Fuzzy Load Balancing for IEEE 802.11 Wireless Networks

Collotta, Mario; Scatà, Gianfranco

doi:10.1016/j.ieri.2014.08.010

Cited by 4 publications

(4 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These features are useful in determining the system control with complicated and uncertain conditions [10]. Thus, most researchers have applied fuzzy-based methods to QoS management in wireless environments [11][12][13][14][15].…”

Section: Qos Management With Fuzzy Logicmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive Flow QoS Management Model for Wireless Communication in Mobile Environments

2016

APH

View full text Add to dashboard Cite

Section: Qos Management With Fuzzy Logicmentioning

confidence: 99%

“…Load balancing can help improve the QoS in WNs. The fuzzy logic may be notified that the mobile node's AP has changed using measured factors such as signal quality or transmission failure [15].…”

Section: Qos Management With Fuzzy Logicmentioning

confidence: 99%

Adaptive Flow QoS Management Model for Wireless Communication in Mobile Environments

2016

APH

View full text Add to dashboard Cite

“…This application starts iteration with binary encoding until good classes of path are found and later encodes the paths of these classes with m-ary encoding for a deeper search. We recall that GA are part of the soft computing paradigm which includes Fuzzy Logic and Neural Network [7] [8].…”

Section: Introductionmentioning

confidence: 99%

GA application with hybrid encoding for QoS routing

Maniscalco¹,

Polito²,

Gentile³

2015

AIP Conference Proceedings

View full text Add to dashboard Cite

The search of routes with multiple Quality of Service (QoS) constraints from sources to destinations connected by networks is a Non Polynomial (NP) problem, which can be approached using Genetic Algorithms (GAs). These are heuristic algorithms that simulate the natural evolution process to solve optimization problems. In this paper we elaborate on tree-based GAs which represent the set of paths from source to destination as a tree. While existing GA applications use m-ary or binary encoding representing single paths and classes of paths in chromosomes, respectively, we propose a GA application with hybrid encoding which uses both of them. This application uses binary encoding from the first iteration until good classes of paths are found and later encodes the best paths of these classes with m-ary encoding. Its objective is taking advantage of the fast convergence due to the per class-processing of binary chromosomes and the lower computational cost of the single path processing of m-ary chromosomes. Simulation results show the performance, in terms of convergence speed, of the proposed GA application with hybrid encoding.

show abstract

“…In fact, in recent years, soft computing techniques are applied in various research fields such as load High Medium High balancing [13], routing [14], industrial networks [15,16] and flight controllers. This paper proposes a fuzzy logic based mechanism that aims at the energy saving in an UAV.…”

Section: Introductionmentioning

confidence: 99%

A fuzzy controller to reduce power consumption in a quadrotor helicopter for environmental monitoring

Pau

Tesoriere

Tirrito

2015

AIP Conference Proceedings

View full text Add to dashboard Cite

The Unmanned Aerial Vehicles (UAV) are aircrafts with no pilot on board. They can be remote controlled aircraft (e.g. flown by a pilot at a ground control station) or can fly autonomously based on pre-programmed flight plans or more complex dynamic automation systems. UAVs are currently used both in military and civil application. A key element of UAV equipment affecting the mission performance is power source for this reason several approaches can be applied in order to reduce the power consumption. Fuzzy Logic Controllers (FLCs) are becoming increasingly popular in everyday life and their applications can obtain significant benefits in terms of energy management. In this paper a FLC is proposed in order to regulate the motor power of a quadrotor helicopter according to the battery level and to the path to complete. Simulation results reveal that using the proposed approach the battery lifetime is increased by 30% with respect to the use of fixed power.

show abstract

Fuzzy Load Balancing for IEEE 802.11 Wireless Networks

Cited by 4 publications

References 15 publications

Adaptive Flow QoS Management Model for Wireless Communication in Mobile Environments

Adaptive Flow QoS Management Model for Wireless Communication in Mobile Environments

GA application with hybrid encoding for QoS routing

A fuzzy controller to reduce power consumption in a quadrotor helicopter for environmental monitoring

Contact Info

Product

Resources

About