distributed reconfiguration is an important problem in multi-robot systems such as mobile sensor nets and metamorphic robot systems. In this work, we present a scalable distributed reconfiguration algorithm, hierarchi...
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distributed reconfiguration is an important problem in multi-robot systems such as mobile sensor nets and metamorphic robot systems. In this work, we present a scalable distributed reconfiguration algorithm, hierarchical median decomposition, to achieve arbitrary target configurations. Our algorithm is built on top of a novel distributed median consensus estimator. The algorithms presented are fully distributed and do not require global communication. We show results from simulations in an open source multi-robot simulator.
In this paper, a review of prediction techniques suitable for ambient intelligence environments is presented. Prediction challenges in sensor networks are considered in two phases including pattern extraction and rule...
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In this paper, a review of prediction techniques suitable for ambient intelligence environments is presented. Prediction challenges in sensor networks are considered in two phases including pattern extraction and rule matching. The prediction techniques reviewed in this paper come from two main research areas, namely, data mining and soft computing techniques. Moreover, a statistical modelling technique based on Markov chain is also considered. In this paper, we identify the centralized and distributed techniques of both data mining and soft computing areas. In addition, we identify the distributed approaches that utilize computational power of sensors in an ambient intelligence environment. Moreover, we show that some techniques use compression, regression or fuzzy methods to reduce the size of the collected sensory data.
We consider the design of a sensor network for detecting an emitter who if present is known to be located in an interval but whose exact position is unknown. We seek to minimize the total system power consumption subj...
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We consider the design of a sensor network for detecting an emitter who if present is known to be located in an interval but whose exact position is unknown. We seek to minimize the total system power consumption subject to detection performance constrains by carefully choosing the thresholds and positions of the sensors. Toward this goal, we propose an iterative algorithm for the optimization problem. Numerical results are given to provide insights into the design of such networks. We show that random sensor placement can perform poorly, in contrast to what many currently believe.
In this paper, we present a distributed Geography-based Fault Tolerant topology control algorithm (DGFT) for static large-scale wireless sensor networks. We introduce the scale-free characteristic of complex networks ...
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In this paper, we present a distributed Geography-based Fault Tolerant topology control algorithm (DGFT) for static large-scale wireless sensor networks. We introduce the scale-free characteristic of complex networks into the topology of large- scale wireless sensor networks to obtain robustness and time efficiency. DGFT enables wireless nodes to define the topology by neighbor relationship, based on certain initialized weights whose distribution follows a negative power law. We prove that the topology constructed under DGFT is strongly connected and bidirectional. Simulation studies show that the resulting topology has good network performance in terms of transmission delay and robustness.
For economic reasons sensor networks are often implemented with resource constrained micro-controllers and low-end radio transceivers. Consequently, communication is inherently unreliable and especially multi-hop comm...
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For economic reasons sensor networks are often implemented with resource constrained micro-controllers and low-end radio transceivers. Consequently, communication is inherently unreliable and especially multi-hop communication suffers severely from packet losses. Transmission protocols that rely on implicit acknowledges for multi-hop communication are energy efficient but require symmetric communication links to work properly. In this paper we introduce IMPACT, a family of transmission protocols that rely on implicit acknowledges and employ a cross layer approach to handle asymmetric links.
We consider the problem of self-deployment and relocation in mobile wireless networks, where nodes are both sensors and actuators. We propose a unified, distributed algorithm that has the following features. During de...
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We consider the problem of self-deployment and relocation in mobile wireless networks, where nodes are both sensors and actuators. We propose a unified, distributed algorithm that has the following features. During deployment, our algorithm yields a regular tessellation of the geographical area with a given node density, called monitoring configuration. Upon the occurrence of a physical phenomenon, network nodes relocate themselves so as to properly sample and control the event, while maintaining the network connectivity. Then, as soon as the event ends, all nodes return to the monitoring configuration. To achieve these goals, we use a virtual force-based strategy, which proves to be very effective even when compared to an optimal centralized solution.
A regeneration-based approach is undertaken to derive an expression for the expected value of total service time for an arbitrary customer distribution when scheduling is performed in a distributed queuing system. The...
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A regeneration-based approach is undertaken to derive an expression for the expected value of total service time for an arbitrary customer distribution when scheduling is performed in a distributed queuing system. The service times and the transfer delays for customers in the shared communication medium are both considered random. The theory is applied to a distributed wireless-sensor network and the interplay between the total service time and the energy consumption of each sensor is investigated.
In this paper, we compare the efficiency of fault detection and diagnosis in networks having different topological properties, such as scale-free networks and Erdos-Renyi random graphs. Efficiency measures include bot...
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In this paper, we compare the efficiency of fault detection and diagnosis in networks having different topological properties, such as scale-free networks and Erdos-Renyi random graphs. Efficiency measures include both the number of tests (e.g., end-to-end network probes) necessary for diagnosis and the computational complexity of diagnosis. We observe that diagnosis in scale-free networks typically requires significantly larger number of tests than diagnosis in random networks. However, the computational complexity of diagnosis appears to be much lower for scale-free networks since the corresponding Bayesian network models used for probabilistic diagnosis tend to have much lower induced width - a topological parameter controlling the complexity of inference in Bayesian networks. We believe that our observations provide important insights for design and deployment of cost-efficient diagnostic methods in computer networks and distributedsystems.
Evaluating position uncertainties is a fundamental problem of wireless sensor network localization. A constraint set, including both positive and negative constraints, is constructed to bound sensor position. By proje...
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Evaluating position uncertainties is a fundamental problem of wireless sensor network localization. A constraint set, including both positive and negative constraints, is constructed to bound sensor position. By projecting the feasible region of this constraint set onto a 2D plane, the feasible scope of sensor position is computed to evaluate node position uncertainty. The projection result, called feasible geographic region (FGR), is approximated by its inner and outer polygon. The polygon approximation will converge to the actual FGR if we incrementally add more polygon vertices. A distributed algorithm is proposed to compute FGR. Finally, we study the impact of node position uncertainty upon a typical network application, target event detection. The feasible scope of target event position is computed even though the sensor position is not certain.
Physical attributes such as temperature exhibit gradual change in value with space. Observations from the sensor nodes are thus highly correlated. In this paper, we propose a scheme to exploit the spatial correlation ...
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Physical attributes such as temperature exhibit gradual change in value with space. Observations from the sensor nodes are thus highly correlated. In this paper, we propose a scheme to exploit the spatial correlation of data in a three dimensional wireless sensor network (WSN), in a way so as to reduce the number of transmissions in the network, thereby saving energy. The presented work is an extension of the earlier proposed TREG scheme which is only applicable to two dimensional WSN. Our scheme involves formation of binary tree and transmission of data along the tree nodes. Simulation has been carried out for different tree heights. Simulation results show that a tree height of four provides results with optimal values.
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