Designed in partnership with exchange participants, Deutsche Boerse’s T7 trading architecture aims to enhance performance across the board, including reduced latency and increased throughput. It’s a new generation of technology to deliver a world of opportunity.
► Visit our website: http://www.eurexchange.com
► Twitter: http://twitter.com/eurexgroup
► LinkedIn: http://www.linkedin.com/company/eurex
Solidity is a programming language for creating smart contracts on the Ethereum blockchain. It allows developers to write smart contracts for applications, financial services, data storage, and more. Some key concepts in understanding Solidity include Ethereum, smart contracts, and the Ethereum Virtual Machine. Solidity code can be compiled in different environments like Remix, Node.js, Docker, or binary packages. The language uses concepts like pragmas, contracts, variables, and data types. Solidity smart contracts have many use cases such as upgrading contracts, trade finance, and digital identity.
This document discusses the 51% attack on blockchains. It begins with a recap of how blockchains work, using Bitcoin as an example, explaining how transactions are ordered into blocks. It then explains that if a single miner or mining pool controlled over 51% of the computing power, they could perform a double spend attack by overriding the transaction ordering on the blockchain. However, the document argues that launching a 51% attack would be prohibitively expensive due to the computing power and infrastructure required. It claims it would not be profitable for an attacker to maintain over 51% of the hash power long enough to override the legitimate blockchain.
"Decentralized Finance (DeFi)" by Brendan Forster, Dharma | Fluidity 2019Fluidity
Presented by Brendan Forster, Co-founder of Dharma, at Fluidity 2019.
Fluidity brings the worlds of finance and technology together to shape the future of blockchain and capital markets. On May 9, 2019, we welcomed companies and teams to help shape the narrative of rebuilding finance at the historic Williamsburgh Savings Bank in Brooklyn, New York.
Resources:
Website: https://fluiditysummit.com
Facebook: https://facebook.com/fluidityio/
Twitter: https://twitter.com/fluidityio
LinkedIn: https://linkedin.com/company/fluidityio/
YouTube: https://youtube.com/channel/UC0NBCYlgLIxjSljf7CV91nQ/
The document discusses various consensus approaches and algorithms used in blockchain networks. It explains that consensus algorithms are needed to achieve agreement across decentralized networks without a central authority. It then describes several types of consensus algorithms including Proof of Work, Proof of Stake, Proof of Activity, Proof of Capacity, Proof of Elapsed Time, and Proof of Burn. Each algorithm is summarized with examples of blockchains that use each approach.
This document discusses Ethereum 2.0 and its goals of improving decentralization, scalability, and energy efficiency over Ethereum 1.0. It outlines the key components of Ethereum 2.0 including using proof of stake instead of proof of work, implementing sharding to partition the blockchain into multiple shards to improve scalability, and transitioning to a new virtual machine. It provides timelines for rolling out these changes and demos running an Ethereum 2.0 beacon node.
Consensus algorithms are an extremely crucial part of blockchain technology. Proof of Work is a type of consensus mechanism where users use their computational devices to solve complex mathematical problems in order to verify and add blocks to the ledger system. On the other hand, in Proof of Stake users will need to stake their coins in order to participate in the verification process.
The difference between the two types of consensus protocol lies within the working mechanism of these two processes. Verification mechanism, incentive policy, vulnerability, motivation, requirement, and scalability are some of the areas where these two differ.
To help you better understand the differences between these two consensus protocols, 101 Blockchain offer an array of lucrative blockchain courses. These courses will help you comprehend the working principles of these two algorithms.
The following courses will help you learn about PoW and PoS->
Blockchain Like a Boss Masterclass
https://academy.101blockchains.com/courses/blockchain-masterclass
Getting Started with Bitcoin Technology
https://academy.101blockchains.com/courses/getting-started-with-bitcoin-technology
Learn more about the certification courses from here ->
Certified Enterprise Blockchain Professional (CEBP) course
https://academy.101blockchains.com/courses/blockchain-expert-certification
Certified Enterprise Blockchain Architect (CEBA) course
https://academy.101blockchains.com/courses/certified-enterprise-blockchain-architect
Certified Blockchain Security Expert (CBSE) course
https://academy.101blockchains.com/courses/certified-blockchain-security-expert
Learn more from our guide ->
https://101blockchains.com/pow-vs-pos-a-comparison/
The document summarizes the Advanced Encryption Standard (AES). It describes how AES was selected by NIST as a replacement for DES. AES (Rijndael cipher) uses a block size of 128 bits, with key sizes of 128, 192, or 256 bits. It operates on data in rounds that include byte substitution, shifting rows, mixing columns, and adding the round key. The key is expanded into an array of words used for each round.
Algorithmic trading (AT) is trading conducted via electronic platforms where buy and sell orders are automatically generated by quantitative models with little human intervention. AT strategies include execution algorithms like VWAP and TWAP that minimize market impact, and alpha generating algorithms like arbitrage and trend following that exploit short-term price anomalies. While AT increases market liquidity and price discovery, it can also increase short-term volatility. Experts note that high-frequency trading puts less privileged traders at a disadvantage due to its high costs and speed, though it benefits the market overall through greater liquidity.
Solidity is a programming language for creating smart contracts on the Ethereum blockchain. It allows developers to write smart contracts for applications, financial services, data storage, and more. Some key concepts in understanding Solidity include Ethereum, smart contracts, and the Ethereum Virtual Machine. Solidity code can be compiled in different environments like Remix, Node.js, Docker, or binary packages. The language uses concepts like pragmas, contracts, variables, and data types. Solidity smart contracts have many use cases such as upgrading contracts, trade finance, and digital identity.
This document discusses the 51% attack on blockchains. It begins with a recap of how blockchains work, using Bitcoin as an example, explaining how transactions are ordered into blocks. It then explains that if a single miner or mining pool controlled over 51% of the computing power, they could perform a double spend attack by overriding the transaction ordering on the blockchain. However, the document argues that launching a 51% attack would be prohibitively expensive due to the computing power and infrastructure required. It claims it would not be profitable for an attacker to maintain over 51% of the hash power long enough to override the legitimate blockchain.
"Decentralized Finance (DeFi)" by Brendan Forster, Dharma | Fluidity 2019Fluidity
Presented by Brendan Forster, Co-founder of Dharma, at Fluidity 2019.
Fluidity brings the worlds of finance and technology together to shape the future of blockchain and capital markets. On May 9, 2019, we welcomed companies and teams to help shape the narrative of rebuilding finance at the historic Williamsburgh Savings Bank in Brooklyn, New York.
Resources:
Website: https://fluiditysummit.com
Facebook: https://facebook.com/fluidityio/
Twitter: https://twitter.com/fluidityio
LinkedIn: https://linkedin.com/company/fluidityio/
YouTube: https://youtube.com/channel/UC0NBCYlgLIxjSljf7CV91nQ/
The document discusses various consensus approaches and algorithms used in blockchain networks. It explains that consensus algorithms are needed to achieve agreement across decentralized networks without a central authority. It then describes several types of consensus algorithms including Proof of Work, Proof of Stake, Proof of Activity, Proof of Capacity, Proof of Elapsed Time, and Proof of Burn. Each algorithm is summarized with examples of blockchains that use each approach.
This document discusses Ethereum 2.0 and its goals of improving decentralization, scalability, and energy efficiency over Ethereum 1.0. It outlines the key components of Ethereum 2.0 including using proof of stake instead of proof of work, implementing sharding to partition the blockchain into multiple shards to improve scalability, and transitioning to a new virtual machine. It provides timelines for rolling out these changes and demos running an Ethereum 2.0 beacon node.
Consensus algorithms are an extremely crucial part of blockchain technology. Proof of Work is a type of consensus mechanism where users use their computational devices to solve complex mathematical problems in order to verify and add blocks to the ledger system. On the other hand, in Proof of Stake users will need to stake their coins in order to participate in the verification process.
The difference between the two types of consensus protocol lies within the working mechanism of these two processes. Verification mechanism, incentive policy, vulnerability, motivation, requirement, and scalability are some of the areas where these two differ.
To help you better understand the differences between these two consensus protocols, 101 Blockchain offer an array of lucrative blockchain courses. These courses will help you comprehend the working principles of these two algorithms.
The following courses will help you learn about PoW and PoS->
Blockchain Like a Boss Masterclass
https://academy.101blockchains.com/courses/blockchain-masterclass
Getting Started with Bitcoin Technology
https://academy.101blockchains.com/courses/getting-started-with-bitcoin-technology
Learn more about the certification courses from here ->
Certified Enterprise Blockchain Professional (CEBP) course
https://academy.101blockchains.com/courses/blockchain-expert-certification
Certified Enterprise Blockchain Architect (CEBA) course
https://academy.101blockchains.com/courses/certified-enterprise-blockchain-architect
Certified Blockchain Security Expert (CBSE) course
https://academy.101blockchains.com/courses/certified-blockchain-security-expert
Learn more from our guide ->
https://101blockchains.com/pow-vs-pos-a-comparison/
The document summarizes the Advanced Encryption Standard (AES). It describes how AES was selected by NIST as a replacement for DES. AES (Rijndael cipher) uses a block size of 128 bits, with key sizes of 128, 192, or 256 bits. It operates on data in rounds that include byte substitution, shifting rows, mixing columns, and adding the round key. The key is expanded into an array of words used for each round.
Algorithmic trading (AT) is trading conducted via electronic platforms where buy and sell orders are automatically generated by quantitative models with little human intervention. AT strategies include execution algorithms like VWAP and TWAP that minimize market impact, and alpha generating algorithms like arbitrage and trend following that exploit short-term price anomalies. While AT increases market liquidity and price discovery, it can also increase short-term volatility. Experts note that high-frequency trading puts less privileged traders at a disadvantage due to its high costs and speed, though it benefits the market overall through greater liquidity.
