Cooperative Caching Strategies for Mobile Peer-to-Peer Networks: A Survey

Zhou, Xinxin; Zou, Zhenwan; Song, Ren‐Jie; Wang, Yanjiao

doi:10.1007/978-981-10-0557-2_28

Cited by 8 publications

(9 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The node has the transmission range of the mobile client node that is 250 m. The system uses only 1 cell that contains 3 nodes, one node as a server, second as a cache, and the third as a client. The next 3 criteria are used to compare the proposed technique with famous LRU algorithm: Cache hit rate : the total percentage of all cache hits for all requests (both misses and hits requests), the aim is to maximize this value. Byte hit rate: the total percentage of all bytes that transfer to the user from the cache instead of over the server. Average latency: The time interval between the time of creating a query in the client and the time of getting demanded data from the data resource. …”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

An intelligent database proactive cache replacement policy for mobile communication system based on genetic programming

Darwish

El-Shnawy

2018

Int J Communication

View full text Add to dashboard Cite

In the mobile environment, the movement of the users, disconnected modes, many data updates, power battery consumption, limited cache size, and limited bandwidth impose significant challenges in information access. Caching is considered one of the most important concepts to deal with these challenges.There are 2 general topics related to the client cache policy: cache invalidation method keeps data in the cache up to date and cache replacement method chooses the cached element(s) that would be removed from the cache once the cache stays full. The aim of this work is to introduce a new technique for cache replacement in a mobile database that takes into consideration the impact of invalidation time for enhancing data availability in the mobile environment by using genetic programming. In this case, each client collects information for every cached item in the cache like access probability, cached document size, and validation time and uses these factors in a fitness function to determine cached items that will be removed from the cache. The experiments were carried by NS2 simulator to assess the efficiency of the proposed method, and the outcomes are judged against existing cache replacement algorithms. It is concluded that the proposed approach performs significantly better than other approaches. KEYWORDScache invalidation, cache replacement, genetic programming, mobile database | INTRODUCTIONWith the rapid changes in technology, mobile communications are the essential part of our daily life. People are using the wireless network for making phone calls, accessing the Internet to download news, the stock market, etc. Different techniques for enhancing the capability and quality of wireless environments have become a hot research area. The development of mobile information systems has met some disadvantages. Mobile machines regularly have slight storage dimension and inadequate energy. Furthermore, mobile client users in wireless environments suffer from frequent disconnections from the server, and also calling the server for information is costly. For that reason, scholars have discovered caching approaches for valuable data managing in the mobile podium. 1-3 Still, a key difficulty is how to preserve the collected items in the cache up to date with the source data at the server.

show abstract

Section: Resultsmentioning

confidence: 99%

“…Caching in the mobile network has been investigated by numerous researchers . In Chavan et al, the impact of data volume (S), access likelihood (A), update occurrence (U), and data retrieval postponement (D) is measured at once for cache replacements.…”

Section: State‐of‐the‐art Cache Replacement Algorithmsmentioning

confidence: 99%

An intelligent database proactive cache replacement policy for mobile communication system based on genetic programming

Darwish

El-Shnawy

2018

Int J Communication

View full text Add to dashboard Cite

show abstract

“…The next three criteria are used to compare the proposed technique with the famous LRU algorithm [1, 22]: Cache hit rate : the total percentage of all cache hits for all requests (both misses and hits requests), the aim is to maximise its value. Byte hit rate : the total percentage of all bytes that transfer to the user from the cache instead of over the server. Average latency : the time interval between the time of generating a query in the requester and the time of receiving requested data object from the data source. The average query latency unit is measured in seconds. …”

Section: Resultsmentioning

confidence: 99%

“…Broadly speaking, caching in the mobile environment has been addressed by many researchers [1,2,7,13,[18][19][20][21][22]. In SAIU [19], the influence of data size, data retrieval delay, access probability and update frequency is considered together for cache replacements.…”

Section: State-of-the-art Cache Replacement Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

Proactive cache replacement technique for mobile networks based on genetic programming

2018

View full text Add to dashboard Cite

In the mobile environment, the movement of users, disconnected modes, many data updates, power battery consumption, limited cache size, and limited bandwidth impose significant challenges to information access. Caching is considered one of the most important concepts to deal with these challenges. There are two general topics related to the client cache policy: cache invalidation method keeps data in the cache up to date; and cache replacement method chooses the cached item(s) which should be deleted from the cache when the cache is full. The aim of this work is to propose a new technique for cache replacement in a mobile database that takes into consideration the impact of invalidation time for enhancing data availability in the mobile environment by using genetic programming. In this case, each client collects information for every cached item in the cache like access probability, cached document size, validation time and uses these factors in a fitness function to determine cached items that will be removed from the cache. The experiments were performed using Network Simulator 2 to evaluate the effectiveness of the proposed approach, and the results are compared with the existing cache replacement algorithms. It is concluded that the proposed approach performs significantly better than other approaches.

show abstract

An Improved Cache Invalidation Policy in Wireless Environment Cooperate with Cache Replacement Policy Based on Genetic Programming

El-Zoghabi

Shenawy

2018

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

Cooperative Caching Strategies for Mobile Peer-to-Peer Networks: A Survey

Cited by 8 publications

References 21 publications

An intelligent database proactive cache replacement policy for mobile communication system based on genetic programming

An intelligent database proactive cache replacement policy for mobile communication system based on genetic programming

Proactive cache replacement technique for mobile networks based on genetic programming

An Improved Cache Invalidation Policy in Wireless Environment Cooperate with Cache Replacement Policy Based on Genetic Programming

Contact Info

Product

Resources

About