4,697 research outputs found
Decentralized Connectivity-Preserving Deployment of Large-Scale Robot Swarms
We present a decentralized and scalable approach for deployment of a robot
swarm. Our approach tackles scenarios in which the swarm must reach multiple
spatially distributed targets, and enforce the constraint that the robot
network cannot be split. The basic idea behind our work is to construct a
logical tree topology over the physical network formed by the robots. The
logical tree acts as a backbone used by robots to enforce connectivity
constraints. We study and compare two algorithms to form the logical tree:
outwards and inwards. These algorithms differ in the order in which the robots
join the tree: the outwards algorithm starts at the tree root and grows towards
the targets, while the inwards algorithm proceeds in the opposite manner. Both
algorithms perform periodic reconfiguration, to prevent suboptimal topologies
from halting the growth of the tree. Our contributions are (i) The formulation
of the two algorithms; (ii) A comparison of the algorithms in extensive
physics-based simulations; (iii) A validation of our findings through
real-robot experiments.Comment: 8 pages, 8 figures, submitted to IROS 201
Simultaneous deployment and tracking multi-robot strategies with connectivity maintenance
Multi-robot teams composed of ground and aerial vehicles have gained attention during the last few years. We present a scenario where both types of robots must monitor the same area from different view points. In this paper, we propose two Lloyd-based tracking strategies to allow the ground robots (agents) to follow the aerial ones (targets), keeping the connectivity between the agents. The first strategy establishes density functions on the environment so that the targets acquire more importance than other zones, while the second one iteratively modifies the virtual limits of the working area depending on the positions of the targets. We consider the connectivity maintenance due to the fact that coverage tasks tend to spread the agents as much as possible, which is addressed by restricting their motions so that they keep the links of a minimum spanning tree of the communication graph. We provide a thorough parametric study of the performance of the proposed strategies under several simulated scenarios. In addition, the methods are implemented and tested using realistic robotic simulation environments and real experiments
Simultaneous Deployment and Tracking Multi-Robot Strategies with Connectivity Maintenance
Multi robot teams composed by ground and aerial vehicles have gained
attention during the last years. We present a scenario where both types of
robots must monitor the same area from different view points. In this paper we
propose two Lloyd-based tracking strategies to allow the ground robots (agents)
follow the aerial ones (targets), keeping the connectivity between the agents.
The first strategy establishes density functions on the environment so that the
targets acquire more importance than other zones, while the second one
iteratively modifies the virtual limits of the working area depending on the
positions of the targets. We consider the connectivity maintenance due to the
fact that coverage tasks tend to spread the agents as much as possible, which
is addressed by restricting their motions so that they keep the links of a
Minimum Spanning Tree of the communication graph. We provide a thorough
parametric study of the performance of the proposed strategies under several
simulated scenarios. In addition, the methods are implemented and tested using
realistic robotic simulation environments and real experiments
Overlapping Multi-hop Clustering for Wireless Sensor Networks
Clustering is a standard approach for achieving efficient and scalable
performance in wireless sensor networks. Traditionally, clustering algorithms
aim at generating a number of disjoint clusters that satisfy some criteria. In
this paper, we formulate a novel clustering problem that aims at generating
overlapping multi-hop clusters. Overlapping clusters are useful in many sensor
network applications, including inter-cluster routing, node localization, and
time synchronization protocols. We also propose a randomized, distributed
multi-hop clustering algorithm (KOCA) for solving the overlapping clustering
problem. KOCA aims at generating connected overlapping clusters that cover the
entire sensor network with a specific average overlapping degree. Through
analysis and simulation experiments we show how to select the different values
of the parameters to achieve the clustering process objectives. Moreover, the
results show that KOCA produces approximately equal-sized clusters, which
allows distributing the load evenly over different clusters. In addition, KOCA
is scalable; the clustering formation terminates in a constant time regardless
of the network size
PADS: Practical Attestation for Highly Dynamic Swarm Topologies
Remote attestation protocols are widely used to detect device configuration
(e.g., software and/or data) compromise in Internet of Things (IoT) scenarios.
