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首页> 外文期刊>Indian Journal of Science and Technology >Efficient Caching and Mobility Adaptive Popular Data Access in Mobile Ad Hoc Networks
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Efficient Caching and Mobility Adaptive Popular Data Access in Mobile Ad Hoc Networks

机译:移动Ad Hoc网络中的高效缓存和移动性自适应流行数据访问

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Background: Caching technique is widely used to cope up with the resource constraints and to improve the data accessibility in MANETs. The key constraints are reducing the data access time, overhead and energy cost. Methods: This work proposes a Popularity-driven Caching and Mobility adaptive query Searching (PCMS) to achieve the constraints. The PCMS consists of Cache Node selection, popularity and data size driven replacement (POP) algorithm and mobility adaptive searching for cache data. With the aim of reducing the access delay of popular data, the PCMS selects a node that is closer to the destination in a route to cache the frequently requested data item and serves the future requests. The PCMS takes into account the data popularity and size to decide caching and replacement policy and thus significantly improves the performance of caching. The mobility adaptive searching for cache data looks for an item in Query Directory (QD) nodes and redirects the request to the concerned caching node. It updates the cache information at QD by adhering to the mobility prediction scheme. Findings: The PCMS considers the data popularity and size as key factors to decide caching and replacement policy for the better utilization of cache memory. The PCMS has successfully reduced the network traffic and improves the Cache Hit Ratio by adhering the mobility prediction based update scheme. Applications/Improvements: The proposed system achieves appreciably better performance in simulation than the existing caching systems by utilizing minimum battery power, bandwidth and access delay.
机译:背景技术:缓存技术被广泛用于应对资源限制并提高MANET中的数据可访问性。关键的限制因素是减少数据访问时间,开销和能源成本。方法:这项工作提出了一种流行驱动的缓存和移动性自适应查询搜索(PCMS)以实现约束。 PCMS由高速缓存节点选择,流行度和数据大小驱动替换(POP)算法以及对高速缓存数据的移动性自适应搜索组成。为了减少流行数据的访问延迟,PCMS选择一条路径中距离目的地较近的节点来缓存频繁请求的数据项并为将来的请求提供服务。 PCMS考虑到数据的流行程度和大小来决定缓存和替换策略,从而显着提高了缓存的性能。缓存数据的移动性自适应搜索在查询目录(QD)节点中查找项目,并将请求重定向到相关的缓存节点。它通过遵循移动性预测方案在QD更新缓存信息。结果:PCMS将数据的普及程度和大小视为决定缓存和替换策略以更好地利用缓存的关键因素。 PCMS通过遵循基于移动性预测的更新方案,成功减少了网络流量并提高了缓存命中率。应用/改进:与现有的缓存系统相比,拟议的系统通过利用最小的电池电量,带宽和访问延迟,在仿真方面实现了明显更好的性能。

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