An Adaptation of GRA Method for Network Selection in Vertical Handover Context

2017 ◽  
pp. 171-179
Author(s):  
Mouad Mansouri ◽  
Cherkaoui Leghris
Keyword(s):  
Vertical Handover ◽  
Network Selection

User-Driven Network Selection during Vertical Handover in 4G Networks

2017 ◽  
Vol 10 ◽  
pp. 1
Author(s):  
Abubakar Muhammad Miyim ◽  
Mahamod Ismail ◽  
Rosdiadee Nordin
Keyword(s):  
Blocking Probability ◽  
Service Selection ◽  
Vertical Handover ◽  
Network Selection ◽  
Selection Strategy ◽  
Intelligent Network ◽  
Decision Algorithm ◽  
Radio Access ◽  
Service Application ◽  
Multi Access

The importance of network selection for wireless networks, is to facilitate users with various personal wireless devices to access their desired services via a range of available radio access networks. The inability of these networks to provide broadband data service applications to users poses a serious challenge in the wireless environment. Network Optimization has therefore become necessary, so as to accommodate the increasing number of users’ service application demands while maintaining the required quality of services. To achieve that, the need to incorporate intelligent and fast mechanism as a solution to select the best value network for the user arises. This paper provides an intelligent network selection strategy based on the user- and network-valued metrics to suit their preferences when communicating in multi-access environment. A user-driven network selection strategy that employs Multi-Access Service Selection Vertical Handover Decision Algorithm (MASS-VHDA) via three interfaces; Wi-Fi, WiMAX and LTE-A is proposed, numerically evaluated and simulated. The results from the performance analysis demonstrate some improvement in the QoS and network blocking probability to satisfy user application requests for multiple simultaneous services.

scholarly journals Nelder-Mead Optimized MADM Decision Support for Vertical Handover

2019 ◽  
Vol 8 (2S3) ◽  
pp. 601-604
Keyword(s):  
Decision Process ◽  
Vertical Handover ◽  
Network Selection ◽  
Heterogeneous Environment ◽  
Challenging Problem ◽  
Wireless Technology ◽  
Decision Strategy ◽  
Handover Decision ◽  
Required Quality

The vertical handover decision strategy is a challenging problem to support seamless mobility in different wireless technology. The handover decision process is reported to facilitate the required Quality of Service, but bad network selection and overload condition of the chosen network fallout in handover failures. Traditional handoff techniques typically are based on single parameter and are inefficient due to superfluous handovers. In addition, existing fuzzy based handoff method reduces the handover failures but increase the computational complexity. Furthermore, the existing mobile controlled handover techniques are not suitable for heterogeneous environment. Therefore this paper focus the need of efficient, robust and flexible vertical handover technique to reduce the handover failures and design an MADM based network controlled handover that maximize QoS in heterogeneous environment

scholarly journals A Novel Model on Curve Fitting and Particle Swarm Optimization for Vertical Handover in Heterogeneous Wireless Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Shidrokh Goudarzi ◽  
Wan Haslina Hassan ◽  
Mohammad Hossein Anisi ◽  
Seyed Ahmad Soleymani ◽  
Parvaneh Shabanzadeh
Keyword(s):  
Particle Swarm Optimization ◽  
Curve Fitting ◽  
Particle Swarm ◽  
Signal Strength ◽  
Pso Algorithm ◽  
Vertical Handover ◽  
Received Signal Strength ◽  
Network Selection ◽  
Received Signal Strength Indicator ◽  
Swarm Optimization

The vertical handover mechanism is an essential issue in the heterogeneous wireless environments where selection of an efficient network that provides seamless connectivity involves complex scenarios. This study uses two modules that utilize the particle swarm optimization (PSO) algorithm to predict and make an intelligent vertical handover decision. In this paper, we predict the received signal strength indicator parameter using the curve fitting based particle swarm optimization (CF-PSO) and the RBF neural networks. The results of the proposed methodology compare the predictive capabilities in terms of coefficient determination (R2) and mean square error (MSE) based on the validation dataset. The results show that the effect of the model based on the CF-PSO is better than that of the model based on the RBF neural network in predicting the received signal strength indicator situation. In addition, we present a novel network selection algorithm to select the best candidate access point among the various access technologies based on the PSO. Simulation results indicate that using CF-PSO algorithm can decrease the number of unnecessary handovers and prevent the “Ping-Pong” effect. Moreover, it is demonstrated that the multiobjective particle swarm optimization based method finds an optimal network selection in a heterogeneous wireless environment.

