141 research outputs found
Exploiting the power of multiplicity: a holistic survey of network-layer multipath
The Internet is inherently a multipath network: For an underlying network with only a single path, connecting various nodes would have been debilitatingly fragile. Unfortunately, traditional Internet technologies have been designed around the restrictive assumption of a single working path between a source and a destination. The lack of native multipath support constrains network performance even as the underlying network is richly connected and has redundant multiple paths. Computer networks can exploit the power of multiplicity, through which a diverse collection of paths is resource pooled as a single resource, to unlock the inherent redundancy of the Internet. This opens up a new vista of opportunities, promising increased throughput (through concurrent usage of multiple paths) and increased reliability and fault tolerance (through the use of multiple paths in backup/redundant arrangements). There are many emerging trends in networking that signify that the Internet's future will be multipath, including the use of multipath technology in data center computing; the ready availability of multiple heterogeneous radio interfaces in wireless (such as Wi-Fi and cellular) in wireless devices; ubiquity of mobile devices that are multihomed with heterogeneous access networks; and the development and standardization of multipath transport protocols such as multipath TCP. The aim of this paper is to provide a comprehensive survey of the literature on network-layer multipath solutions. We will present a detailed investigation of two important design issues, namely, the control plane problem of how to compute and select the routes and the data plane problem of how to split the flow on the computed paths. The main contribution of this paper is a systematic articulation of the main design issues in network-layer multipath routing along with a broad-ranging survey of the vast literature on network-layer multipathing. We also highlight open issues and identify directions for future work
Mobile Ad-Hoc Networks
Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of-the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: quality-of-service and video communication, routing protocol and cross-layer design. A few interesting problems about security and delay-tolerant networks are also discussed. This book is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks
A Dynamical Relay Node placement Solution for MANETs
Network deployment in wireless networks implies the distribution of the communication nodes to improve some key operational aspects, such as energy
saving, coverage, connectivity, or simply reducing the network cost. Most
node placement approaches are focused on static scenarios like WSNs, where
the topology of the network does not vary over time. Nevertheless, there exist certain situations in which the network node locations can continuously
change. In this case, the use of special nodes, so-called Relay Nodes (RNs),
contributes to supporting, maintaining or recovering communication in the
network. The present work introduces a multi-stage dynamical RN placement
solution to lead the RNs to their time-varying optimized positions. The approach, named Dynamical Relay Node placement Solution (DRNS), is based
on the use of Particle Swarm Optimization (PSO) algorithms and is inspired
by Model Predictive Control (MPC) techniques following a bi-objective optimization procedure, where both network connectivity and throughput are
jointly maximized. DRNS is validated in both simulated and real environments composed of mobile robotic nodes, the results showing its goodness and operational suitability for real MANET environments
Design and Implementation of Intrusion Detection Systems using RPL and AOVD Protocols-based Wireless Sensor Networks
Wireless Sensor Network (WSN) technology has grown in importance in recent years. All WSN implementations need secure data transmission between sensor nodes and base stations. Sensor node attacks introduce new threats to the WSN. As a result, an appropriate Intrusion Detection System (IDS) is required in WSN for defending against security attacks and detecting attacks on sensor nodes. In this study, we use the Routing Protocol for Low Power and Lossy Networks (RPL) for addressing security services in WSN by identifying IDS with a network size of more or less 20 nodes and introducing 10% malicious nodes. The method described above is used on Cooja in the VMware virtual machine Workstation with the InstantContiki2.7 operating system. To track the movement of nodes, find network attacks, and spot dropped packets during IDS in WSN, an algorithm is implemented in the Network Simulator (NS2) using the Ad-hoc On-Demand Distance Vector (AODV) protocol in the Linux operating system.Keywords—Intrusion Detection Systems, wireless sensor networks, Cooja simulator, sensor nodes, NS
A PROTOCOL SUITE FOR WIRELESS PERSONAL AREA NETWORKS
A Wireless Personal Area Network (WPAN) is an ad hoc network that consists of devices that surround an individual or an object. Bluetooth® technology is especially suitable for formation of WPANs due to the pervasiveness of devices with Bluetooth® chipsets, its operation in the unlicensed Industrial, Scientific, Medical (ISM) frequency band, and its interference resilience. Bluetooth® technology has great potential to become the de facto standard for communication between heterogeneous devices in WPANs.
