Residential and Industrial Areas Revealed as Most Extreme Hotspots, JDSU Mobile Data Report Finds

(firmenpresse) - MILPITAS, CA -- (Marketwired) -- 03/02/15 -- JDSU (NASDAQ: JDSU)
1% of users consume more than half of all mobile data, consistent with last year's report
50% of data consumed in less than 1% of the network area, confirming that hotspots exist
73% of mobile data in extreme hotspots is consumed in residential and industrial areas, despite assumed widespread use of WiFi
For the fifth consecutive year, scientists at Location Intelligence business unit have revealed the latest trends observed in mobile data usage in a . This year, the study goes beyond extreme usage volumes to reveal the geographic locations with the most extreme data behavior for the very first time. The report highlights the need for mobile operators to understand user behaviour in detail when planning and optimizing their networks.
For the first time, JDSU's study has examined the geographical distribution of mobile data use. The sample covers a representative area of over 17,000 km2 comprising mixed urban, suburban and rural areas.
Remarkably, JDSU found that half of mobile data is being consumed by just 0.35% of the geographical area covered by the network. 90% is consumed in less than 5% of the area. Looked at another way, more than 90% of the geographic area generates less than 1% of total traffic.
The top 100 "extreme hotspots" -- areas where the most extreme mobile data consumption was observed -- were identified and classified into representative zones: Business, Dense Urban, Industrial, Residential and Rural.
Nearly three quarters (73%) of the data being consumed in these hotspots is in Residential and Industrial zones: Residential accounts for almost half (48%); Industrial for exactly one quarter. That Rural should appear in this ranking at all is surprising, but illustrates that without in-depth data analysis, it's difficult to predict where demand will come from.
Consistent with previous years, data consumption is dominated by a relatively small number of users. The latest JDSU study found that 1% of users consume 56% of mobile data.
Indeed, 90% of all mobile data is consumed by just 8.58% of all users. The top 1% of users consume more downlink data, relative to uplink at a ratio of nearly 11:1 on this network under study (11 times more data is downloaded than uploaded) as opposed to the average for this network of nearly 8:1. This is nowhere near as extreme as might be expected, if extreme use was purely -- or even mostly -- driven by streamed content.
The study also looked at the downlink to uplink ratio for the 100 most extreme hotspots and grouped them into the aforementioned zones.
At opposite ends of the scale were Residential, where there is a ratio of only 5.69:1, and Industrial, where the ratio is nearly double this figure at 11.56:1. Typical assumptions would be that industrial zones would exhibit a lower downlink to uplink ratio due to more mixed business use, and that residential areas would exhibit a higher ration driven by media streaming. This study shows that while that may well be the case for the majority of areas, it does not hold true for extreme locations.
Since smartphones began to gain popularity in 2007, mobile operators have been engaged in an ongoing battle to manage spiralling consumer demand for data.
In previous years, JDSU demonstrated that extreme data consumption is limited to a relatively small group of customers. This report reveals that extreme usage is also concentrated in small geographic pockets that do not subscribe to commonly-held industry assumptions. Taken collectively, these findings show that planning network evolution based on industry assumptions and received wisdom will not deliver the best customer or business outcomes. Rather, in-depth data usage and experience intelligence is required for operators to deal with skyrocketing data use in an increasingly competitive environment.
To download a full copy of JDSU's latest Extreme Data Report, please visit: .
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Datum: 02.03.2015 - 07:00 Uhr
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