Device-to-device based path selection for post disaster communication using hybrid intelligence

Public safety network communication methods are concurrence with emerging networks to provide enhanced strategies and services for catastrophe management. If the cellular network is damaged after a calamity, a new-generation network like the internet of things (IoT) is ready to assure network access. In this paper, we suggested a framework of hybrid intelligence to find and re-connect the isolated nodes to the functional area to save life. We look at a situation in which the devices in the hazard region can constantly monitor the radio environment to self-detect the occurrence of a disaster, switch to the device-to-device (D2D) communication mode, and establish a vital connection. The oscillating spider monkey optimization (OSMO) approach forms clusters of the devices in the disaster area to improve network efficiency. The devices in the secluded area use the cluster heads as relay nodes to the operational site. An oscillating particle swarm optimization (OPSO) with a priority-based path encoding technique is used for path discovery. The suggested approach improves the energy efficiency of the network by selecting a routing path based on the remaining energy of the device, channel quality, and hop count, thus increasing network stability and packet delivery

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

STFANET : SDN-Based Topology Management for Flying Ad Hoc Network

In recent years, with the growth in the use of Unmanned Aerial Vehicles (UAVs), UAV-based systems have become popular in both military and civil applications. The lack of reliable communication infrastructure in these scenarios has motivated the use of UAVs to establish a network as flying nodes, also known as Flying Ad Hoc Networks (FANETs). However, the high mobility degree of flying and terrestrial users may be responsible for constant changes in the network topology, which makes more challenging to guarantee their communication during the operational time. In this context, this article presents a Software-defined networking (SDN) based Topology management for FANETs - called of STFANET -, which is a coordination protocol that englobes both an efficient SDN-based UAV communication and a set of topology management algorithms. The goal is to establish and maintain a FANET topology in order to provide a constant and reliable communication link among independent nodes - which are performing individual or collaborative missions - through relays units. Simulation results show the efficiency of the proposed protocol in order to provide communication in a dynamic scenario. Considering its use in a military setting, STFANET managed to achieve 25% of packet loss in transmitting data packets, 1.5ms of latency and 71% of connectivity on average

Aerial Network Assistance Systems for Post-Disaster Scenarios : Topology Monitoring and Communication Support in Infrastructure-Independent Networks

Communication anytime and anywhere is necessary for our modern society to function. However, the critical network infrastructure quickly fails in the face of a disaster and leaves the affected population without means of communication. This lack can be overcome by smartphone-based emergency communication systems, based on infrastructure-independent networks like Delay-Tolerant Networks (DTNs). DTNs, however, suffer from short device-to-device link distances and, thus, require multi-hop routing or data ferries between disjunct parts of the network. In disaster scenarios, this fragmentation is particularly severe because of the highly clustered human mobility behavior. Nevertheless, aerial communication support systems can connect local network clusters by utilizing Unmanned Aerial Vehicles (UAVs) as data ferries. To facilitate situation-aware and adaptive communication support, knowledge of the network topology, the identification of missing communication links, and the constant reassessment of dynamic disasters are required. These requirements are usually neglected, despite existing approaches to aerial monitoring systems capable of detecting devices and networks. In this dissertation, we, therefore, facilitate the coexistence of aerial topology monitoring and communications support mechanisms in an autonomous Aerial Network Assistance System for infrastructure-independent networks as our first contribution. To enable system adaptations to unknown and dynamic disaster situations, our second contribution addresses the collection, processing, and utilization of topology information. For one thing, we introduce cooperative monitoring approaches to include the DTN in the monitoring process. Furthermore, we apply novel approaches for data aggregation and network cluster estimation to facilitate the continuous assessment of topology information and an appropriate system adaptation. Based on this, we introduce an adaptive topology-aware routing approach to reroute UAVs and increase the coverage of disconnected nodes outside clusters. We generalize our contributions by integrating them into a simulation framework, creating an evaluation platform for autonomous aerial systems as our third contribution. We further increase the expressiveness of our aerial system evaluation, by adding movement models for multicopter aircraft combined with power consumption models based on real-world measurements. Additionally, we improve the disaster simulation by generalizing civilian disaster mobility based on a real-world field test. With a prototypical system implementation, we extensively evaluate our contributions and show the significant benefits of cooperative monitoring and topology-aware routing, respectively. We highlight the importance of continuous and integrated topology monitoring for aerial communications support and demonstrate its necessity for an adaptive and long-term disaster deployment. In conclusion, the contributions of this dissertation enable the usage of autonomous Aerial Network Assistance Systems and their adaptability in dynamic disaster scenarios

