# How Does Network Co-Location Impact Latency in Quote Measurement? ▴ Question

**Published:** 2025-08-23
**Categories:** Question

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## Concept

The act of measuring a quote is an attempt to capture a fleeting state of the market. Every measurement, by its nature, is an observation of a past event. The interval between the event’s occurrence ▴ the moment a price is established within an exchange’s [matching engine](https://prime.greeks.live/question/how-does-the-choice-of-market-matching-engine-architecture-impact-simulation-scalability/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) ▴ and its observation by a [trading system](https://prime.greeks.live/question/what-are-the-system-architecture-requirements-for-integrating-fdid-tagging-into-an-order-management-system/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) defines the boundary of informational certainty. Network co-location is the physical and logical placement of a firm’s trading servers within the same data center as the exchange’s own systems.

This proximity is a direct, architectural response to a fundamental physical constraint ▴ the speed of light. By minimizing the physical distance data must travel, co-location fundamentally alters the nature of quote measurement, contracting the window of uncertainty to its absolute minimum.

This process transforms the data from a historical report into a near-real-time input for decision-making engines. The latency inherent in any network is a composite of several factors. [Propagation delay](https://prime.greeks.live/area/propagation-delay/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite), the time it takes for light to travel through fiber optic cables, constitutes the most significant and irreducible component over long distances. Placing a server a few meters from the exchange’s matching engine, connected by a direct cross-connect, effectively reduces this propagation delay to a matter of nanoseconds.

Other sources of latency, such as serialization delay (the time to place data onto the network interface) and processing delay (the time the network hardware takes to handle the data packet), are also optimized within the high-performance environment of a co-location facility. The result is a high-fidelity data stream that represents the market with the least possible temporal distortion.

> Co-location provides a structural advantage by minimizing the physical distance to an exchange, thereby reducing latency and transforming quote measurement from a delayed estimate into a precise, actionable input.

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## The Anatomy of Quote Latency

Understanding the impact of co-location requires dissecting the journey of a [market data](https://prime.greeks.live/area/market-data/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) packet from its creation to its consumption. This journey, often termed the “[tick-to-trade](https://prime.greeks.live/area/tick-to-trade/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite)” lifecycle, begins inside the exchange. When a new order enters the book and creates a new best bid or offer, the exchange’s matching engine generates a market data message.

This message is the “ground truth” of the market at that instant. The measurement of this quote by an external system is contingent on how quickly and predictably that message can be delivered.

The sequence of events for a non-co-located firm involves numerous potential points of delay:

- **Exchange Egress** ▴ The data packet leaves the exchange’s internal network and is handed off to a telecommunications carrier. 

- **Wide Area Network (WAN) Transit** ▴ The packet travels over public or private networks, traversing multiple routers, switches, and physical connection points, each adding microseconds of delay. 

- **Local Carrier Handoff** ▴ The packet arrives in the destination city and is routed through local carrier infrastructure to the firm’s [data center](https://prime.greeks.live/area/data-center/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite). 

- **Firm Ingress** ▴ The packet enters the firm’s network, passing through firewalls and internal switches before reaching the target server. 

- **Application Processing** ▴ The server’s operating system and application software process the packet, finally making the quote data available to the trading strategy. 

Co-location collapses this entire chain. The WAN transit and multiple carrier handoffs are eliminated, replaced by a single, short, and dedicated fiber optic cross-connect within the data center. This architectural simplification is the primary mechanism through which co-location provides its latency advantage, ensuring the received quote is a far more accurate representation of the market’s current state.

