2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW)最新文献_第5页

Machine Learning for Aggregate Computing: a Research Roadmap 聚合计算的机器学习:研究路线图

2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW) Pub Date : 2022-07-01 DOI: 10.1109/ICDCSW56584.2022.00032

Gianluca Aguzzi, Roberto Casadei, Mirko Viroli

{"title":"Machine Learning for Aggregate Computing: a Research Roadmap","authors":"Gianluca Aguzzi, Roberto Casadei, Mirko Viroli","doi":"10.1109/ICDCSW56584.2022.00032","DOIUrl":"https://doi.org/10.1109/ICDCSW56584.2022.00032","url":null,"abstract":"Aggregate computing is a macro-approach for programming collective intelligence and self-organisation in distributed systems. In this paradigm, a single “aggregate program” drives the collective behaviour of the system, provided that the agents follow an execution protocol consisting of asynchronous sense-compute-act rounds. For actual execution, a proper aggregate computing middleware or platform has to be deployed across the nodes of the target distributed system, to support the services needed for the execution of applications. Overall, the engineering of aggregate computing applications is a rich activity that spans multiple concerns including designing the aggregate program, developing reusable algorithms, detailing the execution model, and choosing a deployment based on available infrastructure. Traditionally, these activities have been carried out through ad-hoc designs and implementations tailored to specific contexts and goals. To overcome the complexity and cost of manually tailoring or fixing algorithms, execution details, and deployments, we propose to use machine learning techniques, to automatically create policies for applications and their management. To support such a goal, we detail a rich research roadmap, showing opportunities and challenges of integrating aggregate computing and learning.","PeriodicalId":357138,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123405615","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: 2

Decentralized Self-Adaption With Epidemic Algorithms for Agent-Based Transportation 基于agent的交通系统流行病算法的分散自适应

2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW) Pub Date : 2022-07-01 DOI: 10.1109/ICDCSW56584.2022.00028

S. Schmid, A. Harth

引用次数: 2

Enriching Kademlia by Partitioning 通过分割来丰富卡德米利亚

2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW) Pub Date : 2022-07-01 DOI: 10.1109/ICDCSW56584.2022.00016

João Monteiro, P. Costa, J. Leitao, Alfonso de la Rocha, Yiannis Psaras

{"title":"Enriching Kademlia by Partitioning","authors":"João Monteiro, P. Costa, J. Leitao, Alfonso de la Rocha, Yiannis Psaras","doi":"10.1109/ICDCSW56584.2022.00016","DOIUrl":"https://doi.org/10.1109/ICDCSW56584.2022.00016","url":null,"abstract":"Decentralizing the Web is becoming an increasingly interesting endeavor that aims at improving user security and privacy as well as providing guaranteed ownership of content. One such endeavor that pushes towards this reality, is Protocol Labs' Inter-Planetary File System (IPFS) network, that provides a decentralized large scale file system to support the decentralized Web. To achieve this, the IPFS network leverages the Kademlia DHT to route and store pointers to content stored by network members (i.e., peers). However, due to the large number of network peers, content, and accesses, the DHT routing needs to be efficient and quick to enable a decentralized web that is competitive. In this paper, we present work in progress that aims at improving the Kademlia DHT performance through the manipulation of DHT identifiers by adding prefixes to identifiers. With this, we are able to bias the DHT topological organization towards locality (which can be either geographical or applicational), which creates partitions in the DHT and enables faster and more efficient query resolution on local content. We designed prototypes that implement our proposal, and performed a first evaluation of our work in an emulated network testbed composed of 5000 nodes. Our results show that our proposal can benefit the DHT look up on data with locality with minimal overhead.","PeriodicalId":357138,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130332998","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: 2

You Only Look & Listen Once: Towards Fast and Accurate Visual Grounding 你只看和听一次:快速和准确的视觉基础

2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW) Pub Date : 2022-07-01 DOI: 10.1109/ICDCSW56584.2022.00035

Qing Du, Yucheng Luo

{"title":"You Only Look & Listen Once: Towards Fast and Accurate Visual Grounding","authors":"Qing Du, Yucheng Luo","doi":"10.1109/ICDCSW56584.2022.00035","DOIUrl":"https://doi.org/10.1109/ICDCSW56584.2022.00035","url":null,"abstract":"Visual Grounding (VG) aims to locate the most relevant region in an image, based on a flexible natural language query but not a pre-defined label, thus it can be a useful technique in practice. Most methods in VG operate in a two-stage manner, wherein the first stage an object detector is adopted to generate a set of object proposals from the input image and the second stage is simply formulated as a cross-modal matching problem. There might be hundreds of proposals produced in the first stage that need to be compared in the second stage, which is infeasible for real-time VG applications, and the performance of the second stage may be affected by the first stage. In this paper, we propose a much more elegant one-stage detection based method that joints the region proposal and matching stage as a single detection network. The detection is conditioned on the input query with a stack of novel Relation-to-Attention modules that transform the image-to-query relationship to a relation map, which is used to predict the bounding box directly without proposing large numbers of useless region proposals. During the inference, our approach is about 20 x ~ 30 x faster than previous methods and, remarkably, it achieves comparable performance on several benchmark datasets.","PeriodicalId":357138,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128997266","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

