Simplified scheduling for underwater acoustic networks

The acoustic propagation speed under water poses significant challenges to the design of underwater sensor networks and their medium access control protocols. Similar to the air, scheduling transmissions under water has significant impact on throughput, energy consumption, and reliability. In this paper we present an extended set of simplified scheduling constraints which allows easy scheduling of underwater acoustic communication. We also present two algorithms for scheduling communications, i.e. a centralized scheduling approach and a distributed scheduling approach. The centralized approach achieves the highest throughput while the distributed approach aims to minimize the computation and communication overhead. We further show how the centralized scheduling approach can be extended with transmission dependencies to reduce the end-to-end delay of packets. We evaluate the performance of the centralized and distributed scheduling approaches using simulation. The centralized approach outperforms the distributed approach in terms of throughput, however we also show the distributed approach has significant benefits in terms of communication and computational overhead required to setup the schedule. We propose a novel way of estimating the performance of scheduling approaches using the ratio of modulation time and propagation delay. We show the performance is largely dictated by this ratio, although the number of links to be scheduled also has a minor impact on the performance

Impact Analysis of Different Scheduling and Retransmission Techniques on an Underwater Routing Protocol

Despite many advances in the area of Underwater Wireless Sensor Networks (UWSN) during the last years, still many challenges need to be successfully tackled before large-scale deployment of underwater sensor networks becomes a reality. UWSNs usually employ acoustic channels for communications, which compared with radio-frequency channels, allow much lower bandwidths and have longer propagation delays. In the past, different methods have been proposed to define how a node must acquire the channel in order to start a transmission. Given the large propagation delays of underwater communication channels, a TDMA-based approach may need big time-guards. On the other hand, the very same large propagation delay increases the occurrence of the hidden terminal problem in a CSMA-based approach. In this paper, impacts of utilization of different scheduling and retransmission techniques on an underwater routing protocol will be analyzed. This analysis, in which energy consumption, packet delay, number of duplicate packets, and packet loss are considered, will be carried out by means of simulation using the Network Simulator 3 and a subset of EDETA (Energy-efficient aDaptive hiErarchical and robusT Architecture) routing protocol recently adapted to UWSN

Contribution to Research on Underwater Sensor Networks Architectures by Means of Simulation

El concepto de entorno inteligente concibe un mundo donde los diferentes tipos de dispositivos inteligentes colaboran para conseguir un objetivo común. En este concepto, inteligencia hace referencia a la habilidad de adquirir conocimiento y aplicarlo de forma autónoma para conseguir el objetivo común, mientras que entorno hace referencia al mundo físico que nos rodea. Por tanto, un entorno inteligente se puede definir como aquel que adquiere conocimiento de su entorno y aplicándolo permite mejorar la experiencia de sus habitantes. La computación ubicua o generalizada permitirá que este concepto de entorno inteligente se haga realidad. Normalmente, el término de computación ubicua hace referencia al uso de dispositivos distribuidos por el mundo físico, pequeños y de bajo precio, que pueden comunicarse entre ellos y resolver un problema de forma colaborativa. Cuando esta comunicación se lleva a cabo de forma inalámbrica, estos dispositivos forman una red de sensores inalámbrica o en inglés, Wireless Sensor Network (WSN). Estas redes están atrayendo cada vez más atención debido al amplio espectro de aplicaciones que tienen, des de soluciones para el ámbito militar hasta aplicaciones para el gran consumo. Esta tesis se centra en las redes de sensores inalámbricas y subacuáticas o en inglés, Underwater Wireless Sensor Networks (UWSN). Estas redes, a pesar de compartir los mismos principios que las WSN, tienen un medio de transmisión diferente que cambia su forma de comunicación de ondas de radio a ondas acústicas. Este cambio hace que ambas redes sean diferentes en muchos aspectos como el retardo de propagación, el ancho de banda disponible, el consumo de energía, etc. De hecho, las señales acústicas tienen una velocidad de propagación cinco órdenes de magnitud menor que las señales de radio. Por tanto, muchos algoritmos y protocolos necesitan adaptarse o incluso rediseñarse. Como el despliegue de este tipo de redes puede ser bastante complicado y caro, se debe planificar de forma precisa el hardware y los algoritmos que se necesitan. Con esta finalidad, las simulaciones pueden resultar una forma muy conveniente de probar todas las variables necesarias antes del despliegue de la aplicación. A pesar de eso, un nivel de precisión adecuado que permita extraer resultados y conclusiones confiables, solamente se puede conseguir utilizando modelos precisos y parámetros reales. Esta tesis propone un ecosistema para UWSN basado en herramientas libres y de código abierto. Este ecosistema se compone de un modelo de recolección de energía y unmodelo de unmódemde bajo coste y bajo consumo con un sistema de activación remota que, junto con otros modelos ya implementados en las herramientas, permite la realización de simulaciones precisas con datos ambientales del tiempo y de las condiciones marinas del lugar donde la aplicación objeto de estudio va a desplegarse. Seguidamente, este ecosistema se utiliza con éxito en el estudio y evaluación de diferentes protocolos de transmisión aplicados a una aplicación real de monitorización de una piscifactoría en la costa del mar Mediterráneo, que es parte de un proyecto de investigación español (CICYT CTM2011-2961-C02-01). Finalmente, utilizando el modelo de recolección de energía, esta plataforma de simulación se utiliza para medir los requisitos de energía de la aplicación y extraer las necesidades de hardware mínimas.Climent Bayarri, JS. (2014). Contribution to Research on Underwater Sensor Networks Architectures by Means of Simulation [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/3532

