2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS)最新文献_第9页

Enhancing Availability for the MEC Service: CVaR-based Computation Offloading 增强MEC服务的可用性:基于cvar的计算卸载

2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2020-12-01 DOI: 10.1109/ICPADS51040.2020.00053

Shengli Pan, Zhiyong Zhang, Tao Xue, Guangmin Hu

引用次数: 1

Mitigating Cross-Technology Interference in Heterogeneous Wireless Networks based on Deep Learning 基于深度学习的异构无线网络跨技术干扰抑制

2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2020-12-01 DOI: 10.1109/ICPADS51040.2020.00040

Weidong Zheng, Junmei Yao, Kaishun Wu

{"title":"Mitigating Cross-Technology Interference in Heterogeneous Wireless Networks based on Deep Learning","authors":"Weidong Zheng, Junmei Yao, Kaishun Wu","doi":"10.1109/ICPADS51040.2020.00040","DOIUrl":"https://doi.org/10.1109/ICPADS51040.2020.00040","url":null,"abstract":"With the prosperity of Internet of Things, a large number of heterogeneous wireless devices share the same unlicensed spectrum, leading to severe cross-technology interference (CTI). Especially, the transmission power asymmetry of heterogeneous devices will further deteriorate this problem, making the low-power devices prohibited from data transmission and starved. This paper proposes an enhanced CCA (E-CCA) mechanism to mitigate CTI, so as to improve the performance and fairness among heterogeneous networks. E-CCA contains a signal identification design based on deep learning to identify the signal type within a tolerable time duration, it also contains a CCA adaptive mechanism based on the signal type to avoid CTI. As a result, the ZigBee devices could compete for the channel with WiFi devices more fairly, and the network performance can be improved accordingly. We set up a testbed based on TelosB, a commercial ZigBee platform, and USRP N210, which can be used as the WiFi platform. With the collected signals through USRP N210, over 99.9% signal identification accuracy can be achieved even when the signal duration is tens of microseconds. Simulation results based on NS-3 shows that E-CCA can increase the ZigBee performance dramatically with little throughput degradation for WiFi.","PeriodicalId":196548,"journal":{"name":"2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123189304","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}

引用次数: 1

DyRAC: Cost-aware Resource Assignment and Provider Selection for Dynamic Cloud Workloads

2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2020-12-01 DOI: 10.1109/ICPADS51040.2020.00071

Yannis Sfakianakis, M. Marazakis, A. Bilas

{"title":"DyRAC: Cost-aware Resource Assignment and Provider Selection for Dynamic Cloud Workloads","authors":"Yannis Sfakianakis, M. Marazakis, A. Bilas","doi":"10.1109/ICPADS51040.2020.00071","DOIUrl":"https://doi.org/10.1109/ICPADS51040.2020.00071","url":null,"abstract":"A primary concern for cloud users is how to minimize the total cost of ownership of cloud services. This is not trivial to achieve due to workload dynamics. Users need to select the number, size, type of VMs, and the provider to host their services based on available offerings. To avoid the complexity of re-configuring a cloud service, related work commonly approaches cost minimization as a packing problem that minimizes the resources allocated to services. However, this approach does not consider two problem dimensions that can further reduce cost: (1) provider selection and (2) VM sizing. In this paper, we explore a more direct approach to cost minimization by adjusting the type, number, size of VM instances, and the provider of a cloud service (i.e. a service deployment) at runtime. Our goal is to identify the limits in service cost reduction by online re-deployment of cloud services. For this purpose, we design DyRAC, an adaptive resource assignment mechanism for cloud services that, given the resource demands of a cloud service, estimates the most cost-efficient deployment. Our evaluation implements four different resource assignment policies to provide insight into how our approach works, using VM configurations of actual offerings from main providers (AWS, GCP, Azure). Our experiments show that DyRAC reduces cost by up to 33% compared to typical strategies.","PeriodicalId":196548,"journal":{"name":"2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127650151","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}

引用次数: 1

D2D-Enabled Reliable Data Collection for Mobile Crowd Sensing 用于移动人群传感的d2d可靠数据收集

2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2020-12-01 DOI: 10.1109/ICPADS51040.2020.00033

