0000000000217371
AUTHOR
Cesar Asensio-marco
Consensus-Based Distributed State Estimation of Biofilm in Reverse Osmosis Membranes by WSNs
The appearance of biofilm has become a serious problem in many reverse osmosis based systems such as the ones found in water treatment and desalination plants. In these systems, the use of traditional techniques such as pretreatment or dozing biocides are not effective when the biofilm reaches an irreversible attachment phase. In this work, we present a framework for the use of a WSN as an estimator of the biofilm evolution in a reverse osmosis membrane so that effective solutions can be applied before the irreversible phase is attained. This design is addressed in a complete distributed and decentralized fashion, and subject to realistic constraints where cooperation between nodes is perfo…
A greedy perturbation approach to accelerating consensus algorithms and reducing its power consumption
The average consensus is part of a family of algorithms that are able to compute global statistics by only using local data. This capability makes these algorithms interesting for applications in which these distributed philosophy is necessary. However, its iterative nature usually leads to a large power consumption due to the repetitive communications among the iterations. This drawback highlights the necessity of minimizing the power consumption until consensus is reached. In this work, we propose a greedy approach to perturbing the connectivity graph, in order to improve the convergence time of the consensus algorithm while keeping bounded the power consumption per iteration step. These …
Cross-Layer MAC Protocol for Unbiased Average Consensus Under Random Interference
Wireless Sensor Networks have been revealed as a powerful technology to solve many different problems through sensor nodes cooperation. One important cooperative process is the so-called average gossip algorithm, which constitutes a building block to perform many inference tasks in an efficient and distributed manner. From the theoretical designs proposed in most previous work, this algorithm requires instantaneous symmetric links in order to reach average consensus. However, in a realistic scenario wireless communications are subject to interferences and other environmental factors, which results in random instantaneous topologies that are, in general, asymmetric. Consequently, the estimat…
Fast Distributed Subspace Projection via Graph Filters
A significant number of linear inference problems in wireless sensor networks can be solved by projecting the observed signal onto a given subspace. Decentralized approaches avoid the need for performing such an operation at a central processor, thereby reducing congestion and increasing the robustness and the scalability of the network. Unfortunately, existing decentralized approaches either confine themselves to a reduced family of subspace projection tasks or need an infinite number of iterations to obtain the exact projection. To remedy these limitations, this paper develops a framework for computing a wide class of subspace projections in a decentralized fashion by relying on the notio…
Energy Efficient Consensus Over Directed Graphs
Consensus algorithms are iterative methods that represent a basic building block to achieve superior functionalities in increasingly complex sensor networks by facilitating the implementation of many signal-processing tasks in a distributed manner. Due to the heterogeneity of the devices, which may present very different capabilities (e.g. energy supply, transmission range), the energy often becomes a scarce resource and the communications turn into directed. To maximize the network lifetime, a magnitude that in this work measures the number of consensus processes that can be executed before the first node in the network runs out of battery, we propose a topology optimization methodology fo…
Energy Efficient Consensus Over Complex Networks
The need to extract large amounts of information from the environment to have precise situation awareness and then react appropriately to certain events has led to the emergence of complex and heterogeneous sensor networks. In this context, where the sensor nodes are usually powered by batteries, the design of new methods to make inference processes efficient in terms of energy consumption is necessary. One of these processes, which is present in many distributed tasks performed by these complex networks, is the consensus process. This is the basis for certain tracking algorithms in monitoring and control applications. To improve the energy efficiency of this process, in this paper we propo…
Link scheduling in sensor networks for asymmetric average consensus
Wireless Sensor Networks constitute a recent technology where the nodes cooperate to obtain, in a totally distributed way, certain function of the sensed data. One example is the average consensus algorithm, which allows every node to converge to the global average. However, this algorithm presents two major drawbacks in practice. The first one is that instantaneous symmetric links are required, which are hard to ensure in practice because of the presence of wireless interferences. The second one is that all the nodes are required to communicate with all of their local neighbors in every iteration, which can lead to an unbounded delay. In order to solve these issues, we propose a novel link…
Ensuring High Performance of Consensus-Based Estimation by Lifetime Maximization in WSNs