The piconet, which is the basic Bluetooth® networking unit, utilizes a Master/Slave (MS) configuration that permits only a single master and up to seven active slave devices. This structure limitation prevents Bluetooth® devices from directly participating in larger Mobile Ad Hoc Networks (MANETs) and Wireless Personal Area Networks (WPANs). In order to build larger Bluetooth® topologies, called scatternets, individual piconets must be interconnected. Since each piconet has a unique frequency hopping sequence, piconet interconnections are done by allowing some nodes, called bridges, to participate in more than one piconet. These bridge nodes divide their time between piconets by switching between Frequency Hopping (FH) channels and synchronizing to the piconet\u27s master.
In this dissertation we address scatternet formation, routing, and security to make Bluetooth® scatternet communication feasible. We define criteria for efficient scatternet topologies, describe characteristics of different scatternet topology models as well as compare and contrast their properties, classify existing scatternet formation approaches based on the aforementioned models, and propose a distributed scatternet formation algorithm that efficiently forms a scatternet topology and is resilient to node failures.
We propose a hybrid routing algorithm, using a bridge link agnostic approach, that provides on-demand discovery of destination devices by their address or by the services that devices provide to their peers, by extending the Service Discovery Protocol (SDP) to scatternets.
We also propose a link level security scheme that provides secure communication between adjacent piconet masters, within what we call an Extended Scatternet Neighborhood (ESN)
Artificial intelligence and game theory controlled autonomous UAV swarms
Autonomous unmanned aerial vehicles (UAVs) operating as a swarm can be deployed in austere environments, where cyber electromagnetic activities often require speedy and dynamic adjustments to swarm operations. Use of central controllers, UAV synchronization mechanisms or pre-planned set of actions to control a swarm in such deployments would hinder its ability to deliver expected services. We introduce artificial intelligence and game theory based flight control algorithms to be run by each autonomous UAV to determine its actions in near real-time, while relying only on local spatial, temporal and electromagnetic (EM) information. Each UAV using our flight control algorithms positions itself such that the swarm main-tains mobile ad-hoc network (MANET) connectivity and uniform asset distribution over an area of interest. Typical tasks for swarms using our algorithms include detection, localization and tracking of mobile EM transmitters. We present a formal analysis showing that our algorithms can guide a swarm to maintain a connected MANET, promote a uniform network spread-ing, while avoiding overcrowding with other swarm members. We also prove that they maintain MANET connectivity and, at the same time, they can lead a swarm of autonomous UAVs to follow or avoid an EM transmitter. Simulation experiments in OPNET modeler verify the results of formal analysis that our algorithms are capable of providing an adequate area coverage over a mobile EM source and maintain MANET connectivity. These algorithms are good candidates for civilian and military applications that require agile responses to the changes in dynamic environments for tasks such as detection, localization and tracking mobile EM transmitters
Evolutionary Robot Swarms Under Real-World Constraints
Tese de doutoramento em Engenharia Electrotécnica
e de Computadores, na especialidade de Automação e Robótica, apresentada ao Departamento de Engenharia Electrotécnica e de Computadores da Faculdade de Ciências e Tecnologia da Universidade de CoimbraNas últimas décadas, vários cientistas e engenheiros têm vindo a estudar as estratégias provenientes da natureza. Dentro das arquiteturas biológicas, as sociedades que vivem em enxames revelam que agentes simplistas, tais como formigas ou pássaros, são capazes de realizar tarefas complexas usufruindo de mecanismos de cooperação. Estes sistemas abrangem todas as condições necessárias para a sobrevivência, incorporando comportamentos de cooperação, competição e adaptação. Na “batalha” sem fim em prol do progresso dos mecanismos artificiais desenvolvidos pelo homem, a ciência conseguiu simular o primeiro comportamento em enxame no final dos anos oitenta. Desde então, muitas outras áreas, entre as quais a robótica, beneficiaram de mecanismos de tolerância a falhas inerentes da inteligência coletiva de enxames.
