An Optimal Peak Hour Content Server Cache Update Scheduling Algorithm for 5G HetNets

Ma, Manyou; Wong, Vincent W. S.

doi:10.1109/icc.2019.8761705

Cited by 12 publications

(5 citation statements)

References 8 publications

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“…If the content update period is short, fewer UEs or cells need to be considered compared to off-peak-hour caching. New content generated during peak hours can also be stored, and content with temporal change in content preferences can be considered [30], [31].…”

Section: A Peak Hour Cachingmentioning

confidence: 99%

“…In this paper, a method similar to maximizing the hit ratio, described in Eqs. (30) and (31), is used to find a sub-optimal solution. Similar to Eqs.…”

Section: Off-peak-hour Caching To Maximize the Overload Reduction mentioning

confidence: 99%

“…Similar to Eqs. (30) and (31) has a non-zero value only for an overload cell, and tries to reduce the amount of overload data through different weighting depending on the degree of overload.…”

Section: Off-peak-hour Caching To Maximize the Overload Reduction mentioning

confidence: 99%

“…A lightly overloaded cell may well be intermittently in an underload state when the number of UEs or data requests are at a temporarily low ebb. If some cells are in an underload state even during peak hours, a mobile helper can update all or a part of the cache when passing through an underload cell [30], [31]. Such a caching scheme is referred to as peak-hour caching in this paper.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, in peak-hour caching, it is possible for helpers to consider a smaller number of cells and UEs, and to store content in consideration of these users' characteristics. In addition, helpers can store new content generated during peak hours and content with a large temporal change in content preferences [30], [31].…”

Section: Introductionmentioning

confidence: 99%

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Peak-Hour Caching Schemes of Mobile Devices for Overload Cells in Wireless Caching Systems

Kang

2020

IEEE Access

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In the case of broadband wireless communication systems with high carrier frequencies, high-speed wireless communication is feasible, but if high-capacity backhaul is not supplied to all base stations, a backhaul bottleneck may occur. To solve this backhaul bottleneck problem, one can use wireless caching or device-to-device (D2D) caching technology that installs a cache on a mobile end device, use the cache to store video content, and then supply the video content when requested by other end devices. Prior to peak traffic hours, video content can be stored on mobile end devices according to the content preferences, but it is difficult to solve cell overload problems that occur during peak traffic hours. This is because peak traffic hours can persist for a long time, and thus device positions, content preferences, and cell loads are liable to change during peak traffic hours. Providing broadband radio and high-capacity backhaul to all cells can create cost issues, but if there are some cells with broadband wireless resources and high-capacity backhaul, these cells may often support sufficient data even during peak traffic hours. If a mobile end device can intermittently enter a cell with sufficient data supply, it can update its cache using some short-term information. In this paper, we compare wireless caching schemes that update the caches of mobile end devices during peak traffic hours with the goal of reducing overload data. If high-capacity base stations are installed within a certain distance interval from each other to reduce the content update period, then good performance can be obtained by frequently updating the caches while considering the short-term content preferences of nearby overload cells. In addition, if a mobile device can predict its movement path, performance can be further improved by considering only the overload cells in the predicted path.

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Section: A Peak Hour Cachingmentioning

confidence: 99%

“…In this paper, a method similar to maximizing the hit ratio, described in Eqs. (30) and (31), is used to find a sub-optimal solution. Similar to Eqs.…”

Section: Off-peak-hour Caching To Maximize the Overload Reduction mentioning

confidence: 99%