A Markov Model Based Cache Replacement Policy for Mobile Environment

Chavan, Hariram; Sane, S. S.; Kekre, H. B.

doi:10.1007/978-3-642-20209-4_3

Cited by 4 publications

(10 citation statements)

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“…Data size refers to the size of the data stored in the mobile client's cache. The amount of space required to store the data item in the cache is used to select an item for replacement, so keeping smaller size data items in the cache helps to accommodate a large number of data items [1], [2], [10], [11].…”

Section: Related Workmentioning

confidence: 99%

“…For example (see Figure 2), the "nearby-restaurant" is a data item, the data item value for this data item is {A} with the valid scope {1, 2} or {B} with the valid scope {3, 4}. Note that, a data item value varies when it is queried from different locations [2], [10]. …”

Section: Fig 1: a Mobile System Model [15]mentioning

confidence: 99%

“…It is an umbrella term used to describe technologies that enable people to access network services from anywhere and at any time. Without doubt, mobile computing is becoming an important part of people daily life [1], [2].…”

Section: Introductionmentioning

confidence: 99%

“…A cache invalidation policy maintains data consistency between client's cache and the server database. While cache replacement policy determines which suitable subset of data items is replaced when it does not have enough free space to store a new data item [1], [2], [6], [8].…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, A Distance-Based Predicted Region Policy for Data Cache Replacement in Mobile Environments (DPRP) is proposed. The proposed scheme uses the root-mean squared distance that is based on the distance between the client's current location and the locations of each cached data for a predicted region [2], [10], [11].…”

Section: Introductionmentioning

confidence: 99%

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A Distance-based Predicted Region Policy for Cache Replacement in Mobile Environments

ElDahshan¹,

Ahmed²,

Sobhi³

2015

IJCA

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Mobile computing has developed during recent years. Location dependent services are most popular services that the mobile environments support. Data caching is a critical issue that plays an important role in improving these services and system performance. In mobile environments, due to the limited cache size of mobile devices, the main problem in data caching is cache replacement which is finding a suitable subset of items for eviction from cache. In this paper, to solve this problem, A Distance-Based Predicted Region Policy for Cache Replacement in Mobile Environments is proposed. The proposed policy uses the root-mean squared distance that based on the distance between a client current location and the locations of each object whose data is cached for predicted region. Simulation results show that the proposed policy improves the system performance compared to existing schemes.

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Section: Related Workmentioning

confidence: 99%

Section: Fig 1: a Mobile System Model [15]mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Distance-based Predicted Region Policy for Cache Replacement in Mobile Environments

ElDahshan¹,

Ahmed²,

Sobhi³

2015

IJCA

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

Darwish

El-Shnawy

2018

Int J Communication

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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.

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Proactive cache replacement technique for mobile networks based on genetic programming

2018

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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.

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A Markov Model Based Cache Replacement Policy for Mobile Environment

Cited by 4 publications

References 10 publications

A Distance-based Predicted Region Policy for Cache Replacement in Mobile Environments

A Distance-based Predicted Region Policy for Cache Replacement in Mobile Environments

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

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