MAC/Routing design for under water sensor networks

The huge advances in communication technologies and Micro Electrical and Mechanical Systems (MEMS) have triggered a revolution in sensor networks. One major application of sensor networks is in the investigation of complex and uninhabited under water surfaces; such sensor networks are called the Underwater Wireless Sensor Networks (UWSN). UWSN comprises of a number of sensors which are submerged in water and one or several surface stations or a sinks at which the sensed data is collected. In some underwater sensor applications, autonomous underwater vehicles (AUVs) could be used. The underwater sensor nodes communicate with each other using acoustic signals. Applications for this type of networks include oceanographic data collection, pollution monitoring, offshore exploration and tactical surveillance applications. The novel networking paradigm of UWSN is facing a totally different operating environment than the ground based wireless sensor networks. This introduces new challenges such as huge propagation delays, and limited acoustic link capacity with high attenuation factors. These new challenges have their own impact on the design of most of the networking layers preventing researchers from using the same layers used for other networks. The most affected layers are the Physical, Medium Access Control (MAC), Routing and Transport layers. This work will introduce novel routing and MAC layers’ protocols for UWSNs. The routing protocol will adopt the minimum spanning tree algorithm and focus on maximizing the connectivity of the network, which means maximizing the total number of nodes connected to the root or the sink in this case. The protocol will try also to provide a minimum hop connection for all the nodes in the network taking into account the residual energy, location information and number of children at the next hop node. The other contribution of this work is a MAC Protocol which will incorporate the topology information provided by the routing protocol to minimize the collisions and energy wastage in data transmission. The MAC Protocol will also try to shorten the queuing delays at the intermediate nodes for a message traveling from source to the sink. A comparison will be conducted with other existing routing and MAC protocols. The routing protocol will be tested and compared with the E-Span spanning tree algorithm for data aggregation. The MAC protocol will be compared with Park\u27s protocol proposed in [2] in terms of performance metrics like end-to-end delay and the number of collisions. We will also explore the ability of the proposed protocols to enhance the life span of the network

Rate Region of Scheduling a Wireless Network with Discrete Propagation Delays

We study wireless networks where signal propagation delays are multiples of a time interval. Such a network can be modelled as a weighted hypergraph. The link scheduling problem of such a wireless network is closely related to the independent sets of the periodic hypergraph induced by the weighted hypergraph. As the periodic graph has infinitely many vertices, existing characterizations of graph independent sets cannot be applied to study link scheduling efficiently. To characterize the rate region of link scheduling, a directed graph of finite size called scheduling graph is derived to capture a certain conditional independence property of link scheduling over time. A collision-free schedule is equivalent to a path in the scheduling graph, and hence the rate region is equivalent to the convex hull of the rate vectors associated with the cycles of the scheduling graph. With the maximum independent set problem as a special case, calculating the whole rate region is NP hard and also hard to approximate. We derive two algorithms that benefit from a partial order on the paths in the scheduling graph, and can potentially find schedules that are not dominated by the existing cycle enumerating algorithms running in a given time. The first algorithm calculates the rate region incrementally in the cycle lengths so that a subset of the rate region corresponding to short cycles can be obtained efficiently. The second algorithm enumerates cycles associated with a maximal subgraph of the scheduling graph. In addition to scheduling a wireless network, the independent sets of periodic hypergraphs also find applications in some operational research problems.Comment: This paper was presented in part at INFOCOM 202

