107 research outputs found

    Reliable & Efficient Data Centric Storage for Data Management in Wireless Sensor Networks

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    Wireless Sensor Networks (WSNs) have become a mature technology aimed at performing environmental monitoring and data collection. Nonetheless, harnessing the power of a WSN presents a number of research challenges. WSN application developers have to deal both with the business logic of the application and with WSN's issues, such as those related to networking (routing), storage, and transport. A middleware can cope with this emerging complexity, and can provide the necessary abstractions for the definition, creation and maintenance of applications. The final goal of most WSN applications is to gather data from the environment, and to transport such data to the user applications, that usually resides outside the WSN. Techniques for data collection can be based on external storage, local storage and in-network storage. External storage sends data to the sink (a centralized data collector that provides data to the users through other networks) as soon as they are collected. This paradigm implies the continuous presence of a sink in the WSN, and data can hardly be pre-processed before sent to the sink. Moreover, these transport mechanisms create an hotspot on the sensors around the sink. Local storage stores data on a set of sensors that depends on the identity of the sensor collecting them, and implies that requests for data must be broadcast to all the sensors, since the sink can hardly know in advance the identity of the sensors that collected the data the sink is interested in. In-network storage and in particular Data Centric Storage (DCS) stores data on a set of sensors that depend on a meta-datum describing the data. DCS is a paradigm that is promising for Data Management in WSNs, since it addresses the problem of scalability (DCS employs unicast communications to manage WSNs), allows in-network data preprocessing and can mitigate hot-spots insurgence. This thesis studies the use of DCS for Data Management in middleware for WSNs. Since WSNs can feature different paradigms for data routing (geographical routing and more traditional tree routing), this thesis introduces two different DCS protocols for these two different kinds of WNSs. Q-NiGHT is based on geographical routing and it can manage the quantity of resources that are assigned to the storage of different meta-data, and implements a load balance for the data storage over the sensors in the WSN. Z-DaSt is built on top of ZigBee networks, and exploits the standard ZigBee mechanisms to harness the power of ZigBee routing protocol and network formation mechanisms. Dependability is another issue that was subject to research work. Most current approaches employ replication as the mean to ensure data availability. A possible enhancement is the use of erasure coding to improve the persistence of data while saving on memory usage on the sensors. Finally, erasure coding was applied also to gossiping algorithms, to realize an efficient data management. The technique is compared to the state-of-the-art to identify the benefits it can provide to data collection algorithms and to data availability techniques

    Distributed Communication in Swarms of Autonomous Underwater Vehicles

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    Effective communication mechanisms are a key requirement for schools of submersible robots and their meaningful deployment. Large schools of identical submersibles require a fully distributed communication system which scales well and optimises for ”many-to-many” communication (omnicast, also known as gossiping). As an additional constraint, communication channels under water are typically very low bandwidth and short range. This thesis discusses possible electric and electro-magnetic wireless communication channels suitable for underwater environments. Theoretical findings on the omnicast communication problem are presented, as well as the implementation of a distributed time division multiple access (TDMA) scheduling algorithm in simulation and in hardware. It is shown theoretically and in simulation that short range links in a robotic swarm are actually an advantage, compared to links that cover large parts of the network. Experiments were carried out on custom-developed digital long-wave radio and optical link modules. The results of the experiments are used to revisit the initial assumptions on communication in multi-hop wireless networks

    EFFICIENT DYNAMIC ADDRESSING BASED ROUTING FOR UNDERWATER WIRELESS SENSOR NETWORKS

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    This thesis presents a study about the problem of data gathering in the inhospitable underwater environment. Besides long propagation delays and high error probability, continuous node movement also makes it difficult to manage the routing information during the process of data forwarding. In order to overcome the problem of large propagation delays and unreliable link quality, many algorithms have been proposed and some of them provide good solutions for these issues, yet continuous node movements still need attention. Considering the node mobility as a challenging task, a distributed routing scheme called Hop-by-Hop Dynamic Addressing Based (H2- DAB) routing protocol is proposed where every node in the network will be assigned a routable address quickly and efficiently without any explicit configuration or any dimensional location information. According to our best knowledge, H2-DAB is first addressing based routing approach for underwater wireless sensor networks (UWSNs) and not only has it helped to choose the routing path faster but also efficiently enables a recovery procedure in case of smooth forwarding failure. The proposed scheme provides an option where nodes is able to communicate without any centralized infrastructure, and a mechanism furthermore is available where nodes can come and leave the network without having any serious effect on the rest of the network. Moreover, another serious issue in UWSNs is that acoustic links are subject to high transmission power with high channel impairments that result in higher error rates and temporary path losses, which accordingly restrict the efficiency of these networks. The limited resources have made it difficult to design a protocol which is capable of maximizing the reliability of these networks. For this purpose, a Two-Hop Acknowledgement (2H-ACK) reliability model where two copies of the same data packet are maintained in the network without extra burden on the available resources is proposed. Simulation results show that H2-DAB can easily manage during the quick routing changes where node movements are very frequent yet it requires little or no overhead to efficiently complete its tasks

