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Loss of connectivity in deployed wireless sensor networks can be quite disastrous for the network. A "cut" (which separates the network into two or more components incapable of communicating with each other) is usually hard to detect. An algorithm which enables each node in the network to detect whether a cut has occurred anywhere in the network is(More)
We consider the problem of estimating vector-valued variables from noisy " relative " measurements. The measurement model can be expressed in terms of a graph, whose nodes correspond to the variables being estimated and the edges to noisy measurements of the difference between the two variables. This type of measurement model appears in several sensor(More)
—A wireless sensor network can get separated into multiple connected components due to the failure of some of its nodes, which is called a " cut ". In this article we consider the problem of detecting cuts by the remaining nodes of a wireless sensor network. We propose an algorithm that allows (i) every node to detect when the connectivity to a specially(More)
We study the stability margin of a vehicular formation with distributed control, in which the control at each vehicle only depends on the information from its neighbors in an information graph. We consider a D-dimensional lattice as information graph, of which the 1-D platoon is a special case. The stability margin is measured by the real part of the least(More)
— The thermal storage potential in buildings is an enormous untapped resource for providing various services to the power grid. The large thermal capacities of commercial buildings in particular make the power demands of their Heating, Ventilation, and Air Conditioning (HVAC) systems inherently flexible. In this paper, we show how fans in air handing units(More)
— We study the problem of estimating vector-valued variables from noisy " relative " measurements. This problem arises in several sensor network applications. The measurement model can be expressed in terms of a graph, whose nodes correspond to the variables and edges to noisy measurements of the difference between two variables. We take an arbitrary(More)