9 research outputs found

    Wireless Sensor Networks for Building Robotic Paths - A Survey of Problems and Restrictions

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    The conjugation of small nodes with sensing, communication and processing capabilities allows for the creation of wireless sensor networks (WSNs). These networks can be deployed to measure a very wide range of environmental phenomena and send data from remote locations back to users. They offer new and exciting possibilities for applications and research. This paper presents the background of WSNs by firstly exploring the different fields applications, with examples for each of these fields, then the challenges faced by these networks in areas such as energy-efficiency, node localization, node deployment, limited storage and routing. It aims at explaining each issue and giving solutions that have been proposed in the research literature. Finally, the paper proposes a practical scenario of deploying a WSN by autonomous robot path construction. The requirements for such a scenario and the open issues that can be tackled by it are exposed, namely the issues of associated with measuring RSSI, the degree of autonomy of the robot and connectivity restoration.The authors would like to acknowledge the company Inspiring Sci, Lda for the interest and valuable contribution to the successful development of this work.info:eu-repo/semantics/publishedVersio

    Survey on Connectivity with Mobile Elements in WSNs

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    节点连通性是无线传感器网络研究的热点问题之一,然而由于节点能量耗尽、硬件故障以及通信链路失效等问题的存在,造成网络分割,因此如何确保网络连通成为; 无线传感器网络亟待解决的关键性问题.近年来,一个新的研究趋势是通过引入计算能力较强且能量较为充足的移动性节点来进行连通控制,提高无线传感器网络的; 整体性能.本文对目前利用移动性节点的主流连通控制方法进行了充分调研,通过对这些方法的详细分类和比较,归纳了移动式连通控制的各类方法的特点,分析了; 这些方法的性能和适用范围,总结了研究中存在的主要问题与挑战,并指出了未来可能的研究方向.The connectivity of sensors is one of the main research problems in; wireless sensor networks (WSNs).Data can be forwarded through connected; sensor nodes.However,becauseof energy depletion,hardware failure and; communication link failure,the network may be partitioned.How to; guarantee the connectivity becomes an urgent issue in wireless sensor; networks.Traditional work usually focuses on maximizing the connectivity; with minimum sensors.In recent years,a new research trend is to utilize; mobile elements for connectivity control.Since the mobile element is; more powerful than normal sensors,it improves the performance of many; aspectsin wireless sensor networks.In this paper,we makea comprehensive; investigation about the current major connectivity control methods with; mobile elements.We first summarize the characteristics of mobile; topology control methods via a new classification.Based on the; classification,these methods are compared to each other according to a; serial parameters.Finally,we analyze the performances and the; application scopes of these methods,summarize the main problems,and; point out the future research directions.国家"九七三"重点基础研究发展计划项目; 国家科技支撑计划项目; 国家自然科学基金项目; 福建省科技计划重点项目; 福建省自然科学基金计划项

    Reinforcement Learning in Self Organizing Cellular Networks

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    Self-organization is a key feature as cellular networks densify and become more heterogeneous, through the additional small cells such as pico and femtocells. Self- organizing networks (SONs) can perform self-configuration, self-optimization, and self-healing. These operations can cover basic tasks such as the configuration of a newly installed base station, resource management, and fault management in the network. In other words, SONs attempt to minimize human intervention where they use measurements from the network to minimize the cost of installation, configuration, and maintenance of the network. In fact, SONs aim to bring two main factors in play: intelligence and autonomous adaptability. One of the main requirements for achieving such goals is to learn from sensory data and signal measurements in networks. Therefore, machine learning techniques can play a major role in processing underutilized sensory data to enhance the performance of SONs. In the first part of this dissertation, we focus on reinforcement learning as a viable approach for learning from signal measurements. We develop a general framework in heterogeneous cellular networks agnostic to the learning approach. We design multiple reward functions and study different effects of the reward function, Markov state model, learning rate, and cooperation methods on the performance of reinforcement learning in cellular networks. Further, we look into the optimality of reinforcement learning solutions and provide insights into how to achieve optimal solutions. In the second part of the dissertation, we propose a novel architecture based on spatial indexing for system-evaluation of heterogeneous 5G cellular networks. We develop an open-source platform based on the proposed architecture that can be used to study large scale directional cellular networks. The proposed platform is used for generating training data sets of accurate signal-to-interference-plus-noise-ratio (SINR) values in millimeter-wave communications for machine learning purposes. Then, with taking advantage of the developed platform, we look into dense millimeter-wave networks as one of the key technologies in 5G cellular networks. We focus on topology management of millimeter-wave backhaul networks and study and provide multiple insights on the evaluation and selection of proper performance metrics in dense millimeter-wave networks. Finally, we finish this part by proposing a self-organizing solution to achieve k-connectivity via reinforcement learning in the topology management of wireless networks

