Planning UAV Activities for Efficient User Coverage in Disaster Areas

Climate changes brought about by global warming as well as man-made environmental changes are often the cause of sever natural disasters. ICT, which is itself responsible for global warming due to its high carbon footprint, can play a role in alleviating the consequences of such hazards by providing reliable, resilient means of communication during a disaster crisis. In this paper, we explore the provision of wireless coverage through UAVs (Unmanned Aerial Vehicles) to complement, or replace, the traditional communication infrastructure. The use of UAVs is indeed crucial in emergency scenarios, as they allow for the quick and easy deployment of micro and pico cellular base stations where needed. We characterize the movements of UAVs and define an optimization problem to determine the best UAV coverage that maximizes the user throughput, while maintaining fairness across the different parts of the geographical area that has been affected by the disaster. To evaluate our strategy, we simulate a flooding in San Francisco and the car traffic resulting from people seeking safety on higher ground

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Design of Ad Hoc Wireless Mesh Networks Formed by Unmanned Aerial Vehicles with Advanced Mechanical Automation

Ad hoc wireless mesh networks formed by unmanned aerial vehicles (UAVs) equipped with wireless transceivers (access points (APs)) are increasingly being touted as being able to provide a flexible "on-the-fly" communications infrastructure that can collect and transmit sensor data from sensors in remote, wilderness, or disaster-hit areas. Recent advances in the mechanical automation of UAVs have resulted in separable APs and replaceable batteries that can be carried by UAVs and placed at arbitrary locations in the field. These advanced mechanized UAV mesh networks pose interesting questions in terms of the design of the network architecture and the optimal UAV scheduling algorithms. This paper studies a range of network architectures that depend on the mechanized automation (AP separation and battery replacement) capabilities of UAVs and proposes heuristic UAV scheduling algorithms for each network architecture, which are benchmarked against optimal designs.Comment: 12 page

A Survey on the Various Frameworks Available for Re-Energizing Wireless Senor Networks

Wireless Sensor Networks (WSNs) are finding its applications in different scenarios in our day to day life. However a major problem that our current technology faces these days is the lack of technical knowledge of how these networks can be kept up and functioning to an efficient level. The power consumption and replenishment of these sensors that are deployed in the environment to be monitored has been a challenging factor since decades. Researches on the improvements in the efficiency in the power consumption of WSNs have been going on for quite a while. Premature energy depletion and outdated recharging strategies are some of the major research areas that require improvement in WSNs. In this paper we enumerate the existing technologies and new proposals on the different frameworks that have been designed to enhance the efficiency in recharging Sensors deployed in WSNs. DOI: 10.17762/ijritcc2321-8169.150311

ORNEV: Optimized Recharging of Wireless Sensor Networks using Virtual Base Stations

Several recharging methodologies and frameworks have been proposed for recharging wireless sensor networks. In this paper we study these propositions and device a method that would enhance the recharging capability of the framework and keep the network up and running without the energy getting depleted. We explore a new dimension where we use the SenCars used for charging a node to transmit data just like a node in the WSN. The SenCar acts like a virtual base station for a node that carries high traffic that it will be charging. This cuts down transmission of data through nodes that connects the high traffic node with the base station thereby moving them to sleep mode. This SenCar then directly transmits traffic information from the node it is charging to the base station using cellular technology. DOI: 10.17762/ijritcc2321-8169.150712

Information distribution and recharging dispatch strategy in large wireless networks

Large wireless networks are envisioned to play increasingly important roles as more and more mobile wireless devices and Internet of Things (IoT) devices are put in use. In these networks, it is often the case that some critical information needs to be readily accessible, requiring a careful design of the information distribution technique. In this work, we at first propose PeB, Periodic Broadcast, that takes advantage of periodic broadcast from the information server(s) to leave traces for nodes requesting for the information while maintaining a low overhead. Similar to swarm intelligence, PeB requires each node to keep track of traces, or past records of information flow, through itself toward information servers. We present our extensive investigation of the PeB scheme on cost and network dynamics as compared to other state-of-the-art techniques. When the devices run out of battery, they become static and need to be recharged by the wireless charging vehicles (WCVs). Often times, WCV receives a number of charging requests and form a Hamiltonian cycle and visit these nodes one-by-one. We also propose a heuristic algorithm, termed Quad, that generates a Hamiltonian cycle in a square plane. We then focus on the theoretical study of the length of the Hamiltonian cycles in such networks

A Survey on Mobile Charging Techniques in Wireless Rechargeable Sensor Networks

The recent breakthrough in wireless power transfer (WPT) technology has empowered wireless rechargeable sensor networks (WRSNs) by facilitating stable and continuous energy supply to sensors through mobile chargers (MCs). A plethora of studies have been carried out over the last decade in this regard. However, no comprehensive survey exists to compile the state-of-the-art literature and provide insight into future research directions. To fill this gap, we put forward a detailed survey on mobile charging techniques (MCTs) in WRSNs. In particular, we first describe the network model, various WPT techniques with empirical models, system design issues and performance metrics concerning the MCTs. Next, we introduce an exhaustive taxonomy of the MCTs based on various design attributes and then review the literature by categorizing it into periodic and on-demand charging techniques. In addition, we compare the state-of-the-art MCTs in terms of objectives, constraints, solution approaches, charging options, design issues, performance metrics, evaluation methods, and limitations. Finally, we highlight some potential directions for future research

Adaptive wireless power transfer in mobile ad hoc networks

We investigate the interesting impact of mobility on the problem of efficient wireless power transfer in ad hoc networks. We consider a set of mobile agents (consuming energy to perform certain sensing and communication tasks), and a single static charger (with finite energy) which can recharge the agents when they get in its range. In particular, we focus on the problem of efficiently computing the appropriate range of the charger with the goal of prolonging the network lifetime. We first demonstrate (under the realistic assumption of fixed energy supplies) the limitations of any fixed charging range and, therefore, the need for (and power of) a dynamic selection of the charging range, by adapting to the behavior of the mobile agents which is revealed in an online manner. We investigate the complexity of optimizing the selection of such an adaptive charging range, by showing that two simplified offline optimization problems (closely related to the online one) are NP-hard. To effectively address the involved performance trade-offs, we finally present a variety of adaptive heuristics, assuming different levels of agent information regarding their mobility and energy