The Experts below are selected from a list of 294 Experts worldwide ranked by ideXlab platform
Chengshang Chang - One of the best experts on this subject based on the ideXlab platform.
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a min system theory for constrained traffic regulation and dynamic service guarantees
IEEE ACM Transactions on Networking, 2002Co-Authors: Chengshang Chang, R L Cruz, Jeanyves Le Boudec, Patrick ThiranAbstract:By extending the system theory under the (min, +) algebra to the time-varying setting, we solve the problem of constrained traffic regulation and develop a calculus for dynamic service guarantees. For a constrained traffic-regulation problem with maximum tolerable delay d and maximum buffer size q, the optimal regulator that generates the output traffic conforming to a subadditive envelope f and minimizes the number of discarded packets is a concatenation of the g-clipper with g(t) = min[f(t+ d), f (t)+q] and the maximal f-regulator. The g-clipper is a bufferless device, which optimally drops packets as necessary in order that its output be conformant to an envelope g. The maximal f-regulator is a buffered device that delays packets as necessary in order that its output be conformant to an envelope f. The maximal f-regulator is a linear time-Invariant Filter with impulse response f, under the (min, +) algebra. To provide dynamic service guarantees in a network, we develop the concept of a dynamic server as a basic network element. Dynamic servers can be joined by concatenation, "Filter bank summation," and feedback to form a composite dynamic server. We also show that dynamic service guarantees for multiple input streams sharing a work-conserving link can be achieved by a dynamic service curve earliest deadline scheduling algorithm, if an appropriate admission control is enforced.
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A min, + system theory for constrained traffic regulation and dynamic service guarantees
IEEE ACM Transactions on Networking, 2002Co-Authors: Chengshang Chang, R L Cruz, Jeanyves Le Boudec, Patrick ThiranAbstract:By extending the system theory under the (min, +) algebra to the time-varying setting, we solve the problem of constrained traffic regulation and develop a calculus for dynamic service guarantees. For a constrained traffic-regulation problem with maximum tolerable delay d and maximum buffer size q, the optimal regulator that generates the output traffic conforming to a subadditive envelope f and minimizes the number of discarded packets is a concatenation of the g-clipper with g(t) = min[f(t+d), f(t) + q] and the maximal f-regulator. The g-clipper is a bufferless device, which optimally drops packets as necessary in order that its output be conformant to an envelope g. The maximal f-regulator is a buffered device that delays packets as necessary in order that its output be conformant to an envelope f. The maximal f-regulator is a linear time-Invariant Filter with impulse response f, under the (min, +) algebra.To provide dynamic service guarantees in a network, we develop the concept of a dynamic server as a basic network element. Dynamic servers can be joined by concatenation, "Filter bank summation," and feedback to form a composite dynamic server. We also show that dynamic service guarantees for multiple input streams sharing a work-conserving link can be achieved by a dynamic service curve earliest deadline scheduling algorithm, if an appropriate admission control is enforced.
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a time varying Filtering theory for constrained traffic regulation and dynamic service guarantees
International Conference on Computer Communications, 1999Co-Authors: Chengshang Chang, R L CruzAbstract:By extending the Filtering theory under the (min, +)-algebra to the time varying setting, we solve the problem of constrained traffic regulation and develop a calculus for dynamic service guarantees. For a constrained traffic regulation problem with maximum tolerable delay d and maximum buffer size q, the optimal regulator that generates the output traffic conforming to a subadditive envelope f and minimizes the number of discarded packets is a concatenation of the g-clipper with g(t)=min[f(t+d), f(t)+q] and the maximal f-regulator. The g-clipper is a bufferless device which optimally drops packets as necessary in order that its output be conformant to an envelope g. The maximal f-regulator is a buffered device that delays packets as necessary in order that its output be conformant to an envelope f. The f-regulator is a linear time Invariant Filter with impulse response f, under the (min, +)-algebra. To provide dynamic service guarantees in a network, we develop the concept of a dynamic server as a basic network element. Dynamic servers can be joined by concatenation, "Filter bank summation" and feedback to form a composite dynamic server, we also show that dynamic service guarantees for multiple input streams sharing a work conserving link can be achieved by a dynamic SCED (service curve earliest deadline) scheduling algorithm, if an appropriate admission control is enforced.
