","url":null,"abstract":"","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123810074","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":"HPA: Hierarchical Placement Algorithm for Multi-Cloud Microservices Applications","authors":"HanTing Liang, J. Chou","doi":"10.1109/CloudCom55334.2022.00013","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00013","url":null,"abstract":"Microservices have become a popular way to develop and operate complex (mostly web-based) applications by decomposing software into small loosely coupled services communicating over well-defined APIs. It offers several benefits, including manageability, flexibility and scalability to name a few. However, the orchestration of microservices also becomes more complex and challenging. One of the critical problems is the placement of services which can greatly affect the communication cost and application performance. Especially, with the growing trend of multi-cloud adaptation for enterprise companies, the scale and impact of the placement problem also grows significantly. To tackle the problem, we conduct experiments on public cloud (AWS) to analyze and model the performance impact of placement decision. Then we propose a Hierarchical Placement algorithm (HPA), combining genetic algorithm and spectral clustering technique, to achieve fast and accurate placement decision. Our evaluation results reveal that HPA reduces the service request turn-around time of random placement by up to 44.66%, and only 16% slower than the optimal solution obtained by an ILP solver.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114224392","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":"Message from the OpenIaC Workshop Chairs","authors":"","doi":"10.1109/cloudcom55334.2022.00008","DOIUrl":"https://doi.org/10.1109/cloudcom55334.2022.00008","url":null,"abstract":"","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125843791","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":"Decentralizing Machine Learning Operations using Web3 for IoT Platforms","authors":"John Wickström, M. Westerlund, E. Raj","doi":"10.1109/CloudCom55334.2022.00041","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00041","url":null,"abstract":"Combining machine learning with IoT offers new and exciting possibilities for service innovation. A core challenge for such systems is model training and pipeline monitoring/management while not revealing sensitive data or introducing new attack points. Innovative solutions that reveal network structure and topology are often in conflict with security/privacy design principles. In this paper, we consider the system communication between sensors, edge, and the cloud that does not reveal the origin source or destination of the data. A core contribution is how to apply Machine Learning Operations (MLOps) to decentralized architectures that are not under the direct control of a service provider. The aim is to decouple the Machine Learning (ML) solution, data platform, and sensors while avoiding service level degradation. We utilize an unlinkable end-to-end encrypted asynchronous communication protocol called Whisper that is based on the Ethereum blockchain to achieve sender and receiver anonymity. The Whisper protocol provides a level of darkness that maintains anonymity in communication.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130245707","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":"A Survey on Autonomic Multi-cloud Computing","authors":"Diego Cananea Nobrega De Azevedo, C. Ferraz","doi":"10.1109/CloudCom55334.2022.00015","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00015","url":null,"abstract":"Multi-cloud computing has emerged in the last years to address problems like avoiding vendor lock-in and improving resilience in cloud computing. Recent reports have shown a growing interest from companies in this type of technology. On the other hand, architecting and managing a multi-cloud environment is more complex and brings challenges to be tackled. This work aims to understand how autonomic computing (AC) can help to solve multi-cloud problems. We surveyed six research databases and applied a methodology using objective criteria to select studies and analyze them. The results showed that complexity is the main reason for using AC. In addition, we found that most solutions are reactive and use static thresholds. Among the challenges, we noticed that a factor is the lack of standardization in both areas.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"298 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115931175","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":"GPU Performance Tuning and Power Efficiency on the DGX A100 Cluster","authors":"Khanin Udomchoksakul, Orathai Sangpetch, Akkarit Sangpetch","doi":"10.1109/CloudCom55334.2022.00033","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00033","url":null,"abstract":"The complexity of current Deep learning has been growing rapidly nowadays. Such advancement allows various organizations such as private sectors and government to leverage intelligent systems on their use cases. High Performance Computing (HPC) infrastructure nowadays has pivoted to GPU-oriented systems, enabling developers and researchers to train complex models with large datasets unlike conventional clusters equipped only with CPU cores. However, focus on power efficiency on the HPC system has not been prevalent especially on the new system such as DGX A100 that does not have datapoints on how GPUs consumed power. Even though such HPC cluster can be powerful, always allowing it to run at the maximum capacity results to financial cost to the HPC provider at the end. Therefore, for any organization providing the system, it is crucial for them to balance the cluster capabilities while maintaining overall power consumption which can potentially be costly in the long term. This paper reveals A100 GPU metrics that are relevant to Power usage and explains GPU profiling applied to Deep learning workload on the cluster, saving up to 32% of the power usage while compromising only 11.5% of training time compared to a default profile. Then, the paper investigates literature review that could be learned further adopted to the current system at CMKL university as the next milestone.