Network assisted network selection

2012 ◽  
Author(s):  
Syed Qutub ◽  
Tricha Anjali
Keyword(s):  
Network Selection

A throughput-aware joint vehicle route and access network selection approach based on SMDP

2020 ◽  
Vol 17 (5) ◽  
pp. 243-265 ◽  
Author(s):  
Jiandong Xie ◽  
Sa Xiao ◽  
Ying-Chang Liang ◽  
Li Wang ◽  
Jun Fang
Keyword(s):  
Access Network ◽  
Network Selection ◽  
Vehicle Route ◽  
Selection Approach ◽  
Access Network Selection

Network Selection in Wireless Heterogeneous Environment Based on Available Bandwidth Estimation

2019 ◽  
Vol 12 ◽  
Author(s):  
Kiran Ahuja ◽  
Brahmjit Singh ◽  
Rajesh Khanna
Keyword(s):  
Real Time ◽  
Estimation Error ◽  
Network Selection ◽  
Bandwidth Estimation ◽  
Heterogeneous Environment ◽  
Bootstrap Approximation ◽  
Available Bandwidth ◽  
Internet Connection ◽  
Available Bandwidth Estimation ◽  
Selection Of

Background: With the availability of multiple options in wireless network simultaneously, Always Best Connected (ABC) requires dynamic selection of the best network and access technologies. Objective: In this paper, a novel dynamic access network selection algorithm based on the real time is proposed. The available bandwidth (ABW) of each network is required to be estimated to solve the network selection problem. Method: Proposed algorithm estimates available bandwidth by taking averages, peaks, low points and bootstrap approximation for network selection. It monitors real-time internet connection and resolves the selection issue in internet connection. The proposed algorithm is capable of adapting to prevailing network conditions in heterogeneous environment of 2G, 3G and WLAN networks without user intervention. It is implemented in temporal and spatial domains to check its robustness. Estimation error, overhead, estimation time with the varying size of traffic and reliability are used as the performance metrics. Results: Through numerical results, it is shown that the proposed algorithm’s ABW estimation based on bootstrap approximation gives improved performance in terms of estimation error (less than 20%), overhead (varies from 0.03% to 83%) and reliability (approx. 99%) with respect to existing techniques. Conclusion: Our proposed methodology of network selection criterion estimates the available bandwidth by taking averages, peaks, and low points and bootstrap approximation method (standard deviation) for the selection of network in the wireless heterogeneous environment. It monitors real-time internet connection and resolves internet connections selection issue. All the real-time usage and test results demonstrate the productivity and adequacy of available bandwidth estimation with bootstrap approximation as a practical solution for consistent correspondence among heterogeneous wireless networks by precise network selection for multimedia services.

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 Joint optimization of network selection and task offloading for vehicular edge computing

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Lujie Tang ◽  
Bing Tang ◽  
Li Zhang ◽  
Feiyan Guo ◽  
Haiwu He
Keyword(s):  
Large Scale ◽  
Vehicular Networks ◽  
Access Point ◽  
Edge Computing ◽  
Network Selection ◽  
Network Access ◽  
Task Execution ◽  
Point Selection ◽  
Vehicle Movement ◽  
Task Offloading

AbstractTaking the mobile edge computing paradigm as an effective supplement to the vehicular networks can enable vehicles to obtain network resources and computing capability nearby, and meet the current large-scale increase in vehicular service requirements. However, the congestion of wireless networks and insufficient computing resources of edge servers caused by the strong mobility of vehicles and the offloading of a large number of tasks make it difficult to provide users with good quality of service. In existing work, the influence of network access point selection on task execution latency was often not considered. In this paper, a pre-allocation algorithm for vehicle tasks is proposed to solve the problem of service interruption caused by vehicle movement and the limited edge coverage. Then, a system model is utilized to comprehensively consider the vehicle movement characteristics, access point resource utilization, and edge server workloads, so as to characterize the overall latency of vehicle task offloading execution. Furthermore, an adaptive task offloading strategy for automatic and efficient network selection, task offloading decisions in vehicular edge computing is implemented. Experimental results show that the proposed method significantly improves the overall task execution performance and reduces the time overhead of task offloading.

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