Cluster-based Cache Replacement in 5G Network

10.32920/ryerson.14646492.v1 ◽

2021 ◽

Author(s):

Muhammad Jaseemuddin

Keyword(s):

Mobile Network ◽

Replacement Policy ◽

Superior Performance ◽

Cache Replacement ◽

5G Network ◽

Replacement Decisions ◽

Replacement Technique ◽

Replacement Scheme ◽

Cache Placement ◽

Placement Algorithm

In this thesis, we proposed a Cluster-Based Cache Replacement (CBR) scheme for 5G Networks to reduce the backhaul traffic. We developed our scheme based on the understanding of the degradation of the performance of the cache placement algorithm. We expect that whenever file request pattern differs from the file popularity distribution, such as unpopular files become more popular or vice versa, the caching system should experience performance degradation. We address this problem by presenting a cache replacement scheme based on the idea of Least Frequency Used (LFU) replacement policy, but we consider only the recent request to avoid cache pollution. We evaluated the performance of CBR through simulation and compared its performance with LRU that is widely used as a cache replacement technique in practice. We simulated three different configurations of LRU scheme in a cluster-based mobile network model. Our simulation results show that the CBR outperforms LRU, where it reduces the miss ratio from 86% to 76% and the backhaul traffic from 3.67×105 to 3.47×105 MB with 10% of cache size. This superior performance it achieves by fewer replacement decisions and storing more files in the cache.

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A Cache Replacement Policy for Location Dependent Data in Mobile Environments

Next Generation Data Communication Technologies ◽

10.4018/978-1-61350-477-2.ch013 ◽

2012 ◽

pp. 286-295

Author(s):

Mary Magdalene Jane. F ◽

R Nadarajan ◽

Maytham Safar

Keyword(s):

Experimental Results ◽

Data Availability ◽

Replacement Policy ◽

User Preference ◽

Cache Replacement ◽

Local Data ◽

Performance Metric ◽

Cache Replacement Policy ◽

Replacement Scheme ◽

Cache Hit Ratio

Cache hit ratio is employed as the primary performance metric where the higher the cache hit ratio, the higher the local data availability, lower uplink and downlink costs and less battery consumption. The experimental results show that the proposed replacement scheme is effective when the user preference is considered and the policy significantly outperforms the conventional replacement policies.

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5G Mobile Services and Scenarios: Challenges and Solutions

Sustainability ◽

10.3390/su10103626 ◽

2018 ◽

Vol 10 (10) ◽

pp. 3626 ◽

Cited By ~ 18

Author(s):

Yousaf Zikria ◽

Sung Kim ◽

Muhammad Afzal ◽

Haoxiang Wang ◽

Mubashir Rehmani

Keyword(s):

Mobile Network ◽

Future Internet ◽

Autonomous Driving ◽

Mobile Services ◽

Data Traffic ◽

Fifth Generation ◽

Wide Range ◽

Industrial Iot ◽

5G Network ◽

Massive Number

The Fifth generation (5G) network is projected to support large amount of data traffic and massive number of wireless connections. Different data traffic has different Quality of Service (QoS) requirements. 5G mobile network aims to address the limitations of previous cellular standards (i.e., 2G/3G/4G) and be a prospective key enabler for future Internet of Things (IoT). 5G networks support a wide range of applications such as smart home, autonomous driving, drone operations, health and mission critical applications, Industrial IoT (IIoT), and entertainment and multimedia. Based on end users’ experience, several 5G services are categorized into immersive 5G services, intelligent 5G services, omnipresent 5G services, autonomous 5G services, and public 5G services. In this paper, we present a brief overview of 5G technical scenarios. We then provide a brief overview of accepted papers in our Special Issue on 5G mobile services and scenarios. Finally, we conclude this paper.

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Enabling Service Cache in Edge Clouds

ACM Transactions on Internet of Things ◽

10.1145/3456564 ◽

2021 ◽

Vol 2 (3) ◽

pp. 1-24

Author(s):

Chih-Kai Huang ◽

Shan-Hsiang Shen

Keyword(s):

Virtual Machines ◽

Replacement Policy ◽

Cache Replacement ◽

Cache Replacement Policy ◽

Average Latency ◽

Hit Rates ◽

Iot Devices ◽

Multi Access ◽

Computational Resources ◽

The Cost

The next-generation 5G cellular networks are designed to support the internet of things (IoT) networks; network components and services are virtualized and run either in virtual machines (VMs) or containers. Moreover, edge clouds (which are closer to end users) are leveraged to reduce end-to-end latency especially for some IoT applications, which require short response time. However, the computational resources are limited in edge clouds. To minimize overall service latency, it is crucial to determine carefully which services should be provided in edge clouds and serve more mobile or IoT devices locally. In this article, we propose a novel service cache framework called S-Cache , which automatically caches popular services in edge clouds. In addition, we design a new cache replacement policy to maximize the cache hit rates. Our evaluations use real log files from Google to form two datasets to evaluate the performance. The proposed cache replacement policy is compared with other policies such as greedy-dual-size-frequency (GDSF) and least-frequently-used (LFU). The experimental results show that the cache hit rates are improved by 39% on average, and the average latency of our cache replacement policy decreases 41% and 38% on average in these two datasets. This indicates that our approach is superior to other existing cache policies and is more suitable in multi-access edge computing environments. In the implementation, S-Cache relies on OpenStack to clone services to edge clouds and direct the network traffic. We also evaluate the cost of cloning the service to an edge cloud. The cloning cost of various real applications is studied by experiments under the presented framework and different environments.

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