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![Precision system for institutional digital asset derivatives. Translucent elements denote multi-leg spread structures and RFQ protocols](https://options.greeks.live/wp-content/uploads/2025/07/precision-execution-infrastructure-for-institutional-digital-asset-derivatives-request-for-quote-protocol-optimization.jpg)

## Strategy

Adopting a [co-location strategy](https://prime.greeks.live/question/what-are-the-primary-risks-associated-with-a-co-location-based-trading-strategy/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) is a deliberate investment in informational fidelity. The primary benefit extends beyond the simple reduction of average latency; it encompasses a critical improvement in the predictability of data delivery. This reduction in latency variance, or “jitter,” is paramount for the calibration of sophisticated quantitative models. A trading system can compensate for a known, stable delay.

An unpredictable, high-jitter data feed introduces random noise into the system’s perception of the market, corrupting time-sensitive signals and undermining the precision of execution algorithms. Co-location provides a stable, low-jitter environment, which is the bedrock of deterministic trading performance.

![An intricate, transparent digital asset derivatives engine visualizes market microstructure and liquidity pool dynamics. Its precise components signify high-fidelity execution via FIX Protocol, facilitating RFQ protocols for block trade and multi-leg spread strategies within an institutional-grade Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/prime-os-digital-asset-derivatives-rfq-liquidity-ecosystem.jpg)

## A Tiered Information Landscape

The decision to co-locate creates a distinct competitive advantage, effectively segmenting the market into tiers based on informational proximity. Firms operating from co-located facilities have access to market data that is demonstrably faster and more reliable than what is available to off-site participants. This creates a structural hierarchy where co-located firms can react to market events, update their own pricing models, and place orders before others have even received the initial data packet.

In markets like options, where pricing is derived from the state of an underlying asset, this advantage is magnified. A co-located options [market maker](https://prime.greeks.live/question/how-does-a-market-makers-confirmation-threshold-strategy-impact-both-capital-efficiency-and-market-risk/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) can adjust their quotes in response to a minute fluctuation in the underlying security’s price while a remote participant is still operating on stale data, leading to adverse selection.

> The strategic value of co-location lies in achieving a predictable, low-variance data environment, which is essential for the deterministic performance of quantitative trading systems.

The table below illustrates the orders of magnitude difference in latency profiles, providing a clear picture of the tiered access that co-location creates. The measurements represent one-way latency for a market data packet traveling from the exchange’s gateway to the firm’s application server.

| Deployment Location | Typical One-Way Latency | Primary Latency Contributor | Jitter Profile |
| --- | --- | --- | --- |
| Cross-Continental WAN (e.g. London to New York) | 35-40 milliseconds (ms) | Propagation Delay (Speed of Light) | High |
| Regional WAN (e.g. Chicago to New York) | 5-10 milliseconds (ms) | Propagation & Network Hops | Moderate |
| Metro Area Cloud Provider (Same city as exchange) | 500-1500 microseconds (µs) | Network Hops & Virtualization Overhead | Moderate to Low |
| Co-located Facility (Same data center) | 1-50 microseconds (µs) | Hardware & Software Processing | Extremely Low |

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## Implications for RFQ Environments

In a Request for Quote (RFQ) protocol, a liquidity seeker solicits prices from a select group of market makers for a large or complex order. The market makers who respond must price the order based on their current view of the market’s risk and liquidity. A co-located market maker possesses a superior ability to price these requests competitively and safely. Their internal pricing engine is fed by the most current market data, allowing them to calculate their risk on the potential trade with high precision.

This confidence translates into tighter bid-ask spreads offered in their quotes. A remote market maker, contending with higher latency and jitter, must incorporate a larger uncertainty premium into their price, resulting in wider, less competitive quotes to compensate for the risk of the market moving against them before their hedge is in place. Consequently, co-location becomes a critical enabler for any institution seeking to act as a competitive liquidity provider in electronic markets.

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## Execution

The execution of a co-location strategy involves a meticulous, multi-layered approach to system design, where every component in the data path is optimized for minimal delay. The objective is to construct a complete tick-to-trade pipeline that operates at the boundaries of current technology. This requires a deep understanding of network engineering, hardware optimization, and software architecture, all synchronized with high-precision time protocols. The measurement of quote latency itself becomes a sophisticated discipline, demanding specialized hardware and software to capture and analyze performance at the nanosecond level.