Effective Medium Access Control for Underwater Acoustic Sensor Networks

This work is concerned with the design, analysis and development of effective Medium Access Control (MAC) protocols for Underwater Acoustic Sensor Networks (UASNs). The use of acoustic waves underwater places time-variant channel constraints on the functionality of MAC protocols. The contrast between traffic characteristics of the wide-ranging applications of UASNs makes it hard to design a single MAC protocol that can be adaptive to various applications. This thesis proposes MAC solutions that can meet the environmental and non-environmental challenges posed underwater. Scheduling-based schemes are the most common MAC solutions for UASNs, but scheduling is also challenging in such a dynamic environment. The preferable way of synchronisation underwater is the use of a global scheduler, guard intervals and exchange of timing signals. To this end, single-hop topologies suit UASN applications very well. The Combined Free and Demand Assignment Multiple Access (CFDAMA) is a centralised, scheduling-based MAC protocol demonstrating simplicity and adaptability to the time-variant channel and traffic characteristics. It is shown to minimise end-to-end delay, maximise channel utilisation and maintain fairness amongst nodes. This thesis primarily introduces two novel robust MAC solutions for UASNs, namely CFDAMA with Systematic Round Robin and CFDAMA without clock synchronisation (CFDAMA-NoClock). The former scheme is more suitable for large-scale and widely-spread UASNs, whereas the latter is a more feasible MAC solution when synchronisation amongst node clocks cannot be attained. Both analytical and comprehensive event-driven Riverbed simulations of underwater scenarios selected based on realistic sensor deployments show that the two protocols make it possible to load the channel up to higher levels of its capacity with controlled delay performance superior to that achievable with the traditional CFDAMA schemes. The new scheduling features make the CFDAMA-NoClock scheme a very feasible networking solution for robust and efficient UASN deployments in the real world

Cooperative localisation in underwater robotic swarms for ocean bottom seismic imaging.

Spatial information must be collected alongside the data modality of interest in wide variety of sub-sea applications, such as deep sea exploration, environmental monitoring, geological and ecological research, and samples collection. Ocean-bottom seismic surveys are vital for oil and gas exploration, and for productivity enhancement of an existing production facility. Ocean-bottom seismic sensors are deployed on the seabed to acquire those surveys. Node deployment methods used in industry today are costly, time-consuming and unusable in deep oceans. This study proposes the autonomous deployment of ocean-bottom seismic nodes, implemented by a swarm of Autonomous Underwater Vehicles (AUVs). In autonomous deployment of ocean-bottom seismic nodes, a swarm of sensor-equipped AUVs are deployed to achieve ocean-bottom seismic imaging through collaboration and communication. However, the severely limited bandwidth of underwater acoustic communications and the high cost of maritime assets limit the number of AUVs that can be deployed for experiments. A holistic fuzzy-based localisation framework for large underwater robotic swarms (i.e. with hundreds of AUVs) to dynamically fuse multiple position estimates of an autonomous underwater vehicle is proposed. Simplicity, exibility and scalability are the main three advantages inherent in the proposed localisation framework, when compared to other traditional and commonly adopted underwater localisation methods, such as the Extended Kalman Filter. The proposed fuzzy-based localisation algorithm improves the entire swarm mean localisation error and standard deviation (by 16.53% and 35.17% respectively) at a swarm size of 150 AUVs when compared to the Extended Kalman Filter based localisation with round-robin scheduling. The proposed fuzzy based localisation method requires fuzzy rules and fuzzy set parameters tuning, if the deployment scenario is changed. Therefore a cooperative localisation scheme that relies on a scalar localisation confidence value is proposed. A swarm subset is navigationally aided by ultra-short baseline and a swarm subset (i.e. navigation beacons) is configured to broadcast navigation aids (i.e. range-only), once their confidence values are higher than a predetermined confidence threshold. The confidence value and navigation beacons subset size are two key parameters for the proposed algorithm, so that they are optimised using the evolutionary multi-objective optimisation algorithm NSGA-II to enhance its localisation performance. Confidence value-based localisation is proposed to control the cooperation dynamics among the swarm agents, in terms of aiding acoustic exteroceptive sensors. Given the error characteristics of a commercially available ultra-short baseline system and the covariance matrix of a trilaterated underwater vehicle position, dead reckoning navigation - aided by Extended Kalman Filter-based acoustic exteroceptive sensors - is performed and controlled by the vehicle's confidence value. The proposed confidence-based localisation algorithm has significantly improved the entire swarm mean localisation error when compared to the fuzzy-based and round-robin Extended Kalman Filter-based localisation methods (by 67.10% and 59.28% respectively, at a swarm size of 150 AUVs). The proposed fuzzy-based and confidence-based localisation algorithms for cooperative underwater robotic swarms are validated on a co-simulation platform. A physics-based co-simulation platform that considers an environment's hydrodynamics, industrial grade inertial measurement unit and underwater acoustic communications characteristics is implemented for validation and optimisation purposes