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INFOCOM - A time varying Filtering theory for constrained traffic regulation and dynamic service guarantees
IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Socie, 1999Co-Authors: Chengshang Chang, R L CruzAbstract:By extending the Filtering theory under the (min, +)-algebra to the time varying setting, we solve the problem of constrained traffic regulation and develop a calculus for dynamic service guarantees. For a constrained traffic regulation problem with maximum tolerable delay d and maximum buffer size q, the optimal regulator that generates the output traffic conforming to a subadditive envelope f and minimizes the number of discarded packets is a concatenation of the g-clipper with g(t)=min[f(t+d), f(t)+q] and the maximal f-regulator. The g-clipper is a bufferless device which optimally drops packets as necessary in order that its output be conformant to an envelope g. The maximal f-regulator is a buffered device that delays packets as necessary in order that its output be conformant to an envelope f. The f-regulator is a linear time Invariant Filter with impulse response f, under the (min, +)-algebra. To provide dynamic service guarantees in a network, we develop the concept of a dynamic server as a basic network element. Dynamic servers can be joined by concatenation, "Filter bank summation" and feedback to form a composite dynamic server, we also show that dynamic service guarantees for multiple input streams sharing a work conserving link can be achieved by a dynamic SCED (service curve earliest deadline) scheduling algorithm, if an appropriate admission control is enforced.
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on deterministic traffic regulation and service guarantees a systematic approach by Filtering
IEEE Transactions on Information Theory, 1998Co-Authors: Chengshang ChangAbstract:We develop a Filtering theory for deterministic traffic regulation and service guarantees under the (min, +)-algebra. We show that traffic regulators that generate f-upper constrained outputs can be implemented optimally by a linear time-Invariant Filter with the impulse response f/sub */ under the (min, +)-algebra, where f/sub */ is the subadditive closure defined in the paper. Analogous to the classical Filtering theory, there is an associate calculus, including feedback, concatenation, "Filter bank summation", and performance bounds. The calculus is also applicable to the concept of service curves that can be used for deriving deterministic service guarantees. Our Filtering approach not only yields easier proofs for more general results than those in the literature, but also allows us to design traffic regulators via systematic methods such as concatenation, Filter bank summation, linear system realization, and FIR-IIR realization. We illustrate the use of the theory by considering a window flow control problem and a service curve allocation problem.
Vladimir Stankovic - One of the best experts on this subject based on the ideXlab platform.
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Undirected Graphs: Is the Shift-Enabled Condition Trivial or Necessary?
2019Co-Authors: Liyan Chen, Samuel Cheng, Lina Stankovic, Vladimir StankovicAbstract:It has recently been shown that, contrary to the wide belief that a shift-enabled condition (necessary for any shift-Invariant Filter to be representable by a graph shift matrix) can be ignored because any non-shift-enabled matrix can be converted to a shift-enabled matrix, such a conversion in general may not hold for a directed graph with non-symmetric shift matrix. This paper extends this prior work, focusing on undirected graphs where the shift matrix is generally symmetric. We show that while, in this case, the shift matrix can be converted to satisfy the original shift-enabled condition, the converted matrix is not associated with the original graph, that is, it does not capture anymore the structure of the graph signal. We show via a counterexample, that a non-shift-enabled matrix cannot be converted to a shift-enabled one and still maintain the topological structure of the underlying graph, which is necessary to facilitate localized signal processing.
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Undirected graphs: is the shift-enabled condition trivial or necessary?.
arXiv: Signal Processing, 2018Co-Authors: Liyan Chen, Samuel Cheng, Lina Stankovic, Vladimir StankovicAbstract:It has recently been shown that, contrary to the wide belief that a shift-enabled condition (necessary for any shift-Invariant Filter to be representable by a graph shift matrix) can be ignored because any non-shift-enabled matrix can be converted to a shift-enabled matrix, such a conversion in general may not hold for a directed graph with non-symmetric shift matrix. This letter extends this prior work, focusing on undirected graphs where the shift matrix is generally symmetric. We show that while, in this case, the shift matrix can be converted to satisfy the original shift-enabled condition, the converted matrix is not associated with the original graph, that is, it does not capture anymore the structure of the graph signal. We show via a counterexample, that a non-shift-enabled matrix cannot be converted to a shift-enabled one and still maintain the topological structure of the underlying graph, which is necessary to facilitate localized signal processing.
