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Sensor networks and cooperative control,”
 European Journal of Control,
, 2005
"... Abstract This paper provides a tutorialstyle overview of sensor networks from a systems and control theory perspective. We identify key sensor network design and operational control problems and present solution approaches that have been proposed to date. These include deployment, routing, schedul ..."
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Cited by 45 (2 self)
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Abstract This paper provides a tutorialstyle overview of sensor networks from a systems and control theory perspective. We identify key sensor network design and operational control problems and present solution approaches that have been proposed to date. These include deployment, routing, scheduling, and power control. In the case of mobile nodes, a sensor network is called upon to perform a "mission". We present solution approaches to two types of missions, both involving stochastic mission spaces and cooperative control: reward maximization missions, and coverage control missions. We conclude by outlining some fundamental research questions related to sensor networks and the convergence of communication, computing, and control.
Perturbation analysis and optimization of stochastic hybrid systems
 European Journal of Control
, 2010
"... Abstract We present a general framework for carrying out perturbation analysis in Stochastic Hybrid Systems (SHS) of arbitrary structure. In particular, Infinitesimal Perturbation Analysis (IPA) is used to provide unbiased gradient estimates of performance metrics with respect to various controllab ..."
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Cited by 13 (5 self)
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Abstract We present a general framework for carrying out perturbation analysis in Stochastic Hybrid Systems (SHS) of arbitrary structure. In particular, Infinitesimal Perturbation Analysis (IPA) is used to provide unbiased gradient estimates of performance metrics with respect to various controllable parameters. These can be combined with standard gradientbased algorithms for optimization purposes and implemented on line with little or no distributional information regarding stochastic processes involved. We generalize an earlier concept of "induced events" for this framework to include system features such as delays in control signals or modeling multiple user classes sharing a resource. We apply this generalized IPA to two SHS with different characteristics. First, we develop a gradient estimator for the performance of a linear switched system with control signal delays and a safety constraint and show that it is independent of the random delay distributional characteristics. Second, we derive closedform unbiased IPA estimators for a Stochastic Flow Model (SFM) of systems executing tasks subject to either hard or soft realtime constraints. These estimators are incorporated in a gradientbased algorithm to optimize performance by controlling a task admission threshold parameter. Simulation results are included to illustrate this optimization approach.
Optimal dynamic voltage scaling in powerlimited systems with realtime constraints.
 IEEE Trans. on Mobile Computing,
, 2007
"... Abstract Dynamic voltage scaling is used in powerlimited systems such as sensor networks as a means of conserving energy and prolonging their life. We consider a setting in which the tasks performed by such a system are nonpreemptive, aperiodic and have uncertain arrival times. Our objective is to ..."
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Cited by 7 (3 self)
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Abstract Dynamic voltage scaling is used in powerlimited systems such as sensor networks as a means of conserving energy and prolonging their life. We consider a setting in which the tasks performed by such a system are nonpreemptive, aperiodic and have uncertain arrival times. Our objective is to control the processing rate over different tasks so as to minimize energy subject to hard realtime processing constraints. We prove that the solution to this problem reduces to two simpler problems which can be efficiently solved, leading to a new online dynamic voltage scaling algorithm. This algorithm is shown to have low complexity and, unlike similar stateoftheart approaches, it involves no solution of nonlinear programming problems and is independent of the specific physical characteristics of the system. Both offline and online versions of the algorithm are analyzed and numerical examples are provided to illustrate the relative advantages of the latter over the former.
Optimal admission control of discrete event systems with realtime constraints.
, 2007
"... AbstractThe problem of optimally controlling the processing rate of tasks in Discrete Event Systems (DES) with hard realtime constraints has been solved in ..."
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Cited by 2 (1 self)
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AbstractThe problem of optimally controlling the processing rate of tasks in Discrete Event Systems (DES) with hard realtime constraints has been solved in
CompileTime Scheduling of RealTime Threads on MultiLevelContext Architectures
 In Proc. of the Seventh Swedish Workshop on Computer System Architecture
, 1998
"... Most modern microprocessor architectures are endowed with such mechanisms as caches and instruction pipelines whose temporal behavior are very hard to predict a priori. Despite many recent successful attempts to model the behavior of these mechanisms [14], realtime scheduling research has not bee ..."