The estimation of a parameter corrupted by noise is a common tasks in wireless sensor networks, where the deployed nodes cooperate in order to improve their own inaccurate observations. This cooperation usually involves successive data exchanges and local information updates until a global consensus value is reached. The quality of the final estimator depends on the amount of collected observations, hence the number of active nodes. Moreover, the inherent iterative nature of the consensus process involves a certain energy consumption. Since the devices composing the network are usually battery powered, nodes becoming inactive due to battery depletion emerges as a serious problem. In this wo…
Consensus based distributed estimation of biomass concentration in reverse osmosis membranes
The correct estimation of biofilm formation in industrial environments, such as reverse osmosis plants, has become a topic of great interest. The occurrence of this natural process is the cause of huge economic losses due to a decrease of performance and maintenance costs in these plants. Current solutions based on water pretreatment or the dozing of biocides are not effective due to the lack of information about the state of the biofilm in the water system. In this work, we propose the use of a wireless sensor network that, based on the measurement of the biofilm thickness growth at the substratum of each sensor, estimates the biomass concentration within the biofilm, and, eventually, the …
Adaptive Medium Access Control for Distributed Processing in Wireless Sensor Networks
Signal and information processing tasks over Wireless Sensor Networks can be successfully accomplished by means of a distributed implementation among the nodes. Existing distributed schemes are commonly based on iterative strategies that imply a huge demand of one-hop transmissions, which must be efficiently processed by the lower layers of the nodes. At the link layer, general purpose medium access (MAC) policies for wireless communications usually focus on avoiding collisions. These existing approaches result in a reduction of the number of simultaneous transmissions, and an underutilization of the channel as a consequence. This leads to a decrease in the performance of the distributed ta…
Topology design to reduce energy consumption of distributed graph filtering in WSN
The large number of nodes forming current sensor networks has made essential to introduce distributed mechanisms in many traditional applications. In the emerging field of graph signal processing, the distributed mechanism of information potentials constitutes a distributed graph filtering process that can be used to solve many different problems. An important limitation of this algorithm is that it is inherently iterative, which implies that the nodes incur in a repeated communication cost along the exchange periods of the filtering process. Since sensor nodes are battery powered and radio communications are one of the most energy demanding operations, in this work, we propose to redesign …
A reliable CSMA protocol for high performance broadcast communications in a WSN
Wireless Sensor Networks have been identified as a promising technology to efficiently perform distributed monitoring, tracking and control tasks. In order to accomplish them, since fast decisions are generally required, high values of throughput must be obtained. Additionally, a high packet reception rate is important to avoid wasting energy due to unsuccessful transmissions. These communication requirements are more easily satisfied by exploiting the broadcast nature of the wireless medium, which allows several simultaneous receptions through a unique node transmission. We propose a Medium Access Control protocol that ensures, simultaneously, high values of throughput and a high packet re…
Reducing the observation error in a WSN through a consensus-based subspace projection
An essential process in a Wireless Sensor Network is the noise mitigation of the measured data, by exploiting their spatial correlation. A widely used technique to achieve this reduction is to project the measured data into a proper subspace. We present a low complexity and distributed algorithm to perform this projection. Unlike other algorithms existing in the literature, which require the number of connections at every node to be larger than the dimension of the involved subspace, our algorithm does not require such dense network topologies for its applicability, making it suitable for a larger number of scenarios. Our proposed algorithm is based on the execution of several consensus pro…
DECENTRALIZED SUBSPACE PROJECTION IN LARGE NETWORKS
A great number of applications in wireless sensor networks involve projecting a vector of observations onto a subspace dictated by prior information. Accomplishing such a task in a centralized fashion entails great power consumption, congestion at certain nodes, and suffers from robustness issues. A sensible alternative is to compute such projections in a decentralized fashion. To this end, recent works proposed schemes based on graph filters, which compute projections exactly with a finite number of local exchanges among sensor nodes. However, existing methods to obtain these filters are confined to reduced families of projection matrices or small networks. This paper proposes a method tha…
Fast Graph Filters for Decentralized Subspace Projection
A number of inference problems with sensor networks involve projecting a measured signal onto a given subspace. In existing decentralized approaches, sensors communicate with their local neighbors to obtain a sequence of iterates that asymptotically converges to the desired projection. In contrast, the present paper develops methods that produce these projections in a finite and approximately minimal number of iterations. Building upon tools from graph signal processing, the problem is cast as the design of a graph filter which, in turn, is reduced to the design of a suitable graph shift operator. Exploiting the eigenstructure of the projection and shift matrices leads to an objective whose…