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Shift-enabled graphs: Graphs where shift-Invariant Filters are representable as polynomials of shift operations
IEEE Signal Processing Letters, 2018Co-Authors: Liyan Chen, Samuel Cheng, Vladimir Stankovic, Lina StankovicAbstract:In digital signal processing, shift-Invariant Filters can be represented as a polynomial expansion of a shift operation,that is, the Z-transform representation. When extended to graph signal processing (GSP), this would mean that a shift-Invariant graph Filter can be represented as a polynomial of the adjacency (shift) matrix of the graph. However, the characteristic and minimum polynomials of the adjacency matrix must be identical for the property to hold. While it has been suggested that this condition might be ignored as it is always possible to find a polynomial transform to represent the original adjacency matrix by another adjacency matrix that satisfies the condition, this letter shows that a Filter that is shift Invariant in terms of the original graph may not be shift Invariant anymore under the modified graph and vice versa. We introduce the notion of "shift-enabled graph" for graphs that satisfy the aforementioned condition, and present a concrete example of a graph that is not "shift-enabled" and a shift-Invariant Filter that is not a polynomial of the shift operation matrix. The result provides a deeper understanding of shift-Invariant Filters when applied in GSP and shows that further investigation of shift-enabled graphs is needed to make it applicable to practical scenarios.
Esko Ukkonen - One of the best experts on this subject based on the ideXlab platform.
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a rotation Invariant Filter for two dimensional string matching
Combinatorial Pattern Matching, 1998Co-Authors: Kimmo Fredriksson, Esko UkkonenAbstract:We consider the problem of finding the occurrences of two-dimensional pattern P[1..m, 1..m] in two-dimensional text T[1..n, 1..n] when also rotations of P are allowed. A fast filtration-type algorithm is developed that finds in T the locations where a rotated P can occur. The, corresponding rotations are also found. The algorithm first reads from P a linear string of length m in all θ(m2) orientations that are relevant. We also show that the number of different orientations which P can have is θ(m3). The text T is scanned with Aho-Corasick string matching automaton to find the occurrences of any of these θ(m2) linear strings of length m. Each such occurrence indicates a potential set of occurrences of whole P which are then checked. Some preliminary running times of a prototype implementation of the method are reported.
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CPM - A Rotation Invariant Filter for Two-Dimensional String Matching
Combinatorial Pattern Matching, 1998Co-Authors: Kimmo Fredriksson, Esko UkkonenAbstract:We consider the problem of finding the occurrences of two-dimensional pattern P[1..m, 1..m] in two-dimensional text T[1..n, 1..n] when also rotations of P are allowed. A fast filtration-type algorithm is developed that finds in T the locations where a rotated P can occur. The, corresponding rotations are also found. The algorithm first reads from P a linear string of length m in all θ(m2) orientations that are relevant. We also show that the number of different orientations which P can have is θ(m3). The text T is scanned with Aho-Corasick string matching automaton to find the occurrences of any of these θ(m2) linear strings of length m. Each such occurrence indicates a potential set of occurrences of whole P which are then checked. Some preliminary running times of a prototype implementation of the method are reported.
Cristian R Rojas - One of the best experts on this subject based on the ideXlab platform.
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a stochastic multi armed bandit approach to nonparametric h norm estimation
Conference on Decision and Control, 2017Co-Authors: Matias I Muller, Patricio E Valenzuela, Alexandre Proutiere, Cristian R RojasAbstract:We study the problem of estimating the largest gain of an unknown linear and time-Invariant Filter, which is also known as the H ∞ norm of the system. By using ideas from the stochastic multi-armed bandit framework, we present a new algorithm that sequentially designs an input signal in order to estimate this quantity by means of input-output data. The algorithm is shown empirically to beat an asymptotically optimal method, known as Thompson Sampling, in the sense of its cumulative regret function. Finally, for a general class of algorithms, a lower bound on the performance of finding the H ∞ norm is derived.
