Modeling and Analysis of Connectivity in Mobile Ad Hoc Networks with Misbehaving Nodes

Xing, Fei; Wang, Wenye

doi:10.1109/icc.2006.254994

Cited by 42 publications

(32 citation statements)

References 11 publications

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“…Since every node is autonomous, it needs to decide how to act in the network by itself. Considering the potential impacts of various misbehaviors, we extend the geometric random graph model aforementioned by introducing an additional assumption that all nodes operate independently in the following five states [7], [8]:…”

Section: Node Classificationmentioning

confidence: 99%

“…Then, the probability that a node occupies a specific grid, denoted by p, is very small. With large N and small p, the node distribution can be modeled by the Poisson distribution [7], [8]:…”

Section: (I) Poisson Modelmentioning

confidence: 99%

“…In the literature [3]- [5], some authors gave different definitions of network survivability. Xing and Wang [7] perceived the survivability of a wireless ad hoc network as the probabilistic k-connectivity, and provided a quantitative analysis on the impacts of both node misbehavior and failure on network survivability. This work was extended latter in [8] by conducting a comprehensive simulation experiment.…”

Section: Introductionmentioning

confidence: 99%

“…We refer to the asymptotic relationship among these three stochastic models, and show that our models asymptotically approach to the Poisson model as the number of active nodes increases [9], i.e., the Poisson model is a complementary approach of our macroscopic models. We further perform not only the steady-state analysis [7]- [9] but also the transient analysis of the network survivability. The remaining part of this paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

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Survivability Analysis for a Wireless Ad Hoc Network Based on Semi-Markov Model

Zhang

2012

IEICE Trans. Inf. & Syst.

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SUMMARYNetwork survivability is defined as the ability of a network keeping connected under failures and/or attacks. In this paper, we propose two stochastic models; binomial model and negative binomial model, to quantify the network survivability and compare them with the existing Poisson model. We give mathematical formulae of approximate network survivability for respective models and use them to carry out the sensitivity analysis on model parameters. Throughout numerical examples it is shown that the network survivability can change drastically when the number of network nodes is relatively small under a severe attack mode which is called the Black hole attack. key words: network survivability, wireless ad hoc network, DoS attack, semi-Markov process, transient analysis

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Section: Node Classificationmentioning

confidence: 99%

Section: (I) Poisson Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Survivability Analysis for a Wireless Ad Hoc Network Based on Semi-Markov Model

Zhang

2012

IEICE Trans. Inf. & Syst.

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“…Also the Ping-Pong effect caused due to unnecessary handoff has been reduced. However in practice, all the mobile nodes in the network are not cooperative, but can be in other states like failed state, selfish state or malicious state [20][21]. In [22], a five node network model is developed to consider all the four states, namely, cooperative state, failed state, selfish state and malicious state in calculating the handover probability, UHP, MHP and WDP considering BW as performance metric.…”

Section: Introductionmentioning

confidence: 99%

BW and SS based Handover Analysis of Four States of Mobile Node in a Five Node Network Model

Halhalli¹,

Kulkarni²,

Anjaneyulu³

2015

IJCA

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Handover algorithms based on different performance metric are used to provide seamless handover and need to be evaluated in terms of unnecessary handover and missing handovers. Wrong decision probability (WDP) is one such performance metric used to measure the efficiency of handover algorithms and is measured based on Unnecessary handover probability (UHP) and Missing handover probability (MHP) for handover evaluation. In this work handover probability (HP), UHP, MHP and WDP are computed for a five node network model. The handoff algorithm for the five node network model is designed based on combination of Received signal strength (RSS) and Bandwidth (BW), and is evaluated using Wrong Decision Probability model considering the four states of mobile node, namely Cooperative state, failed state, selfish state and malicious state. Analytical and simulation results are presented to validate the vertical handover. Results are compared with the results of single state five node network model. KeywordsMissing handover probability (MHP), Unnecessary handover probability (UHP), Wrong decision probability (WDP), Bandwidth (BW), Received Signal strength (RSS),

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A Method to Evaluate MANET Connectivity Based on Communication Demand and Probability

Zhang

Liu

2013

The Proceedings of the Second International Conference on Communications, Signal Processing, and Systems

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Modeling and Analysis of Connectivity in Mobile Ad Hoc Networks with Misbehaving Nodes

Cited by 42 publications

References 11 publications

Survivability Analysis for a Wireless Ad Hoc Network Based on Semi-Markov Model

Survivability Analysis for a Wireless Ad Hoc Network Based on Semi-Markov Model

BW and SS based Handover Analysis of Four States of Mobile Node in a Five Node Network Model

A Method to Evaluate MANET Connectivity Based on Communication Demand and Probability

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