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## High-Precision Time Synchronization

Accurate latency measurement is impossible without a globally consistent time reference. All servers and network devices within the trading system, as well as the exchange’s systems, must be synchronized to a common clock. The industry standard for this is the [Precision Time Protocol](https://prime.greeks.live/area/precision-time-protocol/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) (PTP), specifically the IEEE 1588 standard. PTP allows for clock synchronization across a network into the sub-microsecond range.

A typical co-located setup involves deploying a dedicated PTP grandmaster clock that receives its time signal from GPS satellites. This time is then distributed to all servers and switches, which act as PTP clients. Every market data packet received is timestamped by the network interface card (NIC) upon arrival, before it even reaches the server’s CPU. This hardware timestamping bypasses the non-deterministic delays of the operating system’s software clock, providing a highly accurate measurement of network transit time.

> Executing a co-location strategy requires optimizing the entire tick-to-trade pipeline, from hardware selection to software architecture, all verified by nanosecond-level latency measurement.

The following table provides a granular breakdown of a latency budget for a single market data packet within a highly optimized, co-located environment. It illustrates where nanoseconds are won and lost in the path from the exchange to the trading application.

| Process Step | Typical Latency Contribution | Key Enabling Technology | Optimization Goal |
| --- | --- | --- | --- |
| Exchange Matching Engine to Gateway | 5-10 microseconds (µs) | Exchange’s Internal Fabric | N/A (Exchange Controlled) |
| Exchange Gateway to Fiber Cross-Connect | 50-200 nanoseconds (ns) | 10/40GbE SFP+ Optics | Shortest possible cable path |
| Network Switch Transit (Internal) | 150-300 nanoseconds (ns) | Ultra-low latency switches (e.g. Arista, Mellanox) | Cut-through forwarding |
| NIC to Server Memory (DMA) | 500-800 nanoseconds (ns) | Kernel Bypass NICs (e.g. Solarflare, Mellanox) | Avoid OS kernel interaction |
| Application Feed Handler Processing | 1-5 microseconds (µs) | Optimized C++, CPU Pinning | Efficient message parsing |
| Strategy Logic Signal Generation | 1-10 microseconds (µs) | FPGA or highly optimized code | Fast decision making |

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## Operational Implementation Framework

Deploying a co-located trading system is a significant engineering undertaking. It requires careful planning and execution across several domains. The process can be structured as a sequence of critical operational steps.

- **Data Center and Cabinet Selection** ▴ The first step is securing space within the primary data center of the target exchange (e.g. Equinix NY4 for NASDAQ, CME’s DC3 in Aurora for its markets). Within the data center, cabinet placement matters; proximity to the exchange’s own server cages can further reduce latency by nanoseconds. 

- **Network Architecture Design** ▴ This involves designing a redundant, ultra-low latency internal network. It includes selecting switches that support cut-through forwarding, which begins sending a packet before it has been fully received, drastically reducing transit time. Redundant fiber cross-connects to the exchange’s gateways are essential for uptime. 

- **Server Hardware Optimization** ▴ Servers are custom-built for performance. This includes selecting CPUs with the highest clock speeds, ensuring optimal NUMA (Non-Uniform Memory Access) configuration to keep data processing close to the relevant CPU core, and using specialized NICs that offer [kernel bypass](https://prime.greeks.live/area/kernel-bypass/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) and hardware timestamping. 

- **Software Stack Engineering** ▴ The software must be designed to minimize internal latency. This often involves writing applications in low-level languages like C++, using event-driven architectures to avoid blocking operations, and pinning specific processes to individual CPU cores to prevent context switching by the operating system. 

- **Continuous Performance Monitoring** ▴ Once deployed, the system requires constant monitoring. Latency measurements are captured for every packet, and statistical analysis is performed in real time to detect any degradation in performance, which could indicate a network issue or a hardware problem. This vigilance is key. 

