35,843 research outputs found
A Low-Cost Robust Distributed Linearly Constrained Beamformer for Wireless Acoustic Sensor Networks with Arbitrary Topology
We propose a new robust distributed linearly constrained beamformer which
utilizes a set of linear equality constraints to reduce the cross power
spectral density matrix to a block-diagonal form. The proposed beamformer has a
convenient objective function for use in arbitrary distributed network
topologies while having identical performance to a centralized implementation.
Moreover, the new optimization problem is robust to relative acoustic transfer
function (RATF) estimation errors and to target activity detection (TAD)
errors. Two variants of the proposed beamformer are presented and evaluated in
the context of multi-microphone speech enhancement in a wireless acoustic
sensor network, and are compared with other state-of-the-art distributed
beamformers in terms of communication costs and robustness to RATF estimation
errors and TAD errors
Robust Distributed Optimization in Wireless Sensor Network
Wireless sensor networks continue to get tremendous popularity, as evidenced by the increasing number of applications for these networks. The limiting factors of the sensor nodes, such as their finite energy supplies and their moderate processing abilities, as well as the unreliable wireless medium restrict the performance of wireless sensor networks. Energy efficient communication is a critical design objective for wireless sensor networks which are usually highly energy constrained. To achieve these goals, this thesis describes a distributed approach for solving several optimization problems in wireless sensor network.
The idea of distributed signal processing relies on the divide-and-conquer paradigm, which is often used in multiprocessor computers. According to the divide-and-conquer paradigm, a problem is divided into multiple sub-problems of smaller size. Every sensor solves each subproblem by using the same algorithm, and the solution to the original problem is obtained by combining the outputs from the different sensors. By designing appropriate communication protocols and collaborative computational schemes, sensors operate as distributed adaptive filters and generate the desired result. In an incremental mode of cooperation, information flows in a sequential manner from one node to the adjacent node. This mode of operation requires a cyclic pattern of collaboration among the nodes. In a diffusion implementation, on the other hand, each node communicates with all its neighbours as dictated by the network topology. READ FULL ABSTRACT IN THE DOCUMEN
A Polyhedral Approximation Framework for Convex and Robust Distributed Optimization
In this paper we consider a general problem set-up for a wide class of convex
and robust distributed optimization problems in peer-to-peer networks. In this
set-up convex constraint sets are distributed to the network processors who
have to compute the optimizer of a linear cost function subject to the
constraints. We propose a novel fully distributed algorithm, named
cutting-plane consensus, to solve the problem, based on an outer polyhedral
approximation of the constraint sets. Processors running the algorithm compute
and exchange linear approximations of their locally feasible sets.
Independently of the number of processors in the network, each processor stores
only a small number of linear constraints, making the algorithm scalable to
large networks. The cutting-plane consensus algorithm is presented and analyzed
for the general framework. Specifically, we prove that all processors running
the algorithm agree on an optimizer of the global problem, and that the
algorithm is tolerant to node and link failures as long as network connectivity
is preserved. Then, the cutting plane consensus algorithm is specified to three
different classes of distributed optimization problems, namely (i) inequality
constrained problems, (ii) robust optimization problems, and (iii) almost
separable optimization problems with separable objective functions and coupling
constraints. For each one of these problem classes we solve a concrete problem
that can be expressed in that framework and present computational results. That
is, we show how to solve: position estimation in wireless sensor networks, a
distributed robust linear program and, a distributed microgrid control problem.Comment: submitted to IEEE Transactions on Automatic Contro
QoS Provision for Wireless Sensor Networks
Wireless sensor network is a fast growing area of research, receiving attention not only within the computer science and electrical engineering communities, but also in relation to network optimization, scheduling, risk and reliability analysis within industrial and system engineering. The availability of micro-sensors and low-power wireless communications will enable the deployment of densely distributed sensor/actuator networks. And an integration of such system plays critical roles in many facets of human life ranging from intelligent assistants in hospitals to manufacturing process, to rescue agents in large scale disaster response, to sensor networks tracking environment phenomena, and others.
The sensor nodes will perform significant signal processing, computation, and network self-configuration to achieve scalable, secure, robust and long-lived networks. More specifically, sensor nodes will do local processing to reduce energy costs, and key exchanges to ensure robust communications. These requirements pose interesting challenges for networking research. The most important technical challenge arises from the development of an integrated system which is 1)energy efficient because the system must be long-lived and operate without manual intervention, 2)reliable for data communication and robust to attackers because information security and system robustness are important in sensitive applications, such as military.
Based on the above challenges, this dissertation provides Quality of Service (QoS) implementation and evaluation for the wireless sensor networks. It includes the following 3 modules, 1) energy-efficient routing, 2) energy-efficient coverage, 3). communication security. Energy-efficient routing combines the features of minimum energy consumption routing protocols with minimum computational cost routing protocols. Energy-efficient coverage provides on-demand sensing and measurement. Information security needs a security key exchange scheme to ensure reliable and robust communication links. QoS evaluation metrics and results are presented based on the above requirements
Distributed Cooperative Localization in Wireless Sensor Networks without NLOS Identification
In this paper, a 2-stage robust distributed algorithm is proposed for
cooperative sensor network localization using time of arrival (TOA) data
without identification of non-line of sight (NLOS) links. In the first stage,
to overcome the effect of outliers, a convex relaxation of the Huber loss
function is applied so that by using iterative optimization techniques, good
estimates of the true sensor locations can be obtained. In the second stage,
the original (non-relaxed) Huber cost function is further optimized to obtain
refined location estimates based on those obtained in the first stage. In both
stages, a simple gradient descent technique is used to carry out the
optimization. Through simulations and real data analysis, it is shown that the
proposed convex relaxation generally achieves a lower root mean squared error
(RMSE) compared to other convex relaxation techniques in the literature. Also
by doing the second stage, the position estimates are improved and we can
achieve an RMSE close to that of the other distributed algorithms which know
\textit{a priori} which links are in NLOS.Comment: Accepted in WPNC 201
Analyzing Energy-efficiency and Route-selection of Multi-level Hierarchal Routing Protocols in WSNs
The advent and development in the field of Wireless Sensor Networks (WSNs) in
recent years has seen the growth of extremely small and low-cost sensors that
possess sensing, signal processing and wireless communication capabilities.
These sensors can be expended at a much lower cost and are capable of detecting
conditions such as temperature, sound, security or any other system. A good
protocol design should be able to scale well both in energy heterogeneous and
homogeneous environment, meet the demands of different application scenarios
and guarantee reliability. On this basis, we have compared six different
protocols of different scenarios which are presenting their own schemes of
energy minimizing, clustering and route selection in order to have more
effective communication. This research is motivated to have an insight that
which of the under consideration protocols suit well in which application and
can be a guide-line for the design of a more robust and efficient protocol.
MATLAB simulations are performed to analyze and compare the performance of
LEACH, multi-level hierarchal LEACH and multihop LEACH.Comment: NGWMN with 7th IEEE Inter- national Conference on Broadband and
Wireless Computing, Communication and Applications (BWCCA 2012), Victoria,
Canada, 201
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