A social-aware caching algorithm for improving performance of online social network services in a multi-cloud environment
Pages 384 - 388
Abstract
Existing online social network (OSN) services use caching systems with the least recently used (LRU) algorithm as an eviction policy for improving service performance. However, they do not consider the characteristics of users' usage pattern in OSN services. In addition, they do not consider the fact that the users and cloud servers are geographically distributed over a large area. It makes relatively unnecessary data occupy limited memory space. Consequently, they cannot prevent the degradation of cache efficiency.
We introduce a social-aware caching algorithm to improve the performance of OSN services in a multi-cloud environment. Our approach is designed to consider the locations of the user and cloud server and to allocate memory space differently to each user by considering the user's frequency of service usage.
To validate our approach, we implemented a OSN service that manages user data in the same way as Twitter that is a representative OSN service. Furthermore, we experimented with actual users' locations and times of use as collected from Twitter. Our findings indicate that this approach can improve the cache hit ratio by an average of more than 24% and reduce the execution delay by an average of more than 1095 ms.
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Information & Contributors
Information
Published In
November 2017
545 pages
ISBN:9781450353656
DOI:10.1145/3162957
- Conference Chairs:
- Jalel Ben-Othman,
- Feng Gang,
- Program Chairs:
- Jain-Shing Liu,
- Masayuki Arai
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 24 November 2017
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- Research-article
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- Ministry of Education
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ICCIP 2017
ICCIP 2017: 2017 the 3rd International Conference on Communication and Information Processing
November 24 - 26, 2017
Tokyo, Japan
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Overall Acceptance Rate 61 of 301 submissions, 20%
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