scholarly journals ENHANCED NETWORK SELECTION AND HANDOVER SCHEMA FOR HETEROGENEOUS WIRELESS NETWORKS

2019 ◽  
Vol 01 (03) ◽  
pp. 160-171 ◽  
Author(s):  
Duraipandian M
Keyword(s):  
Wireless Networks ◽  
Heterogeneous Wireless Networks ◽  
Vertical Handover ◽  
User Preference ◽  
Network Selection ◽  
Order Preference ◽  
Simple Additive Weighting ◽  
Topsis Technique ◽  
The Cost ◽  
Grey Relational

The seamless communication between the devices of the heterogeneous wireless networks still remains as a challenge due to the delay incurred, the cost difference and the bandwidth variations.so it becomes necessary for a perfect management of the hand over and the selection of the network to provide a continuous conveyance in the broadcasting or the sharing of the information’s. So the paper initiates an enhanced network selection and a vertical hand over schema that is context aware and based on the user preference utilizing the grey relational analysis integrated with the particle swarm optimization. The performance analysis of the proposed method of vertical handover evinces the perfect network selection that enables a continuous connection for the heterogeneous networks and shows an enhanced throughput and latency in handover compared to the other methods like TOPSIS (technique for order preference by similarity to ideal solution) and SAW(simple additive weighting).

Seamless Handover in Heterogeneous Wireless Network Using Cognitive Advisor Based Decision Making Algorithm

2017 ◽  
Vol 14 (1) ◽  
pp. 517-523
Author(s):  
V Sivasankaran ◽  
V Nagarajan
Keyword(s):  
Wireless Networks ◽  
Wireless Network ◽  
Heterogeneous Wireless Networks ◽  
Optimization Technique ◽  
Vertical Handover ◽  
User Preference ◽  
Network Selection ◽  
Modern Trend ◽  
Mobile Nodes ◽  
Effective Network

An important and modern trend in wireless network is managing and accessing in heterogeneous wireless networks structures effectively. Vertical handover or handoff technology is major and acting vital role in wireless communication, it has key challenging issues in wireless network, while handover gets call drop kind of latency and call quality minimization. So the communication networks needs an efficient and dynamic services and knowledge monitoring management to select network for handover of different network environments (example: WiMAX, WiFi, WLAN, etc.). In this paper we proposed the concepts of knowledgeable monitoring (KM-method), cognitive advisor (CA) and Advanced Handover Optimization (AHO) technique to improve effective network selection for seamless communication, while travels over heterogeneous wireless networks (HWN). KM-method monitoring and manage effective network selection and holding connected mobile nodes inform header files also maintaining re-initiate to next network information (network IP address, user ID, new path, etc.). CAVHO-Cognitive Advisor based Vertical Handover (VSH and V2H) and KM-methods perform and measures velocity and direction of mobility nodes through SRSS sequential Received Strength Signal. Also CA receives the nearest networks details of each another using nearest neighbouring concept with SDT ratio Algorithm. Optimization technique (AHO) performs dynamically balancing the threshold level of speed, load and quality based on Receiving signal strength and user preference. Simulation results of CAVHO Shows it secure and increases the handover probability of access also proposed system reduce delay and improve quality of services and throughput.

scholarly journals A Use of Fuzzy TOPSIS to Improve the Network Selection in Wireless Multiaccess Environments

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Mouad Mansouri ◽  
Cherkaoui Leghris
Keyword(s):  
Fuzzy Topsis ◽  
Analytic Network Process ◽  
Vertical Handover ◽  
Network Selection ◽  
Mobile Terminals ◽  
Access Technology ◽  
Ideal Situation ◽  
Network Process ◽  
Selection Step ◽  
Order Preference

