MANET环境下数据缓存的有效管理模型

Amer Abu Salem
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摘要

移动自组织(MANET)网络面临的主要挑战是为所需的移动节点提供所需的数据。基于路由发现和路由维护两种主要方法的自组织按需距离矢量(AODV)路由协议是一种高效的基于请求的MANET路由协议。路由发现是指从报文源探测到目的路由的过程,而路由维护是指探测到链路故障并进行修复的过程。在移动自组织网络中,协作缓存倾向于提高数据可用性,缓存发现和缓存管理策略的协调在manet的协作缓存中非常重要,因为对数据的请求和对请求数据的响应可能会因为干扰、网络拥塞或转发节点无法到达或路由中断而减少。协作缓存管理在协作缓存中要复杂得多,因为它还依赖于邻近节点来决定缓存什么。本文提出了三种算法:(1)基于缓存数据和数据位置的缓存接纳控制的组合算法,以节省空间和减少数据冗余;(2)基于值的缓存放置和替换策略,而不是更常见的最近最少使用的策略,取决于描述缓存项的指标,以增加本地缓存命中率;(3)缓存一致性的组合算法,包括生存时间、拉和推策略,以增强数据可用性和系统可扩展性。提出的算法通过NS3仿真程序实现;其中使用AODV协议在多个参数下创建网络,实现了较好的系统性能。
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An Effective Management Model for Data Caching in MANET Environment
A mobile ad-hoc (MANET) network has the main challenge to provide the needed data for the desired mobile nodes. An efficient on request routing protocol for MANET is Ad-hoc on-demand Distance Vector (AODV), which is based on two main methods: route discovery and route maintenance. Route discovery is the process used to detect a route to the destination from the packet source, while route maintenance is the process used to detect a link failure and repair it. Cooperative caching tends improving data availability in mobile ad-hoc networks, the coordination of cache discovery and cache management strategies is very significant in the cooperative caching of MANETs because requests for data and answers to requested data can be reduced simply due to interference, network congestion, or when a forwarding node is out of reach and the route breaks down. Cooperative cache management is much more complicated in cooperative caching because it also depends on neighbouring nodes to decide what to cache. In this paper, three algorithms were proposed: (1) a combination algorithm for cache admission control based on cache data and location of data to save space and reduce data redundancy, (2) a value-based policy for cache placement and replacement instead of the more common least recently used strategy, depending on metrics that describe cached items to increase the local cache hit ratio, and (3) a combined algorithm for cache consistency that includes time-to-live, pull, and push policies to enhance data availability and system scalability. The proposed algorithm implemented by the NS3 simulation program; which used to create a network using the AODV protocol in several parameters and achieve better system performance.
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