Enabling Disaster Resilient 4G Mobile Communication Networks

The 4G Long Term Evolution (LTE) is the cellular technology expected to outperform the previous generations and to some extent revolutionize the experience of the users by taking advantage of the most advanced radio access techniques (i.e. OFDMA, SC-FDMA, MIMO). However, the strong dependencies between user equipments (UEs), base stations (eNBs) and the Evolved Packet Core (EPC) limit the flexibility, manageability and resiliency in such networks. In case the communication links between UEs-eNB or eNB-EPC are disrupted, UEs are in fact unable to communicate. In this article, we reshape the 4G mobile network to move towards more virtual and distributed architectures for improving disaster resilience, drastically reducing the dependency between UEs, eNBs and EPC. The contribution of this work is twofold. We firstly present the Flexible Management Entity (FME), a distributed entity which leverages on virtualized EPC functionalities in 4G cellular systems. Second, we introduce a simple and novel device-todevice (D2D) communication scheme allowing the UEs in physical proximity to communicate directly without resorting to the coordination with an eNB.Comment: Submitted to IEEE Communications Magazin

Energy Efficient UAV-Assisted Emergency Communication with Reliable Connectivity and Collision Avoidance

Emergency communication is vital for search and rescue operations following natural disasters. Unmanned Aerial Vehicles (UAVs) can significantly assist emergency communication by agile positioning, maintaining connectivity during rapid motion, and relaying critical disaster-related information to Ground Control Stations (GCS). Designing effective routing protocols for relaying crucial data in UAV networks is challenging due to dynamic topology, rapid mobility, and limited UAV resources. This paper presents a novel energy-constrained routing mechanism that ensures connectivity, inter-UAV collision avoidance, and network restoration post-UAV fragmentation while adapting without a predefined UAV path. The proposed method employs improved Q learning to optimize the next-hop node selection. Considering these factors, the paper proposes a novel, Improved Q-learning-based Multi-hop Routing (IQMR) protocol. Simulation results validate IQMRs adaptability to changing system conditions and superiority over QMR, QTAR, and QFANET in energy efficiency and data throughput. IQMR achieves energy consumption efficiency improvements of 32.27%, 36.35%, and 36.35% over QMR, Q-FANET, and QTAR, along with significantly higher data throughput enhancements of 53.3%, 80.35%, and 93.36% over Q-FANET, QMR, and QTAR.Comment: 13 page

INTERFACE MODE ASSIGNMENT METHOD FOR SELF-RECONSTRUCTION OF WIRELESS MESH NETWORKS

The key features of computer networks available for disaster situation is reliable, fault tolerance and self-configurable. Therefore, using wireless mesh network for disaster prevention and recover system has gain much attention from the research community in last decades. In addition, from the practical aspects of the network infrastructures of the disaster system, we should assume the core capabilities such as wireless connectivity in wide range, ease of use, and low cost so on. In this paper, we propose an interface mode assignment method for reconstructing a route from an isolated router to a gateway (GW) router in a wireless mesh network based on IEEE 802.11 infrastructure mode after a disaster occurrance. The proposed method assigns an adequate mode to each interface in an isolated router to recover the network reachability in distributed manner. Simulation results show the effectiveness of the proposed method via two different scenarios

Characterizing Logistics Operations Within a Federal Staging Area for Hurricane Response: A Qualitative Analysis of Federal, State and Local Perspectives

A successful deployment of logistics operations following a disaster is a collective contribution of federal, state, and local entities to ascertain an efficient and effective response. This research analyzes data from interviews with disaster response logistics experts from these entities. The objective is to investigate the information sources and planning processes used in these organizations to plan vehicle routes for critical resource deliveries to impacted areas. Special attention is directed to the impacts of incomplete knowledge of infrastructure status, such as road disruptions due to debris or flooding. Supported by both qualitative and quantitative evidence, the study finds that incomplete knowledge of infrastructure status poses serious critical transportation risks such as delivery delays in disaster relief distribution. This research reveals both similarities and differences in logistical decision-making among these organization types and emphasizes the need for improved information sharing and coordination among emergency response organizations. The findings of this research are expected to guide future initiatives aimed at disaster relief routing thereby enhancing emergency response capabilities and outcomes