FDCP: cache placement model for information-centric networking using fluid dynamics theory

2018 ◽  
Vol 12 (4) ◽  
pp. 789-808 ◽  
Author(s):  
Fan Wu ◽  
Wang Yang ◽  
Guochao He
Keyword(s):  
Fluid Dynamics ◽  
Information Centric Networking ◽  
Cache Placement

scholarly journals Information-Centric Networking Cache Placement Method Based on Cache Node Status and Location

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Dapeng Man ◽  
Yao Wang ◽  
Hanbo Wang ◽  
Jiafei Guo ◽  
Jiguang Lv ◽  
...  
Keyword(s):  
Information Exchange ◽  
Network Architecture ◽  
Cache Replacement ◽  
Data Simulation ◽  
Information Centric Networking ◽  
Network Location ◽  
Deployment Strategy ◽  
Cooperative Cache ◽  
Web Cache ◽  
Cache Placement

Information-Centric Networking with caching is a very promising future network architecture. The research on its cache deployment strategy is divided into three categories, namely, noncooperative cache, explicit collaboration cache, and implicit collaboration cache. Noncooperative caching can cause problems such as high content repetition rate in the web cache space. Explicit collaboration caching generally reflects the best caching effect but requires a lot of communication to satisfy the exchange of cache node information and depends on the controller to perform the calculation. On this basis, implicit cooperative caching can reduce the information exchange and calculation between cache nodes while maintaining a good caching effect. Therefore, this paper proposes an on-path implicit cooperative cache deployment method based on the dynamic LRU-K cache replacement strategy. This method evaluates the cache nodes based on their network location and state and selects the node with the best state value on the transmission path for caching. Each request will only select one or two nodes for caching on the request path to reduce the redundancy of the data. Simulation experiments show that the cache deployment method based on the state and location of the cache node can improve the hit rate and reduce the average request length.

A Distributed Cache Placement Scheme for Large-Scale Information-Centric Networking

IEEE Network ◽  
2020 ◽  
Vol 34 (6) ◽  
pp. 126-132
Author(s):  
Boubakr Nour ◽  
Hakima Khelifi ◽  
Hassine Moungla ◽  
Rasheed Hussain ◽  
Nadra Guizani
Keyword(s):  
Large Scale ◽  
Information Centric Networking ◽  
Cache Placement ◽  
Distributed Cache

scholarly journals A Cache Placement Strategy with Energy Consumption Optimization in Information-Centric Networking

2019 ◽  
Vol 11 (3) ◽  
pp. 64 ◽  
Author(s):  
Xin Zheng ◽  
Gaocai Wang ◽  
Qifei Zhao
Keyword(s):  
Energy Consumption ◽  
Success Rate ◽  
Energy Savings ◽  
Rapid Development ◽  
Information Centric Networking ◽  
Additional Energy ◽  
Comparison Results ◽  
Optimal Stopping Theory ◽  
Energy Consumption Optimization ◽  
Cache Placement

With the rapid development of cloud computing, big data, and Internet of Things, Information-Centric Networking (ICN) has become a novel hotspot in the field of future Internet architecture, and new problems have appeared. In particular, more researchers consider information naming, delivery, mobility, and security in ICN. In this paper, we mainly focus on the cache placement strategy and network performance of ICN, and propose a cache placement strategy with energy consumption optimization. In order to optimize the energy consumption of the ICN, the best cache placement node is selected from the view of users. First of all, the distance sequence of different nodes arriving at each user is obtained in terms of detection results of network distribution channels, and the corresponding energy consumption of information distribution is obtained from the distance sequence. Secondly, the reward function of the cache node is derived using two factors of energy consumption, which includes the additional energy consumed by the change of the cache node and the energy consumption of the content distribution. Finally, we construct the optimal stopping theory problem to solve the maximum expected energy saving. In simulations, we give the comparison results of energy savings, caching benefit, and delivery success rate. The results show that the strategy proposed by this paper has higher delivery success rate and lower energy consumption than other strategies.

An Introduction to Fluid Dynamics

2000 ◽  
Author(s):  
G. K. Batchelor
Keyword(s):  
Fluid Dynamics

A First Course in Fluid Dynamics

1983 ◽  
Author(s):  
A. R. Paterson
Keyword(s):  
Fluid Dynamics
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