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.
Path Selection Using Available Bandwidth Estimation in Overlay-Based Video Streaming