Intel® QuickAssist Technology Introduction, Applications, and Lab, Including ...Michelle Holley
Abstract: Intel® QuickAssist Technology improves performance and efficiency across the data center and other computing platforms by handling the compute-intensive operations of bulk cryptography, public key cryptography, and data compression. In this course, we will give an overview of the technology along with the summary of resources to get started with integrating Intel® QAT into your platform solutions. We will also demonstrate using Intel® QAT with applications such as OpenSSL, NGINX, and HAProxy, with a hands-on lab.
Speaker Bios:
Joel Auernheimer, a Platform Application Engineer at Intel, has been focused on enabling customers to integrate Intel® QuickAssist Technology in their platform solutions. Joel is a native of Phoenix, Arizona and enjoys hiking, basketball, soccer, singing, and spending time with friends and family.
Joel Schuetze has been with Intel since 1996. For the last 9+ years he has worked as Platform Application Engineer supporting customers with Intel QuickAssist Technology.
The document discusses the design of secure hash algorithms SHA-256 and SHA-3. SHA-256 has a block size of 512 bits and processes messages in 64 rounds. SHA-3 uses a sponge construction that absorbs data into a state and then squeezes out the output hash. Both algorithms are used to secure blockchains like Bitcoin and Ethereum.
Ethereum is the largest decentralized software platform that allows you to build smart contracts and decentralized applications without any downtime and without any third party interference.
VISIT:- http://www.oodlestechnologies.com/online-cryptocurrency-wallet
Distributed systems and blockchain technologyAlket Cecaj
Blockchain is a distributed ledger system where nodes work together to validate transactions in a coordinated fashion without a central authority. It allows for decentralized consensus through mechanisms like proof-of-work. The main challenges in distributed systems are coordination between nodes and achieving fault tolerance. The CAP theorem states that a distributed system cannot achieve consistency, availability, and partition tolerance simultaneously. Blockchain sacrifices consistency for availability and partition tolerance. It uses elements like addresses, transactions, blocks, and consensus mechanisms like proof-of-work to securely and immutably record transactions on the distributed ledger.
Blockchain consensus algorithms allow distributed networks to agree on a single transaction history. The document discusses several popular consensus algorithms including proof of work (PoW), proof of stake (PoS), practical Byzantine fault tolerance (PBFT), Istanbul Byzantine fault tolerance (IBFT), proof of authority (PoA), and RAFT. It provides overviews of how each algorithm works and compares their properties such as finality, tolerance for malicious nodes, trust requirements, and energy usage.
Consensus Algorithms - Nakov @ jProfessionals - Jan 2018Svetlin Nakov
This document provides an overview of blockchain consensus algorithms including proof-of-work, proof-of-stake, delegated proof-of-stake, proof-of-authority, and PBFT. It discusses the requirements for consensus algorithms and describes how various popular cryptocurrencies implement different consensus mechanisms. Several Java-based blockchain projects are also mentioned, including IOTA, NEM, and TRON.
Basics you need to know about Solidity and how it works. Learn the simple way of building a smart contract in Solidity. Tools that can be used with Solidity.
Ethereum Tutorial - Ethereum Explained | What is Ethereum? | Ethereum Explain...Simplilearn
The document provides an overview of Ethereum, including its key features like cryptocurrency (Ether), smart contracts, the Ethereum Virtual Machine (EVM), decentralized applications (Dapps), and decentralized autonomous organizations (DAOs). It discusses how Ether is used to pay for transactions and computational resources on the Ethereum network. It also explains how smart contracts are programs that facilitate exchanges without a central authority, and how the EVM executes smart contract code. Dapps are similar to traditional web applications, but run on a distributed network instead of centralized servers.
Watch this talk here: https://www.confluent.io/online-talks/apache-kafka-architecture-and-fundamentals-explained-on-demand
This session explains Apache Kafka’s internal design and architecture. Companies like LinkedIn are now sending more than 1 trillion messages per day to Apache Kafka. Learn about the underlying design in Kafka that leads to such high throughput.
This talk provides a comprehensive overview of Kafka architecture and internal functions, including:
-Topics, partitions and segments
-The commit log and streams
-Brokers and broker replication
-Producer basics
-Consumers, consumer groups and offsets
This session is part 2 of 4 in our Fundamentals for Apache Kafka series.
The document provides biographical details about Oliver Velez, an experienced trader and founder of multiple trading firms. It outlines his career history starting from trading in college in 1984 to present. It describes the various trading firms he established like Pristine Capital Management and Mastertrader.com. It also summarizes his accomplishments like authoring several best-selling trading books. The rest of the document discusses Velez's current trading organization iFundTraders which has multiple teams of traders around the world and its goals to scale up the number of funded traders.
This document provides an introduction to blockchain technology. It defines blockchain as a distributed ledger of transactions stored in immutable blocks chained together using cryptography. It explains key concepts such as nodes, blocks, hashes, mining, and proof-of-work. Blockchain allows for trustless transactions without intermediaries by achieving consensus among peers on the network. Examples of blockchain networks and potential use cases are also discussed.
Overview of what is Bitcoin, Ethereum, Smart Contract and Blockchain.
First explained what is Bitcoin and its entities involved. Then Ethereum and what is called Blockchain.
Examples of the existing platforms those are using Ethereum.
Ethereum Blockchain with Smart contract and ERC20Truong Nguyen
This document discusses blockchain technology, Ethereum, and smart contracts. It begins with an overview of blockchain and how it works using blocks, transactions, and miners to validate transactions. It then discusses Ethereum, describing it as an open blockchain platform that allows anyone to build decentralized applications and smart contracts using its Ethereum Virtual Machine. It explains what smart contracts are and how they work using code on the blockchain to automatically execute agreed upon terms. Finally, it discusses ERC20, which defines a standard for Ethereum tokens, and sidechains, which are separate blockchains attached to parent blockchains to provide enhancements like security and performance.
"How to Run a Quantitative Trading Business in China with Python" by Xiaoyou ...Quantopian
From QuantCon 2017: Running a quantitative trading business in China used to be very difficult and require strong IT skills, however it's getting much easier nowadays, when traders with no professional IT training can also do all the tasks in quantitative trading using Python.
In this sharing session, Xiaoyou will share his experience in using Python for data collection, strategy development and automated trading. He will also introduce some related open source projects including TuShare, quantOS, vn.py and so on.
This document provides an overview of statistical arbitrage (SA) strategies and their application to 130/30 products using synthetic equity index swaps. It begins by discussing the efficient market hypothesis and how SA circumvents some of its limitations. It then describes various SA trading strategies, including pairs trading, stochastic spread approaches, cointegration approaches, high frequency strategies, and behavioral strategies. The document applies some of these SA strategies to 130/30 products using synthetic index swaps and finds they can improve the risk-return profile of active equity management.
This document provides an overview of the Advanced Encryption Standard (AES). It discusses how AES was created through an encryption algorithm competition organized by the National Institute of Standards and Technology to replace the aging Triple DES standard. AES is a symmetric block cipher that encrypts 128-bit blocks using 128, 192, or 256-bit keys and 10, 12, or 14 rounds respectively. The AES encryption process takes the plaintext through several stages - substitution, shifting rows, mixing columns, and adding the round key - with the inverse being applied for decryption. Some potential security attacks on AES are also mentioned, such as related-key and XSL attacks, but it remains secure if implemented correctly.
This document provides an overview and agenda for a session on advanced topics in IP multicast deployment. It discusses tools and techniques for deploying IP multicast, including examples of PIM mode configurations, rendezvous point deployment models, interconnecting PIM domains, label switched multicast, high availability techniques, and multicast in wireless environments. The target audience is network engineers in enterprise and service provider networks.
This proof-of-concept demonstrates ultra-low end-to-end latency for financial market data. It uses a Cisco Nexus 3548 switch with Warp mode to achieve sub-200 nanosecond latency between the switch and an FPGA-based feed handler from Enyx. The feed handler processes market data from NASDAQ with less than 1.4 microseconds of latency. Measurement from TS-Associates show that over 99% of packets experience less than 1.3 microseconds of latency through the FPGA. This integrated solution from Cisco, Enyx, Universal E-Business Solutions and TS-Associates provides the low latency needed for high-frequency trading with real market data.
The document describes an IoT protocol gateway that allows communication between multiple PLCs/devices and transfer of data to information systems via open protocols like Modbus TCP/RTU. The gateway supports over 450 PLC protocol drivers, has flexible I/O and wireless options, and provides an easy way to convert proprietary protocols to Modbus TCP/RTU with minimal configuration needed. It also lists the product portfolio and contact information for Advantech's Open HMI and Control Solutions division.
Intel® QuickAssist Technology Introduction, Applications, and Lab, Including ...Michelle Holley
Abstract: Intel® QuickAssist Technology improves performance and efficiency across the data center and other computing platforms by handling the compute-intensive operations of bulk cryptography, public key cryptography, and data compression. In this course, we will give an overview of the technology along with the summary of resources to get started with integrating Intel® QAT into your platform solutions. We will also demonstrate using Intel® QAT with applications such as OpenSSL, NGINX, and HAProxy, with a hands-on lab.
Speaker Bios:
Joel Auernheimer, a Platform Application Engineer at Intel, has been focused on enabling customers to integrate Intel® QuickAssist Technology in their platform solutions. Joel is a native of Phoenix, Arizona and enjoys hiking, basketball, soccer, singing, and spending time with friends and family.
