A Multi-Level Cache Approach for Realtime Visualization of Massive 3D GIS Data

2012 ◽  
Vol 1 (3) ◽  
pp. 37-48
Author(s):  
Xiaoming Li ◽  
Weiping Xu ◽  
Qing Zhu ◽  
Jinxing Hu ◽  
Han Hu ◽  
...  
Keyword(s):  
High Efficiency ◽  
Replacement Policy ◽  
Visual Exploration ◽  
Cache Replacement ◽  
3D Gis ◽  
Dynamic Data ◽  
Memory Cache ◽  
Spatial Database Engine ◽  
Multi Level ◽  
Data Loading

The real-time visualization of 3D GIS at a whole city scale always faces the challenge of dynamic data loading with high-efficiency. Based on the multi-tier distributed 3D GIS framework, this paper presents a multi-level cache approach for dynamic data loading. It aims to establish in 3D GIS spatial database engine (3DGIS-SDE) the unified management mechanism of caches on three levels, including: the client memory cache (CMC) oriented to sharing application, the client file cache (CFC) organized by index, as well as the application server memory cache (ASMC) of structural consistency. With the help of the proposed optimized cache replacement policy, multi-level cache consistency maintenance as well as multithread loading model designed in the paper, the engine is able to adaptively make full use of each-level caches according to their own application properties and achieve effective coordination between them. Finally, a practical 3D GIS database based on Oracle 11g is employed for test. The experimental results prove this approach could satisfy multi-user concurrent applications of 3D visual exploration.

Enabling Service Cache in Edge Clouds

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.

Penalty- and Locality-aware Memory Allocation in Redis Using Enhanced AET

2021 ◽  
Vol 17 (2) ◽  
pp. 1-45
Author(s):  
Cheng Pan ◽  
Xiaolin Wang ◽  
Yingwei Luo ◽  
Zhenlin Wang
Keyword(s):  
Large Data ◽  
Data Locality ◽  
Memory Allocation ◽  
Cache Management ◽  
Cache Replacement ◽  
Time Model ◽  
Memory Cache ◽  
Management Scheme ◽  
Data Volume ◽  
Replacement Algorithms

Due to large data volume and low latency requirements of modern web services, the use of an in-memory key-value (KV) cache often becomes an inevitable choice (e.g., Redis and Memcached). The in-memory cache holds hot data, reduces request latency, and alleviates the load on background databases. Inheriting from the traditional hardware cache design, many existing KV cache systems still use recency-based cache replacement algorithms, e.g., least recently used or its approximations. However, the diversity of miss penalty distinguishes a KV cache from a hardware cache. Inadequate consideration of penalty can substantially compromise space utilization and request service time. KV accesses also demonstrate locality, which needs to be coordinated with miss penalty to guide cache management. In this article, we first discuss how to enhance the existing cache model, the Average Eviction Time model, so that it can adapt to modeling a KV cache. After that, we apply the model to Redis and propose pRedis, Penalty- and Locality-aware Memory Allocation in Redis, which synthesizes data locality and miss penalty, in a quantitative manner, to guide memory allocation and replacement in Redis. At the same time, we also explore the diurnal behavior of a KV store and exploit long-term reuse. We replace the original passive eviction mechanism with an automatic dump/load mechanism, to smooth the transition between access peaks and valleys. Our evaluation shows that pRedis effectively reduces the average and tail access latency with minimal time and space overhead. For both real-world and synthetic workloads, our approach delivers an average of 14.0%∼52.3% latency reduction over a state-of-the-art penalty-aware cache management scheme, Hyperbolic Caching (HC), and shows more quantitative predictability of performance. Moreover, we can obtain even lower average latency (1.1%∼5.5%) when dynamically switching policies between pRedis and HC.

scholarly journals An adaptive cache replacement policy based on fine-grain reusability monitor

2018 ◽  
Vol 15 (2) ◽  
pp. 20171099-20171099 ◽  
Author(s):  
Duk-Jun Bang ◽  
Min-Kwan Kee ◽  
Hong-Yeol Lim ◽  
Gi-Ho Park
Keyword(s):  
Replacement Policy ◽  
Cache Replacement ◽  
Fine Grain ◽  
Cache Replacement Policy ◽  
Adaptive Cache

Importance of Mobile Photography in Dental Practice

2021 ◽  
Vol 11 (02) ◽  
pp. 99-99
Author(s):  
Dilkush Zafar ◽  
Ahsan Inayat ◽  
Uzma Anam Iqbal
Keyword(s):  
Digital Technology ◽  
High Efficiency ◽  
Cell Phones ◽  
Clinical History ◽  
Dental Practice ◽  
Dental Procedures ◽  
Dental Practices ◽  
Multi Level ◽  
Working Practices ◽  
Improved Technology

This letter aims to explain the importance of using cell phones to take helpful images with high efficiency in various types of dental procedures. In our dental practices’ photography is an effective tool. Its applications are widespread such as in the diagnosis and treatment planning, keeping an illustrative clinical history, legal documentation, publishing, and delivering lectures.1 In modern dentistry, photography has grown into a standard of treatment. With the advent of digital technology these days, photography has now become simpler and widely available. Even then, few practitioners introduce them in their daily practices due to reasons such as a lack of expertise in cameras, lenses, and technique, disruption of workflow, and cost considerations. The use of smartphones with improved technology, however, is constantly emerging. It allows every practitioner with minimal interruptions in their patient workflow to incorporate photography into his or her practice.2 Making images from mobile in dentistry has multi-level importance. Its implementation in dental practice is simple, swift, and extremely useful in recording working practices, conducting health promotion sessions, and administering clinical examinations, thus providing dentists and patients with many advantages.1-2

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