Proceedings of the 12th International Conference on Management of Digital EcoSystems最新文献

Internet of Things: The Way Ahead 物联网:未来之路

Proceedings of the 12th International Conference on Management of Digital EcoSystems Pub Date : 2020-11-02 DOI: 10.1145/3415958.3433085

Z. Maamar

{"title":"Internet of Things: The Way Ahead","authors":"Z. Maamar","doi":"10.1145/3415958.3433085","DOIUrl":"https://doi.org/10.1145/3415958.3433085","url":null,"abstract":"The Internet of Things (IoT) is among the latest Information and Communication Technologies (ICT) developments that is making the boundaries between reality and fiction vanish. According to Mark Weiser, \"...The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it.\" [5]. The International Data Corporation (IDC) also mentions the huge spending on IoT that \"...will increase by a compound annual growth rate of 13.6% from 2017 to 2022, reaching $1.2 trillion within the next four years\"1. To sustain this rapid growth, IoT should overcome different obstacles such as diversity of things' development technologies and communication standards, users' reluctance and sometimes rejection due to things invading their privacy, lack of killer applications that demonstrate the necessity of things, lack of an IoT-oriented software engineering discipline, and finally, the passive nature of things. To address these obstacles, the research community is putting forward many solutions that would make things proactive and responsive to their cyber-physical surroundings. This should allow things for instance, to reach out to peers that expose collaborative behavior, to form dynamic alliances when necessary, to avoid peers that expose malicious behavior, and to be accountable for their actions. In this keynote presentation, we discuss our ongoing research agenda on IoT with focus on four initiatives: process-of-things [3], mutation-of-things [1], cloud-fog-things [2, 6], and finally, vetting-things [4].","PeriodicalId":198419,"journal":{"name":"Proceedings of the 12th International Conference on Management of Digital EcoSystems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125867725","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

Spatial Information Retrieval in Digital Ecosystems: A Comprehensive Survey 数字生态系统空间信息检索研究综述

Proceedings of the 12th International Conference on Management of Digital EcoSystems Pub Date : 2020-11-02 DOI: 10.1145/3415958.3433038

A. Carniel

{"title":"Spatial Information Retrieval in Digital Ecosystems: A Comprehensive Survey","authors":"A. Carniel","doi":"10.1145/3415958.3433038","DOIUrl":"https://doi.org/10.1145/3415958.3433038","url":null,"abstract":"Spatial information retrieval is a common task of digital ecosystems due to the popularity of collecting and storing spatial information and phenomena in the world of the Internet of Things (IoT). Spatial relationships play an important role in this context by specifying how two or more spatial objects are related or connected. Examples of spatial relationships include topological relationships (e.g., intersect, overlap, contains), metric relationships (e.g., nearest neighbors), and direction relationships (e.g., cardinal directions like north and south). Many works in the literature have proposed definitions and implementations of spatial queries based on specific types of spatial relationships. Hence, a holistic view of these works is important to understand their applicability and relations. This paper advances in the literature by providing a comprehensive survey of the implementations and types of spatial queries that can be used by digital ecosystems. We present a novel characterization based on spatial relationships to define topological-based, metric-based, and direction-based spatial queries. For each type of spatial query, we present its intuitive and formal definitions together with possible strategies of implementation. Further, we identify hybrid spatial queries as combinations of two or more spatial relationships, and spatial joins as generalization cases. In addition, we present some equivalences between some types of queries. As a result, we point out future research topics in spatial information retrieval.","PeriodicalId":198419,"journal":{"name":"Proceedings of the 12th International Conference on Management of Digital EcoSystems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115981542","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: 3

Towards a Crypto Asset Taxonomy: A Text Classification-based Approach 迈向加密资产分类:基于文本分类的方法

Proceedings of the 12th International Conference on Management of Digital EcoSystems Pub Date : 2020-11-02 DOI: 10.1145/3415958.3433078

Ozan Kose, P. Senkul, Gokce E. Phillips

{"title":"Towards a Crypto Asset Taxonomy: A Text Classification-based Approach","authors":"Ozan Kose, P. Senkul, Gokce E. Phillips","doi":"10.1145/3415958.3433078","DOIUrl":"https://doi.org/10.1145/3415958.3433078","url":null,"abstract":"There are over 1900 cryptocurrencies trading in the market as of September 2020 and the number is rapidly growing. In the current crypto scene, cryptocurrencies are seen as investment vehicles by many, yet every crypto asset is designed to operate in a specific sector within a pre-defined business model. In addition to sector, there are various characteristics and factors that differentiate one crypto asset from another. Crypto investors can leverage these factors and characteristics and use these indicators to create different trading strategies. In our work, in order to guide the decision-making process for investors and to help them analyse crypto assets in a holistic manner, we classify the crypto assets under various characteristics, aiming towards a crypto asset taxonomy. In this paper, we focus on automated annotation of the cryptocurrencies in terms of sector, transaction anonymity and asset type through the public information. Though the information we utilise is public, it is scattered around quite a vast number of sources in different formats. Therefore, we generated an annotated dataset by collecting information from various sources. We utilised several supervised learning algorithms, including both traditional ones and more recent neural models, and analyzed the classification performance for the three aspects.","PeriodicalId":198419,"journal":{"name":"Proceedings of the 12th International Conference on Management of Digital EcoSystems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131648079","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