A área de investigação deste estudo incide na robótica de enxame, consistindo num domínio particular dos sistemas robóticos cooperativos que incorpora os mecanismos de inteligência coletiva de enxames na robótica. Mais especificamente, propõe-se uma solução completa de robótica de enxames a ser aplicada em contexto real. Nesta ótica, as operações de busca e salvamento foram consideradas como o caso de estudo principal devido ao nível de complexidade associado às mesmas. Tais operações ocorrem tipicamente em cenários dinâmicos de elevadas dimensões, com condições adversas que colocam em causa a aplicabilidade dos sistemas robóticos cooperativos. Este estudo centra-se nestes problemas, procurando novos desafios que não podem ser ultrapassados através da simples adaptação da literatura da especialidade em algoritmos de enxame, planeamento, controlo e técnicas de tomada de decisão.
As contribuições deste trabalho sustentam-se em torno da extensão do método Particle Swarm Optimization (PSO) aplicado a sistemas robóticos cooperativos, denominado de Robotic Darwinian Particle Swarm Optimization (RDPSO). O RDPSO consiste numa arquitetura robótica de enxame distribuída que beneficia do particionamento dinâmico da população de robôs utilizando mecanismos evolucionários de exclusão social baseados na sobrevivência do mais forte de Darwin. No entanto, apesar de estar assente no caso de estudo do RDPSO, a aplicabilidade dos conceitos aqui propostos não se encontra restrita ao mesmo, visto que todos os algoritmos parametrizáveis de enxame de robôs podem beneficiar de uma abordagem idêntica.
Os fundamentos em torno do RDPSO são introduzidos, focando-se na dinâmica dos robôs, nos constrangimentos introduzidos pelos obstáculos e pela comunicação, e nas suas propriedades evolucionárias. Considerando a colocação inicial dos robôs no ambiente como algo fundamental para aplicar sistemas de enxames em aplicações reais, é assim introduzida uma estratégia de colocação de robôs realista. Para tal, a população de robôs é dividida de forma hierárquica, em que são utilizadas plataformas mais robustas para colocar as plataformas de enxame no cenário de forma autónoma. Após a colocação dos robôs no cenário, é apresentada uma estratégia para permitir a criação e manutenção de uma rede de comunicação móvel ad hoc com tolerância a falhas. Esta estratégia não considera somente a distância entre robôs, mas também a qualidade do nível de sinal rádio frequência, redefinindo assim a sua aplicabilidade em cenários reais. Os aspetos anteriormente mencionados estão sujeitos a uma análise detalhada do sistema de comunicação inerente ao algoritmo, para atingir uma implementação mais escalável do RDPSO a cenários de elevada complexidade. Esta elevada complexidade inerente à dinâmica dos cenários motivaram a ultimar o desenvolvimento do RDPSO, integrando para o efeito um mecanismo adaptativo baseado em informação contextual (e.g., nível de atividade do grupo).
Face a estas considerações, o presente estudo pode contribuir para expandir o estado-da-arte em robótica de enxame com algoritmos inovadores aplicados em contexto real. Neste sentido, todos os métodos propostos foram extensivamente validados e comparados com alternativas, tanto em simulação como com robôs reais. Para além disso, e dadas as limitações destes (e.g., número limitado de robôs, cenários de dimensões limitadas, constrangimentos reais limitados), este trabalho contribui ainda para um maior aprofundamento do estado-da-arte, onde se propõe um modelo macroscópico capaz de capturar a dinâmica inerente ao RDPSO e, até certo ponto, estimar analiticamente o desempenho coletivo dos robôs perante determinada tarefa.
Em suma, esta investigação pode ter aplicabilidade prática ao colmatar a lacuna que se faz sentir no âmbito das estratégias de enxames de robôs em contexto real e, em particular, em cenários de busca e salvamento.Over the past decades, many scientists and engineers have been studying nature’s best and time-tested
patterns and strategies. Within the existing biological architectures, swarm societies revealed that
relatively unsophisticated agents with limited capabilities, such as ants or birds, were able to cooperatively
accomplish complex tasks necessary for their survival. Those simplistic systems embrace all
the conditions necessary to survive, thus embodying cooperative, competitive and adaptive behaviours.
In the never-ending battle to advance artificial manmade mechanisms, computer scientists simulated
the first swarm behaviour designed to mimic the flocking behaviour of birds in the late eighties.
Ever since, many other fields, such as robotics, have benefited from the fault-tolerant mechanism
inherent to swarm intelligence.
