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Video Processing in the Cloud

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Video Processing in the Cloud
Lowest price (incl. delivery)
7 149,00 JPY
Typical price524,53 PLN
Lowest (90 days)35,99 PLN
Offers6
Last updated1週間前
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Price history (90 days)
Full history
2026-08-08 2026-08-15
価格推移
更新日時価格
2026-08-0839,99
2026-08-1435,99
2026-08-1551,99
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SP SpringerNatureLink Shop INT 7 149,00 JPY free 7 149,00 JPY 在庫あり 5日前 View offer
SP Springer Nature Author 7 149,00 JPY 19,00 JPY 7 168,00 JPY 在庫あり 1週間前 View offer
SP SpringerNatureLink Shop INT 49,99 USD 29,00 USD 78,99 USD 在庫あり 5日前 View offer
SP SpringerNatureLink Shop INT 54,99 USD free 54,99 USD 在庫あり 5日前 View offer
SP SpringerNatureLink Shop INT 54,99 USD free 54,99 USD 在庫あり 5日前 View offer
SP SpringerNatureLink Shop INT 59,00 EUR free 59,00 EUR 在庫あり 5日前 View offer

価格や在庫状況は変更される場合があります。 最終更新: 08.08.2026 23:08.

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As computer systems evolve, the volume of data to be processed increases significantly, either as a consequence of the expanding amount of available information, or due to the possibility of performing highly complex operations that were not feasible in the past. Nevertheless, tasks that depend on the manipulation of large amounts of information are still performed at large computational cost, i.e., either the processing time will be large, or they will require intensive use of computer resources. In this scenario, the efficient use of available computational resources is paramount, and creates a demand for systems that can optimize the use of resources in relation to the amount of data to be processed. This problem becomes increasingly critical when the volume of information to be processed is variable, i.e., there is a seasonal variation of demand. Such demand variations are caused by a variety of factors, such as an unanticipated burst of client requests, a time-critical simulation,or high volumes of simultaneous video uploads, e.g. as a consequence of a public contest. In these cases, there are moments when the demand is very low (resources are almost idle) while, conversely, at other moments, the processing demand exceeds the resources capacity. Moreover, from an economical perspective, seasonal demands do not justify a massive investment in infrastructure, just to provide enough computing power for peak situations. In this light, the ability to build adaptive systems, capable of using on demand resources provided by Cloud Computing infrastructures is very attractive.

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