The Fog Makes Sense: Enabling Social Sensing Services With Limited Internet Connectivity

Social sensing services use humans as sensor carriers, sensor operators and sensors themselves in order to provide situation-awareness to applications. This promises to provide a multitude of benefits to the users, for example in the management of natural disasters or in community empowerment. However, current social sensing services depend on Internet connectivity since the services are deployed on central Cloud platforms. In many circumstances, Internet connectivity is constrained, for instance when a natural disaster causes Internet outages or when people do not have Internet access due to economical reasons. In this paper, we propose the emerging Fog Computing infrastructure to become a key-enabler of social sensing services in situations of constrained Internet connectivity. To this end, we develop a generic architecture and API of Fog-enabled social sensing services. We exemplify the usage of the proposed social sensing architecture on a number of concrete use cases from two different scenarios.Comment: Ruben Mayer, Harshit Gupta, Enrique Saurez, and Umakishore Ramachandran. 2017. The Fog Makes Sense: Enabling Social Sensing Services With Limited Internet Connectivity. In Proceedings of The 2nd International Workshop on Social Sensing, Pittsburgh, PA, USA, April 21 2017 (SocialSens'17), 6 page

Communication and Control in Collaborative UAVs: Recent Advances and Future Trends

The recent progress in unmanned aerial vehicles (UAV) technology has significantly advanced UAV-based applications for military, civil, and commercial domains. Nevertheless, the challenges of establishing high-speed communication links, flexible control strategies, and developing efficient collaborative decision-making algorithms for a swarm of UAVs limit their autonomy, robustness, and reliability. Thus, a growing focus has been witnessed on collaborative communication to allow a swarm of UAVs to coordinate and communicate autonomously for the cooperative completion of tasks in a short time with improved efficiency and reliability. This work presents a comprehensive review of collaborative communication in a multi-UAV system. We thoroughly discuss the characteristics of intelligent UAVs and their communication and control requirements for autonomous collaboration and coordination. Moreover, we review various UAV collaboration tasks, summarize the applications of UAV swarm networks for dense urban environments and present the use case scenarios to highlight the current developments of UAV-based applications in various domains. Finally, we identify several exciting future research direction that needs attention for advancing the research in collaborative UAVs

Flying mobile edge computing towards 5G and beyond: an overview on current use cases and challenges

The increasing computational capacity of multiple devices, the advent of complex applications, and data generation create new challenges of scalability, ubiquity, and seamless services to meet the most diverse network demands and requirements, such as reliability, latency, battery lifetime. For this reason, the 5th Generation (5G) network comes to mitigate the most diverse challenges inherent to the current dynamic mobile networks and their increasing data rates. Unmanned Aerial Vehicles (UAVs) have also been considered as communication relays or mobile base stations to assist mobile users with limited or no available wireless infrastructure. They can provide connections for mobile users in hard-to-reach areas, replacing damaged or overloaded ground infrastructure and working as mobile clouds, providing low but increasing computational power. However, the feasibility of a Flying Edge Computing requires special attention in terms of resource allocation techniques, cooperation with existing ground units and among multiple UAVs, coordination with user mobility, computation efficiency, collision avoidance, and recharging approaches. Thus, the cooperation among UAVs and the current terrestrial Mobile Edge Computing can be relevant in some cases once the computation power of a single UAV might be insufficient. It is important to understand the feasibility of current proposals and establish new approaches that consider the usage of multiple UAVs and recharging approaches. In this paper we discuss the challenges of a 5G extended network through the help of UAVs. The proposed multi-tier architecture employs UAVs with different mobility models, providing support to ground nodes. Moreover, the support of the UAVs as edge nodes will also be evaluated.publishe

Optimizing Energy Efficiency in UAV-Based Wireless Communication Networks: A Comparative Analysis of TAODV and DSR Protocols using the Trust Score Algorithm for Signal Processing

This study presents a comprehensive analysis of energy efficiency optimization in signal processing algorithms for UAV-based wireless communication networks. Employing a multifaceted approach that integrates mathematical modeling, game theory analysis, and an array of testing methodologies, the research aims to address the critical challenge of enhancing communication protocol performance while minimizing energy consumption. Central to our investigation is the development and application of the Trust Score Algorithm (TSA), a novel quantitative tool designed to evaluate and compare the efficacy of various signal processing algorithms across multiple dimensions, including energy efficiency, reliability, adaptability, security, and latency. Through detailed comparative analysis and data visualization techniques, the study reveals that the Proposed_TAODV protocol significantly outperforms traditional TAODV and DSR protocols in several key metrics. These include throughput efficiency, end-to-end delay, and packet delivery ratio, particularly as the number of UAV nodes scales up. Such findings underscore the Proposed_TAODV protocol's superior stability and performance, advocating for its potential in improving the sustainability and effectiveness of UAV-based communication networks. The research methodology encompasses both theoretical and empirical testing phases, ranging from simulation-based analysis, to validate the performance of the signal processing algorithms under varied operational conditions. The results not only affirm the superior performance of the Proposed_TAODV protocol but also highlight the utility of the TSA in guiding the selection and optimization of signal processing algorithms for UAV networks

Unmanned aerial vehicles optimal airtime estimation for energy aware deployment in IoT-enabled fifth generation cellular networks

[EN] Cellular networks based on new generation standards are the major enabler for Internet of things (IoT) communication. Narrowband-IoT and Long Term Evolution for Machines are the newest wide area network-based cellular technologies for IoT applications. The deployment of unmanned aerial vehicles (UAVs) has gained the popularity in cellular networks by using temporary ubiquitous coverage in the areas where the infrastructure-based networks are either not available or have vanished due to some disasters. The major challenge in such networks is the efficient UAVs deployment that covers maximum users and area with the minimum number of UAVs. The performance and sustainability of UAVs is largely dependent upon the available residual energy especially in mission planning. Although energy harvesting techniques and efficient storage units are available, but these have their own constraints and the limited onboard energy still severely hinders the practical realization of UAVs. This paper employs neglected parameters of UAVs energy consumption in order to get actual status of available energy and proposed a solution that more accurately estimates the UAVs operational airtime. The proposed model is evaluated in test bed and simulation environment where the results show the consideration of such explicit usage parameters achieves significant improvement in airtime estimation.The research is funded by the Department of Computer Science, Iqra University, Islamabad Campus, PakistanMajeed, S.; Sohail, A.; Qureshi, KN.; Kumar, A.; Iqbal, S.; Lloret, J. (2020). Unmanned aerial vehicles optimal airtime estimation for energy aware deployment in IoT-enabled fifth generation cellular networks. EURASIP Journal on Wireless Communications and Networking. 2020(1):1-14. https://doi.org/10.1186/s13638-020-01877-01142020