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12th ACM International Conference on Distributed and Event-Based Systems (DEBS)

作者： Bansod, Rishikesh Virk, Rupinder Raval, Mehul TCS Res Mumbai Maharashtra India TCS Mumbai Maharashtra India

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 based systems. These systems have limitations of scalability and fault-tolerance. With the 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.

关键词： In-memory Distributed Computing in-memory data grid Low Latency Streaming High Throughput Caching Trade Surveillance

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Low Latency, High Throughput Trade Surveillance System Using in-memory data grid 18

Low Latency, High Throughput Trade Surveillance System Using...

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Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems

作者： Rishikesh Bansod Rupinder Virk Mehul Raval TCS Research Mumbai India TCS Mumbai India

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 based systems. These systems have limitations of scalability and fault-tolerance. With the 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.

关键词： High Throughput Caching In-memory Distributed Computing in-memory data grid Low Latency Streaming Trade Surveillance

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Performance Evaluation of NewSQL databases in a Distributed Architecture

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IEEE ACCESS 2025年 13卷 11185-11194页

作者： Zhang, Zhiyao Megargel, Alan Jiang, Lingxiao Singapore Management Univ Sch Comp & Informat Syst Singapore 178902 Singapore

In the last decade, application architectures have evolved drastically, moving from monolithic architectures to distributed architectures where deployment has shifted from dedicated on-premises servers to the cloud. Distributed architectures and cloud computing has enabled businesses to scale their application components across different geographical locations. While it is easy to scale the application layer, scaling its database layer that relies on traditional SQL databases is challenging and often is a common source of bottlenecks when it comes to application performance. This paper evaluates the performance characteristics between two NewSQL databases solutions, MySQL NDB Cluster vs. TIBCO ActiveSpaces IMDG. Serving as an application layer, a simulation of banking microservices, handling loyalty rewards, is developed to interface with these databases to derive additional insights and comparison. In the context of a geographically distributed architecture, our experiment results show that MySQL NDB Cluster is more suited for critical business transactions requiring ACID properties while TIBCO ActiveSpaces is better suited for use cases that require big data ingestion, such as IoT platforms.

关键词： database performance NewSQL SQL MySQL NDB IMDG in-memory data grid database performance NewSQL SQL MySQL NDB IMDG in-memory data grid

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Fast Responsive Framework for Optimal Power Flow Analysis in Power System

Fast Responsive Framework for Optimal Power Flow Analysis in...

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IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)

作者： Gong, Xundong Lu, Jinyue Zong, Shaolei Chen, Ming Xia, Yongxiang State Grid Jiangsu Elect Power Co Nanjing Peoples R China Hangzhou Dianzi Univ Hangzhou Peoples R China State Grid Wuxi Power Supply Co Wuxi Jiangsu Peoples R China

ISBN: (纸本)9781665450737

The analysis of optimal power flow (OPF) plays an important role in the safe operation, economic dispatching and reliability analysis in modern power system. However, with the large-scale integration of renewable energy sources and power electronics, higher requirements are put forward for online analysis of power system. Most previous studies only focused on the execution efficiency of the algorithm without considering the cost of data processing and transmission. In fact, the transmission of massive data between different platforms and computational nodes is the major factor limiting the response time of online analysis. In this paper, a fast responsive framework, which integrates the in-memory data grid and parallel computing, is proposed to improve the response time of OPF analysis. The case studies based on the IEEE baseline network show that the proposed framework can greatly improve the speed of data access and accelerate the computing time of OPF.

关键词： Online analysis in-memory data grid distributed cache optimal power flow

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Application of In-memory Computing to Online Power grid Analysis

Application of In-Memory Computing to Online Power Grid Anal...

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10th IFAC Symposium on Control of Power and Energy Systems (CPES)

作者： Zhou, Mike Feng, Donghao State Grid EPRI Beijing Peoples R China KeDong Elect Power Control Syst Com Beijing Peoples R China

To address the hard disk and network data I/O bottleneck issue in the large-scale online power grid analysis, an in-memory computing based power grid analysis approach is proposed in this paper. Typical in-memory computing application scenarios in the online power grid analysis are discussed. Using a large-scale online analysis network model as a sample case, in -memory computing simulations corresponding to the scenarios were performed, and the simulation results and analysis of the performance of the simulation are presented. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： In-memory Computing in-memory data grid Object-oriented Modeling Online Power grid Analysis

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Developing and Validating Virtualized Transactional Application of Educational Institutes using InFraMegh 5

Developing and Validating Virtualized Transactional Applicat...