Pengfei Wang, Zhen Yu, Chi Lin, Leyou Yang, Yaqing Hou, Qiang Zhang

{"title":"D2D-Enabled Reliable Data Collection for Mobile Crowd Sensing","authors":"Pengfei Wang, Zhen Yu, Chi Lin, Leyou Yang, Yaqing Hou, Qiang Zhang","doi":"10.1109/ICPADS51040.2020.00033","DOIUrl":"https://doi.org/10.1109/ICPADS51040.2020.00033","url":null,"abstract":"With increasing more powerful sensing capacities of mobile devices, the Mobile Crowd Sensing (MCS) system requires to collect larger sensing data from participants. Nevertheless, collecting such large volume of data will cost a lot for participants, base stations and MCS server. Even worse, some sensing data cannot satisfy the MCS sensing requirement due to the low quality and are filtered by the MCS server in clouds. Inspired by the D2D technique, where mobile devices can communicate directly with the help of the nearby base station, in 5G networks, we propose the Reliable Data Collection (RDC) algorithm to validate the generated sensing data at device sides in this paper. To be specific, the whole progress is formulated as a Probability problem of Discovering Reliable sensing data (PDR) at client sides, and Expectation Maximization (EM) is leveraged to devise the algorithm. Finally, the extensive simulations and real-world use case are conducted to evaluate the performance of RDC algorithm, and the result shows that RDC outperforms the other two benchmarks in estimating accuracy and saving data collection cost.","PeriodicalId":196548,"journal":{"name":"2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128147766","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}

引用次数: 6

Use of Genetic Programming Operators in Data Replication and Fault Tolerance 遗传规划算子在数据复制和容错中的应用

2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2020-12-01 DOI: 10.1109/ICPADS51040.2020.00047

Syed Mohtashim Abbas Bokhari, Oliver E. Theel

{"title":"Use of Genetic Programming Operators in Data Replication and Fault Tolerance","authors":"Syed Mohtashim Abbas Bokhari, Oliver E. Theel","doi":"10.1109/ICPADS51040.2020.00047","DOIUrl":"https://doi.org/10.1109/ICPADS51040.2020.00047","url":null,"abstract":"Distributed systems are a need of the current times to balance the workload since providing highly accessible data objects is of utmost importance. Faults hinder the availability of the data, thereby leading systems to fail. In this regard, data replication in distributed systems is a means to mask failures and mitigate any such possible hindrances in the availability of the data. This replicated behavior is then controlled by data replication strategies, but there are numerous scenarios reflecting different trade-offs between several quality metrics. It demands designing new replication strategies optimized for the given scenarios, which may be left unaddressed otherwise. This research, therefore, uses an automatic mechanism based on genetic programming to construct new optimized replication strategies (up-to-now) unknown. This mechanism uses a so-called voting structure of directed acyclic graphs (each representing a computer program) as a unified representation of replication strategies. These structures are interpreted by our general algorithm at run-time in order to derive respective quorums to manage replicated objects eventually. For this, the research particularly demonstrates the usefulness of various genetic operators through their instances, exploiting the heterogeneity between existing strategies, thereby creating innovative strategies flexibly. This mechanism creates new hybrid strategies and evolves them over several generations of evolution, to make them optimized while maintaining the consistency (validity) of the solutions. Our approach is very effective and extremely flexible to offer competitive results with respect to the contemporary strategies as well as generating novel strategies even with a slight use of relevant genetic operators.","PeriodicalId":196548,"journal":{"name":"2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121078870","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}

引用次数: 0

MPI Parallelization of NEUROiD Models Using Docker Swarm 基于Docker Swarm的神经网络模型的MPI并行化

2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2020-12-01 DOI: 10.1109/ICPADS51040.2020.00092

Raghu Sesha Iyengar, M. Raghavan

引用次数: 1

Virtual Machine Consolidation for NUMA Systems: A Hybrid Heuristic Grey Wolf Approach NUMA系统的虚拟机整合:一种混合启发式灰狼方法

2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2020-12-01 DOI: 10.1109/ICPADS51040.2020.00079