Ultimately, the successful execution of a co-location strategy provides a firm with a more accurate and timely perception of the market. This superior sensory input is the foundation upon which all subsequent quantitative analysis, risk management, and trade execution decisions are built, offering a persistent structural advantage in electronic markets.

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## References

- Harris, Larry. _Trading and Exchanges ▴ Market Microstructure for Practitioners._ Oxford University Press, 2003.

- Lehalle, Charles-Albert, and Sophie Laruelle, editors. _Market Microstructure in Practice._ World Scientific Publishing, 2018.

- O’Hara, Maureen. _Market Microstructure Theory._ Blackwell Publishers, 1995.

- Budish, Eric, Peter Cramton, and John Shim. “The High-Frequency Trading Arms Race ▴ Frequent Batch Auctions as a Market Design Response.” _The Quarterly Journal of Economics,_ vol. 130, no. 4, 2015, pp. 1547-1621.

- Hasbrouck, Joel. “High-Frequency Quoting ▴ A Post-Implementation Analysis of the Designated Market Maker Program.” _Journal of Financial Markets,_ vol. 35, 2017, pp. 48-72.

- FINRA. “Understanding High-Frequency Trading ▴ An Overview of the Market, the Players, and the Technology.” _FINRA Office of the Chief Economist,_ 2016.

- CME Group. “Co-Location and Proximity Hosting.” _CME Group Market Structure Report,_ 2021.

- Easthope, C. et al. “The Impact of Network Latency on Financial Market Liquidity.” _IEEE Journal on Selected Areas in Communications,_ vol. 34, no. 11, 2016, pp. 2979-2992.

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## Reflection

The relentless pursuit of lower latency through co-location has defined the technological trajectory of modern financial markets for over a decade. Having established a physical presence at the heart of the market, the next frontier of optimization moves inward. The challenge shifts from conquering physical distance to refining the internal logic and processing pathways within the server itself. How does an operational framework evolve when the external environment is stable and the primary source of delay becomes the system’s own decision-making process?

The knowledge of co-location’s impact serves as a foundational component, enabling a shift in focus toward the efficiency of algorithms and the architecture of risk systems. The ultimate strategic potential lies in leveraging this superior informational vantage point to build more intelligent, resilient, and capital-efficient trading systems.

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## Glossary

<a href="https://prime.greeks.live/question/how-does-the-choice-of-market-matching-engine-architecture-impact-simulation-scalability/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Matching Engine

The scalability of a market simulation is fundamentally dictated by the computational efficiency of its matching engine's core data structures and its capacity for parallel processing. </a><a href="https://prime.greeks.live/question/what-are-the-system-architecture-requirements-for-integrating-fdid-tagging-into-an-order-management-system/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Trading System

Integrating FDID tagging into an OMS establishes immutable data lineage, enhancing regulatory compliance and operational control. </a><a href="https://prime.greeks.live/area/propagation-delay/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Precision-engineered system components in beige, teal, and metallic converge at a vibrant blue interface. This symbolizes a critical RFQ protocol junction within an institutional Prime RFQ, facilitating high-fidelity execution and atomic settlement for digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/principal-rfq-connectivity-layer-for-digital-asset-derivatives-execution.jpg)

## Propagation Delay

Meaning ▴ Propagation delay quantifies the temporal interval required for a data signal or an execution instruction to traverse a communication medium, such as fiber optic cable, or for a logical circuit to process an input and produce a stable output. </a><a href="https://prime.greeks.live/area/tick-to-trade/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A Prime RFQ interface for institutional digital asset derivatives displays a block trade module and RFQ protocol channels. Its low-latency infrastructure ensures high-fidelity execution within market microstructure, enabling price discovery and capital efficiency for Bitcoin options](https://options.greeks.live/wp-content/uploads/2025/08/prime-os-rfq-protocol-engine-high-fidelity-execution-digital-asset-derivatives.jpg)

