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• W1154991326 abstract "Our approach coordinately manages radio resources with multiple radio access technologies in an optimum way. A mobility prediction module and a remaining bandwidth estimation module are established at each BS as shown in the lower part of the above figure. The global radio resource manager located at the upper part of this figure consists of a bandwidth utilization optimization module. A mobile host (MH) collects required parameters and the latest MH's state is immediately updated at the BS the MH resides in when a MH's state changes. The mobility prediction module will check with a pre-built lookup table to determine whether the handoff will occur. If the handoff is predicted to occur, the MH sends out a bandwidth requirement to a nearest BS, and the remaining bandwidth estimation module in the target BS will be activated to determine the amount of remaining bandwidth that can be used by the handoffs. In case some BS finds that its bandwidth is going to be inadequate, a bandwidth adjustment coordinator located at the BS will request the common bandwidth utilization optimization module at its upper level to reallocate the bandwidth for the BSs/APs of different RATs. The results of the bandwidth reallocation will then be sent back to each BS to reassign the bandwidth to the MHs. A mobility prediction module is proposed to predict the mobility pattern of mobile host.A lookup table records the probability for the possible handoffs moving into the coverage of the BS.Bandwidth is estimated for the possible arriving MHs outside the coverage of the BS.The optimization of utilization and fairness for the bandwidth allocation are addressed.Hybrid Genetic Algorithm is employed to achieve real-time computation requirement. Recently, people have been able to connect with different types of networks anytime, anywhere using advanced network technologies. In order to properly distribute wireless network resources among different clients, this work proposed a user mobility prediction algorithm, which takes the coverage of different kinds of base stations, and the volatile mobility of pedestrians, vehicles, and mass transportation, into consideration. In addition, a novel bandwidth utilization optimization technique is proposed in the algorithm to allocate bandwidth more efficiently. The Hybrid Genetic Algorithm, which combines the Genetic Algorithm and local searches to improve the frequency of finding a Pareto set, is used to realize the optimization problem as well. Compared with our previous work and the other four methods in the literature, the simulation results show that our proposed work can achieve desirable performance by network utilization, throughput, and QoS quality in the heterogeneous wireless networks." @default.
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• W1154991326 date "2015-12-01" @default.
• W1154991326 modified "2023-09-24" @default.
• W1154991326 title "A self-adaptive joint bandwidth allocation scheme for heterogeneous wireless networks" @default.
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• W1154991326 doi "https://doi.org/10.1016/j.asoc.2015.08.001" @default.
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