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International Conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Arora, Indu Gupta, Anu MCM DAV Coll Women Dept Comp Sci & Applicat Chandigarh India Panjab Univ Dept Comp Sci & Applicat Chandigarh India

ISBN: (纸本)9781509020287

Cloud Computing (CC) is considered a constructive technology for read-intensive analytical applications rather than write-intensive transactional applications. Deploying transactional applications in the Cloud is not considered safe due to requirement of stringent ACID guarantees. These rules can be enforced in Cloud using middleware tools like CloudTran and Oracle Coherence. It becomes a major challenge to integrate these tools for a transactional application developer. So, an integrated framework for educational institutes named as 'InFraMegh' is developed. It works on top of CloudTran and Oracle Coherence. InFraMegh focuses on Cloud data Management layer and provides generalized API for managing data in cache and database. InFraMegh speeds up and eases the development efforts of transactional application developer for Cloud. As proof of concept, a transactional application of educational institutes named as Student Registration Return System (SRRS) is used for verifying the functionality of InFraMegh. SRRS is virtualized using XenApp and accessed on client machines. Virtualized SRRS is tested in single-user and multi-user environments. Its performance is found better over traditional client-server architecture. Hence, InFraMegh expedites efforts of developers in developing transaction applications in Cloud. It allows educational institutes to manage data in Cloud.

关键词： in-memory data grid Transactional Applications Cloud Computing Educational Institutes SaaS

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Developing and Validating Virtualized Transactional Application of Educational Institutes using InFraMegh

Developing and Validating Virtualized Transactional Applicat...

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International Conference on Advances in Computing, Communications and Informatics

作者： Indu Arora Anu Gupta Department of Computer Science and Applications MCM DAV College for Women Chandigarh-India Department of Computer Science and Applications Panjab University Chandigarh-India

ISBN: (纸本)9781509020300

关键词： in-memory data grid Transactional Applications Cloud Computing Educational Institutes SaaS

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Improved Resilience through Extended KVS-Based Messaging System

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2015年第3期E98D卷 578-587页

作者： Kinoshita, Masafumi Takada, Osamu Mizutani, Izumi Koike, Takafumi Leibnitz, Kenji Murata, Masayuki Hitachi Ltd Yokohama Res Lab Yokohama Kanagawa 2440817 Japan Osaka Univ Grad Sch Informat Sci & Technol Suita Osaka 5650871 Japan Hitachi Ltd Telecommun & Network Syst Div Kawasaki Kanagawa 2128567 Japan Natl Inst Informat & Commun Technol Ctr Informat & Neural Networks CiNet Suita Osaka 5650871 Japan Osaka Univ Suita Osaka 5650871 Japan

In the big data era, messaging systems are required to process large volumes of message traffic with high scalability and availability. However, conventional systems have two issues regarding availability. The first issue is that failover processing itself has a risk of failure. The second issue is to find a trade-off between consistency and availability. We propose a resilient messaging system based on a distributed in-memory key-value store (KVS). Its servers are interconnected with each other and messages are distributed to multiple servers in normal processing state. This architecture can continue messaging services wherever in the messaging system server/process failures occur without using failover processing. Furthermore, we propose two methods for improved resilience: the round-robin method with a slowdown KVS exclusion and the two logical KVS counter-rotating rings to provide short-term-availability in the messaging system. Evaluation results demonstrate that the proposed system can continue service without failover processing. Compared with the conventional method, our proposed distribution method reduced 92% of error responses to clients caused by server failures.

关键词： KVS (key-value store) in-memory data grid messaging queue distribution system

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Building a CDR analytics platform for real-time services 16

Building a CDR analytics platform for real-time services

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16th Asia-Pacific Network Operations and Management Symposium (APNOMS)

作者： Shih, Chia-Chun Huang, Chi-Chang Lin, Bo-Ting Huang, Chao-Wen Hu, Wan-Hsun Cheng, Chien-Wei Chunghwa Telecom Labs Billing Informat Lab Taipei Taiwan

ISBN: (纸本)9784885522888

Growing real-time services require discovering transient customer needs in CDRs. In this paper, we propose a CDR analytics system architecture for event-based analytics processing in real time. This system is expected to allow marketing staff to inject analytics-based rules to trigger marketing campaigns. We also propose two implementations which are based on off-the-shelf computing tools.

关键词： Real-time CDR processing Real-time analytics Stream computing in-memory data grid

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