## Tick-To-Trade

Meaning ▴ Tick-to-Trade quantifies the elapsed time from the reception of a market data update, such as a new bid or offer, to the successful transmission of an actionable order in response to that event. </a><a href="https://prime.greeks.live/area/market-data/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A central crystalline RFQ engine processes complex algorithmic trading signals, linking to a deep liquidity pool. It projects precise, high-fidelity execution for institutional digital asset derivatives, optimizing price discovery and mitigating adverse selection](https://options.greeks.live/wp-content/uploads/2025/07/prime-os-rfq-protocols-high-fidelity-digital-asset-derivatives-execution.jpg)

## Market Data

Meaning ▴ Market Data comprises the real-time or historical pricing and trading information for financial instruments, encompassing bid and ask quotes, last trade prices, cumulative volume, and order book depth. </a><a href="https://prime.greeks.live/area/data-center/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Data Center

Meaning ▴ A data center represents a dedicated physical facility engineered to house computing infrastructure, encompassing networked servers, storage systems, and associated environmental controls, all designed for the concentrated processing, storage, and dissemination of critical data. </a><a href="https://prime.greeks.live/question/what-are-the-primary-risks-associated-with-a-co-location-based-trading-strategy/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Co-Location Strategy

A co-location strategy's primary risks are the systemic, operational, and financial fragilities inherent in its high-speed design. </a><a href="https://prime.greeks.live/question/how-does-a-market-makers-confirmation-threshold-strategy-impact-both-capital-efficiency-and-market-risk/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Market Maker

A market maker's confirmation threshold is the core system that translates risk policy into profit by filtering order flow. </a><a href="https://prime.greeks.live/area/precision-time-protocol/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Precision Time Protocol

Meaning ▴ Precision Time Protocol, or PTP, is a network protocol designed to synchronize clocks across a computer network with high accuracy, often achieving sub-microsecond precision. </a><a href="https://prime.greeks.live/area/kernel-bypass/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Institutional-grade infrastructure supports a translucent circular interface, displaying real-time market microstructure for digital asset derivatives price discovery. Geometric forms symbolize precise RFQ protocol execution, enabling high-fidelity multi-leg spread trading, optimizing capital efficiency and mitigating systemic risk](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-request-for-quote-protocol-high-fidelity-execution-market-microstructure-intelligence-layer.jpg)

## Kernel Bypass

Meaning ▴ Kernel Bypass refers to a set of advanced networking techniques that enable user-space applications to directly access network interface hardware, circumventing the operating system's kernel network stack. </a>

**Tags:** [Network Co-Location](https://options.greeks.live/area/network-co-location/), [Propagation Delay](https://options.greeks.live/area/propagation-delay/), [Quote Latency Measurement](https://options.greeks.live/area/quote-latency-measurement/), [Data Center Proximity](https://options.greeks.live/area/data-center-proximity/), [Precision Time Protocol (PTP)](https://options.greeks.live/area/precision-time-protocol-ptp/), [Tick-to-Trade](https://options.greeks.live/area/tick-to-trade/)	

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A Smart Trading system manages network latency by minimizing physical distance and optimizing the data transmission path.

- 
### [What Specific Software Optimizations Complement Network Topology for Enhanced Quote Capture?](https://options.greeks.live/question/what-specific-software-optimizations-complement-network-topology-for-enhanced-quote-capture/)
![Central blue-grey modular components precisely interconnect, flanked by two off-white units. This visualizes an institutional grade RFQ protocol hub, enabling high-fidelity execution and atomic settlement. It optimizes capital efficiency within digital asset derivatives market microstructure.](https://options.greeks.live/wp-content/uploads/2025/07/digital-asset-derivatives-rfq-core-interconnect-for-high-fidelity-execution.jpg)

Software optimizations precisely calibrate network data flows, enabling ultra-low latency quote capture for superior institutional execution.