Automatic and Personalized Sequencing of Music Playlists 音乐播放列表的自动和个性化排序

2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW) Pub Date : 2022-07-01 DOI: 10.1109/ICDCSW56584.2022.00046

M. Furini, M. Montangero

引用次数: 0

Program Committee: ICDCSW 2022 项目委员会:ICDCSW 2022

2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW) Pub Date : 2022-07-01 DOI: 10.1109/icdcsw56584.2022.00008

引用次数: 0

Temperature Annealing Knowledge Distillation from Averaged Teacher 平均教师的温度退火知识蒸馏

2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW) Pub Date : 2022-07-01 DOI: 10.1109/ICDCSW56584.2022.00034

Xiaozhe Gu, Zixun Zhang, Tao Luo

{"title":"Temperature Annealing Knowledge Distillation from Averaged Teacher","authors":"Xiaozhe Gu, Zixun Zhang, Tao Luo","doi":"10.1109/ICDCSW56584.2022.00034","DOIUrl":"https://doi.org/10.1109/ICDCSW56584.2022.00034","url":null,"abstract":"Despite the success of deep neural networks (DNNs) in almost every field, their deployment on edge devices has been restricted due to the significant memory and computational resource requirements. Among various model compression techniques for DNNs, Knowledge Distillation (KD) is a simple but effective one, which transfers the knowledge of a large teacher model to a smaller student model. However, as pointed out in the literature, the student is unable to mimic the teacher perfectly even when it has sufficient capacity. As a result, the student may not be able to retain the teacher's accuracy. What's worse, the student performance may be impaired by the wrong knowledge and potential over- regularization effect of the teacher. In this paper, we propose a novel method TAKDAT which is short for Temperature Annealing Knowledge Distillation from A veraged Teacher. Specifically, TAKDAT comprises of two con-tributions: 1) we propose to use an averaged teacher, which is an equally weighted average of model checkpoints traversed by SGD, in the distillation. Compared to a normal teacher, an averaged teacher provides richer similarity information and has less wrong knowledge; 2) we propose a temperature annealing scheme to gradually reduce the regularization effect of the teacher. Finally, extensive experiments verify the effectiveness of TAKDAT, e.g., it achieves a test accuracy of 74.31 % on CIFARI00 for ResNet32.","PeriodicalId":357138,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132776358","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

The Royal Game of Ur: A Digital Reproduction of an Ancient Sumerian Game 乌尔的皇家游戏:古代苏美尔游戏的数字复制

2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW) Pub Date : 2022-07-01 DOI: 10.1109/ICDCSW56584.2022.00049

Mirko Franco, Marco Nardelotto, C. Palazzi

引用次数: 0

Flash Freezing Flash Boys: Countering Blockchain Front-Running Flash Freezing Flash Boys:对抗区块链的先行者

2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW) Pub Date : 2022-07-01 DOI: 10.1109/ICDCSW56584.2022.00026

Haoqian Zhang, Louis-Henri Merino, Vero Estrada-Galiñanes, B. Ford

引用次数: 15

On the BER Performance of RIS-Enhanced NOMA-Assisted Backscatter Communication under Nakagami-m Fading ris增强noma辅助后向散射通信在Nakagami-m衰落下的误码率性能

2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW) Pub Date : 2022-07-01 DOI: 10.1109/ICDCSW56584.2022.00039

M. Usman, S. Basharat, H. Pervaiz, S. Hassan, Haejoon Jung

{"title":"On the BER Performance of RIS-Enhanced NOMA-Assisted Backscatter Communication under Nakagami-m Fading","authors":"M. Usman, S. Basharat, H. Pervaiz, S. Hassan, Haejoon Jung","doi":"10.1109/ICDCSW56584.2022.00039","DOIUrl":"https://doi.org/10.1109/ICDCSW56584.2022.00039","url":null,"abstract":"Backscatter communication (BackCom) has been envisioned as a prospective candidate for enabling the sustained operation of battery-constrained Internet-of- Things (IoT) devices. This approach involves the transmission of information by a backscatter node (BSN) through passive reflection and modulation of an impinging radio-frequency (RF) signal. However, the short operational range and low data rates of contemporary BackCom systems render them insufficient on their own to provide ubiquitous connectivity among the plethora of IoT devices. Meanwhile, wireless networks are rapidly evolving towards the smart radio paradigm. Thus, to enhance the coverage range and capacity, reconfigurable intelligent surfaces (RISs) can be incorporated into the existing BackCom systems. RISs employ passive reflective elements to adaptively configure the stochastic wireless environment in a cost-effective and energy- efficient manner. Furthermore, non-orthogonal multiple access (NOMA) can be exploited to improve the spectral efficiency of the BackCom systems. In this paper, we present the design and bit error rate (BER) analysis of an RIS-enhanced NOMA-assisted bistatic BackCom system under Nakagami-m fading channel. Our extensive simulation results reveal the effectiveness of the proposed system over the conventional NOMA-assisted BackCom system without RIS, and demonstrate the impact of various factors, including the power-reflection coefficients, RIS phase-shift designs, number of reflecting elements, RIS location, and split factor, on the BER performance of the proposed RIS-assisted system.","PeriodicalId":357138,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127037573","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: 2