LOCAL CACHING
The current paradigm of cloud computing is the result of a progressive shift in the balance between data storage and data transfer: information is stored and processed wherever it is most convenient and inexpensive because the marginal cost of transferring it has become negligible, at least on wire line networks [2]. For wireless devices, though, this cost is not always negligible. The understanding that mobile users are subject to sporadic abundance of connectivity amidst stretches of deprivation is hardly new, and the natural idea of opportunistically leveraging the former to alleviate the latter has been entertained since the
1990s [3]. However, this idea of caching massive amounts of data at the edge of the wire line network right before the wireless hop only applies to delay-tolerant traffic, and thus made little sense in voice-centric systems. Caching might finally make sense now in data-centric systems [4]. Thinking ahead, it is easy to envision mobile devices with truly vast amounts of memory. Under this assumption, and given that a substantial share of the data that circulates wireless corresponds to the most popular audio/video/social content that is in vogue at a given time, it is clearly inefficient to transmit such content via uni cast, but it is frustratingly impossible to resort to multicast because the demand is asynchronous. We hence see local caching as an important alternative, at both the radio access network edge (e.g., at small cells) and mobile devices, also thanks to enablers such as mm Wave and D2D.
LOCAL CACHINGThe current paradigm of cloud computing is the result of a progressive shift in the balance between data storage and data transfer: information is stored and processed wherever it is most convenient and inexpensive because the marginal cost of transferring it has become negligible, at least on wire line networks [2]. For wireless devices, though, this cost is not always negligible. The understanding that mobile users are subject to sporadic abundance of connectivity amidst stretches of deprivation is hardly new, and the natural idea of opportunistically leveraging the former to alleviate the latter has been entertained since the1990s [3]. However, this idea of caching massive amounts of data at the edge of the wire line network right before the wireless hop only applies to delay-tolerant traffic, and thus made little sense in voice-centric systems. Caching might finally make sense now in data-centric systems [4]. Thinking ahead, it is easy to envision mobile devices with truly vast amounts of memory. Under this assumption, and given that a substantial share of the data that circulates wireless corresponds to the most popular audio/video/social content that is in vogue at a given time, it is clearly inefficient to transmit such content via uni cast, but it is frustratingly impossible to resort to multicast because the demand is asynchronous. We hence see local caching as an important alternative, at both the radio access network edge (e.g., at small cells) and mobile devices, also thanks to enablers such as mm Wave and D2D.
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