- 
### [What Are the Specific Technological Requirements for Integrating Low-Latency Data Feeds into an Institutional Crypto Options Desk?](https://options.greeks.live/question/what-are-the-specific-technological-requirements-for-integrating-low-latency-data-feeds-into-an-institutional-crypto-options-desk/)
![Intricate dark circular component with precise white patterns, central to a beige and metallic system. This symbolizes an institutional digital asset derivatives platform's core, representing high-fidelity execution, automated RFQ protocols, advanced market microstructure, the intelligence layer for price discovery, block trade efficiency, and portfolio margin.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-core.jpg)

An institutional crypto options desk requires a co-located, hardware-accelerated infrastructure running binary protocols to achieve the microsecond-level data fidelity necessary for competitive execution.

- 
### [How Does Co-Location Impact Latency in High-Frequency Options Trading?](https://options.greeks.live/question/how-does-co-location-impact-latency-in-high-frequency-options-trading/)
![A Principal's RFQ engine core unit, featuring distinct algorithmic matching probes for high-fidelity execution and liquidity aggregation. This price discovery mechanism leverages private quotation pathways, optimizing crypto derivatives OS operations for atomic settlement within its systemic architecture.](https://options.greeks.live/wp-content/uploads/2025/08/principals-rfq-engine-driving-optimal-digital-asset-derivatives.jpg)

Co-location grants a latency advantage by minimizing physical distance to an exchange's matching engine, enabling superior execution speed.

- 
### [What Are the Most Effective Technological Strategies for Reducing Latency in Institutional Trading Systems?](https://options.greeks.live/question/what-are-the-most-effective-technological-strategies-for-reducing-latency-in-institutional-trading-systems/)
![Stacked precision-engineered circular components, varying in size and color, rest on a cylindrical base. This modular assembly symbolizes a robust Crypto Derivatives OS architecture, enabling high-fidelity execution for institutional RFQ protocols. It embodies layered liquidity aggregation, optimized price discovery within market microstructure, and capital efficiency for digital asset derivatives.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-rfq-protocol-architecture-optimized-for-high-fidelity-execution.jpg)

Effective latency reduction integrates proximity hosting, hardware acceleration, and kernel-bypass software into a single, optimized execution system.

- 
### [What Are the Technological Prerequisites for a Market Maker to Effectively Capitalize on a Speed Bump?](https://options.greeks.live/question/what-are-the-technological-prerequisites-for-a-market-maker-to-effectively-capitalize-on-a-speed-bump/)
![A precise, metallic central mechanism with radiating blades on a dark background represents an Institutional Grade Crypto Derivatives OS. It signifies high-fidelity execution for multi-leg spreads via RFQ protocols, optimizing market microstructure for price discovery and capital efficiency. This intelligence layer supports algorithmic trading.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-system-microstructure-hub.jpg)

A market maker requires a co-located, FPGA-accelerated system to win the latency race against a speed bump's fixed delay.

- 
### [What Is the Role of Latency in the Success of Pre-Trade Information Leakage Prediction Models?](https://options.greeks.live/question/what-is-the-role-of-latency-in-the-success-of-pre-trade-information-leakage-prediction-models/)
![Institutional-grade infrastructure supports a translucent circular interface, displaying real-time market microstructure for digital asset derivatives price discovery. Geometric forms symbolize precise RFQ protocol execution, enabling high-fidelity multi-leg spread trading, optimizing capital efficiency and mitigating systemic risk.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-request-for-quote-protocol-high-fidelity-execution-market-microstructure-intelligence-layer.jpg)

Latency is the primary determinant of a leakage model's value; it defines the actionable window between prediction and loss.

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---

**Original URL:** https://options.greeks.live/question/how-does-network-co-location-impact-latency-in-quote-measurement/