Kangli Hu, Weiwei Lin, Tiansheng Huang, Keqin Li, Like Ma

{"title":"Virtual Machine Consolidation for NUMA Systems: A Hybrid Heuristic Grey Wolf Approach","authors":"Kangli Hu, Weiwei Lin, Tiansheng Huang, Keqin Li, Like Ma","doi":"10.1109/ICPADS51040.2020.00079","DOIUrl":"https://doi.org/10.1109/ICPADS51040.2020.00079","url":null,"abstract":"Virtual machines consolidation is known as a powerful means to reduce the number of activated physical machines (PMs), so as to achieve energy-saving for the data centers. Although the consolidation technique is widely studied in non-NUMA systems, we could only trace a few studies targeting NUMA systems. But the virtual machines (VMs) deployment of NUMA systems is quite different from that of non-NUMA systems. More specifically, consolidating VMs in NUMA systems need to decide both target physical machines and NUMA architectures to host the VMs, and more complicated constraints originated from the real usage of NUMA systems that need to be considered. Being motivated by these challenges, we in this paper formally derive the system model according to the real business model of NUMA systems and based on which, we propose a hybrid heuristics swarm intelligence optimization algorithm HHGWA for an efficient solution. To do the evaluation, extensive simulations that integrate real VM and PM information are conducted, the result of which indicates a superior performance of our proposed algorithm.","PeriodicalId":196548,"journal":{"name":"2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126680703","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}

引用次数: 0

ABC: An Auction-Based Blockchain Consensus-Incentive Mechanism ABC:基于拍卖的区块链共识激励机制

2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2020-12-01 DOI: 10.1109/ICPADS51040.2020.00085

Zhengpeng Ai, Y. Liu, Xingwei Wang

引用次数: 4

Gecko: Guaranteeing Latency SLO on a Multi-Tenant Distributed Storage System Gecko:多租户分布式存储系统时延SLO保障

2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2020-12-01 DOI: 10.1109/ICPADS51040.2020.00051

Z. Leng, D. Jiang, Liuying Ma, Jin Xiong

{"title":"Gecko: Guaranteeing Latency SLO on a Multi-Tenant Distributed Storage System","authors":"Z. Leng, D. Jiang, Liuying Ma, Jin Xiong","doi":"10.1109/ICPADS51040.2020.00051","DOIUrl":"https://doi.org/10.1109/ICPADS51040.2020.00051","url":null,"abstract":"Meeting tail latency Service Level Objective (SLO) as well as achieving high resource utilization is important to distributed storage systems. Recent works adopt strict priority scheduling or constant rate limiting to provide SLO guarantee but cause under-utilization resources. To address this issue, we first analyze the relationship between workload burst and latency SLO. Based on burst patterns and latency SLOs, we classify tenants into two categories: Postponement-Tolerable tenant and Postponement-Intolerable tenant. We then explore the opportunity to improve resource utilization by carefully allocating resources to each tenant type. We design Rate-Limiting-Priority scheduling algorithm to limit the impact of high priority tenants on low priority ones. Meanwhile, we propose Postponement-Aware scheduling algorithm which allows Postponement-Intolerable tenants to preempt system capacity from Postponement-Tolerable tenants. This helps to increase resource utilization. We propose a latency SLO guarantee framework Gecko. Gecko guarantees multi-tenant latency SLOs via combining the two proposed scheduling algorithms together with an admission control strategy. We evaluate Gecko with real production traces and the results show that Gecko admits 44% more tenants on average than state-of-the-art techniques meanwhile guaranteeing latency SLO.","PeriodicalId":196548,"journal":{"name":"2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS)","volume":"81 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133124658","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}

引用次数: 1

Massively Parallel Causal Inference of Whole Brain Dynamics at Single Neuron Resolution 单神经元分辨率下全脑动力学的大规模并行因果推理

2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS) Pub Date : 2020-11-22 DOI: 10.1109/ICPADS51040.2020.00035

Wassapon Watanakeesuntorn, Keichi Takahashi, Koheix Ichikawa, Joseph Park, G. Sugihara, Ryousei Takano, J. Haga, G. Pao

引用次数: 5