The Jamming problem in IEEE 802.11‐based mobile <i>ad hoc</i> networks with hidden terminals: Performance analysis and enhancement

Li, Yun; Wang, Chonggang; Zhao, Weiliang; You, Xiaohu

doi:10.1002/dac.1007

Cited by 5 publications

(5 citation statements)

References 25 publications

(16 reference statements)

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“…A new coalition game is proposed wherein the coalition value is based on the secondary user's spectral efficiencies, the intersecondary user's interference, and the interference caused to the primary user . An adaptive scheme proposed for reducing the jamming effect, while adjusting the minimum contention window in the IEEE 802.11 MAC . TC‐JAM scheme is proposed to ensure the PDR where jammers are avoided and network lifetime is increased in the WSNs .…”

Section: Related Workmentioning

confidence: 99%

“…30 An adaptive scheme proposed for reducing the jamming effect, while adjusting the minimum contention window in the IEEE 802.11 MAC. 31 TC-JAM scheme is proposed to ensure the PDR where jammers are avoided and network lifetime is increased in the WSNs. 32 In Jahanshahi et al, 33 the authors proposed to cluster the jammed signals at BS in wireless cellular networks.…”

Section: Related Workmentioning

confidence: 99%

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Fuzzy logic–based jamming detection algorithm for cluster‐based wireless sensor network

Vijayakumar

Ganeshkumar

Anandaraj

et al. 2018

Int J Communication

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Summary In this paper, a fuzzy logic–based jamming detection algorithm (FLJDA) is proposed to detect the presence of jamming in downstream data communication for cluster‐based wireless sensor networks. The proposed FLJDA keeps an eye on the existing nodes and new node to determine their behavior by applying fuzzy logic on measured jamming detection metrics. To monitor the behavior of the nodes, the FLJDA computes the jamming detection metrics, namely, packet delivery ratio and received signal strength indicator. The major features of this paper are the following: (1) The jamming detection algorithm is specifically implemented for downstream data communication, (2) cluster head estimates jamming detection metrics for detecting the jamming unlike the existing algorithms where individual nodes explicitly collect the jamming detection metrics, and (3) the proposed algorithm optimizes the jamming detection metrics on the basis of fuzzy logic unlike the existing approaches, which uses merely jamming detection threshold alone for jamming detection. The simulation results of the proposed system provide the true detection ratio as high as 99.89%.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Fuzzy logic–based jamming detection algorithm for cluster‐based wireless sensor network

Vijayakumar

Ganeshkumar

Anandaraj

et al. 2018

Int J Communication

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“…Their focus was on increasing privacy, while introducing noise signal, and not of proposing a scheme for antijamming scheme. Li et al proposed an adaptive scheme to reduce the jamming effect, while adjusting the minimum contention window in the IEEE 802.11 MAC.…”

Section: Related Workmentioning

confidence: 99%

Topology control in the presence of jammers for wireless sensor networks

Bhavathankar

Mondal

Misra

2017

Int J Communication

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In this paper, the problem of ensuring packet delivery ratio and high network lifetime in wireless sensor networks in the presence of single or multiple jammers is studied using single-leader-multiple-followers Stackelberg game theory. A topology control scheme is proposed, in which the sink node, which acts as the leader, identifies the set of jamming affected nodes. On the other hand, the sensor nodes, which act as followers, need to decide an optimum transmission power level, while ensuring an optimal set of neighbor nodes covered. A scheme, named TC-JAM, for ensuring packet delivery ratio, while avoiding jammers and increasing network lifetime in wireless sensor networks, is proposed. In existing literatures, the sensor nodes are envisioned to be equipped with multiple interfaces, while having access for multiple channels. However, in TC-JAM, the sensor nodes have simple hardware with single interface for communication, ie, the sensor nodes have single channel for communication. Additionally, in the proposed scheme, TC-JAM, each sensor node has a provision to vary its transmission power according to the chosen strategies. Using TC-JAM, the energy consumption of the overall network reduces by up to 62%, and the network lifetime increases by 56% to 73%. KEYWORDSDynamic transmission power level model, jammer, network lifetime, stackelberg game, topology control, wireless sensor network 1 Int J Commun Syst. 2017;30:e3289.wileyonlinelibrary.com/journal/dac

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“…The classic example hereof is where a powerful transmitter is generating "white noise" over the communications channel where the network interfaces of the routers would otherwise operate, effectively preventing these router interfaces from successfully receiving transmissions from each other. While this can happen on all network interface and channel types, wireless networks are especially vulnerable to such; commercial WiFi "jammers" are, for example, readily available [17].…”

Section: Radio Jammingmentioning

confidence: 99%

Security Issues in the Optimized Link State Routing Protocol Version 2 (Olsrv2)

Herberg¹,

Clausen²

2010

IJNSA

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Mobile Ad hoc NETworks (MANETs) are leaving the confines of research laboratories, to find place in real-world deployments. Outside specialized domains (military, vehicular, etc.), city-wide community-networks are emerging, connecting regular Internet users with each other, and with the Internet, via MANETs. Growing to encompass more than a handful of "trusted participants", the question of preserving the MANET network connectivity, even when faced with careless or malicious participants, arises, and must be addressed.A first step towards protecting a MANET is to analyze the vulnerabilities of the routing protocol, managing the connectivity. By understanding how the algorithms of the routing protocol operate, and how these can be exploited by those with ill intent, countermeasures can be developed, readying MANETs for wider deployment and use.This memorandumtakes an abstract look at the algorithms that constitute the Optimized Link State Routing Protocol version 2 (OLSRv2), and identifies for each protocol element the possible vulnerabilities and attacks -in a certain way, provides a "cookbook" for how to best attack an operational OLSRv2 network, or for how to proceed with developing protective countermeasures against these attacks.

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The Jamming problem in IEEE 802.11‐based mobile ad hoc networks with hidden terminals: Performance analysis and enhancement

Cited by 5 publications

References 25 publications

Fuzzy logic–based jamming detection algorithm for cluster‐based wireless sensor network

Fuzzy logic–based jamming detection algorithm for cluster‐based wireless sensor network

Topology control in the presence of jammers for wireless sensor networks

Security Issues in the Optimized Link State Routing Protocol Version 2 (Olsrv2)

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