Evaluation of distributed Complex event Processing (CEP) systems is a rather challenging task. To simplify this task, we developed the open simulation framework for distributed CEP, called DCEP-Sim. the goal of this t...
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ISBN:
(纸本)9781450357821
Evaluation of distributed Complex event Processing (CEP) systems is a rather challenging task. To simplify this task, we developed the open simulation framework for distributed CEP, called DCEP-Sim. the goal of this tutorial is to facilitate the process of using DCEP-Sim. Since DCEP-Sim is designed and implemented in the popular network simulator ns-3 we introduce the most important concepts of ns-3. Simulations in ns-3 are configured and executed though a main program called an ns-3 script. We use a simple example script to explain how simulations with DCEP-Sim are set up and executed. To give an idea how DCEP-Sim can be adjusted to particular needs, we explain how DCEP-Sim can be adapted (e.g., through changing the workload and the network topology) and how new distributed CEP solutions can be added by explaining how to add a new operator to DCEP-Sim.
the design of the distributed Decentralized Storage Platform (DDSP) requires to develop an efficient data validation method taking into account the network scalability issue, possibility to check data without knowledg...
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Popularly known for powering cryptocurrencies such as Bitcoin and Ethereum, blockchains is seen as a disruptive technology capable of impacting a wide variety of domains, ranging from finance to governance, by offerin...
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ISBN:
(纸本)9781450357821
Popularly known for powering cryptocurrencies such as Bitcoin and Ethereum, blockchains is seen as a disruptive technology capable of impacting a wide variety of domains, ranging from finance to governance, by offering superior security, reliability, and transparency in a decentralized manner. In this tutorial presentation, we first study the original Bitcoin design, as well as Ethereum and Hyperledger, and reflect on their design from an academic perspective. We provide an overview of potential applications and associated research challenges, as well as a survey of ongoing research projects. We mention opportunities blockchain creates for event-basedsystems. Finally, we conclude with a walkthrough showing the process of developing a decentralized application (DApp), using a popular Smart Contract language (Solidity) for the blockchain platform of Ethereum.
the primary consumption of news is now increasingly online and has resulted in a large volume of online news from varied news outlets. Consequently, news aggregators have become popular for clustering, ranking and per...
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ISBN:
(纸本)9781450357821
the primary consumption of news is now increasingly online and has resulted in a large volume of online news from varied news outlets. Consequently, news aggregators have become popular for clustering, ranking and personalization of news which process millions of news articles each day. In addition, since news articles stream constantly, there is a need for a scalable event-based system which can facilitate news mining in an online fashion. To address these challenges, we propose a distributed framework to process news articles and cluster them to facilitate many news mining tasks. the core of our system is a novel and scalable distributed clustering algorithm using Locality Sensitive Hashing which is robust to outliers and noise. In addition, we also propose an online version of the clustering algorithm to dynamically maintain the news event clusters. We implement the proposed solution on Apache Spark. Using a large news collection with over 8 million news articles, we show that our approach outperforms widely-used clustering techniques such as K-Means both in run time and clustering quality.
Trade surveillance is an important concern in recent trading engines to detect and prevent fraudulent trades at earliest. In traditional trading platforms, to achieve high throughput and low latency requirements focus...
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ISBN:
(纸本)9781450357821
Trade surveillance is an important concern in recent trading engines to detect and prevent fraudulent trades at earliest. In traditional trading platforms, to achieve high throughput and low latency requirements focus of developers has always been on high-performance languages such as C, C++ and FPGA basedsystems. these systems have limitations of scalability and fault-tolerance. Withthe arrival of in-memory technology, these requirements can be met with Java-based frameworks like Ignite, Flink, Spark. In this paper, we propose a novel way of implementing trade surveillance architecture using Apache Ignite In-Memory Data Grid (IMDG). Paper discusses the engineering approach to tune system architecture on the single node in terms of achieving high throughput, low latency and then scaling out to multiple nodes.
Nowadays data stream processing systems need to efficiently handle large volumes of data in near real-time. To achieve this, the schedulers within such systems minimise the data movement between highly communicating t...
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ISBN:
(纸本)9781450357821
Nowadays data stream processing systems need to efficiently handle large volumes of data in near real-time. To achieve this, the schedulers within such systems minimise the data movement between highly communicating tasks, improving system throughput. However, finding an optimal schedule for these systems is NP-hard. In this research, we propose a heuristic scheduling algorithm which reliably and efficiently finds the highly communicating tasks by exploiting graph partitioning algorithms and a mathematical optimisation software package. We evaluate our scheduler with two popular existing schedulers R-Storm and Aniello et al.'s 'Online scheduler' using two real-world applications and show that our proposed scheduler outperforms R-Storm, increasing throughput by between 3% and 30% and Online scheduler by 20 86% as a result of finding a more efficient schedule.
the Internet of things (IoT) envisions a huge number of networked sensors connected to the internet. these sensors collect large streams of data which serve as input to wide range of IoT applications and services such...