Joel Schuetze has been with Intel since 1996. For the last 9+ years he has worked as Platform Application Engineer supporting customers with Intel QuickAssist Technology.
The document discusses the design of secure hash algorithms SHA-256 and SHA-3. SHA-256 has a block size of 512 bits and processes messages in 64 rounds. SHA-3 uses a sponge construction that absorbs data into a state and then squeezes out the output hash. Both algorithms are used to secure blockchains like Bitcoin and Ethereum.
Ethereum is the largest decentralized software platform that allows you to build smart contracts and decentralized applications without any downtime and without any third party interference.
VISIT:- http://www.oodlestechnologies.com/online-cryptocurrency-wallet
Distributed systems and blockchain technologyAlket Cecaj
Blockchain is a distributed ledger system where nodes work together to validate transactions in a coordinated fashion without a central authority. It allows for decentralized consensus through mechanisms like proof-of-work. The main challenges in distributed systems are coordination between nodes and achieving fault tolerance. The CAP theorem states that a distributed system cannot achieve consistency, availability, and partition tolerance simultaneously. Blockchain sacrifices consistency for availability and partition tolerance. It uses elements like addresses, transactions, blocks, and consensus mechanisms like proof-of-work to securely and immutably record transactions on the distributed ledger.
Blockchain consensus algorithms allow distributed networks to agree on a single transaction history. The document discusses several popular consensus algorithms including proof of work (PoW), proof of stake (PoS), practical Byzantine fault tolerance (PBFT), Istanbul Byzantine fault tolerance (IBFT), proof of authority (PoA), and RAFT. It provides overviews of how each algorithm works and compares their properties such as finality, tolerance for malicious nodes, trust requirements, and energy usage.
Consensus Algorithms - Nakov @ jProfessionals - Jan 2018Svetlin Nakov
This document provides an overview of blockchain consensus algorithms including proof-of-work, proof-of-stake, delegated proof-of-stake, proof-of-authority, and PBFT. It discusses the requirements for consensus algorithms and describes how various popular cryptocurrencies implement different consensus mechanisms. Several Java-based blockchain projects are also mentioned, including IOTA, NEM, and TRON.
Basics you need to know about Solidity and how it works. Learn the simple way of building a smart contract in Solidity. Tools that can be used with Solidity.
Ethereum Tutorial - Ethereum Explained | What is Ethereum? | Ethereum Explain...Simplilearn
The document provides an overview of Ethereum, including its key features like cryptocurrency (Ether), smart contracts, the Ethereum Virtual Machine (EVM), decentralized applications (Dapps), and decentralized autonomous organizations (DAOs). It discusses how Ether is used to pay for transactions and computational resources on the Ethereum network. It also explains how smart contracts are programs that facilitate exchanges without a central authority, and how the EVM executes smart contract code. Dapps are similar to traditional web applications, but run on a distributed network instead of centralized servers.
Watch this talk here: https://www.confluent.io/online-talks/apache-kafka-architecture-and-fundamentals-explained-on-demand
This session explains Apache Kafka’s internal design and architecture. Companies like LinkedIn are now sending more than 1 trillion messages per day to Apache Kafka. Learn about the underlying design in Kafka that leads to such high throughput.
This talk provides a comprehensive overview of Kafka architecture and internal functions, including:
-Topics, partitions and segments
-The commit log and streams
-Brokers and broker replication
-Producer basics
-Consumers, consumer groups and offsets
This session is part 2 of 4 in our Fundamentals for Apache Kafka series.
The document provides biographical details about Oliver Velez, an experienced trader and founder of multiple trading firms. It outlines his career history starting from trading in college in 1984 to present. It describes the various trading firms he established like Pristine Capital Management and Mastertrader.com. It also summarizes his accomplishments like authoring several best-selling trading books. The rest of the document discusses Velez's current trading organization iFundTraders which has multiple teams of traders around the world and its goals to scale up the number of funded traders.
This document provides an introduction to blockchain technology. It defines blockchain as a distributed ledger of transactions stored in immutable blocks chained together using cryptography. It explains key concepts such as nodes, blocks, hashes, mining, and proof-of-work. Blockchain allows for trustless transactions without intermediaries by achieving consensus among peers on the network. Examples of blockchain networks and potential use cases are also discussed.
Overview of what is Bitcoin, Ethereum, Smart Contract and Blockchain.
First explained what is Bitcoin and its entities involved. Then Ethereum and what is called Blockchain.
Examples of the existing platforms those are using Ethereum.
Ethereum Blockchain with Smart contract and ERC20Truong Nguyen
This document discusses blockchain technology, Ethereum, and smart contracts. It begins with an overview of blockchain and how it works using blocks, transactions, and miners to validate transactions. It then discusses Ethereum, describing it as an open blockchain platform that allows anyone to build decentralized applications and smart contracts using its Ethereum Virtual Machine. It explains what smart contracts are and how they work using code on the blockchain to automatically execute agreed upon terms. Finally, it discusses ERC20, which defines a standard for Ethereum tokens, and sidechains, which are separate blockchains attached to parent blockchains to provide enhancements like security and performance.
"How to Run a Quantitative Trading Business in China with Python" by Xiaoyou ...Quantopian
From QuantCon 2017: Running a quantitative trading business in China used to be very difficult and require strong IT skills, however it's getting much easier nowadays, when traders with no professional IT training can also do all the tasks in quantitative trading using Python.
In this sharing session, Xiaoyou will share his experience in using Python for data collection, strategy development and automated trading. He will also introduce some related open source projects including TuShare, quantOS, vn.py and so on.
This document provides an overview of statistical arbitrage (SA) strategies and their application to 130/30 products using synthetic equity index swaps. It begins by discussing the efficient market hypothesis and how SA circumvents some of its limitations. It then describes various SA trading strategies, including pairs trading, stochastic spread approaches, cointegration approaches, high frequency strategies, and behavioral strategies. The document applies some of these SA strategies to 130/30 products using synthetic index swaps and finds they can improve the risk-return profile of active equity management.
This document provides an overview of the Advanced Encryption Standard (AES). It discusses how AES was created through an encryption algorithm competition organized by the National Institute of Standards and Technology to replace the aging Triple DES standard. AES is a symmetric block cipher that encrypts 128-bit blocks using 128, 192, or 256-bit keys and 10, 12, or 14 rounds respectively. The AES encryption process takes the plaintext through several stages - substitution, shifting rows, mixing columns, and adding the round key - with the inverse being applied for decryption. Some potential security attacks on AES are also mentioned, such as related-key and XSL attacks, but it remains secure if implemented correctly.
This document provides an overview and agenda for a session on advanced topics in IP multicast deployment. It discusses tools and techniques for deploying IP multicast, including examples of PIM mode configurations, rendezvous point deployment models, interconnecting PIM domains, label switched multicast, high availability techniques, and multicast in wireless environments. The target audience is network engineers in enterprise and service provider networks.
This proof-of-concept demonstrates ultra-low end-to-end latency for financial market data. It uses a Cisco Nexus 3548 switch with Warp mode to achieve sub-200 nanosecond latency between the switch and an FPGA-based feed handler from Enyx. The feed handler processes market data from NASDAQ with less than 1.4 microseconds of latency. Measurement from TS-Associates show that over 99% of packets experience less than 1.3 microseconds of latency through the FPGA. This integrated solution from Cisco, Enyx, Universal E-Business Solutions and TS-Associates provides the low latency needed for high-frequency trading with real market data.
The document describes an IoT protocol gateway that allows communication between multiple PLCs/devices and transfer of data to information systems via open protocols like Modbus TCP/RTU. The gateway supports over 450 PLC protocol drivers, has flexible I/O and wireless options, and provides an easy way to convert proprietary protocols to Modbus TCP/RTU with minimal configuration needed. It also lists the product portfolio and contact information for Advantech's Open HMI and Control Solutions division.
This document provides information about the NMS TX4000 product from Launch 3 Telecom, including how to purchase it, specifications, payment and shipping details, warranty, and services. It describes the TX4000 as a Dialogic NMS board supporting a specific number of SS7 links and software. Contact information and a link to view the product datasheet are provided.
Cdot Max ng architecture working modelsRahmanScholar
This document provides an overview of CDOT's MAX NG system and the migration from the existing MAX system. The key points are:
1. MAX NG features a distributed architecture with centralized control and uses software to provide enhanced services like video calling. This reduces infrastructure costs and makes upgrades simpler.
2. Migrating the MAX system involves converting line and trunk interfaces to VoIP gateways, moving switching functions to an external softswitch, and replacing internal media paths with IP.
3. The MAX NG architecture consists of a core network for service delivery and an access network of upgraded MAX exchanges. The core uses softswitches and other servers while the access uses Line Access Gateway Units and a Central Access
The document discusses openness in the AXE telecommunications system from Ericsson. It defines two types of openness: network openness, which refers to the ability to interconnect with other networks using standard protocols, and system openness, which involves using commercially available standard hardware and software components to build the AXE system. The document outlines how Ericsson has increased system openness over time by introducing more standard components like commercial processors, Windows NT, and off-the-shelf hardware, while focusing proprietary development on the interface between components. This allows Ericsson to benefit from advances in other industries while concentrating on its core switching capabilities.