Scalable Execution of Big Data Workflows using Software Containers 使用软件容器实现大数据工作流的可扩展执行

Proceedings of the 12th International Conference on Management of Digital EcoSystems Pub Date : 2020-11-02 DOI: 10.1145/3415958.3433082

Yared Dejene Dessalk, Nikolay Nikolov, M. Matskin, A. Soylu, D. Roman

引用次数: 7

Data-Intensive Object-Oriented Adaptive Web Systems: Implementing and Experimenting the OO-XAHM Framework 数据密集型面向对象自适应Web系统:OO-XAHM框架的实现和实验

Proceedings of the 12th International Conference on Management of Digital EcoSystems Pub Date : 2020-11-02 DOI: 10.1145/3415958.3433051

A. Cuzzocrea, Edoardo Fadda

引用次数: 3

Towards a Predictive Framework for Power Consumption of Jobs in HPC Facilities 构建高性能计算设备作业能耗预测框架

Proceedings of the 12th International Conference on Management of Digital EcoSystems Pub Date : 2020-11-02 DOI: 10.1145/3415958.3433042

Nitin Sukhija, Alexander Gessinger, Elizabeth Bautista

引用次数: 2

Big-Data Driven Digital Ecosystem Framework for Online Predictive Control 大数据驱动的在线预测控制数字生态系统框架

Proceedings of the 12th International Conference on Management of Digital EcoSystems Pub Date : 2020-11-02 DOI: 10.1145/3415958.3433077

A. Suleykin, N. Bakhtadze, P. Panfilov

引用次数: 1

A Generic Flexible and Scalable Framework for Hierarchical Parallelization of Population-Based Metaheuristics 基于群体的元启发式分层并行化的通用、灵活和可扩展框架

Proceedings of the 12th International Conference on Management of Digital EcoSystems Pub Date : 2020-11-02 DOI: 10.1145/3415958.3433041

Hatem Khalloof, Mohammad Mohammad, Shadi Shahoud, Clemens Düpmeier, V. Hagenmeyer

{"title":"A Generic Flexible and Scalable Framework for Hierarchical Parallelization of Population-Based Metaheuristics","authors":"Hatem Khalloof, Mohammad Mohammad, Shadi Shahoud, Clemens Düpmeier, V. Hagenmeyer","doi":"10.1145/3415958.3433041","DOIUrl":"https://doi.org/10.1145/3415958.3433041","url":null,"abstract":"Population-based metaheuristics -such as Evolutionary Algorithms (EAs)- are one of the most popular methods for solving highly complex and large-scale optimization problems. Nevertheless, finding an adequate solution with such approaches often requires computationally intensive fitness function evaluations especially in real-world applications. To speed up the computation, exploiting modern software techniques for parallelizing population-based metaheuristics on a cluster or a cloud is a viable approach. In the present paper, a generic, flexible and scalable framework for hierarchical hybridization of distributed population-based metaheuristics in a cluster environment is introduced. Three lightweight technologies, namely microservices, container virtualization and the publish/subscribe messaging paradigm are used to develop this framework. The combination of these technologies enables easy hybridizations of different parallelization models of population-based metaheuristics, a full decoupling between services providing basic building blocks of the algorithm and a seamless deployment in a scalable runtime environment. For evaluation purposes, the EA GLEAM (General Learning Evolutionary Algorithm and Method) is exemplarily integrated into the framework and successfully deployed in a cluster environment. Scalability and applicability of the framework are explored by hybridizing the Coarse-Grained Model with the Global Model for solving the problem of unit commitment of distributed energy resources utilizing renewable energy generation. The results show that the new proposed framework introduces an excellent performance for scaling up the optimization speed of complex unit commitment optimization problems.","PeriodicalId":198419,"journal":{"name":"Proceedings of the 12th International Conference on Management of Digital EcoSystems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125844576","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: 3

Graph Embeddings in Criminal Investigation: Extending the Scope of Enquiry Protocols 刑事调查中的图嵌入:扩展查询协议的范围

Proceedings of the 12th International Conference on Management of Digital EcoSystems Pub Date : 2020-11-02 DOI: 10.1145/3415958.3433102

V. Bellandi, P. Ceravolo, S. Maghool, S. Siccardi

引用次数: 1

Trajectory Prediction for Maritime Vessels Using AIS Data 基于AIS数据的船舶轨迹预测

Proceedings of the 12th International Conference on Management of Digital EcoSystems Pub Date : 2020-11-02 DOI: 10.1145/3415958.3433079

Gozde Karatas, P. Senkul, Orhan Ayran

引用次数: 2