Vertical handover decision based on quality of experience in heterogeneous wireless networks

Valenzuela, Gracieth; Ferreira, Isac; Nóbrega, Obionor de Oliveira; Cunha, Paulo Roberto Freire

doi:10.1145/2261605.2261615

Cited by 4 publications

(1 citation statement)

References 10 publications

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“…Marquez-Barja et al (2012) used geo-location, context information and route calculation for handover decision making to improve the performance of handover. Valenzuela et al (2012) has developed network selection based on the quality of experience and traffic load of the Science Publications AJAS target networks. But these two approaches do not consider about the formal attributes that plays role in handover decision making.…”

Section: Related Workmentioning

confidence: 99%

An Intelligent Vertical Handover Decision Algorithm for Wireless Heterogeneous Networks

Narayanan¹,

Rajeswari²,

Sureshkumar³

2014

American Journal of Applied Sciences

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The Next Generation Wireless Networks (NGWN) should be compatible with other communication technologies to offer the best connectivity to the mobile terminal which can access any IP based services at any time from any network without the knowledge of its user. It requires an intelligent vertical handover decision making algorithm to migrate between technologies that enable seamless mobility, always best connection and minimal terminal power consumption. Currently existing decision engines are simple, proprietary and its handover is only based on the received signal strength which has been proven unintelligent. The proposed decision algorithm gains intelligence by combining fuzzy logic system to handle imprecise data, multiple attribute decision making to handle multiple attributes for decision making and context aware strategies to reduce unnecessary handover. The proposed intelligent decision algorithm detects new network which offers best connectivity than current network and does authentication and mobile IP registration before making the handover; thereby reducing the packet loss to ensure high quality of service. This algorithm is capable of forwarding data packets to appropriate attachment point to maximize battery lifetime and also to maintain load balancing. The performance analysis shows that the proposed algorithm efficiently uses the network resources by switching between 3G and Wi-Fi under the different RF environmental conditions to offer best connectivity with minimal service cost to the users. It is observed that average handover delay for the experiment is 30-40ms and the integration of cellular network with WLAN using the proposed intelligent decision algorithm reduces the call dropping rate (<0.006) and call blocking probability (<0.00607) as well as unnecessary handover in heterogeneous networks.

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Section: Related Workmentioning

confidence: 99%