Performance analysis of IEEE 802.11 ad hoc networks in the presence of hidden terminals

Vassis, Dimitris; Kormentzas, George

doi:10.1016/j.comnet.2007.01.025

Cited by 9 publications

(4 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this paper we propose a further development beyond the study and design of WLANs: the problem of optimally deploying APs to cover Wi-Fi clients within a complex space. So this manuscript intended three significant contributions: (1) to present a new intelligent modelling approach for WLAN deployment based on a multiobjective genetic algorithm; (2) to examine its applicability into small, medium, and large scenarios; and (3) to integrate the algorithm with the previous developments and provide a complete decision-making software for ICT technicians. To achieve this goal, we propose an evolutionary genetic strategy based on nondominated sorting genetic algorithm II (NSGA-II) where the optimization approach is applied into a demanding WLAN infrastructure.…”

Section: Complexitymentioning

confidence: 99%

“…These are the maximum bandwidth and Wi-Fi protocol. Since the rate and modulation scheme used in the WLAN set the media sensibility (i.e., rate in Mbps versus power in dBm), this serves to filter out the solution calculated by the algorithm in (3) and satisfy the design constraints. Therefore, the planning of the AP location plays a key role in maximizing the WLAN transmission coverage and communication throughput.…”

Section: Map Structure and Objectivesmentioning

confidence: 99%

“…This indeed includes several factors such as the area morphology (i.e., verticality and horizontality of planes), number of clients populating the WLAN (i.e., distribution, density), type of IEEE 802.11 technology (i.e., modulation scheme and frame management), effective isotropic radiated power (EIRP), and physical distance and obstacle materials (i.e., water, glass, plastic, metal, wood, and concrete). The traditional deployment is consequently no effective for practitioners due to requirements in time and cost, which may drastically reduce the WLAN performance and usability due to operability problems concerning design (e.g., interferences and frame collisions due to home devices, hidden node problem) [3].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal Modeling of Wireless LANs: A Decision-Making Multiobjective Approach

Sanguino

Betancourt

2018

Complexity

View full text Add to dashboard Cite

Communication infrastructure planning is a critical design task that typically requires handling complex concepts on networking aimed at optimizing performance and resources, thus demanding high analytical and problem-solving skills to engineers. To reduce this gap, this paper describes an optimization algorithm—based on evolutionary strategy—created as an aid for decision-making prior to the real deployment of wireless LANs. The developed algorithm allows automating the design process, traditionally handmade by network technicians, in order to save time and cost by improving the WLAN arrangement. To this end, we implemented a multiobjective genetic algorithm (MOGA) with the purpose of meeting two simultaneous design objectives, namely, to minimize the number of APs while maximizing the coverage signal over a whole planning area. Such approach provides efficient and scalable solutions closer to the best network design, so that we integrated the developed algorithm into an engineering tool with the goal of modelling the behavior of WLANs in ICT infrastructures. Called WiFiSim, it allows the investigation of various complex issues concerning the design of IEEE 802.11-based WLANs, thereby facilitating design of the study and design and optimal deployment of wireless LANs through complete modelling software. As a result, we comparatively evaluated three target applications considering small, medium, and large scenarios with a previous approach developed, a monoobjective genetic algorithm.

show abstract

Section: Complexitymentioning

confidence: 99%

Section: Map Structure and Objectivesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Modeling of Wireless LANs: A Decision-Making Multiobjective Approach

Sanguino

Betancourt

2018

Complexity

View full text Add to dashboard Cite

show abstract

“…In [1] the effectiveness of RTS/CTS packets exchange in the presence of Hidden nodes was evaluated. The results show that the system performance improves when the RTS/CTS packets are implemented.…”

Section: Related Workmentioning

confidence: 99%

The implementation of LIFS in a single channel MAC protocol

Velempini

Dlodlo

2010

Melecon 2010 - 2010 15th IEEE Mediterranean Electrotechnical Conference

View full text Add to dashboard Cite

The combination of RTS/CTS and EIFS enhancements has not adequately addressed the hidden terminal problem (HTP) in the receiver neighbourhood. The EIFS scheme protects ACK packets, while DATA packets are not shielded as the EIFS expires before they are delivered. Our proposed scheme is designed to address the shortcomings of the EIFS in protecting data packets. We propose a scheme which implements a Long Inter-Frame Space (LIFS) which protects DATA packets and calms HTPs within the receiver's carrier sensing range. The performance of the scheme was evaluated through NS 2 simulations. The simulation results show an improvement in network performance. The scheme reduces end to end delay in all the tagged flows.

show abstract

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

Wang²,

Zhao

et al. 2009

Int J Communication

View full text Add to dashboard Cite

SUMMARYThe hidden-terminal problem significantly degrades the performance of IEEE 802.11 DCF. Many previous works have investigated its influence on the throughput of CSMA-based medium access control (MAC) protocols, especially IEEE 802.11 DCF. In this paper, we introduce a new Jamming problem for IEEE 802.11-based mobile ad hoc networks, which is caused by hidden terminals. An analytical model is established for this problem. Based on this model, an adaptive DCF (ADCF), is designed to solve the jamming problem through adaptively adjusting the minimum contention window of hidden terminals. Simulation results effectively demonstrate that the proposed A-DCF can avoid the jamming and in turn greatly improve channel utilization and throughput.

show abstract

Performance analysis of IEEE 802.11 ad hoc networks in the presence of hidden terminals

Cited by 9 publications

References 7 publications

Optimal Modeling of Wireless LANs: A Decision-Making Multiobjective Approach

Optimal Modeling of Wireless LANs: A Decision-Making Multiobjective Approach

The implementation of LIFS in a single channel MAC protocol

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

Contact Info

Product

Resources

About