Constantly faster, mobile terminals are developing, as well as wireless networks, to satisfy the growth of “Always Best Connected” demand. Users nowadays want to access the best available wireless network, either from 3GPP or IEEE group technologies, wherever they are, without losing their sessions. Consequently, mobile terminals must seamlessly transfer the communications to another access technology (vertical handover) if needed, as they often move into heterogeneous wireless environments. This work aims to optimize the network selection step in the vertical handover process. Multiattribute Decision-Making methods naturally fit this context. Nevertheless, they make wrong handover decisions sometimes, due to imprecise data collected from the metrics. This manuscript presents the use of a hybrid method, combining the fuzzy technique for order preference by similarity to the ideal situation and fuzzy analytic network process, in the network selection, to improve the quality of service and avoid, as much as possible, unnecessary handovers. The results demonstrate that this combination is the best, compared to the other methods of the same type in the network selection context.

scholarly journals A fuzzy based vertical handover network selection scheme for device-to-device communication

2020 ◽  
Vol 17 (1) ◽  
pp. 324
Author(s):  
Meenakshi Subramani ◽  
Vinoth Babu Kumaravelu
Keyword(s):  
Wireless Networks ◽  
Vertical Handover ◽  
Multiple Attribute Decision Making ◽  
Network Selection ◽  
Selection Scheme ◽  
Handover Decision ◽  
Multiple Attribute ◽  
Device To Device ◽  
Simple Additive Weighting ◽  
The Impact

<p>One of the most attractive and challenging areas in the upcoming next-generation 5G wirelessnetworkistheverticalhandover(VHO).Recently,manyoftheheterogeneous wireless communication technologies are introduced to satisfy the demands of users in all situations. Due to the deployment of heterogeneous networks, the users can access the internet anywhere, anytime through different wireless networks. To obtain seamless service and service continuity, the device should be handed over to the best wireless networks. Here, a half handover scheme for Device-to-Device (D2D) communication is implemented for the selection of the best network. The target network selection for vertical handover can be handled using multiple attribute decision making (MADM) methods. An intelligent and fast vertical handover decision is much needed, which should be reliable even for random and uncertain environments. Fuzzy logic is proved to be effective in handling imprecise data. Hence, in this work, the impact of combining fuzzy with the conventional MADM scheme, simple additive weighting(SAW)isanalyzedandthehybridschemeiscomparedwiththeconventional MADM schemes like SAW, Techniques for order preference by similarity to ideal solution (TOPSIS), VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR) in terms of handover decision delay. Since, the numbers of handovers executed are low,thehandoverdecisiondelayperformanceoftheproposedschemeissuperiorthan the considered classical MADM schemes.</p>

scholarly journals Artificial intelligence based handover decision and network selection in heterogeneous internet of vehicles

2021 ◽  
Vol 22 (2) ◽  
pp. 1124
Author(s):  
Shaik Mazhar Hussain ◽  
Kamaludin Mohamad Yusof ◽  
Rolito Asuncion ◽  
Shaik Ashfaq Hussain
Keyword(s):  
Short Range ◽  
Learning Algorithm ◽  
Success Probability ◽  
Access Network ◽  
Vertical Handover ◽  
Network Selection ◽  
Internet Of Vehicles ◽  
Handover Decision ◽  
Radio Access ◽  
Current Characteristics

Internet of vehicles (IoV) is an emerging area that gives support for vehicles via internet assisted communication. IoV with 5G provides ubiquitous connectivity due to the participation of more than one radio access network. The mobility of vehicles demands to make handover in such heterogeneous network. The vehicles at short range uses dedicated short range communication (DSRC), while it has to use better technology for long range and any type of traffic. Usually, the previous work will directly select the network for handover or it connects with available radio access. Due to this, the occurrence of handover takes place frequently.  In this paper, the integration of DSRC, LTE and mmWave 5G on IoV is incorporated with novel handover decision making, network selection and routing. The handover decision is to ensure whether there is a need for vertical handover by using Dynamic Q-learning algorithm that uses entropy function for threshold prediction as per the current characteristics of the environment. Then the network selection is based on fuzzy-convolution neural network (F-CNN) that creates fuzzy rules from signal strength, distance, vehicle density, data type and line of sight. V2V chain routing is proposed to select V2V pairs using jellyfish optimization algorithm (JOA) that takes in account of channel, vehicle and transmission metrics. This system is developed in OMNeT++ simulator and the performances are evaluated in terms of success probability, handover failure, unnecessary handover, mean throughput, delay and packet loss.

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