    Consortium for Robotics and Unmanned Systems Education and Research (CRUSER) 2019 Annual Report

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    Prepared for: Dr. Brian Bingham, CRUSER DirectorThe Naval Postgraduate School (NPS) Consortium for Robotics and Unmanned Systems Education and Research (CRUSER) provides a collaborative environment and community of interest for the advancement of unmanned systems (UxS) education and research endeavors across the Navy (USN), Marine Corps (USMC) and Department of Defense (DoD). CRUSER is a Secretary of the Navy (SECNAV) initiative to build an inclusive community of interest on the application of unmanned systems (UxS) in military and naval operations. This 2019 annual report summarizes CRUSER activities in its eighth year of operations and highlights future plans.Deputy Undersecretary of the Navy PPOIOffice of Naval Research (ONR)Approved for public release; distribution is unlimited

    Consortium for Robotics and Unmanned Systems Education and Research (CRUSER) 2019 Annual Report

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    Prepared for: Dr. Brian Bingham, CRUSER DirectorThe Naval Postgraduate School (NPS) Consortium for Robotics and Unmanned Systems Education and Research (CRUSER) provides a collaborative environment and community of interest for the advancement of unmanned systems (UxS) education and research endeavors across the Navy (USN), Marine Corps (USMC) and Department of Defense (DoD). CRUSER is a Secretary of the Navy (SECNAV) initiative to build an inclusive community of interest on the application of unmanned systems (UxS) in military and naval operations. This 2019 annual report summarizes CRUSER activities in its eighth year of operations and highlights future plans.Deputy Undersecretary of the Navy PPOIOffice of Naval Research (ONR)Approved for public release; distribution is unlimited

    High-Performance Modelling and Simulation for Big Data Applications

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    This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

    Reference Model for Interoperability of Autonomous Systems

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    This thesis proposes a reference model to describe the components of an Un-manned Air, Ground, Surface, or Underwater System (UxS), and the use of a single Interoperability Building Block to command, control, and get feedback from such vehicles. The importance and advantages of such a reference model, with a standard nomenclature and taxonomy, is shown. We overview the concepts of interoperability and some efforts to achieve common refer-ence models in other areas. We then present an overview of existing un-manned systems, their history, characteristics, classification, and missions. The concept of Interoperability Building Blocks (IBB) is introduced to describe standards, protocols, data models, and frameworks, and a large set of these are analyzed. A new and powerful reference model for UxS, named RAMP, is proposed, that describes the various components that a UxS may have. It is a hierarchical model with four levels, that describes the vehicle components, the datalink, and the ground segment. The reference model is validated by showing how it can be applied in various projects the author worked on. An example is given on how a single standard was capable of controlling a set of heterogeneous UAVs, USVs, and UGVs

    High-Performance Modelling and Simulation for Big Data Applications

    Get PDF
    This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

    Aerial Base Station Deployment for Post-Disaster Public Safety Applications

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    Earthquakes and floods are constant threats to most of the countries in the world. After such catastrophes, a rapid response is needed, which includes communications not only for first responders but also for local civilians. Even though there are technologies and specialized personnel for rapid deployment, it is common that external factors will hinder the arrival of help while communication requirements are urgently required. Such communication technologies would aid tasks regarding organization and information dissemination from authorities to the civilians and vice-versa. This necessity is due to protocols and applications to allocate the number of emergency resources per location and to locate missing people. In this thesis, we investigate the deployment problem of Mobile Aerial Base Stations (MABS). Our main objective is to ensure periodic wireless communication for geographically spread User Equipment (UE) based on LTE technology. First, we establish a precedent of emergency situations where MABS would be useful. We also provide an introduction to the study and work conducted in this thesis. Second, we provide a literature review of existing solutions was made to determine the advantages and disadvantages of certain technologies regarding the described necessity. Third, we determine how MABS, such as gliders or light tactical balloons that are assumed to be moving at an average speed of 50 km/h, will be deployed. These MABS would visit different cluster centroids determined by an Affinity Propagation Clustering algorithm. Additionally, a combination of graph theory and Genetic Algorithm (GA) is implemented through mutators and fitness functions to obtain best flyable paths through an evolution pool of 100. Additionally, Poisson, Normal, and Uniform distributions are utilized to determine the amount of Base Stations and UEs. Then, for every distribution combination, a set of simulations is conducted to obtain the best flyable paths. Serviced UE performance indicators of algorithm efficiency are analyzed to determine whether the applied algorithm is effective in providing a solution to the presented problem. Finally, in Chapter 5, we conclude our work by supporting that the proposed model would suffice the needs of mobile users given the proposed emergency scenario. Adviser: Yi Qia
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