Seamless vertical handoff using modified weed optimization algorithm for heterogeneous wireless networks

Velmurugan, T.; Хара, Сибарам; Nandakumar, S.; Sumathi, D.

doi:10.3103/s0735272717100028

Cited by 11 publications

(4 citation statements)

References 14 publications

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“…Velmurugan et al [31] aimed at reducing the frequency of hand-off calls and power consumption of mobile nodes by using the multi-objective whale optimization (M-WO) algorithm for vertical hand-off (VHO) decision making. Simulation results showed that under certain conditions, the multi-objective whale optimization (M-WO) algorithm outperformed some existing algorithms such as optimization based on SSF (strongest signal first) and OPTG, in terms of call drop rate, load, and battery lifetime of the mobile terminal.…”

Section: Related Workmentioning

confidence: 99%

Ant colony optimization-based solution to optimize load balancing and throughput for 5G and beyond heterogeneous networks

Alam,

Chugh,

Azad

et al. 2024

J Wireless Com Network

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The escalating demand for data in wireless communication systems has posed significant challenges in recent years. This trend is predicted to continue, with explosive data usage and evolving quality of service demands from mobile users. The rapid increase in traffic demand, combined with the intricate nature of heterogeneous network (HetNet) scenarios, has significantly heightened the challenges confronting mobile network operators. These challenges encompass service quality, load distribution, coverage, and the overall user experience. Conventional approaches that prioritize maximum received power in the cell association mechanism tend to sustain network imbalances within the HetNets, making it difficult to cater for the diverse traffic requirements of mobile users. In this study, instead of focusing solely on enhancing individual user downlink rates, we maximize the number of users whose downlink needs are satisfied by integrating a cell range extension (CRE) technique with an ant colony optimization algorithm. Our proposed method considers both the workload of base stations and the signal to interference-plus-noise ratio of user devices to formulate an objective function aimed at calculating specific CRE bias values for individual small base stations. A comparative analysis of the proposed approach with existing techniques demonstrates its effectiveness. Simulation results underscore the success of our proposed strategy in meeting users’ throughput needs while reducing network imbalances and call drop rates.

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Section: Related Workmentioning

confidence: 99%

Ant colony optimization-based solution to optimize load balancing and throughput for 5G and beyond heterogeneous networks

Alam,

Chugh,

Azad

et al. 2024

J Wireless Com Network

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“…The main limitation of this method is that it did not support high number of BSs. Velmurugan et al used modified weed optimization methodology for the mobile nodes in different networks during handoff process. The authors utilized vertical handoff between two different networks.…”

Section: Literature Surveymentioning

confidence: 99%

Performance improvement in vertical heterogeneous handoff methodology using CANFIS classification approaches

Mohanapriya¹,

Jayanthi²

2018

Concurrency and Computation

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Summary Detection of malicious Base Stations (BS) in heterogeneous wireless networks is significant for developing an efficient system in wireless networks. In this paper, the handoff is performed between two different networks such as Wi‐Fi and WiMax, which may be located in different locations in the same region. The trust features, Cumulative Binary Features and Cost Index Features of each BS in different wireless network environment, are derived individually, which differentiates the behavior of the normal BS and malicious BS in different networks using Co‐Active Neuro Fuzzy Inference System (CANFIS) classification approach. The proposed methodology is compared with other state‐of‐arts methods for evaluating the individuality and efficiency. The proposed heterogeneous handoff methodology achieves 96.02% of packet delivery ratio, 90% detection rate, 94.6% of precision, and 15.99 ms of latency.

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“…To provide seamless roaming and service continuity there is a need to combine various wireless access technologies and define reliable intersystem handover strategies. Related works on intersystem handover are focused on performance optimization [9], [10] and algorithms for handover decision [11], [12], [13].…”

Section: Related Work and Research Motivationmentioning

confidence: 99%

Mobile Edge Service for Intersystem Handover

Pencheva¹,

Atanasov²,

Kireva-Mihova³

et al. 2018

IJET

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Multi-access Edge Computing (MEC) appears to be an integrating technology for radio access networks to enhance the access capacity, optimize network performance and improve quality of experience for end users. MEC distributes cloud capabilities for storage and computing in the radio access network, close to the end users. As far as the development of advanced Application Programming Interfaces is a key area, we propose a new mobile edge service that enables 3rd party control on intersystem handover. The proposed service enables authorized applications to initiate intersystem handover following specific policy. The service is described by information flows illustrating the basic functionality, data models that provide mediation functions, and handover state models considering some implementation issues.

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Seamless vertical handoff using modified weed optimization algorithm for heterogeneous wireless networks

Cited by 11 publications

References 14 publications

Ant colony optimization-based solution to optimize load balancing and throughput for 5G and beyond heterogeneous networks

Ant colony optimization-based solution to optimize load balancing and throughput for 5G and beyond heterogeneous networks

Performance improvement in vertical heterogeneous handoff methodology using CANFIS classification approaches

Mobile Edge Service for Intersystem Handover

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