Resource Allocation in High Data Rate Mesh WPAN: A Survey Paper

Sindian, Samar; Khalil, Ayman; Samhat, Abed Ellatif; Crussière, Matthieu; Hélard, Jean-François

doi:10.1007/s11277-013-1330-6

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…Beyond exchanges information between devices, BLE provides new opportunities to explore positioning. In [103], researchers study how BLE beacons radio signals can be used for indoor location scenarios, as well as their human mobility tracking precision. In an outdoor context, Zigbee is promising to be of lower cost in comparison with BLE.…”

Section: Coverage Human Mobility Comparisonmentioning

confidence: 99%

Mobile Networks and Internet of Things Infrastructures to Characterize Smart Human Mobility

2021

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The evolution of Mobile Networks and Internet of Things (IoT) architectures allows one to rethink the way smart cities infrastructures are designed and managed, and solve a number of problems in terms of human mobility. The territories that adopt the sensoring era can take advantage of this disruptive technology to improve the quality of mobility of their citizens and the rationalization of their resources. However, with this rapid development of smart terminals and infrastructures, as well as the proliferation of diversified applications, even current networks may not be able to completely meet quickly rising human mobility demands. Thus, they are facing many challenges and to cope with these challenges, different standards and projects have been proposed so far. Accordingly, Artificial Intelligence (AI) has been utilized as a new paradigm for the design and optimization of mobile networks with a high level of intelligence. The objective of this work is to identify and discuss the challenges of mobile networks, alongside IoT and AI, to characterize smart human mobility and to discuss some workable solutions to these challenges. Finally, based on this discussion, we propose paths for future smart human mobility researches.

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Section: Coverage Human Mobility Comparisonmentioning

confidence: 99%

Mobile Networks and Internet of Things Infrastructures to Characterize Smart Human Mobility

2021

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“…Different works [2][3][4][5][6] investigate the resource allocation mechanisms and propose solutions to overcome these limitations while trying to extend the coverage area of an IEEE 802.15.3-based WPAN. A detailed description of these works is presented in [7].…”

Section: Introductionmentioning

confidence: 99%

Admission control and resource allocation strategies for IEEE 802.15.5

Sindian

Crussière

Hélard

et al. 2014

J Wireless Com Network

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In this paper, a novel two-tier mechanism for the access control and resource allocation of a two-hop high data rate IEEE 802.15.5 network is proposed. One of the main contributions in this proposal is the use of a dynamic superframe size in the IEEE 802.15.5. Additionally, the ideas of using a superframe utilization threshold and a channel time allocation period (CTAP) utilization threshold are incorporated, with the aim of allowing more devices to access the shared superframe. Using these thresholds, two new hop-1 resource allocation algorithms are described; CTAP utilization threshold-based resource allocation algorithm (CTRA) and superframe utilization threshold-based resource allocation algorithm (STRA). These algorithms control the access of the hop-1 Mesh PicoNet Coordinators (MPNCs) and Mesh DEVices (MDEVs) to the channel time resources in the superframe. Furthermore, an algorithm for the distribution of the hop-1 MPNCs' resources among the real-time (RT) and non-real-time (NRT) MDEVs at hop-2 is introduced. In this mechanism, a new flag metric is applied to provide higher priorities to MPNCs over MDEVs in the hop-1 algorithms and to the RT MDEVs over the NRT MDEVs in the hop-2 algorithm. Simulation results show the superiority of the proposed mechanism over others by providing a higher satisfaction factor and higher fairness among the competing devices at both hop-1 and hop-2 of the IEEE 802.15.5.

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