    End-to-End Resilience Mechanisms for Network Transport Protocols

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    The universal reliance on and hence the need for resilience in network communications has been well established. Current transport protocols are designed to provide fixed mechanisms for error remediation (if any), using techniques such as ARQ, and offer little or no adaptability to underlying network conditions, or to different sets of application requirements. The ubiquitous TCP transport protocol makes too many assumptions about underlying layers to provide resilient end-to-end service in all network scenarios, especially those which include significant heterogeneity. Additionally the properties of reliability, performability, availability, dependability, and survivability are not explicitly addressed in the design, so there is no support for resilience. This dissertation presents considerations which must be taken in designing new resilience mechanisms for future transport protocols to meet service requirements in the face of various attacks and challenges. The primary mechanisms addressed include diverse end-to-end paths, and multi-mode operation for changing network conditions

    Resilient scalable internet routing and embedding algorithms

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    Feasibility of wireless mesh for LTE-Advanced small cell access backhaul

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    Mobiilidatan määrä on muutaman viime vuoden aikana kasvanut voimakkaasti ja nykyiset ennustukset arvioivat eksponentiaalista kasvukäyrää tulevien vuosien aikana. Matkapuhelinjärjestelmät ovat kehittyneet nopeasti tämän trendin ohjaamana. Neljännen sukupolven matkapuhelinverkkostandardien myötä, uudet innovaatiot kuten heterogeeniset verkkoratkaisut tarjoavat ratkaisun nykyisiin skaalautuvuus- ja kapasiteettiongelmiin. Joitain ilmeisiä ongelmakohtiakin kuitenkin esiintyy kuten heterogeenisten verkkojen runkokytkennän toteuttaminen. Yksi lupaavimmista tavoista toteuttaa heterogeenisten verkkojen runkokytkentä on langaton ja itseorganisoituva mesh-verkko. Tämän opinnäytetyön tavoitteena on varmistaa ja testata Nokia Siemens Networksin kehittämän mesh-runkokytkentäverkkokonseptin toteutettavuutta ja toiminnallisuutta soveltuvan validointijärjestelmän avulla. Kaiken kaikkiaan validointijärjestelmä ja sen päälle toteutettu mesh-protokolla toimivat moitteettomasti koko kehitys- ja testausprosessin ajan. Konseptin eri ominaisuudet ja mekanismit todistettiin täysin toteutettaviksi ja toimiviksi. Muutamalla lisäominaisuudella ja konseptiparannuksella mesh-konsepti tarjoaa houkuttelevan ja innovatiivisen ratkaisun heterogeenisten verkkojen runkokytkentään tulevaisuudessa.Mobile traffic demands and volumes are increasing and will dramatically keep increasing in the future. Along with this, mobile networks have evolved to better match this growth. Fourth generation cellular network standard introduced a set of new innovations for mobile communications, including support for heterogeneous network deployments. Heterogeneous networking is the likely answer for future mobile data capacity shortage but also poses some challenges, the most evident being how to implement the backhauling. One of the most promising heterogeneous network backhaul solutions is a meshed radio system with self-organizing features. The main scope of this master's thesis is the verification of functionality and feasibility of a wireless mesh backhaul concept developed by Nokia Siemens Networks through a proof-of-concept system. All in all, the wireless mesh proof-of-concept system performed strongly throughout the development and testing process. The different functionalities were proven to work successfully together. With further development and enhancement, the system concept displays extreme potential for a state-of-the-art heterogeneous network backhaul technology

    A Framework to Quantify Network Resilience and Survivability

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    The significance of resilient communication networks in the modern society is well established. Resilience and survivability mechanisms in current networks are limited and domain specific. Subsequently, the evaluation methods are either qualitative assessments or context-specific metrics. There is a need for rigorous quantitative evaluation of network resilience. We propose a service oriented framework to characterize resilience of networks to a number of faults and challenges at any abstraction level. This dissertation presents methods to quantify the operational state and the expected service of the network using functional metrics. We formalize resilience as transitions of the network state in a two-dimensional state space quantifying network characteristics, from which network service performance parameters can be derived. One dimension represents the network as normally operating, partially degraded, or severely degraded. The other dimension represents network service as acceptable, impaired, or unacceptable. Our goal is to initially understand how to characterize network resilience, and ultimately how to guide network design and engineering toward increased resilience. We apply the proposed framework to evaluate the resilience of the various topologies and routing protocols. Furthermore, we present several mechanisms to improve the resilience of the networks to various challenges
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