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116627022","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":"FVMM: Fast VM Migration for Virtualization-based Fault Tolerance Using Templates","authors":"Wen-hsiu Tsai, Po-Jui Tsao, Che-Rung Lee","doi":"10.1109/CloudCom55334.2022.00012","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00012","url":null,"abstract":"In the era of cloud computing, virtualization based fault tolerance that utilizes the continuous virtual machine (VM) migration to synchronize a VM and its remote replica is a common technique to achieve high availability. However, traditional live VM migration, whose goal is to minimize the system downtime, has a long duration owing to the expense of the pre-copy for machine status and memory content, which increases the period of failover when failures occur. In this paper, we proposed a new VM migration method, called Fast VM Migration (FVMM), which utilizes the templating technique to accelerate the VM migration by reducing the cost of pre-copy. The templating technique that creates VMs from a master copy, called a template, is a usually used to deploy many similar VMs in a large virtual environment. FVMM employs VM templating to mitigate the cost of pre-copy. Its implementation is optimized with six new techniques: SFVMM and LFVMM, COW templating, continuous templating, asynchronous transmission buffering, VM recovery from continuous templating, and templating regularly. We also applied FVMM for virtualization based fault tolerance to accelerate the failover process. Experimental results show that FVMM is more than 56 times faster than pre-copy live migration for a VM with 16GB, and can reduce upto 32% of the system downtime and the fault tolerance resynchronization time comparing to the methods using pre-copy live migration.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122707655","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":"Privacy and security challenges for autonomous agents : A study of two social humanoid service robots","authors":"Dennis Biström, Magnus Westerlund, B. Duncan, M. Jaatun","doi":"10.1109/CloudCom55334.2022.00040","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00040","url":null,"abstract":"The development of autonomous agents have gained renewed interest, largely due to the recent successes of machine learning. Social robots can be considered a special class of autonomous agents that are often intended to be integrated into sensitive environments. We present experiences from our work with two specific humanoid social service robots, and highlight how eschewing privacy and security by design principles leads to implementations with serious privacy and security flaws. The paper introduces the robots as platforms and their associated features, ecosystems and cloud platforms that are required for certain use cases or tasks. The paper encourages design aims for privacy and security, and then in this light studies the implementation from two different manufacturers. The results show a worrisome lack of design focus in handling privacy and security. The paper aims not to cover all the security flaws and possible mitigations, but does look closer into the use of the WebSocket protocol and it’s challenges when used for operational control. The conclusions of the paper provide insights on how manufacturers can rectify the discovered security flaws and presents key policies like accountability when it comes to implementing technical features of autonomous agents.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127767546","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":"Software Vulnerability Assessment: Vendor, Scanner, and User Analysis","authors":"Kietthibhum Boonchuay, Wachirawich Siripaktanakon, Orathai Sangpetch, Akkarit Sangpetch","doi":"10.1109/cloudcom55334.2022.00038","DOIUrl":"https://doi.org/10.1109/cloudcom55334.2022.00038","url":null,"abstract":"Given the complexity of existing software stacking on top of each other, many vulnerabilities are just waiting to be discovered. Certain vulnerabilities can lead to severe exploitation and loss. In this paper, we try to understand how safely we, as users, are against potential exploitations due to known vulnerabilities found in commonly used software. First, we assess the capability of current vulnerability scanners to detect known vulnerabilities. In our analysis, we use 6 months of the real vulnerability scanning log. Surprisingly, our analysis shows that the existing vulnerability scanners could take at least 2,999 days to discover 90% of the known vulnerabilities and 50% of the high-severity-level vulnerabilities could take 3,328 days to be discovered. Then, we evaluate the effectiveness of existing software vendors’ patching mechanisms by measuring how long the computing devices were exposed before being patched. Our investigation suggests where we should improve to lower the risk of exploitations.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132930864","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":"NFT as a proof of Digital Ownership-reward system integrated to a Secure Distributed Computing Blockchain Framework","authors":"Asahi Cantu, Jiahui Geng, Chunming Rong","doi":"10.1109/CloudCom55334.2022.00024","DOIUrl":"https://doi.org/10.1109/CloudCom55334.2022.00024","url":null,"abstract":"Today, the global economy is dependent on the Internet and computational resources. Although they are tightly interconnected, it is difficult to evaluate their degree of interdependence. Keeping up with the pace of technology can be a challenging task, mainly when updating the hardware and software infrastructure. Every day, corporations and governments are faced with this issue; most have been victims of cyber attacks, security breaches, and data leaks. The consequences are significant in monetary losses; damage remediation is unattainable, even impossible, in certain circumstances. The repercussions might include reputational damage, legal responsibility, and threats to national security (when attacks are carried out against critical infrastructures to control the resources of a country), to name a few. Similarly, data has become such an integral part of many industries that it is one of the most critical targets for attackers that often is encrypted by ransomware, stolen, or corrupted. Without data, many companies are not able to continue operating as they do. The combination of all these factors complicates the ability of organizations to cooperate, trust, and share information in efforts to research and develop solutions for industry and government.This work proposes a Blockchain-based infrastructure solution provided by “Hyperledger Fabric” technology for companies to securely transmit and share information using the latest encryption and data storage technologies operating on the model of distributed systems and smart contracts. By presenting unique digital assets as Non-Fungible Tokens (NFT), the infrastructure is able to trust the integrity of the data, while protecting it from counterfeiting. Through the use of a Blockchain-based file storage system known as IPFS, and by connecting all the relevant elements together through a web-based application, it is possible to demonstrate that the implementation of such systems is feasible, highly scalable and a useful tool that many organizations can utilize to create new work systems and worktflows for digital asset management.","PeriodicalId":282963,"journal":{"name":"2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"174 S399","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113973040","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}