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Cited by 1 (0 self)
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Most modern microprocessor architectures are endowed with such mechanisms as caches and instruction pipelines whose temporal behavior are very hard to predict a priori. Despite many recent successful attempts to model the behavior of these mechanisms [14], realtime scheduling research has not been able to keep pace with the progress in microprocessor design. This has led to an unfortunate gap between realtime scheduling theory and its practice. An important remaining problem is to analyze the effects of context switch operations on the schedulability analysis. While traditional realtime schedulabilityanalysis techniques [5, 6] simply assumed that a context switch can be performed at negligible cost, more recent techniques [7, 8] are capable of incorporating a nonnegligible contextswitch cost into the schedulability analysis. Unfortunately, these schedulability analyses are based on the assumption that the cost for a context switch is constant and independent of the underlying t...
Online Optimal Control of a Class of Discrete Event Systems with RealTime Constraints
"... AbstractWe consider Discrete Event Systems involving tasks with realtime constraints and seek to control processing times so as to minimize a cost function subject to each task meeting its own constraint. It has been shown that the ofTline version of this problem can be efficiently solved by the ..."
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AbstractWe consider Discrete Event Systems involving tasks with realtime constraints and seek to control processing times so as to minimize a cost function subject to each task meeting its own constraint. It has been shown that the ofTline version of this problem can be efficiently solved by the Critical Task Decomposition Algorithm [9]. The online version has been dealt with to date using worstcase analysis so as to bypass the complexity of random efTects. This approach, however, does not make use of probability distributions and results in an overly consenative solution. In this paper, we develop a new online algorithm without relying on worstcase analysis, in which a "best solution in probability" can be efficiently obtained by estimating the probability distribution of the otTline optimal control. We introduce a condition termed ''nonsingularity'' under which the best solution in probability leads to the online optimal control. Numerical examples are included to illustrate our results and show substantial performance improvements over worstcase analysis.
Optimal Dynamic Voltage Scaling in EnergyLimited Nonpreemptive Systems with RealTime Constraints
"... AbstractDynamic voltage scaling is used in energylimited systems as a means of conserving energy and prolonging their life. We consider a setting in which the tasks performed by such a system are nonpreemptive and aperiodic. Our objective is to control the processing rate over different tasks so ..."
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AbstractDynamic voltage scaling is used in energylimited systems as a means of conserving energy and prolonging their life. We consider a setting in which the tasks performed by such a system are nonpreemptive and aperiodic. Our objective is to control the processing rate over different tasks so as to minimize energy subject to hard realtime processing constraints. Under any given task scheduling policy, we prove that the optimal solution to the offline version of the problem can be efficiently obtained by exploiting the structure of optimal sample paths, leading to a new dynamic voltage scaling algorithm termed the Critical Task Decomposition Algorithm (CTDA). The efficiency of the algorithm rests on the existence of a set of critical tasks that decompose the optimal sample path into decoupled segments within which optimal processing times are easily determined. The algorithm is readily extended to an online version of the problem as well. Its worstcase complexity of both offline and online problems is OðN 2 Þ.
Sensor Networks and Cooperative Control
, 2005
"... This paper provides a tutorialstyle overview of sensor networks from a systems and control theory perspective. We identify key sensor network design and operational control problems and present solution approaches that have been proposed to date. These include deployment, routing, scheduling, and p ..."
Abstract
 Add to MetaCart
This paper provides a tutorialstyle overview of sensor networks from a systems and control theory perspective. We identify key sensor network design and operational control problems and present solution approaches that have been proposed to date. These include deployment, routing, scheduling, and power control. In the case of mobile nodes, a sensor network is called upon to perform a “mission”. We present solution approaches to two types of missions, both involving stochastic mission spaces and cooperative control: reward maximization missions, and coverage control missions. We conclude by outlining some fundamental research questions related to sensor networks and the convergence of communication, computing, and control.