In this paper we attempt to give a networking solution by applying VLSI architecture techniques to router design for networking systems to provide intelligent control over the network. Networking routers to have limited input/output configurations, which we attempt to overcome by adopting bridging loops to reduce the latency and security concerns. Other techniques we explore include the use of multiple protocols. We attempt to overcome the security and latency issues with protocol switching technique embedded in the router engine itself. The approach is based on hardware coding to reduce the impact of latency issues as the hardware itself is designed according to the need. We attempt to provide a multipurpose networking router by means of Verilog code, thus we can maintain the same switching speed with more security we embed the packet storage buffer on chip and generate the code as self-independent VLSI based router. Our main focus is the implementation of hardware IP .router. The approach enables the router to process multiple incoming IP packets with different versions of protocols simultaneously, e.g. for IPv4 and IPv6. The approach will results in increased switching speed of routing per packet for both current trend protocols, which we believe would result inconsiderable enhancement in networking systems.
The IBM Flex System Interconnect Fabric provides a scalable network fabric for connecting compute nodes and storage within a Flex System POD using a single IP management approach. Key components include the SI4093 System Interconnect module for connecting nodes within a chassis and G8264CS aggregation switches. The fabric reduces latency and simplifies management by representing the POD as a single network element to upstream networks while providing a loop-free Layer 2 network internally.
Transforming a traditional home gateway into a hardwareaccelerated SDN switchIJECEIAES
Nowadays, traditional home gateways must support increasingly complex applica-tions while keeping their cost reasonably low. Software Defined Networking (SDN) would simplify the management of those devices, but such an approach is typically reserved for new hardware devices, specifically engineered for this paradigm. As a consequence, typical SDN-based home gateway performs the switching in software, resulting in non-negligible performance degradation. In this paper, we provide our experience and findings of adding the OpenFlow support into a non-OpenFlow compatible home gateway, exploiting the possible hardware speedup available in the existing platform. We present our solution that transparently offloads a portion of the OpenFlow rule into the hardware, while keeping the remaining ones in software, being able to support the presence of multiple hardware tables with a different set of features. Moreover, we illustrate the design choices used to implement the func-tionalities required by the OpenFlow protocol (e.g., packet-in, packet-out messages) and finally, we evaluate the resulting architecture, showing the significant advantage in terms of performance that can be achieved by exploiting the underlying hardware, while maintaining an SDN-type ability to program and to instantiate desired network operations from a central controller.
The document discusses the drivers behind converging voice and data networks. The public switched telephone network (PSTN) architecture is inflexible and cannot adapt quickly enough, while data traffic has overtaken voice on many networks. True convergence of data, voice and video requires high-speed broadband access. IP networks provide a flexible, standards-based architecture and allow for more rapid feature development and deployment compared to the proprietary nature of the PSTN. Open interfaces in the packet, call control and application layers enable more vendors to create interoperable solutions.
Accelerating system verilog uvm based vip to improve methodology for verifica...VLSICS Design
In this paper we present the development of Acceleratable UVCs from standard UVCs in System Verilog
and their usage in UVM based Verification Environment of Image Signal Processing designs to increase
run time performance. This paper covers development of Acceleratable UVCs from standard UVCs for
internal control and data buses of ST imaging group by partitioning of transaction-level components and
cycle-accurate signal-level components between the software simulator and hardware accelerator
respectively. Standard Co-Emulation API: Modeling Interface (SCE-MI) compliant, transaction-level
communications link between test benches running on a host system and Emulation machine is established.
Accelerated Verification IPs are used at UVM based Verification Environment of Image Signal Processing
designs both with simulator and emulator as UVM acceleration is an extension of the standard simulationonly
UVM and is fully backward compatible with it. Acceleratable UVCs significantly reduces development
schedule risks while leveraging transaction models used during simulation.
In this paper, we discuss our experiences on UVM based methodology adoption on TestBench-Xpress
(TBX) based technology step by step. We are also doing comparison between the run time performance
results from earlier simulator-only environment and the new, hardware-accelerated environment. Although
this paper focuses on Acceleratable UVC’s development and their usage for image signal processing
designs. Same concept can be extended for non-image signal processing designs.
GMNS will design and implement a computer network for First Bourne Tax Services including installing hardware such as servers, switches, routers, firewalls, and access points. The network will utilize virtualization and cloud services including containers for functions like DHCP, DNS, file sharing, and security cameras. Hardware specifications are provided for the EMC storage servers and considerations for storage configuration, RAID levels, and calculating disk IOPS.
The document describes the Cisco Catalyst 4908G Ethernet switch. It provides details on how to purchase the switch from Launch 3 Telecom, including payment and shipping options. It also provides information on the warranty and additional services offered by Launch 3 Telecom, such as repair, maintenance contracts, and installation services for the Cisco switch.
HyperTransport is a high-speed serial point-to-point interconnect that was developed as an alternative to traditional I/O buses to address increasing bandwidth needs. It provides high bandwidth, low latency communication between components using a packet-based protocol and source synchronous signaling. HyperTransport supports multiple topologies including daisy chaining, switches, and stars and can scale from personal computers to large multiprocessor systems. It has largely replaced front-side buses and can integrate processors, memory, and I/O subsystems more efficiently than previous bus architectures.
A NETWORK-BASED DAC OPTIMIZATION PROTOTYPE SOFTWARE 2 (1).pdfSaiReddy794166
The International Journal of Engineering and Science and Research is online journal in English published. The aim is to publish peer review and research articles without delay in the developing in engineering and science Research.The International Journal of Engineering and Science and Research is online journal in English published. The aim is to publish peer review and research articles without delay in the developing in engineering and science Research.
The document describes the Genexis fiber-to-the-home (FTTH) network architecture, which uses a point-to-point topology to connect each user to the central office via a dedicated fiber. The network supports both Ethernet/IP connectivity and CATV broadcast services. Key elements include routers and switches to transport IP traffic, and optical transmitters, amplifiers, and splitters to distribute CATV signals. The architecture is based on open standards and provides high bandwidth to users in a scalable and cost-effective manner.
The document discusses the functions of the transport layer in the OSI model. It explains that the transport layer accepts data from the session layer, breaks it into packets and delivers them to the network layer. It is responsible for guaranteeing successful arrival of data at the destination and provides end-to-end communication between source and destination transport layers. The transport layer separates upper layers from low-level data transmission details and handles any data loss or damage. It can transmit packets in the same order or as isolated messages depending on the network and protocol.
CAN and TTP are the two wired network protocols used for distributed .pdfssuserc77a341
CAN and TTP are the two wired network protocols used for distributed embedded system
network communication discussed in class. Another very popular protocol is flexRay, Give a
clear description ofFlexray and indicate the main differences between Flexray. CAN, and TTP
(do not just summarize these difference in a table). To get credit for this question you must
include your sources as references|
Solution
ISSN(Online): 2320
-
9801
ISSN (Print): 23
20
-
9798
I
nternational
J
ournal of
I
nnovative
R
esearch in
C
omputer
and
C
ommunication
E
ngineering
(An ISO 3297: 2007 Certified Organization)
Vol.2, Special Issue 4, September 2014
Copyright to
IJIRCCE
www.ijircce.com
63
Several time
-
triggered technologies su
ch as time
-
triggered CAN (TTCAN
[7], [8]), time
-
triggered protocol (TTP,
[9], [10]), and
FlexRay
[11], [12] have been designed to provide predictable medium access at a higher available
bandwidth. An example
of in
-
vehicle network for a typical car is shown in figure 1 below.
Figure 1.
In
-
vehicle network example.
Time
-
triggered protocol (TTP) has been developed by Technical University of Vienna after two
decades of e
xtensive
research. Messages using TTP ar
e statistically schedule based on the progression of time. It has an advantage that it can
precisely control the message transmission and reception time. This characteristic makes it
suitable
for safety critical
applications. However, there are three drawb
acks to see: it is inefficient in terms of network utilization and periodic
message response time and the other being lack of flexibility.
Nowadays, either an event
-
triggered or a time
-
triggered mechanism is required for message transmissions in the
vehi
cle network, and in some cases, both of them are required at the same time in complex control
system
s. A hybrid
type of protocol has evolved called
FlexRay
communication protocol which allows transmitting both event
-
triggered
and time
-
triggered messages on
the same bus, thus taking the advantages of both approaches.
In this paper, we selected the most commonly used protocol CAN which is an event
-
triggered technology, TTP
which is a time
-
triggered protocol and the newest protocol in the market,
FlexRay
, fo
r comparison. The section II
describes the history and background of the three protocols. The section III will present an
overvie
w of how the three
protocols work. A number of different comparisons of the three protocols is made in section IV.
Fina
lly, the
real
-
time
demands are discussed in section V followed by conclusions.
II.
HISTORY
AND
BACKGROUND
A.
Controller Area Network
It is a serial bus system, which was developed by Robert Bosch in 1980’s for automotive
applications
. The design
was simple, efficient
and robust communication network. The CAN protocol is internationally standardized in ISO
11898
-
1 and comprises the data link layer and components of the physical layer of the 7
-
layer ISO
-
OSI reference
model. CAN, which is now available from mo.
●Records data in the USB drive
●Battery Powered Handheld Troubleshooter for Field Testing
●5.7-inch TFT color display
●Supports TTL, I2C, SPI, IrDA,
●CAN, LIN, FlexRay, LAN and USB
●Mega Speed Mesurement
●Supports Logic Analyzer Analysis and Analog Waveform Analysis
●Outputs edited digital waveform.
The LE-8200A is the top-level model of battery-powered communications protocol analyzer. The LE-8200A has an enlarged display in response to an increasing demand without degrading the excellent portability of the LE Series. It is ideal for development tests of communications systems and industrial equipment, as well as for after-sale services and communication trouble analysis. LE-series have been used in the industries of railways, aviation, and a variety of manufactures for few decades where reliability is very important. With optional kits, it can be used for developing network, in-vehicle, PC peripheral, embedded devices. Unlike the software based analyzers, it cannot be affected by the capability of PC and can be used in the place where PC is not allowed.
