How to model wireless mesh networks topology

Sanni, Mistura L.; Hashim, Aisha Hassan Abdalla; Anwar, Farhat; Ahmed, Gharib Subhi Mahmoud; Sellami, Anis

doi:10.1088/1757-899x/53/1/012037

Cited by 6 publications

(3 citation statements)

References 5 publications

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“…On the other hand, the mesh Microgrid simulation model is based on a structure that contains 9 wireless Mesh Access Points (MAPs) organized in a square grid topology, as illustrated in Figure 6. Actually, the efficiency of this topology has been proved in previous research [23]. Our MAPs are established according to IEEE 802.11s stack with HWMP protocol and peering management.…”

Section: Simulation Results A) Description Of Simulation Scenariomentioning

confidence: 99%

New Traceback Approach Deployment in Smart Mesh Microgrids against DoS Attacks

Gassara¹,

Gassara²

2022

Preprint

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Today's major challenge for smart Microgrids is to ensure the security of communications in a large number of changing data sets that are vulnerable to attacks by denial of services in constant evolution. The Internet Protocol Traceback defines a set of methods that help identify the source of an attack with minimal requirements for memory and processing. However, the concept of Traceback is not yet being used in smart Microgrids. As a result, the main challenge of this article is to incorporate a new Traceback approach into the cybernetic system of a smart mesh Microgrid, which can be tested using a network simulator (NS-3) based on delay, debit, and packet loss rate parameters. In fact, the simulation results show the efficacy of this approach compared to others existing in the literature. Furthermore, using the proposed Traceback technique and the mesh nodes, we were able to create a smart meshed Microgrid. Moreover, using the Traceback approach given for merging Intel Galileo Gen.1 nodes with the Compex WLE200NX.11a/b/g/n to establish a secure test bench, which is deployed as a prototype at the Sfax Digital Research Center in Tunisia, we were able to create an intelligent Microgrid. In fact, by identifying all attack vectors and revealing their origins, we could boost the efficiency of our operation by 100%.

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Section: Simulation Results A) Description Of Simulation Scenariomentioning

confidence: 99%

New Traceback Approach Deployment in Smart Mesh Microgrids against DoS Attacks

Gassara¹,

Gassara²

2022

Preprint

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“…In fact, we performed our simulation for 1000 seconds. For the sake of simplicity and traceback clarity, we based our simulation model on a simple structure that contains 9 wireless Mesh Access Points MAPs arranged in a square grid topology, which proves its efficiency in a previous research, in a maximal 300 m × 300 m area as shown in Figure . Our 9 MAPs are installed based on IEEE 802.11s stack with peering management and HWMP protocol.…”

Section: Simulation Procedures and Interpretations Of Resultsmentioning

confidence: 99%

Deployment and validation of out of band IP traceback approach (OBTA) in wireless mesh network

Gassara

Bouabidi

Zarai

et al. 2018

Int J Communication

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Summary Wireless mesh networks (WMNs) have acquired recently enormous attention and momentum; therefore, security aspects have been a fundamental concern for them. Among catastrophic threats on WMNs, Denial‐of‐Service attacks that have become a severe danger because of their plug‐and‐play structural design. Unfortunately, preventing a Denial‐of‐Service attack presents a challenging issue. This fact is induced with the appearance of the source IP addresses spoofing. The resolution key of this issue is to reveal the attack source based on the path through which the attack packet passes. For this, many researchers in IP traceability field propose various methods and techniques to deal with the issue. In this article, we conceive a novel approach named out of band IP traceback approach in WMN (IEEE 802.11s). We create a new architecture using signaling messages for discovering the real source(s) of IP packets. Our solution is based on a security‐oriented signaling protocol. This protocol allows specialized signaling entities to communicate via reliable signaling information. This fact permits us to perform a simple and efficient traceback. In our novel approach, we use 2 radios: the first one transmits normal data packets whereas the second is reserved to exchange IP traceback information. The performance of the proposed scheme is analyzed via simulation analysis using the Network Simulator 3. The simulation results show that our scheme is efficient in dealing with the traceback problem in WMN environments.

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“…TGs can differ mainly in how nodes placement is decided [17] and what each node represents [7]. Node placement strategy can be based either on some predefined model or on real-world measurements.…”

Section: Background and Related Workmentioning

confidence: 99%

A Methodology to Select Topology Generators for WANET Simulations (Extended Version)

O’Sullivan¹,

Aniello²,

Sassone³

2019

Preprint

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Many academic and industrial research works on WANETs rely on simulations, at least in the first stages, to obtain preliminary results to be subsequently validated in real settings. Topology generators (TG) are commonly used to generate the initial placement of nodes in artificial WANET topologies, where those simulations take place. The significance of these experiments heavily depends on the representativeness of artificial topologies. Indeed, if they were not drawn fairly, obtained results would apply only to a subset of possible configurations, hence they would lack of the appropriate generality required to port them to the real world. Although using many TGs could mitigate this issue by generating topologies in several different ways, that would entail a significant additional effort. Hence, the problem arises of what TGs to choose, among a number of available generators, to maximise the representativeness of generated topologies and reduce the number of TGs to use. In this paper, we address that problem by investigating the presence of bias in the initial placement of nodes in artificial WANET topologies produced by different TGs. We propose a methodology to assess such bias and introduce two metrics to quantify the diversity of the topologies generated by a TG with respect to all the available TGs, which can be used to select what TGs to use. We carry out experiments on three wellknown TGs, namely BRITE, NPART and GT-ITM. Obtained results show that using the artificial networks produced by a single TG can introduce bias.

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How to model wireless mesh networks topology

Cited by 6 publications

References 5 publications

New Traceback Approach Deployment in Smart Mesh Microgrids against DoS Attacks

New Traceback Approach Deployment in Smart Mesh Microgrids against DoS Attacks

Deployment and validation of out of band IP traceback approach (OBTA) in wireless mesh network

A Methodology to Select Topology Generators for WANET Simulations (Extended Version)

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