Efficient offloading and load distribution based on D2D relaying and UAVs for emergent wireless networks

The device to device (D2D) and unmanned aerial vehicle (UAV) communications are considered as enabling technologies of the emergent 5th generation of wireless and cellular system (5G). Consequently, it is important to determine their corresponding performance with respect to the 5G requirements. In particular, we focus on enhancing the offloading and load balancing performance in three directions. In the first direction, we study the achievable data rate of user relay assisting other users in two-tier networks. We propose a novel heuristic communication scheme called device-for-device (D4D). The D4D enables moving users to share their resource by taking advantage of cooperative communication. We study the moving user rate sensitivity to the relay selection and blocking probability. In the second direction, we study the offloading from macrocell to small cell and load balancing among small cell. Also, we design a new utility weight function that enables a balanced relay assignment. We propose a novel low complexity algorithm for centralized scheme maximizing the load among small cells as well as users subject to SINR threshold constraints. The simulations show that our proposed schemes achieve performance in load balancing compared to those obtained with the previous or traditional method. In the third direction, we study the 3D deployment of multiple UAVs for emergent on-demand offloading. We propose a novel on-demand deployment scheme based on maximizing both the operator’s profit and the quality of service. The proposed scheme is based on solving a non-convex problem by combining k-means clustering with pattern search to find the suboptimal location of UAVs. The simulation results show that our proposed scheme maximizes the operator’s profit and improves offloading traffic efficiency. Our global contribution was the development of a scheme to improve the quality of service and the performance in emergent networks through the improvement of the load distribution and resource sharing using D2D and UAV

Relaying in the Internet of Things (IoT): A Survey

The deployment of relays between Internet of Things (IoT) end devices and gateways can improve link quality. In cellular-based IoT, relays have the potential to reduce base station overload. The energy expended in single-hop long-range communication can be reduced if relays listen to transmissions of end devices and forward these observations to gateways. However, incorporating relays into IoT networks faces some challenges. IoT end devices are designed primarily for uplink communication of small-sized observations toward the network; hence, opportunistically using end devices as relays needs a redesign of both the medium access control (MAC) layer protocol of such end devices and possible addition of new communication interfaces. Additionally, the wake-up time of IoT end devices needs to be synchronized with that of the relays. For cellular-based IoT, the possibility of using infrastructure relays exists, and noncellular IoT networks can leverage the presence of mobile devices for relaying, for example, in remote healthcare. However, the latter presents problems of incentivizing relay participation and managing the mobility of relays. Furthermore, although relays can increase the lifetime of IoT networks, deploying relays implies the need for additional batteries to power them. This can erode the energy efficiency gain that relays offer. Therefore, designing relay-assisted IoT networks that provide acceptable trade-offs is key, and this goes beyond adding an extra transmit RF chain to a relay-enabled IoT end device. There has been increasing research interest in IoT relaying, as demonstrated in the available literature. Works that consider these issues are surveyed in this paper to provide insight into the state of the art, provide design insights for network designers and motivate future research directions

A survey on intelligent computation offloading and pricing strategy in UAV-Enabled MEC network: Challenges and research directions

The lack of resource constraints for edge servers makes it difficult to simultaneously perform a large number of Mobile Devices’ (MDs) requests. The Mobile Network Operator (MNO) must then select how to delegate MD queries to its Mobile Edge Computing (MEC) server in order to maximize the overall benefit of admitted requests with varying latency needs. Unmanned Aerial Vehicles (UAVs) and Artificial Intelligent (AI) can increase MNO performance because of their flexibility in deployment, high mobility of UAV, and efficiency of AI algorithms. There is a trade-off between the cost incurred by the MD and the profit received by the MNO. Intelligent computing offloading to UAV-enabled MEC, on the other hand, is a promising way to bridge the gap between MDs' limited processing resources, as well as the intelligent algorithms that are utilized for computation offloading in the UAV-MEC network and the high computing demands of upcoming applications. This study looks at some of the research on the benefits of computation offloading process in the UAV-MEC network, as well as the intelligent models that are utilized for computation offloading in the UAV-MEC network. In addition, this article examines several intelligent pricing techniques in different structures in the UAV-MEC network. Finally, this work highlights some important open research issues and future research directions of Artificial Intelligent (AI) in computation offloading and applying intelligent pricing strategies in the UAV-MEC network

A Survey on UAV-Aided Maritime Communications: Deployment Considerations, Applications, and Future Challenges

Maritime activities represent a major domain of economic growth with several emerging maritime Internet of Things use cases, such as smart ports, autonomous navigation, and ocean monitoring systems. The major enabler for this exciting ecosystem is the provision of broadband, low-delay, and reliable wireless coverage to the ever-increasing number of vessels, buoys, platforms, sensors, and actuators. Towards this end, the integration of unmanned aerial vehicles (UAVs) in maritime communications introduces an aerial dimension to wireless connectivity going above and beyond current deployments, which are mainly relying on shore-based base stations with limited coverage and satellite links with high latency. Considering the potential of UAV-aided wireless communications, this survey presents the state-of-the-art in UAV-aided maritime communications, which, in general, are based on both conventional optimization and machine-learning-aided approaches. More specifically, relevant UAV-based network architectures are discussed together with the role of their building blocks. Then, physical-layer, resource management, and cloud/edge computing and caching UAV-aided solutions in maritime environments are discussed and grouped based on their performance targets. Moreover, as UAVs are characterized by flexible deployment with high re-positioning capabilities, studies on UAV trajectory optimization for maritime applications are thoroughly discussed. In addition, aiming at shedding light on the current status of real-world deployments, experimental studies on UAV-aided maritime communications are presented and implementation details are given. Finally, several important open issues in the area of UAV-aided maritime communications are given, related to the integration of sixth generation (6G) advancements

Architecture design for disaster resilient management network using D2D technology

Huge damages from natural disasters, such as earthquakes, floods, landslide, tsunamis, have been reported in recent years, claiming many lives, rendering millions homeless and causing huge financial losses worldwide. The lack of effective communication between the public rescue/safety agencies, rescue teams, first responders and trapped survivors/victims makes the situation even worse. Factors like dysfunctional communication networks, limited communications capacity, limited resources/services, data transformation and effective evaluation, energy, and power deficiency cause unnecessary hindrance in rescue and recovery services during a disaster. The new wireless communication technologies are needed to enhance life-saving capabilities and rescue services. In general, in order to improve societal resilience towards natural catastrophes and develop effective communication infrastructure, innovative approaches need to be initiated to provide improved quality, better connectivity in the events of natural and human disasters. In this thesis, a disaster resilient network architecture is proposed and analysed using multi-hop communications, clustering, energy harvesting, throughput optimization, reliability enhancement, adaptive selection, and low latency communications. It also examines the importance of mode selection, power management, frequency and time resource allocation to realize the promises of Long-term Evolution (LTE) Device to Device (D2D) communication. In particular, to support resilient and energy efficient communication in disaster-affected areas. This research is examined by thorough and vigorous simulations and validated through mathematical modelling. Overall, the impact of this research is twofold: i) it provides new technologies for effective inter- and intra-agency coordination system during a disaster event by establishing a stronger and resilient communication; and ii) It offers a potential solution for stakeholders such as governments, rescue teams, and general public with new informed information on how to establish effective policies to cope with challenges before, during and after the disaster events