ALOE Transit SBC is a session border controller that combines security, media management, and transcoding services in a single, highly scalable software platform. The product can be easily deployed in complex network structures and features network topology hiding and distributed architecture, which makes the network less vulnerable to malicious attacks.
The document discusses how Tata Consultancy Services (TCS) upgraded their TCS BaNCS securities trading application to use Intel Xeon E5-2670 processors. This reduced the application's latency by up to 86% and doubled its throughput. The key techniques used were enabling parallel processing across multiple CPU cores, optimizing for features like Intel Turbo Boost and Hyper-Threading, and improving NUMA awareness of the application. The lower latency trading platform provided by this upgrade gives financial institutions using the TCS BaNCS application a significant competitive advantage.
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3. T7® Technology Roadmap
Deutsche Börse Group 2
This initiative includes
Provision of a portfolio of interfaces that meet the needs of
different user groups
High throughput and low latency of the trading system
Delivery of functionality the market demands with
shortened lead time
Exceptional level of transparency & customer service
Recent developments
Upgrade of the co-location network infrastructure
(29 May 2017)
Introduction of the “first-in first-out” (FIFO) principle on high-
frequency gateways (Release 5.0, 19 June 2017)
Migration of the Xetra® market to T7
(26 June and 3 July 2017)
Outlook
We will roll out T7 release 6 on 4 December 2017.
The release will include the following
Functionality to meet the MiFID II regulatory requirements
Enable submission of good-till-date (GTD) and good-till-
cancel (GTC) orders via high-frequency sessions
A new Selective Request for Quote Service
Introduction of partition specific gateways (details in this
presentation)
Deutsche Börse is pursuing its Technology Roadmap to deliver innovative and superior
trading technology.
For further details about T7 please visit our web sites:
www.eurexchange.com/t7 and www.xetra.com/xetra-en/technology/t7
4. Deutsche Börse Group 3
Processed transactions and response times
T7 Enhanced Trading Interface – round-trip times
Deutsche Börse has continuously
invested in its trading system and
has been able to reduce the
processing time of technical
transactions significantly. Since
the beginning of this year the
median round-trip time has been
reduced by 60 µs to below 75 µs
and average daily round-trip is
now below 180 µs. Note that
numbers include cash market from
26 June 2017 onwards.
5. Deutsche Börse Group 4
Overview of T7
T7 consists of partitions. Here, a partition is a failure
domain in charge of matching, persisting and producing
market data for a subset of products. Each T7 partition is
distributed over two rooms in the Equinix data centre.
There are 10 Eurex T7 partitions in charge of futures and
options trading available on Eurex Exchange. Since launch
of Xetra on T7 there are 10 Xetra T7 partitions serving the
XETR market. A separate additional partition is used for
each of EEX (XEEE), Vienna (XVIE) and Dublin (XDUB)
markets.
There are 10 equity and 16 derivatives high-frequency
gateways in the Equinix data centre shared by all Trading
Participants of the respective markets.
The reference data contains the mapping of products to
partition IDs.
With the introduction of partition specific (PS) gateways
there will be a one to one mapping of active PS gateways
to partitions. The default active PS gateways will be
located on the same side as the active matching engines.
Note that the active half of a partition is either on side A
(for even partitions) or on side B (for odd partitions).
Only in case of the failure of a matching engine or a
market data publisher, the active half of the service will
shift to the other room.
6. Deutsche Börse Group 5
Middleware, network, hardware and OS overview
T7 uses state-of-the-art infrastructure components
Intel Xeon E5-2667 v3 CPUs (Haswell) on all servers hosting core services (Matching engines, un-netted market data
publishers, high-frequency gateways).
Intel Xeon E5-2690 CPUs (Sandy Bridge) or E5-2683 v4 (Broadwell) on non-performance critical servers.
The operating system used is Red Hat Linux 6.7 with real-time kernel on all core components.
T7 internal communication between its core components is based on IBM WebSphere MQ Low Latency Messaging using an
Infiniband network in order to deliver the required speed, capacity and stability requirements.
T7 network access
Deutsche Börse offers Trading Participants to connect via 10 GbE cross connects to its T7 platform in the Equinix data centre.
The co-location 2.0 offering uses Cisco 3548x switches. All cables are normalized to give an overall maximum deviation
between any two cross connects of less then +/- 1 m (+/- 5 ns).
Participant facing interface cards on the gateways and market data publishers use Solarflare EnterpriseOnload technology to
bypass the kernel TCP stack.
7. Orders/quotes – optimal access
Deutsche Börse Group 6
Daily statistics about private “last mile” performance between the high-frequency gateways and Participant servers as well as
best in class numbers (per location and system wide) are provided within the member portal (member.deutsche-boerse.com).
We expect that a good daily average TCP/IP round-trip will be less than 6 µs for 10 GbE connections in co-location 2.0.
The network latency can be further examined by comparing the provided RequestTime (t_3n) and SendingTime (t_9) with
timestamps taken at the customer installation.
Note that using 10 Mbps connections (built on 1 GbE cross connects) to connect to T7 low-frequency or high-frequency
gateways results in an additional latency of about 50 µs (round-trip) compared to the 10 GbE access to high-frequency
gateways .
Using 10 GbE cross connects in co-location 2.0 offering
for the access to the high-frequency ETI gateways in the
Equinix facility provides the fastest way for order and
quote management in T7.
The T7 gateways duties include all validations that do not
need the knowledge of the order book or market state.
The static network latency differences between different
gateway to matcher links is 2 µs maximum.
To achieve lowest possible latency, it is recommended to
use the short order layout if possible - this saves about 8
µs gateway processing time on the way in compared to
“normal” lean orders.
8. Deutsche Börse Group 7
Processing inside a partition
In case that during this phase several new orders/quotes transactions arrive at the core matching component the processing
remains unchanged, i.e. no batching takes place.
The generation of market data other than EOBI (by the market data publisher), listener broadcasts and trade confirmations (by
the persistency server) are done on separate servers. Hence the order of the resulting messages from these servers is not
deterministic.
T7 Partition
t_8
Market data publisher
(EMDI)
Market data publisher
(EOBI)
Core matching
Persistency Layer:
Trade/Order
Confirmation
Orders/quotes entered for a specific product are sent by the gateway server to the
respective matching engine (residing in a partition).
The matching priority is assigned when the orders/quotes are read into the
matching engine.
The core matching component works as follows:
when an order/quote arrives, it is functionally processed (e.g. put in the book or
matched).
handover of data to the EOBI Market data publisher
handover of all data resulting from the (atomic) processing of the incoming
order/quote to the market data and persistency components in the partition.
Resulting responses and private broadcasts are sent out in the following order:
direct response to the order/quote entered (for persistent as well as for non-
persistent orders and quotes)
fast execution information for booked orders/quotes (in case of a match)
10. Co-location 2.0
Co-location 2.0 is an improved 10GbE connectivity introduced in parallel to the existing 10GbE network (Co-Location 1.0).
Reduced complexity
Fewer customer facing switches
Customers may reach any switch from any data-center room
Passive components in customer rooms, i.e. cables and patch panels only
Increased predictability
Reduced latency variance
Hardware refresh of switches (Cisco Nexus 3548x)
Switches operate in cut-through mode, configured to use “Warp mode” to minimize latency
Switches exhibit very low switch jitter within the precision of measurement devices (+/- 4 ns), both for ETI and market data
Equidistant cables with a tolerance of +/- 1m verified using an optical time-domain reflectometer (OTDR) and packet round-trip
measurements
Reduced latency
One way latency improvement of 2.3 µs compared to co-location 1.0
Improved monitoring
Tapping and timestamping at network boundary and internally
Deutsche Börse Group 9
Overview
11. Co-location 2.0
2 switches per gateway room per market (‘distribution layer’, only one market shown)
Eurex®: 8 centrally located switches (‘access layer’, 4 per side, A and B)
Xetra®: 4 centrally located switches (2 per side, A and B, not shown below)
Customers can connect to any access layer switch from any of the 7 co-located rooms
There is a separate Market Data network with same layout
Deutsche Börse Group 10
Network topology
C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C CC C C C C C C
Customer room 1 Customer room 3Customer room 2 Customer room 4 Customer room 5 Customer room 6
C C
GW A 1 GW A n
Side A
GW B 1 GW B n
Side B
C C C C C C
Customer room 7
C
12. We are constantly measuring the latency profile of our co-location
infrastructure using taps and aggregation switches that use
hardware assisted timestamping on ingress port.
Extra care has been taken to ensure the time synchronization
between these timestamping devices using a combination of white
rabbit, pps and ptp. With this we achieve a time synch better than
10 ns.
The latency profiles between the three measurement points is
shown below. Latency between access layer and distribution layer
is identical for all access layer switches within the measurement
precision.
Co-location 2.0
Access layer switch latency
Deutsche Börse Group 11
Latency profile
Access to distribution layer latency
GW A 1 GW A n
Access
layer
Distribution
layer
14. Deutsche Börse Group 13
Inbound message sequencing
Inbound sequencing inside the T7 system takes place
on the network in front of the trading gateways,
in the gateway for messages of all sessions connected
routed to one matching engine,
in the matcher for messages of all sessions.
Inbound ordering is preserved
within the messages of a session routed to one matching
engine (=partition),
between the messages sent from one gateway to one
matching engine (=partition).
Matcher
Gateway N
Gateway 1
Aa B
Session A
Session B
Aa
B
C
Session E E
Session C
CD
Sequencing point
Ba A CDE
S
S Sequencer Switch
ED
Core matchingSession D
CED
A Ba
EOBI 2
EOBI 1
timestamp
15. Inbound latency spectrum
Deutsche Börse Group 14
Orders/quotes – inbound latency profile
The top graphs on the left show the latency distribution of the
three parts of our trading infrastructure which an order/quote
traverses before time-priority is assigned.
