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In a device-to-device content delivery network (D2D-CDN), user equipment (UE) covered by a base station can forward content received from the base station to other uncovered UEs in a multi-hop manner to increase network coverage. However, infrastructures, such as local base stations, are destroyed and D2D-CDN cannot operate normally due to the lack of base stations as a content source in disaster scenarios. Unmanned aerial vehicle (UAV) can temporarily serve as a content source with its flexibility to deliver content to terrestrial UEs, which we call it UAV base station (UAV-BS). However, the placement of UAV-BS will be affected by many factors, such as UE distribution and communication interference. Therefore, how to place UAV-BS in a reasonable way to maximize the network throughput and the number of covered UEs while ensuring the communication quality of service (QoS) is still a challenging problem. To solve this problem, first, we propose a UAV-BS placement optimization model (U-POM) and formulate an optimization problem. Secondly, we prove that our maximization problem is NP-hard and propose an improved artificial bee colony algorithm (ABC), called the global optimal artificial bee colony (GOABC) algorithm. Finally, we construct an analysis and testing platform to analyze the accuracy and the stability of the GOABC algorithm. The results highlight the effectiveness of the proposed GOABC algorithm in maximizing network throughput and the number of covered UEs while ensuring the communication QoS. [ABSTRACT FROM AUTHOR]

Collaborative crowdsensing (CCS) requires the recruited team to collaborate closely to complete sensing tasks with high quality of service (QoS). The team recruitment of CCS is mainly influenced by the subjective willingness of participants and the objective trust evaluation of the sensing platform; that is, the higher the subjective mutual willingness to work together and the objective mutual trust among participants, the more efficiency with which the CCS tasks will be achieved. However, the existing research lacks comprehensive consideration of mutual willingness and mutual trust among recruited participants. This results in poor QoS. To address this problem, we propose a novel team recruitment method for CCS that jointly considers the willingness and trust to recruit optimal teams. First, we build a graph convolutional network-based willingness-trust network (GCN-WTN) model for CCS to obtain mutual willingness and trust among participants more accurately. Second, we propose a willingness and trust-based team recruitment (WT-TR) method to recruit the optimal teams for CCS. This method introduces the consensus and similarity constraints into the willingness and trust networks to better meet the collaboration needs of CCS. Finally, we implement a recruitment simulation platform for CCS to simulate the team recruitment process and validate the effectiveness of our proposed method. The experimental results show that the teams recruited by the proposed method can significantly improve QoS for CCS. [ABSTRACT FROM AUTHOR]

Quality of service (QoS) provisioning is one of the most important criteria in newly emerging UWB WPANs, as they are expected to support a wide variety of applications from time-constrained, multimedia streaming to throughput-hungry, content transfer applications. Recently, the WiMedia Alliance has announced the PHY/MAC specification together with the common radio platform for UWB WPANs. The WiMedia MAC uses the contention-free reservation-based access, which supports isochronous traffic with distributed reservation protocol (DRP), and the contention-based access, which provides service differentiation for best effort and variable-rate real-time traffic with prioritized channel access (PCA), similar to the enhanced distributed coordinated access (EDCA) in IEEE 802.11e. In this paper, we conduct a comprehensive theoretical analysis and show that with the currently recommended parameter setting, EDCA cannot provide adequate QoS. In particular, without responding to the system dynamics (e.g., taking account of the number of active stations in each class), EDCA cannot allocate bandwidth in a deterministic proportional manner and the system bandwidth is underutilized. After identifying the deficiency of EDCA, we propose an enhanced QoS-provisioning framework for the PCA scheme that dynamically controls channel access to adjust allocated bandwidth depending on the change of application's bit rate, i.e., variable-rate real-time traffic. We show that in this framework, 1) variable-rate real-time traffic is adaptively guaranteed of deterministic bandwidth via a contention-based reservation access method; 2) best effort traffic is provided with deterministic proportional QoS; and 3) moreover, the bandwidth utilization in PCA is maximized. By deterministic proportional QoS, we mean that the proposed protocol will maintain the ratio, r_j, of per-station throughput attained by a station of class j to that attained by a station of class 1 at the targeted value, and yet, the real amount of network bandwidth is changing according to the current available network bandwidth. We have also validated and evaluated the QoS provisioning capability and practicality of the proposed PCA framework both via simulation and an empirical study with the Multiband Atheros Driver for WiFi (MADWifi) Linux driver for Wireless LAN devices with the Atheros chipset. [ABSTRACT FROM PUBLISHER]