A Location Dependent Semantic Cache Replacement Strategy in Mobile Environment

Tabassum, Kahkashan; Syed, Mahmood Quadri; Damodaram, A.

doi:10.1007/978-3-642-27299-8_23

Cited by 5 publications

(10 citation statements)

References 3 publications

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“…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 . Still, a key difficulty is how to preserve the collected items in the cache up to date with the source data at the server.…”

Section: Introductionmentioning

confidence: 99%

“…Most of the previous cache replacement policies did not take into consideration the nature of the mobile environment . Therefore, the goal is to develop a new intelligent algorithm for cache replacement policy by taking into consideration the invalidation time to enhance data availability in the mobile environment using GP.…”

Section: Introductionmentioning

confidence: 99%

“…These 2 requisites disagreement with the features of a mobile network. The most important challenges facing the current mobile caching mechanisms are as follows: (1) a page‐based caching mechanism is not appropriate in the mobile context; (2) the replacement strategy for each mobile client should be based on the query access patterns of its cached items rather than the regularly engaged least recently used (LRU) or most recently used approaches; (3) the replacement mechanism should be adaptive, so that it will choose candidates for replacement matching to convinced scoring rules based on local information; and finally, (4) each mobile client is responsible for invalidating its cached items so that the most recent versions can be refreshed when they are required. In general, building an intelligent mobile cache replacement system dealing with these challenges is necessitated to improve the accuracy and performance.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

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

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“…However, mobile environments properties as limited bandwidth, limited client power, frequent network disconnections, asymmetric communication, and limited client capacities led to many challenging problems for mobile data applications [3], [4].…”

Section: Introductionmentioning

confidence: 99%

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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“…This problem is analyzed, and a modified CEB with a median circle is proposed by Kahkashan Tabassum et. al [10]. The median circle radius is in between the inscribe circles radius and the outer circle radius.…”

Section: Related Workmentioning

confidence: 99%

Neural Network based Mobility aware Prefetch Caching and Replacement Strategies in Mobile Environment

Chavan¹,

Sane²,

Kekre³

2013

IJACSA

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Abstract-The Location Based Services (LBS) have ushered the way mobile applications access and manage Mobile Database System (MDS). Caching frequently accessed data into the mobile database environment, is an effective technique to improve the MDS performance. The cache size limitation enforces an optimized cache replacement algorithm to find a suitable subset of items for eviction from the cache. In wireless environment mobile clients move freely from one location to another and their access pattern exhibits temporal-spatial locality. To ensure efficient cache utilization, it is important to consider the movement direction, current and future location, cache invalidation and optimized prefetching for mobile clients when performing cache replacement. This paper proposes a Neural Network based Mobility aware Prefetch Caching and Replacement policy (NNMPCR) in Mobile Environment to manage LBS data. The NNMPCR policy employs a neural network prediction system that is able to capture some of the spatial patterns exhibited by users moving in a wireless environment. It is used to predict the future behavior of the mobile client. A cache-miss-initiated prefetch is used to reduce future misses and valid scope invalidation technique for cache invalidation. This makes the policy adaptive to clients movement behavior and optimizes the performance compared to earlier policies.

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A Location Dependent Semantic Cache Replacement Strategy in Mobile Environment

Cited by 5 publications

References 3 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

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

Neural Network based Mobility aware Prefetch Caching and Replacement Strategies in Mobile Environment

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