The three parts are: gateway network interface card (NIC) to
gateway application start (t_3n to t_3), gateway application
space processing (t_3 to t_3’), gateway-out to matching
engine-in (t_3’ to t_5).
Graphs show all transactions sent to high-frequency
gateways on 29 Aug 2017.
The top right graph shows the systematic latency difference
in the internal network when traversing sides from gateway to
matching engine of ~1.3 µs.
The bottom graph shows the aggregate inbound latency from
the gateway NIC to the matching engine in. The gateway
processing part is the most relevant for the total variance on
the inbound path of a transaction.
The median inbound latency has been reduced by 10 µs
since the last update of this presentation in March 2017
(Eurex only).
NIC to gateway app
(t_3 to t_3n)
Gateway processing
(t_3’ – t_3)
Gateway to matcher
(t_5 – t_3n)
NIC to matching engine
(t_5 – t_3n)
16. Inbound latency spectrum
Inbound latency variance has three main sources:
Statistical effects (always present)
Queuing / overloading effects (e.g. ‘microbursts’, input rate > processing rate)
Data dependent latency differences (e.g. mass quotes requests with 100 quote pairs versus a single quote pair)
The below graphs show inbound latency distributions (t_5 - t_3n) for messages processed by high-frequency gateways for the
Eurex market.
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Orders/quotes – Eurex inbound latency variance
* Free transactions are defined as those whose predecessor has
been consumed by the matching engine when the transaction
arrived at the gateway
17. Inbound latency spectrum
The inbound latency is slightly higher for Xetra than for Eurex as there are more checks done on the gateway.
The below graphs show inbound latency distributions (t_5 - t_3n) for messages processed by high-frequency gateways for the
Xetra market.
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Orders/quotes – Xetra inbound latency variance
18. Inbound latency spectrum
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Orders – inbound latency variance implications
The matching sequence may be different from the incoming sequence due to the statistical distribution of the inbound latencies. The
graph below shows the ‘theoretically expected’ probability of re-ordering of two consecutive transactions compared to the actual
observed reordering between the most competitive transaction types. Overtaking is not possible within a high-frequency gateway as
it operates in first-in first-out (FIFO) mode.
For Xetra the median inbound latencies are slightly higher ( 26.1 µs for NewOrderShort and 23.3 µs for Order Delete requests),
while the confidence intervals are smaller at 5 µs and 4.7 µs respectively (10 to 90 percentile).
Inbound latency of free orders by type (Eurex)
Percentiles
Order Delete
NIC to ME
(t_5 - t_3n)
NIC to GW
(t_3 - t_3n)
GW
(t_3' - t_3)
GW to ME
(t_5 - t_3')
10% 18.4 2.3 8.2 6.8
25% 19.8 2.4 9.3 7.5
50% 21.3 2.5 10.4 8.4
75% 22.8 2.7 11.5 9.0
90% 24.2 2.9 12.5 9.5
Confidence
intervals
25-75% 3.0 0.2 2.2 1.5
10-90% 5.9 0.5 4.3 2.7
Percentiles
NewOrderShort
NIC to ME
(t_5 - t_3n)
NIC to GW
(t_3 - t_3n)
GW
(t_3' - t_3)
GW to ME
(t_5 - t_3')
10% 21.0 2.3 10.6 7.0
25% 22.8 2.4 12.1 7.7
50% 24.8 2.5 13.8 8.5
75% 26.6 2.6 15.2 9.1
90% 28.3 2.8 16.5 9.6
Confidence
intervals
25-75% 3.8 0.2 3.1 1.3
10-90% 7.3 0.5 5.9 2.6
19. Inbound latency spectrum
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Orders/quotes – latency variance for inbound transactions
Inbound latency spectrum for the fastest order transaction
The graph top left shows the “free”, i.e. un-queued, inbound
latency (t_5 - t_3n) spectrum for the fastest
NewOrderSingleShort request in case a Participant sends
several functionally identical transactions simultaneously via 1,
2, 4, 8 and 16 different high-frequency gateways.
The statistical gain comparing the inbound latency of 1 against
the fastest of a swarm of 16 requests is ~4 µs.
The graph bottom left shows the respective cumulated
probability for the fastest request.
Since the introduction of the FIFO processing on high
frequency gateways with T7 release 5 there is no incentive to
send more than one identical transaction to a single gateway.
As a reaction we have noticed a significant drop in multiplicity.
21. Partition Specific Gateway
Latency jitter on parallel inbound paths has incentivized multiplicity to reduce latency.
This lead to higher system load at busy times and thus created higher, less predictable latencies.
The introduction of a single (low-latency) point of entry will address these issues.
Increased predictability
Each partition will have only one partition specific (PS) gateway assigned to it. This gateway operates in first-in first-out (FIFO)
mode. Thus the reception sequence of the PS gateway will determine the sequence of matching (based on the timestamp of the
first bit of the frame that completes a ETI message).
Co-location 2.0 offers a highly deterministic, predictable and equal network access.
Reduced complexity
There will be only one low latency entry point per partition. There is no need to probe multiple gateways to achieve best
matching priority. All partitions will stay accessible via the low frequency gateways.
Reduced latency
The PS Gateway will be tuned for highest throughput and will offer a lower base latency than the current high-frequency
gateways.
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Motivation
22. Partition Specific Gateway
The active partition specific gateway will reside on the same side as the active matching engine per default.
There will be a network link between side A and B via the distribution layer switches with a latency of more than 50 µs.
This guarantees that all partition specific gateways are reachable via a single line in case of a failure.
Note that PS Gateways will be available only for Xetra and Eurex markets, whereas EEX, Xetra Vienna and Xetra Dublin
will offer access via low-frequency gateways only.
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Topology
Standby PS 1 Matcher 1
Active PS 2
Active PS 4
Active PS 8
Standby PS 3
Standby PS 5
Active PS 6
Standby PS 7
Matcher 2
Active PS 1
Standby PS 2
Standby PS 4
Standby PS 8
Active PS 3
Active PS 5
Standby PS 6
Active PS 7
C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C CC
Side A Side B
C C C C C C C C C C C C CC
Customer Room
1
Customer Room
3
Customer Room
2
Customer Room
4
Customer Room
5
Customer Room
6
Customer Room
7
C
Matcher 3
Matcher 4
Matcher 5
Matcher 6
Matcher 7
Matcher 8
Matcher 9
Matcher 10
Matcher (Non PS enabled)
LF 1 LF 2
Standby PS 9 Active PS 9
Standby PS 10Active PS 10
>50µs
23. Partition Specific Gateway
The partition specific gateway uses the same ETI protocol as the existing ETI gateways (low-frequency and high-frequency).
It will offer the same functionality as the high-frequency gateways, but only for a single partition.
Session setup
All high-frequency sessions will be eligible to connect to a partition specific gateway.
A session may only connect to a single gateway at any given point in time.
There will be a maximum number of sessions per participant allowed to login to a single PS gateway at any given point in time.
Connection
The connection process follows the three-step logon procedure, with a Connection Gateway Request message to retrieve the
assigned active and standby PS gateway from the connection gateway, followed by a Session Logon at the PS gateway. The
initial Connection Gateway Request message has to contain the target partition ID.
You may send a session logon to the standby PS gateway to test network connectivity. Those logons will be rejected with the
appropriate error code (refer to the respective ETI manual for details).
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Implementation
24. Partition Specific Gateway
The partition specific gateways will be introduced in a stepwise approach:
Step 1 – parallel setup of a futures partition
December 2017: The first PS gateway will be enabled for Eurex partition 4 (hosting FGBM and FDXM) in parallel to the existing
high frequency gateways.
Step 2 – PS Gateway only for a futures partition
January 2018: access to partition 4 via high frequency gateways will be cut off.
Step 3 – parallel setup of an options partition
January 2018: A PS gateway will be enabled for Eurex partition 9 (hosting options) in parallel to the existing high frequency
gateways in (a week after step 2).
Step 4 – PS Gateway only for an options partition
January 2018: access to partition 4 via high frequency gateways will be cut off.
Step 5/6 – PS Gateway only for the remaining Eurex partitions
February 2018: PS gateway only access will be enabled for all other Eurex partitions
The migration schedule for Xetra is not fixed yet, but a similar approach will be implemented in the first half of 2018.
The final and detailed migration schedule will be published via implementation news.
Note: EEX and Xetra Vienna and Dublin will not adopt the PS Gateway concept.
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Migration
25. Partition Specific Gateway
When a failure of a partition specific gateway is detected all sessions logged in via that gateway will be logged out and their
orders and quotes deleted.
Subsequently the standby PS gateway will be activated and allow session logins. A connection request should be sent to the
Connection Gateway. The response will indicate the active PS gateway and the session can then login to this PS gateway.
There will be an activation phase during which no order management via the activated PS gateway will be possible. This is
currently foreseen to be 60 seconds to allow participants some time to evaluate the situation and re-login.
After the activation phase an ETI ServiceAvailability broadcast will be sent to the connected sessions and order management
service will be available.
Schematic partition specific gateway failover
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Failover
Active PS
Gateway
Standby PS
Gateway
Failed PS
Gateway
Standby PS
Gateway
Activated PS
Gateway
Failed PS
Gateway
Active PS
Gateway
Failed PS
Gateway
Normal
operation
Active
gateway fails
Standby
activated
Failover
completed
< 20 sec 60 sec
26. Throttle and session limits
In order to protect its trading system, T7 has several measures in place to ensure that its most vital components are
not harmed by a malfunctioning client application. Therefore transaction limits are imposed on T7 sessions.
