large storage overhead

USAGE SUMMARY

The phrase "large storage overhead" is correct and usable in written English.
It can be used when discussing the additional storage space required by a system or application beyond the actual data being stored. Example: "The new database system has a large storage overhead, which may impact our overall storage costs."

✓ Grammatically correct

Science

News & Media

Human-verified examples from authoritative sources

Exact Expressions

2 human-written examples

However, this comes with the tradeoff of large storage overhead.

Human-centric Computing and Information Sciences

First, the cooperation table requires large storage overhead.

EURASIP Journal on Wireless Communications and Networking

Human-verified similar examples from authoritative sources

Similar Expressions

58 human-written examples

By broadcasting many different spoof messages, the malicious node can incur a large amount of computation, communication, and storage overhead for node.

EURASIP Journal on Wireless Communications and Networking

These techniques are highly memory intensive requiring large storage space and impose a high computational overhead.

Knowledge-Based Systems

The proposed scheme reduces the communication and storage overhead in big data environment.

Data Science and Engineering

The speed of the system and the small storage overhead make it suitable for use in large databases with online user interfaces.

Computer Vision and Image Understanding

However, using a large number of segments also comes at the expense of higher computational and storage overhead.

EURASIP Journal on Wireless Communications and Networking

Performance analysis shows that our solution reduces the overhead of large-scale broadcast authentication at the expense of increased less processing and storage overhead.

EURASIP Journal on Wireless Communications and Networking

The protocol can use DNP3-SA encryprimitivesitives without the need for major upgrades to existing platforms, and performance analysis shows that our solution reduces the overhead of large-scale broadcast authentication at the expense of minor increased processing and storage overhead.

EURASIP Journal on Wireless Communications and Networking

However, meeting QoS requirements in WSNs introduces certain overhead to routing protocols in terms of energy consumption, intensive computations, and significantly large storage.

EURASIP Journal on Wireless Communications and Networking

Such combinations of models usually outperform individual ones by wide margin at the cost of larger storage and training overhead [31].

EURASIP Journal on Wireless Communications and Networking

Expert writing Tips

Best practice

When evaluating different solutions, always consider the trade-offs between performance gains and the "large storage overhead" introduced. Choose the solution that minimizes the storage footprint without significantly compromising performance.

Common error

Avoid using "large storage overhead" interchangeably with storage capacity. "Large storage overhead" refers to the additional storage needed beyond the raw data itself, not the total amount of storage available.

Linguistic Context

The phrase "large storage overhead" functions as a noun phrase, typically acting as the subject or object of a sentence. It describes a specific attribute or characteristic of a system or process. As indicated by Ludwig AI, the phrase is correct and usable in written English.

Expression frequency: Uncommon

Frequent in

Science

70%

News & Media

15%

Formal & Business

5%

Less common in

Encyclopedias

3%

Wiki

2%

Reference

0%

Ludwig's WRAP-UP

In summary, "large storage overhead" is a noun phrase used to describe the extra storage space required by a system or application beyond the raw data itself. As Ludwig AI confirms, the phrase is grammatically correct and usable in English. While it appears most frequently in scientific and technical contexts, its meaning is readily understood across various domains. To enhance clarity, quantify the overhead whenever possible and be mindful of the scope, differentiating it from total storage capacity.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

significant storage footprint

Replaces "overhead" with "footprint" to emphasize the physical space occupied by the storage.

substantial memory requirement

Focuses on the memory aspect of storage, highlighting the amount of memory needed.

considerable storage burden

Replaces "overhead" with "burden" to stress the load or difficulty associated with the storage.

extensive storage needs

Shifts the focus to the requirement for large amounts of storage space.

high storage demand

Emphasizes the need for significant storage capacity.

large disk space consumption

Specifies the consumption of disk space, providing a more technical alternative.

massive data storage requirements

Highlights the scale of the data storage needs.

notable memory footprint

Highlights the impact on memory usage.

significant disk usage

Highlights disk usage in storage.

sizeable storage allocation

Emphasizes the amount of storage space allocated.

FAQs

What does "large storage overhead" mean?

The term "large storage overhead" refers to the extra storage space required by a system, application, or process beyond the actual data being stored. This additional space may be needed for metadata, indexing, temporary files, or other supporting data structures.

When is "large storage overhead" a problem?

A "large storage overhead" becomes problematic when it consumes a significant portion of available storage resources, leading to increased costs, reduced performance, or scalability limitations. It is particularly concerning in resource-constrained environments.

What are some alternatives to saying "large storage overhead"?

Depending on the context, you could use alternatives such as "significant storage footprint", "substantial memory requirement", or "considerable storage burden".

How can I reduce "large storage overhead" in my system?

To minimize "large storage overhead", consider techniques such as data compression, deduplication, efficient indexing strategies, and optimized data structures. Regularly review and clean up temporary files and unnecessary metadata.