Unfortunately, the performances of such protocols are unsatisfactory when
dealing with thousands of smart devices. Recently, researchers are focusing on
addressing this limitation. The approach is to run attestation in a collective
way, with the goal of reducing computation and communication. Despite these
advances, current solutions for attestation are still unsatisfactory because of
their complex management and strict assumptions concerning the topology (e.g.,
being time invariant or maintaining a fixed topology). In this paper, we
propose PADS, a secure, efficient, and practical protocol for attesting
potentially large networks of smart devices with unstructured or dynamic
topologies. PADS builds upon the recent concept of non-interactive attestation,
by reducing the collective attestation problem into a minimum consensus one. We
compare PADS with a state-of-the art collective attestation protocol and
validate it by using realistic simulations that show practicality and
efficiency. The results confirm the suitability of PADS for low-end devices,
and highly unstructured networks.Comment: Submitted to ESORICS 201
On Mobility Management in Multi-Sink Sensor Networks for Geocasting of Queries
In order to efficiently deal with location dependent messages in multi-sink wireless sensor networks (WSNs), it is key that the network informs sinks what geographical area is covered by which sink. The sinks are then able to efficiently route messages which are only valid in particular regions of the deployment. In our previous work (see the 5th and 6th cited documents), we proposed a combined coverage area reporting and geographical routing protocol for location dependent messages, for example, queries that are injected by sinks. In this paper, we study the case where we have static sinks and mobile sensor nodes in the network. To provide up-to-date coverage areas to sinks, we focus on handling node mobility in the network. We discuss what is a better method for updating the routing structure (i.e., routing trees and coverage areas) to handle mobility efficiently: periodic global updates initiated from sinks or local updates triggered by mobile sensors. Simulation results show that local updating perform very well in terms of query delivery ratio. Local updating has a better scalability to increasing network size. It is also more energy efficient than ourpreviously proposed approach, where global updating in networks have medium mobility rate and speed
Behavior Mixing with Minimum Global and Subgroup Connectivity Maintenance for Large-Scale Multi-Robot Systems
In many cases the multi-robot systems are desired to execute simultaneously
multiple behaviors with different controllers, and sequences of behaviors in
real time, which we call \textit{behavior mixing}. Behavior mixing is
accomplished when different subgroups of the overall robot team change their
controllers to collectively achieve given tasks while maintaining connectivity
within and across subgroups in one connected communication graph. In this
paper, we present a provably minimum connectivity maintenance framework to
ensure the subgroups and overall robot team stay connected at all times while
providing the highest freedom for behavior mixing. In particular, we propose a
real-time distributed Minimum Connectivity Constraint Spanning Tree (MCCST)
algorithm to select the minimum inter-robot connectivity constraints preserving
subgroup and global connectivity that are \textit{least likely to be violated}
by the original controllers. With the employed safety and connectivity barrier
certificates for the activated connectivity constraints and collision
avoidance, the behavior mixing controllers are thus minimally modified from the
original controllers. We demonstrate the effectiveness and scalability of our
approach via simulations of up to 100 robots with multiple behaviors.Comment: To appear in Proceedings of IEEE International Conference on Robotics
and Automation (ICRA) 202
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Graph-theoretic channel modeling and topology control protocols for wireless sensor networks
This report addresses two different research problems: (i) It presents a wireless channel model that reduces the complexity associated with high order Markov chains; and (ii) presents energy efficient topology control protocols which provide reliability while maintaining the topology in an energy efficient manner. For the above problems, real wireless sensor network traces were collected and extensive simulations were performed for evaluating the proposed protocols.
Accurate simulation and analysis of wireless networks are inherently dependent on accurate models which are able to provide real-time channel characterization. High-order Markov chains are typically used to model errors and losses over wireless channels. However, complexity (i.e., the number of states) of a high-order Markov model increases exponentially with the memory-length of the underlying channel.
In this report, a novel graph-theoretic methodology that uses Hamiltonian circuits to reduce the complexity of a high-order Markov model to a desired state budget is presented. The implication of unused states in complexity reduction of higher order Markov model is also explained. The trace-driven performance evaluations for real wireless local area network (WLAN) and wireless sensor network (WSN) channels demonstrate that the proposed Hamiltonian Model, while providing orders of magnitude reduction in complexity, renders an accuracy that is comparable to the Markov model and better than the existing reduced state models.
Furthermore, a methodology to preserve energy is presented to increase the network lifetime by reducing the node degree forming an active backbone while considering network connectivity. However, in energy stringent wireless sensor networks, it is of utmost importance to construct the reduced topology with the minimal control overhead. Moreover, most wireless links in practice are lossy links with connectivity probability which desires that a routing protocol provides routing flexibility and reliability at a minimum energy consumption cost. For this purpose, distributed and semi-distributed novel graph-theoretic topology construction protocols are presented that exploit cliques and polygons in a WSN to achieve energy efficiency and reliability. The proposed protocols also facilitate load rotation under topology maintenance, thereby extending the network lifetime. In addition to the above, the report also evaluates why the backbone construction using connected dominating set (CDS) in certain cases remains unable to provide connected sensing coverage in the area covered. For this purpose, a novel protocol that reduces the topology while considering sensing area coverage is presented
Resilient Wireless Sensor Networks Using Topology Control: A Review
Wireless sensor networks (WSNs) may be deployed in failure-prone environments, and WSNs nodes easily fail due to unreliable wireless connections, malicious attacks and resource-constrained features. Nevertheless, if WSNs can tolerate at most losing k − 1 nodes while the rest of nodes remain connected, the network is called k − connected. k is one of the most important indicators for WSNs’ self-healing capability. Following a WSN design flow, this paper surveys resilience issues from the topology control and multi-path routing point of view. This paper provides a discussion on transmission and failure models, which have an important impact on research results. Afterwards, this paper reviews theoretical results and representative topology control approaches to guarantee WSNs to be k − connected at three different network deployment stages: pre-deployment, post-deployment and re-deployment. Multi-path routing protocols are discussed, and many NP-complete or NP-hard problems regarding topology control are identified. The challenging open issues are discussed at the end. This paper can serve as a guideline to design resilient WSNs
Unified Power Management in Wireless Sensor Networks, Doctoral Dissertation, August 2006
Radio power management is of paramount concern in wireless sensor networks (WSNs) that must achieve long lifetimes on scarce amount of energy. Previous work has treated communication and sensing separately, which is insufficient for a common class of sensor networks that must satisfy both sensing and communication requirements. Furthermore, previous approaches focused on reducing energy consumption in individual radio states resulting in suboptimal solutions. Finally, existing power management protocols often assume simplistic models that cannot accurately reflect the sensing and communication properties of real-world WSNs. We develop a unified power management approach to address these issues. We first analyze the relationship between sensing and communication performance of WSNs. We show that sensing coverage often leads to good network connectivity and geographic routing performance, which provides insights into unified power management under both sensing and communication performance requirements. We then develop a novel approach called Minimum Power Configuration that ingegrates the power consumption in different radio states into a unified optimization framework. Finally, we develop two power management protocols that account for realistic communication and sensing properties of WSNs. Configurable Topology Control can configure a network topology to achieve desired path quality in presence of asymmetric and lossy links. Co-Grid is a coverage maintenance protocol that adopts a probabilistic sensing model. Co-Grid can satisfy desirable sensing QoS requirements (i.e., detection probability and false alarm rate) based on a distributed data fusion model
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