All ETI sessions (HF and LF) are available with throttle values of 150 messages/sec or 50 messages/sec.
Furthermore LF sessions that cannot enter orders/quotes but can only receive trade and listener broadcasts are avaivable (at a
reduced price).
All ETI session types have an assigned disconnect limit of
450 for sessions with a throttle value of 150 messages/sec, i.e. a session will be disconnected in case of more than 450
consecutive rejects due to exceeding the transaction limit (throttle).
150 for sessions with a throttle value of 50 messages/sec, i.e. a session will be disconnected in case of more than 150
consecutive rejects due to exceeding the transaction limit (throttle).
Please note that in case the disaster recover facility is used, all ETI sessions will have a throttle limit of 30 messages per
second.
For both limits, all technical transactions are counted using a sliding window.
The number of ETI sessions which can be ordered is limited. Currently, up to 80 sessions can be ordered. If more than 80
sessions are required please get in touch with your Technical Key Account Manager.
There will be a limit on maximum number of sessions per participant and partition that can connect to a partition specific
gateway concurrently. This limit is currently assumed to be 80 sessions but subject to review.
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28. T7® topology
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Matching engine:
order book maintenance & execution
creation of direct responses as well as
execution messages for passive
orders/quotes
creation of EOBI order book messages
creation of EOBI order book snapshot
messages
Persistency:
persistent order storage
trade/execution history
transaction history for standard orders
creation of listener broadcast for standard
orders
Market Data (EMDI):
creation of order book delta messages
creation of order book snapshot messages
PTP based synchronization of clocks using hardware support is used for high-frequency gateways, matching engines and market data servers in
production (and also in simulation). Hence time stamps on these servers can be used to analyze one way transport times.
T7 PartitionParticipant Gateway
EMDI
t_8
Market data
publisher (EMDI)
Market data
publisher (EOBI)
EOBI
Core matching
ETIt_1
t_2
t_3n t_3’
t_5
t_7t_9
t_8
t_11
t_10
t_6
t_4’t_4
t_3
Persistency Layer
Retransmit Requests
Trade/Order
Notifications
29. Trading system dynamics
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Matching engine and market data performance
Matching dynamics Eurex partition 6 (20 Sep 2017) During micro-bursts, the input into the matching engine may
be greater than the throughput capabilities. This in turn
causes queuing which results in higher latencies.
Higher latencies cause risk (i.e. it takes longer to place/pull
an order).
T7 provides real-time insight in the matching engine and
market data performance. It publishes the sending time of a
EOBI packet as it leaves the matching engine (t_9) as well
as the matching engine in time (t_5).
T7 publishes the performance indicator (t_8-t_5) explicitly in
the EMDI UDP packet header.
The Gantt chart on the left shows the paths
Matching engine in (t_5) to
Start matching (t_7) to
EOBI SendingTime (t_9) [where available] to
Matching engine out (t_6) to
ETI SendingTime (t_4)
Typical throughput rates are 650 / ms at t_5, 200 / ms at t_7
and 220 / ms at t_6.
EOBI send times are now usually well before the matching
engine send time of responses.
30. Orders/quotes – detailed performance data
For the top 15 futures products, daily statistics about the matching engine processing times as well as Eurex Enhanced
Transaction Interface gateway processing times are provided via the ‘Member Section’ on Eurex Exchange’s website. The ETI
round-trip times are calculated based on t_4 – t_3 (gateway SendingTime – gateway application start). Since introduction of
FIFO Gateways reduced multiplicity has resulted in lower average matching engine processing times. The table below
additionally contains latency figures for DAX equities for reference.
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Our transparency
Product Product Average Median
99th
percent Average Median
99th
percent Average Median
99th
percent
EURO STOXX 50® Index Futures FESX 104 27 900 192 85 1320 190 84 1500
STOXX® Europe 50 Index Futures FSTX 43 24 600 144 81 1100 142 76 1500
DAX® Futures FDAX 57 25 435 151 81 960 150 80 1000
Mini-DAX® Futures FDXM 46 27 306 129 83 640 131 86 750
MDAX® Futures F2MX 40 24 484 118 76 940 118 78 1000
SMI® Futures FSMI 36 23 246 111 76 520 111 78 750
Euro-Bund Futures FGBL 127 29 1060 200 91 1240 203 88 1500
Euro-Bobl Futures FGBM 90 26 840 176 104 1060 167 86 1250
Euro-Schatz Futures FGBS 62 23 700 154 109 900 138 78 1000
Euro-Buxl® Futures FGBX 66 28 520 131 81 720 134 82 750
Long-Term Euro-BTP Futures FBTP 71 31 493 139 90 660 140 90 750
Euro-OAT Futures FOAT 53 27 423 122 84 600 122 84 750
EURO STOXX® Banks Futures FESB 53 25 640 132 74 1120 133 76 1250
VSTOXX® Futures FVS 44 26 467 138 89 920 125 82 1250
STOXX® Europe 600 Index Futures FXXP 49 24 640 130 74 1140 133 76 1250
DAX® Equities 24 20 92 115 76 1000 116 80 750
Matching engine
Round-trip times (in µs)
Enhanced Trading Interface
Round-trip times
(all GWs, t_4 - t_3 in µs)
Enhanced Trading Interface
Round-trip times
(HF GWs, t_4 - t_3n in µs)
32. Trading system dynamics
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Latency characteristics of EOBI versus ETI
EOBI vs ETI (Eurex Futures)
T7 is designed to publish order book updates first on its
public data feed.
The top diagram shows the time difference distribution
between public and private data for Eurex futures (EOBI first
datagram vs ETI responses, t_9-t_4), the graph below
shows the same for Xetra DAX equities.
The data is a production sample from 29 August 2017.
EOBI update is usually at least 30 µs faster than the private
response for order book updates and at least 45 µs faster for
executions.
The first EOBI datagram was faster in approximately 99.9
percent of the cases compared to the ETI response and also
the first passive ETI book order notification (not shown).
EOBI vs ETI (Xetra DAX equities)
33. Trading system dynamics
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Latency characteristics of EOBI versus EMDI
Latency characteristics of EMDI versus EOBI After the integration of the EOBI publisher into the matching
engine the market data updates provided via EOBI is almost
always faster than EMDI.
The top diagram shows the distribution of t_9 minus t_8, i.e.
EOBI first datagram versus EMDI sending time, the bottom
diagram shows the cumulative distribution.
The graphs show data of EURO STOXX 50® Index Futures
(FESX) after hardware upgrade and move of the EOBI
disseminator into the matching engine (29 August 2017). This
move reduced the median latency by more than 30 µs for
EOBI messages.
EOBI was faster in more than 99.98 percent of the cases
with trades involved and in 99.96 percent of order book
updates without trades.
A very similar latency characteristic applies to the T7 Cash
Market.
34. Trading system dynamics
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Latency characteristics of ETI versus EOBI versus EMDI
Outbound latency for FESX trades (29 Aug 2017) This diagram displays the dependency of the median latency
on the complexity of a trade for ETI (t_4-t_7), EMDI (t_8-t_7)
and EOBI (t_9-t_7). Note that for ETI we display the gateway
sending time of the first passive notification and for EOBI the
sending time of the UDP datagram containing the Execution
Summary message.
In about 99.95% of all trades, we disseminate order book
data on EOBI first (even true for larger trades).
The merge of EOBI with the matching engine (since 13
March 2017) reduced the latency of EOBI significantly.
35. Market data distribution
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Latency difference of primary and secondary feed
EMDI
EOBI
Please note that for products assigned to an even partition, market
data is published first on the A stream and then on the B stream
whereas, for products assigned to an odd partition market data is
published first on the B stream and then on the A stream.
The partition ID / product ID is contained in the UDP datagram
header of the order book incremental messages and can be used
for filtering on UDP datagram level for EMDI / EOBI.
Furthermore, a UDP datagram on the T7 EMDI / EOBI order book
delta or snapshot channel will only contain data of exactly one
product (e.g. EURO STOXX 50® Index Futures).
The median latency difference between the A and the B
incremental feed is about 8.4 µs for EMDI (see top diagram to the
left) and 2.3 µs for EOBI (see bottom diagram to the left).
T7 provides a csv file on a daily basis with the minute-by-minute
network latency (minimum, average, maximum 99 per cent) for the
A and B streams of EMDI for non co-location access points. This
information can help you determine whether you or T7 had an
issue causing a market data delay. The file is provided in the
member portal (member.deutsche-boerse.com).
36. Eurex: Market data volume
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Eurex EMDI
Eurex EOBI
Each data point equals the maximum bandwidth produced on
a 1 millisecond scale by the incremental B stream in Mbps.
The provided data shows one data point per minute for
29 Aug 2017.
Eurex market data peak data volume can be a significantly
higher on high volume trading days. Hence Participants that
want to receive data for all Eurex Exchange’s products or US
only products with less than 1 ms queuing delays need to
use a connection with a bandwidth of more than 1,000 Mbps
(all products) or 300 Mbps (for U.S. only products),
respectively.
Enhanced Order Book Interface market data is currently only
available to Trading Participants using 10 GbE connections.
Trading Participant are advised to take two cross connects
(one for each market data stream) in co-location to receive
market data.
Latency sensitive Trading Participants are advised to use two
10 GbE connections (one for each market data stream) in co-
location to receive market data.
37. Xetra: Market data volume
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Xetra EMDI
Xetra EOBI
Each data point equals the maximum bandwidth produced on
a 1 millisecond scale by the incremental B stream in Mbps.
