Research on Cache Placement in ICN

2018 ◽  
pp. 603-611
Author(s):  
Yu Zhang ◽  
Yangyang Li ◽  
Ruide Li ◽  
Wenjing Sun
Keyword(s):  
Cache Placement

scholarly journals History-Aware Online Cache Placement in Fog-Assisted IoT Systems: An Integration of Learning and Control

2021 ◽  
pp. 1-1
Author(s):  
Xin Gao ◽  
Xi Huang ◽  
Yinxu Tang ◽  
Ziyu Shao ◽  
Yang Yang
Keyword(s):  
Cache Placement ◽  
Integration Of Learning ◽  
And Control

scholarly journals Joint Optimization on Trajectory, Cache Placement, and Transmission Power for Minimum Mission Time in UAV-Aided Wireless Networks

2021 ◽  
Vol 10 (7) ◽  
pp. 426
Author(s):  
Tingting Lan ◽  
Danyang Qin ◽  
Guanyu Sun
Keyword(s):  
Wireless Communication ◽  
Power Allocation ◽  
Optimization Problems ◽  
Base Station ◽  
Optimization Techniques ◽  
Joint Optimization ◽  
Transmission Power ◽  
Wireless Backhaul ◽  
Mission Time ◽  
Cache Placement

In recent years, due to the strong mobility, easy deployment, and low cost of unmanned aerial vehicles (UAV), great interest has arisen in utilizing UAVs to assist in wireless communication, especially for on-demand deployment in emergency situations and temporary events. However, UAVs can only provide users with data transmission services through wireless backhaul links established with a ground base station, and the limited capacity of the wireless backhaul link would limit the transmission speed of UAVs. Therefore, this paper designed a UAV-assisted wireless communication system that used cache technology and realized the transmission of multi-user data by using the mobility of UAVs and wireless cache technology. Considering the limited storage space and energy of UAVs, the joint optimization problem of the UAV’s trajectory, cache placement, and transmission power was established to minimize the mission time of the UAV. Since this problem was a non-convex problem, it was decomposed into three sub-problems: trajectory optimization, cache placement optimization, and power allocation optimization. An iterative algorithm based on the successive convex approximation and alternate optimization techniques was proposed to solve these three optimization problems. Finally, in the power allocation optimization, the proposed algorithm was improved by changing the optimization objective function. Numerical results showed that the algorithm had good performance and could effectively reduce the task completion time of the UAV.

Optimal cache placement with local sharing: An ISP guide to the benefits of the sharing economy

2020 ◽  
Vol 171 ◽  
pp. 107153
Author(s):  
Osnat Mokryn ◽  
Adi Akavia ◽  
Yossi Kanizo
Keyword(s):  
Sharing Economy ◽  
Cache Placement

scholarly journals Performance of cache placement using supervised learning techniques in mobile edge networks

IET Networks ◽  
2021 ◽  
Author(s):  
Lubna Mohammed ◽  
Alagan Anpalagan ◽  
Ahmed S. Khwaja ◽  
Muhammad Jaseemuddin
Keyword(s):  
Supervised Learning ◽  
Learning Techniques ◽  
Cache Placement ◽  
Edge Networks

scholarly journals Matching-based cache placement decision for 5G network caching

2021 ◽  
Author(s):  
Shadi Sadeghpour Kharkan
Keyword(s):  
Graph Matching ◽  
Placement Problem ◽  
Matching Problem ◽  
Matching Algorithm ◽  
Cell Network ◽  
5G Network ◽  
Backhaul Link ◽  
Random Placement ◽  
Cache Placement ◽  
Bottleneck Link

In this thesis, we present a cache placement scheme to deal with backhaul link constraint in Small Cell Network for 5G wireless network. We formulated the cache placement problem as a graph matching problem and presented an optimal file-helper matching algorithm. We defined stability criterion for the matching and found that our matching solution is stable in the sense that every helper finds at least one file to cache given that no file exceed minimum cache size. We achieved a unique placement of a file within a cluster of helpers to increase the number of files cached within a cluster. Further, our experimental evaluation demonstrates that our algorithm increases local and neighbor hit ratios as compared to a random placement, which in turn significantly decreases the traffic that goes over the backhaul bottleneck link.

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