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a stochastic multi armed bandit approach to nonparametric h infinity norm estimation
Conference on Decision and Control, 2017Co-Authors: Matias I Mueller, Patricio E Valenzuela, Alexandre Proutiere, Cristian R RojasAbstract:We study the problem of estimating the largest gain of an unknown linear and time-Invariant Filter, which is also known as the H-infinity norm of the system. By using ideas from the stochastic mult ...
Liyan Chen - One of the best experts on this subject based on the ideXlab platform.
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Undirected Graphs: Is the Shift-Enabled Condition Trivial or Necessary?
2019Co-Authors: Liyan Chen, Samuel Cheng, Lina Stankovic, Vladimir StankovicAbstract:It has recently been shown that, contrary to the wide belief that a shift-enabled condition (necessary for any shift-Invariant Filter to be representable by a graph shift matrix) can be ignored because any non-shift-enabled matrix can be converted to a shift-enabled matrix, such a conversion in general may not hold for a directed graph with non-symmetric shift matrix. This paper extends this prior work, focusing on undirected graphs where the shift matrix is generally symmetric. We show that while, in this case, the shift matrix can be converted to satisfy the original shift-enabled condition, the converted matrix is not associated with the original graph, that is, it does not capture anymore the structure of the graph signal. We show via a counterexample, that a non-shift-enabled matrix cannot be converted to a shift-enabled one and still maintain the topological structure of the underlying graph, which is necessary to facilitate localized signal processing.
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Undirected graphs: is the shift-enabled condition trivial or necessary?.
arXiv: Signal Processing, 2018Co-Authors: Liyan Chen, Samuel Cheng, Lina Stankovic, Vladimir StankovicAbstract:It has recently been shown that, contrary to the wide belief that a shift-enabled condition (necessary for any shift-Invariant Filter to be representable by a graph shift matrix) can be ignored because any non-shift-enabled matrix can be converted to a shift-enabled matrix, such a conversion in general may not hold for a directed graph with non-symmetric shift matrix. This letter extends this prior work, focusing on undirected graphs where the shift matrix is generally symmetric. We show that while, in this case, the shift matrix can be converted to satisfy the original shift-enabled condition, the converted matrix is not associated with the original graph, that is, it does not capture anymore the structure of the graph signal. We show via a counterexample, that a non-shift-enabled matrix cannot be converted to a shift-enabled one and still maintain the topological structure of the underlying graph, which is necessary to facilitate localized signal processing.
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Shift-enabled graphs: Graphs where shift-Invariant Filters are representable as polynomials of shift operations
IEEE Signal Processing Letters, 2018Co-Authors: Liyan Chen, Samuel Cheng, Vladimir Stankovic, Lina StankovicAbstract:In digital signal processing, shift-Invariant Filters can be represented as a polynomial expansion of a shift operation,that is, the Z-transform representation. When extended to graph signal processing (GSP), this would mean that a shift-Invariant graph Filter can be represented as a polynomial of the adjacency (shift) matrix of the graph. However, the characteristic and minimum polynomials of the adjacency matrix must be identical for the property to hold. While it has been suggested that this condition might be ignored as it is always possible to find a polynomial transform to represent the original adjacency matrix by another adjacency matrix that satisfies the condition, this letter shows that a Filter that is shift Invariant in terms of the original graph may not be shift Invariant anymore under the modified graph and vice versa. We introduce the notion of "shift-enabled graph" for graphs that satisfy the aforementioned condition, and present a concrete example of a graph that is not "shift-enabled" and a shift-Invariant Filter that is not a polynomial of the shift operation matrix. The result provides a deeper understanding of shift-Invariant Filters when applied in GSP and shows that further investigation of shift-enabled graphs is needed to make it applicable to practical scenarios.