The area of research presented in this Ph.D. Thesis focuses on swarm robotics, which is a particular
domain of multi-robot systems (MRS) that embodies the mechanisms of swarm intelligence
into robotics. More specifically, this Thesis proposes a complete swarm robotic solution that can be
applied to real-world missions. Although the proposed methods do not depend on any particular application,
search and rescue (SaR) operations were considered as the main case study due to their
inherent level of complexity. Such operations often occur in highly dynamic and large scenarios, with
harsh and faulty conditions, that pose several problems to MRS applicability. This Thesis focuses on
these problems raising new challenges that cannot be handled appropriately by simple adaptation of
state-of-the-art swarm algorithms, planning, control and decision-making techniques.
The contributions of this Thesis revolve around an extension of the Particle Swarm Optimization
(PSO) to MRS, denoted as Robotic Darwinian Particle Swarm Optimization (RDPSO). The RDPSO
is a distributed swarm robotic architecture that benefits from the dynamical partitioning of the whole
swarm of robots by means of an evolutionary social exclusion mechanism based on Darwin’s survival-of-the-fittest.
Nevertheless, although currently applied solely to the RDPSO case study, the applicability
of all concepts herein proposed is not restricted to it, since all parameterized swarm robotic
algorithms may benefit from a similar approach The RDPSO is then proposed and used to devise the applicability of novel approaches. The fundamentals
around the RDPSO are introduced by focusing on robots’ dynamics, obstacle avoidance,
communication constraints and its evolutionary properties. Afterwards, taking the initial deployment
of robots within the environment as a basis for applying swarm robotics systems into real-world applications,
the development of a realistic deployment strategy is proposed. For that end, the population
of robots is hierarchically divided, wherein larger support platforms autonomously deploy
smaller exploring platforms in the scenario, while considering communication constraints and obstacles.
After the deployment, a way of ensuring a fault-tolerant multi-hop mobile ad hoc communication
network (MANET) is introduced to explicitly exchange information needed in a collaborative realworld
task execution. Such strategy not only considers the maximum communication range between
robots, but also the minimum signal quality, thus refining the applicability to real-world context. This
is naturally followed by a deep analysis of the RDPSO communication system, describing the dynamics
of the communication data packet structure shared between teammates. Such procedure is a
first step to achieving a more scalable implementation by optimizing the communication procedure
between robots. The highly dynamic characteristics of real-world applications motivated us to ultimate
the RDPSO development with an adaptive strategy based on a set of context-based evaluation
metrics.
This thesis contributes to the state-of-the-art in swarm robotics with novel algorithms for realworld
applications. All of the proposed approaches have been extensively validated in benchmarking
tasks, in simulation, and with real robots. On top of that, and due to the limitations inherent to those
(e.g., number of robots, scenario dimensions, real-world constraints), this Thesis further contributes
to the state-of-the-art by proposing a macroscopic model able to capture the RDPSO dynamics and,
to some extent, analytically estimate the collective performance of robots under a certain task. It is
the author’s expectation that this Ph.D. Thesis may shed some light into bridging the reality gap
inherent to the applicability of swarm strategies to real-world scenarios, and in particular to SaR operations.FCT - SFRH/BD /73382/201
Optimal Relay Placement in Multi-hop Wireless Networks
Relay node placement in wireless environments is a research topic recurrently
studied in the specialized literature. A variety of network performance goals,
such as coverage, data rate and network lifetime, are considered as criteria
to lead the placement of the nodes. In this work, a new relay placement approach to maximize network connectivity in a multi-hop wireless network is
presented. Here, connectivity is defined as a combination of inter-node reachability and network throughput. The nodes are placed following a two-step
procedure: (i) initial distribution, and (ii) solution selection. Additionally,
a third stage for placement optimization is optionally proposed to maximize
throughput. This tries to be a general approach for placement, and several
initialization, selection and optimization algorithms can be used in each of
the steps. For experimentation purposes, a leave-one-out selection procedure and a PSO related optimization algorithm are employed and evaluated
for second and third stages, respectively. Other node placement solutions
available in the literature are compared with the proposed one in realistic
simulated scenarios. The results obtained through the properly devised experiments show the improvements achieved by the proposed approach
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