The provided data shows one data point per minute for
29 Aug 2017.
Xetra Market Data peak data volume can be a significantly
higher on high volume trading days. Hence Participants that
want to receive data with less than 1 ms queuing delays
need to use a connection with a bandwidth of more than 500
Mbps (EMDI, All products) or 300 Mbps (EMDI, DAX®
equities only).
Enhanced Order Book Interface market data is currently only
available to Trading Participants using 10 GbE connections.
Trading Participant are advised to take two cross connects
(one for each market data stream) in co-location to receive
market data.
Latency sensitive Trading Participants are advised to use two
10 GbE connections (one for each market data stream) in co-
location to receive market data.
39. What you need to be fast…
A few recommendations to achieve the lowest possible latency:
Use the Equinix co-location facility to be close to Deutsche Börse T7.
Use state-of-the-art switches (if any) and only have at most one hop between the exchange network and your server.
Use good network interface cards and TCP/IP acceleration, e.g. a Linux kernel-by-pass library.
Use two 10 GbE (cross-) connections in co-location 2.0 for EMDI or EOBI market data and two 10 GbE (cross-) connections for
T7 ETI.
Try the two different high-frequency gateways assigned to each ETI session to see which delivers the better performance for
your strategy (try it out and compare your time stamps as well as P&L for different days).
Measure and analyze your own time stamps (e.g. the reaction time as recommended on the next slide).
Use state of the art time synchronization, e.g. by the exchange provided time service to synch your clocks with ours via PTP.
Trade notifications need to be processed to create safety (only the trade notifications contain legally binding information about a
trade!). Therefore, we recommend to use either a low-frequency ETI session or a FIX trade capture drop copy to confirm the
fast execution information provided by the execution reports via high-frequency sessions*.
Try to use the EOBI Execution Summary for fast trading decisions and position keeping (passive executions).
For a consistent order book, all incremental updates following the Execution Summary should always be processed.
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40. What you need to be fast…
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Participant reaction time measurement
T7 PartitionParticipant Gateway
EMDI
t_8
Market data publisher
(EMDI)
Market data publisher
(EOBI)
EOBI
Core matching
ETIt_1
t_2
t_3n t_3’
t_5
t_7
t_9
t_8
t_11
t_10
t_6
t_4’t_4
t_3
Measure the time between market data
reception (t_10/t_11) and your reaction
(t_1), take note of aggressor in timestamps
(t_3n) of executions.
42. Enhanced Order Book Interface
Exceptions to fast trading decisions based on the Execution Summary
The Execution Summary at the beginning of an EOBI packet can be used for fast trading decisions (and
passive position keeping) in the majority of cases. However there are certain scenarios where this may lead
to a wrong perception of the order book on client side. This includes cases where:
The Request-In timestamp is not set:
This is for example in case of more than one market order being triggered by an incoming order/quote. In
such a scenario, there will be one Execution Summary sent for each market order. The Execution Summary
for the first market order will be at the beginning of the packet but the Execution Summaries for the other
market orders will follow in the same or in the next packet(s) before CompletionIndicator is set to 1.
The Implied flag is set:
In case of synthetic matching, the LastQty shows the total matched quantity that result from all involved
instruments‘ order books. At the same time only the instrument of the aggressing order is given. In order to
have correct order books, Participants have to process all incremental updates following the Execution
Summary. There is a potential shortcut in this case which is explained on the next two slides.
In equity markets the execution of hidden quantity of Iceberg orders is not reflected in the hiddenQty field of
the EOBI Execution summary.
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43. Enhanced Order Book Interface
Fast trading decision in case of synthetic matching (derivatives markets only)
In case of synthetic matching (TradeCondition in the Execution Summary set to ‚Implied Trade‘), Participants
only interested in the front month instrument will also have to read all details that follow the Execution
Summary.
However, we see that not each combination of instruments is traded with the same frequency (even during a
roll when, on average, more synthetic matches take place). In our benchmark futures, we see that there are
three highly liquid and three less liquid instruments. The front month, the second maturity and the spread
between the two are defined as the liquid instruments, the third maturity and combinations thereof are
considered as less liquid.
A possible shortcut which can speed up the decision-making process is available to Participants that base
their trading decisions primarily on the Execution Summary. These Participants could potentially save
processing time by considering the order books of the three most liquid instruments only.
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44. Enhanced Order Book Interface
Fast trading decision in case of synthetic matching (cont.)
If the instrument in the Execution Summary belongs to one of the three liquid instruments and the
TradeCondition field is set to ‚Implied Trade‘, Participants can apply the following logic to infer the order books
for these liquid instruments:
Check price (‚LastPx‘), total quantity (‚LastQty‘) and side (‚AggressorSide‘) in the Execution Summary.
Delete orders in the incoming instrument‘s order book which have a better price than ‚LastPx‘.
Check whether a combination of orders in the two other liquid books yields a better price than ‚LastPx‘. If
true, delete the orders contributing to these combinations from the respective order books.
Calculate the remaining quantity (‚LastQty‘ minus already deleted quantities). If possible, remove this
quantity from the incoming instrument‘s order book at ‚LastPx‘. If there is not enough quantity available
then try to delete the still remaining quantity from the synthetic order book combination at ‚LastPx‘.
In case the total deleted quantities from the incoming instrument‘s order book and the combined synthetic
order book do not add up to the ‚LastQty‘ it can be concluded that the order book is not correct afterwards.
Our data show that in over 99.7% of the trade cases, it is possible to build a correct order book by using this
shortcut.
Please note that for a consistent order book, Participants should always process all incremental updates
following the Execution Summary.
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45. T7® timestamps
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T7 PartitionParticipant Gateway
EMDI
t_8
Market data publisher
(EMDI)
Market data publisher
(EOBI)
EOBI
Core matching
ETIt_1
t_2
t_3n t_3’
t_5
t_7
t_9
t_8
t_11
t_10
t_6
t_4’t_4
t_3
46. Description of time stamps
t_1,t_2: can be taken by a Participant (e.g. via a network capture) when a request/ response is read from/written to the socket.
t_4: taken by the ETI gateway when a response/ notification is written to the socket on the Participant´s side of the gateway;
contained in (private) ETI response/ notification.
t_3n: taken by the ETI gateway when the first bit of a request arrives on the HF gateway NIC; contained in (private) ETI
response for transactions sent via HF gateways.
t_3: taken by the ETI gateway application when a request is read from the socket on the Participant´s side of the gateway;
contained in (private) ETI response for transactions sent via LF gateways.
t_3’: taken by the ETI gateway right before a request is sent towards the matching engine; contained in (private) ETI response.
t_4’: taken by the ETI gateway when a response/ notification is received by the ETI gateway from the matching engine;
contained in (private) ETI response/ notification.
t_5, t_6: taken by the matching engine when a request/response is read/written; contained in (private) ETI response.
t_7: time at which the matching engine maintains the order book
t_8: time taken by EMDI publisher just before the first respective UDP datagram is written to the UDP socket.
t_9: time taken by EOBI publisher just before the first respective UDP datagram is written to the UDP socket.
t_10, t_11: can be taken by a Participant (e.g. via a network capture) when a UDP datagram is read from the UDP socket.
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Definition
47. T7 time stamp reference
The time stamps t_3,…,t_9 are available via the following fields:
t_3, t_3n: Tag 5979 (“RequestTime”) in the T7 ETI Response
in the T7 EMDI Depth Incremental message, in case a trade is reported
in the T7 EOBI Execution Summary message
t_3’: Tag 7764 (“RequestOut”) in the T7 ETI Response (from the matching engine)
t_4’: Tag 7765 (“ResponseIn”) in the T7 ETI Response (from the matching engine)
Tag 25043 (“NotificationIn”) in the T7 ETI Notification (from the matching engine)
t_4: Tag 52 (“SendingTime”) in the T7 ETI Response and Notification
t_5: Tag 21002 (“TrdRegTSTimeIn“) in the T7 ETI Response (from the matching engine)
Tag 21002 (“TrdRegTSTimeIn”) in the T7 EOBI Order Add, Order Modify, Order Modify Same Priority and
Order Delete messages
Tag 28820 (“AggressorTimestamp“) in the T7 EMDI Depth Incremental message, in case a trade is reported Tag
28820 (“AggressorTimestamp“) in the T7 EOBI Execution Summary message
t_6: Tag 21003 (“TrdRegTSTimeOut“) in the T7 ETI Response and Notification (from the matching engine)
t_7: Tag 17 (“ExecID“) in the T7 ETI Response (from the matching engine)
in the T7 EOBI Execution Summary message
Tag 273 (“MDEntryTime”) in the T7 EMDI Depth Incremental message
Tag 21008 (“TrdRegTSTimePriority”) in the T7 EOBI Order Add and Order Modify messages
Tag 60 (“TransactTime”) in the T7 EOBI Order Modify Same Priority and Order Delete messages
t_8: no Tag (“SendingTime”) in the T7 EMDI UDP packet header
t_9: Tag 60 (“TransactTime”) in the T7 EOBI packet header
(t_8-t_5): no Tag (“PerformanceIndicator“) in the T7 EMDI UDP packet header of the T7 EMDI Depth Incremental stream.
Notes on time stamps:
All time stamps provided are 8 byte integers (in nanoseconds after Unix epoch).
The PerformanceIndicator is a 4 byte integer (in nanoseconds as well).
Deutsche Börse Group 46
48. Thank you for your attention
Contact
Name Sebastian Neusüß, Andreas Lohr
E-Mail monitoring@deutsche-boerse.com
For updates refer to http://www.eurexchange.com/exchange-en/technology/high-frequency_trading