2018 11th IFIP Wireless and Mobile Networking Conference (WMNC) 2018
DOI: 10.23919/wmnc.2018.8480927
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Mobility Beamforming Prediction and a Round Robin Scheduling in a Directional MAC for MANET

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Cited by 4 publications
(4 citation statements)
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“…Another neighborhood maintenance protocol, proposed in [34], has the mobility awareness feature; however, it is inefficient for the intended MANETs due to the additional acknowledgement message overheads. Furthermore, there are several recent studies offering interference solutions via directional or smart antennas as in [35][36][37][38], but implementation of directional antennas for crowded MANETs require more complex and costly hardware. Hence, these protocols are also not applicable to the intended MANET scenarios.…”
Section: Related Workmentioning
confidence: 99%
“…Another neighborhood maintenance protocol, proposed in [34], has the mobility awareness feature; however, it is inefficient for the intended MANETs due to the additional acknowledgement message overheads. Furthermore, there are several recent studies offering interference solutions via directional or smart antennas as in [35][36][37][38], but implementation of directional antennas for crowded MANETs require more complex and costly hardware. Hence, these protocols are also not applicable to the intended MANET scenarios.…”
Section: Related Workmentioning
confidence: 99%
“…Nevertheless, these works are suitable for Vehicular ad Hoc Network (VANET) environments and do not properly address the deafness problem which is very relevant in MANET. In [28] we introduce a predictive location mechanism that also provides for a frame scheduler with priority in order to reduce the handoff problem. However, in this case, the energy consumption of nodes is not considered.…”
Section: Mobility Issues Directional Mac Workmentioning
confidence: 99%
“…For example, in [33], the authors attempt to limit the handoff problem through the use of an efficient beam control mechanism; a similar approach is proposed in [34] in which handoff is reduced using a predictive location model that is able to estimate future movements of nodes. Similarly, the work [35] presents a predictive location algorithm using in-frame priority scheduling in order to reduce the handoff.…”
mentioning
confidence: 99%