Formation coordination and network management of UAV networks using particle swarm optimization and software-defined networking

In recent years, with the growth in the use of Unmanned Aerial Vehicles (UAVs), UAV-based systems have become popular in both military and civil applications. The lack of reliable communication infrastructure in these scenarios has motivated the use of UAVs to establish a network as flying nodes, also known as UAV networks. However, the high mobility degree of flying and terrestrial users may be responsible for constant changes in nodes’ positioning, which makes it more challenging to guarantee their communication during the operational time. In this context, this work presents a framework solution for formation coordination and network management of UAVs, which aims to establish and maintain a set of relays units in order to provide a constant, reliable and efficient communication link among user nodes - which are performing individual or collaborative missions on its turn. Such a framework relies on a set of formation coordination algorithms - including the Particle Swarm Optimization (PSO) evolutionary algorithm -, and also considers the use of Software-defined Networking-based (SDN) communication protocol for network management. For coordination proposes, a novel particle selection criteria is proposed, which aims to guarantee network manageability of UAV formations, therefore being able to guarantee service persistence in case of nodes’ failure occurrence, as well as to provide required network performance, as a consequence. Simulations performed in OMNeT++ show the efficiency of the proposed solution and prove a promising direction of the solution for accomplishing its purposes.Em regiões de confrontos militares, em cenários pós-catástrofes naturais e, inclusive, em grandes áreas de cultivo agrícola, é comum a ausência de uma infra-estrutura préestabelecida de comunicação entre usuários durante a execução de uma ou mais operações eventuais. Nestes casos, Veículos Aéreos Não Tripulados (VANTs) podem ser vistos como uma alternativa para o estabelecimento de uma rede temporária durante essas missões. Para algumas aplicações, a alta mobilidade destes usuários podem trazem grandes desafios para o gerenciamento autônomo de uma estrutura de comunicação aérea, como a organização espacial dos nós roteadores e as políticas de encaminhamento de pacotes adotadas durante a operação. Tendo isso em vista, esse trabalho apresenta o estudo de uma solução que visa o estabelecimento e manutenção das conexões entre os usuários - nos quais executam tarefas individuais ou colaborativas -, através do uso de algoritmos de coordenação de formação - no qual inclui o algoritmo evolucionário Otimização por Enxame de Partículas -, e, também, de conceitos relacionados a Rede Definidas por Software para o gerenciamento da rede. Ainda, é proposto um novo critério de seleção das partículas do algoritmo evolucionário, visando garantir gerenciabilidade das topologias formadas e, consequentemente, a persistência do serviço em caso de falha dos nós roteadores, assim como o cumprimento de especificações desejadas para o desempenho da rede. Simulações em OMNeT++ mostraram a eficácia da proposta e sustentam o modelo proposto a fim de atingir seus objetivos

A Survey on Energy Optimization Techniques in UAV-Based Cellular Networks: From Conventional to Machine Learning Approaches

Wireless communication networks have been witnessing an unprecedented demand due to the increasing number of connected devices and emerging bandwidth-hungry applications. Albeit many competent technologies for capacity enhancement purposes, such as millimeter wave communications and network densification, there is still room and need for further capacity enhancement in wireless communication networks, especially for the cases of unusual people gatherings, such as sport competitions, musical concerts, etc. Unmanned aerial vehicles (UAVs) have been identified as one of the promising options to enhance the capacity due to their easy implementation, pop up fashion operation, and cost-effective nature. The main idea is to deploy base stations on UAVs and operate them as flying base stations, thereby bringing additional capacity to where it is needed. However, because the UAVs mostly have limited energy storage, their energy consumption must be optimized to increase flight time. In this survey, we investigate different energy optimization techniques with a top-level classification in terms of the optimization algorithm employed; conventional and machine learning (ML). Such classification helps understand the state of the art and the current trend in terms of methodology. In this regard, various optimization techniques are identified from the related literature, and they are presented under the above mentioned classes of employed optimization methods. In addition, for the purpose of completeness, we include a brief tutorial on the optimization methods and power supply and charging mechanisms of UAVs. Moreover, novel concepts, such as reflective intelligent surfaces and landing spot optimization, are also covered to capture the latest trend in the literature.Comment: 41 pages, 5 Figures, 6 Tables. Submitted to Open Journal of Communications Society (OJ-COMS