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ISBN:
(纸本)9781450357821
the Internet of things (IoT) envisions a huge number of networked sensors connected to the internet. these sensors collect large streams of data which serve as input to wide range of IoT applications and services such as e-health, e-commerce, and automotive services. Complex event Processing (CEP) is a powerful tool that transforms streams of raw sensor data into meaningful information required by these IoT services. Often these streams of data collected by sensors carry privacy-sensitive information about the user. thus, protecting privacy is of paramount importance in IoT services based on CEP. In this paper we present a novel pattern-level access control mechanism for CEP based services that conceals private information while minimizing the impact on useful non-sensitive information required by the services to provide a certain quality of service (QoS). the idea is to reorder events from the event stream to conceal privacy-sensitive event patterns while preserving non-privacy sensitive event patterns to maximize QoS. We propose two approaches, namely an ILP-based approach and a graph-based approach, calculating an optimal reordering of events. Our evaluation results show that these approaches are effective in concealing private patterns without significant loss of QoS.
the proceedings contain 59 papers. the special focus in this conference is on Evolutionary Multi-Criterion Optimization. the topics include: Multi-objective techniques for single-objective local search: A case study o...
ISBN:
(纸本)9783030125974
the proceedings contain 59 papers. the special focus in this conference is on Evolutionary Multi-Criterion Optimization. the topics include: Multi-objective techniques for single-objective local search: A case study on traveling salesman problem;multimodality in multi-objective optimization – More boon than bane?;solving nonlinear equation systems using multiobjective differential evolution;process-monitoring-for-quality— A model selection criterion for genetic programming;evolutionary many-constraint optimization: An exploratory analysis;generating uniformly distributed points on a unit simplex for evolutionary many-objective optimization;on timing the nadir-point estimation and/or termination of reference-based multi- and many-objective evolutionary algorithms;variation rate: An alternative to maintain diversity in decision space for multi-objective evolutionary algorithms;indicator-based weight adaptation for solving many-objective optimization problems;Investigating the normalization procedure of NSGA-III;an empirical investigation of the optimality and monotonicity properties of multiobjective archiving methods;MAC: Many-objective automatic algorithm configuration;A parallel tabu search heuristic to approximate uniform designs for reference set based MOEAs;Comparison of reference- and hypervolume-based MOEA on solving many-objective optimization problems;diversity over dominance approach for many-objective optimization on reference-points-based framework;a two-stage evolutionary algorithm for many-objective optimization;CRI-EMOA: A pareto-front shape invariant evolutionary multi-objective algorithm;the hypervolume indicator as a performance measure in dynamic optimization;Comparison of hypervolume, IGD and IGD+ from the viewpoint of optimal distributions of solutions;Diversity-indicator based multi-objective evolutionary algorithm: DI-MOEA;the expected R2-indicator improvement for multi-objective bayesian optimization;evolutionary multi-objective optimization u
the proceedings contain 23 papers. the special focus in this conference is on Agents and Artificial Intelligence. the topics include: Using generic ontologies to infer the geographic focus of text;Smart device stealin...
ISBN:
(纸本)9783030054526
the proceedings contain 23 papers. the special focus in this conference is on Agents and Artificial Intelligence. the topics include: Using generic ontologies to infer the geographic focus of text;Smart device stealing and CANDIES;integrated route, charging and activity planning for whole day mobility with electric vehicles;scalable collaborative filtering based on splitting-merging clustering algorithm;foundations of inconsistency-tolerant model checking: Logics, translations, and examples;Inherited properties of FL0 concept similarity measure under preference profile;SEMTec: Social emotion mining techniques for analysis and prediction of facebook post reactions;gamma-star canonical forms in the type-theory of acyclic algorithms;the application of Keirsey’s temperament model to twitter data in portuguese;an Approach for detecting and resolving indirect normative conflicts in multi-agent systems;a constraint solving web service for a handwritten Japanese historical kana reprint support system;parameterized mapping distances for semi-structured data;aspectual classifications: Use of raters’ associations and co-occurrences of verbs for aspectual classification in German;linguistic information in word embeddings;comparative quantitative evaluation of distributed methods for explanation generation and validation of floor plan recommendations;population dynamics necessary to avert unpopular norms;modelling and simulating extreme opinion diffusion;learning from monte carlo rollouts with opponent models for playing tron;conditional uncertainty in constraint networks;safe deep reinforcement learning hybrid electric vehicle energy management;planning under uncertainty through goal-driven action selection.
Data Stream Management systems (DSMSs) performing online analytics rely on the efficient execution of large numbers of Aggregate Continuous Queries (ACQs). In this paper, we study the problem of generating high qualit...
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