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Preventing the impact of selfish behavior under MANET using Neighbor Credit Value based AODV routing algorithm

机译:使用基于邻居信用值的AODV路由算法防止MANET下自私行为的影响

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Mobile Ad hoc Network (MANET) nodes exchange information using the multi-hop wireless communications without the need for any pre-existing infrastructure. Routing protocols of MANET are designed with an assumption that the nodes will cooperate in routing process. To achieve high throughput and reliablecommunication, the nodes are expected to cooperate with each other. Routing protocol plays a crucial role in an effective communication between nodes and operates on the assumption that the nodes are fully cooperative. Due to the open structure and limited battery-based energy in MANET, some nodes may not cooperate correctly or behave maliciously and such kind of misbehavior impacts the fairness, reliability and efficiency in MANET. Previous work addressed the ways to overcome these kinds of node misbehaviors and attacks. Most of theexisting works need time to analyse the neighbor traffic and decide whether a neighbor is behaving maliciously or not. Further, the existing credit-based detection mechanisms may mark a genuine idle node as a malicious node. This work addresses a simple Neighbor Credit Value based AODV (NCV-AODV) routing algorithm for the detection of selfish behavior which avoids such false detection. The proposed idea is implemented in Ad hoc On Demand Distance Vector (AODV) routing protocol and an extensive analysis on the performance of the proposed detection mechanism against the selfish behavior of some MANET nodes are conducted.
机译:移动自组织网络(MANET)节点使用多跳无线通信来交换信息,而无需任何预先存在的基础架构。 MANET的路由协议是在假设节点将在路由过程中协作的前提下设计的。为了实现高吞吐量和可靠的通信,期望节点之间相互协作。路由协议在节点之间的有效通信中起着至关重要的作用,并且在节点完全协作的前提下进行操作。由于MANET的开放结构和基于电池的能源有限,某些节点可能无法正确协作或恶意行为,并且这种不当行为会影响MANET的公平性,可靠性和效率。先前的工作探讨了克服此类节点错误行为和攻击的方法。现有的大多数工作都需要时间来分析邻居流量并确定邻居是否表现出恶意。此外,现有的基于信用的检测机制可以将真正的空闲节点标记为恶意节点。这项工作解决了一种简单的基于邻居信用值的AODV(NCV-AODV)路由算法,用于检测自私行为,从而避免了这种错误检测。该提议的思想在Ad hoc按需距离矢量(AODV)路由协议中实现,并对提议的检测机制针对某些MANET节点的自私行为进行了广泛的分析。

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