The Experts below are selected from a list of 118146 Experts worldwide ranked by ideXlab platform
R.m. Nelms - One of the best experts on this subject based on the ideXlab platform.
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Centralized Online Algorithm for Optimal Energy Distribution in Connected Microgrid
Online Algorithms for Optimal Energy Distribution in Microgrids, 2015Co-Authors: Yu Wang, Shiwen Mao, R.m. NelmsAbstract:This chapter investigates a distributed Online Algorithm for power distribution in a connected MG, based on the centralized Algorithm presented in Chap. 2. In this chapter, we take into account more practical factors, such as the user privacy and the distributed control manner. Based on the model introduced in National Institute of Standard and Technology, we first present a formulation that captures the key design factors such as user’s utility, grid load smoothing, and energy provisioning cost. The problem is shown to be convex and can be solved with a centralized Online Algorithm proposed in Chap. 2. We then develop a distributed Online Algorithm that decomposes and solves the Online problem in a distributed manner, and prove that the distributed Online solution is asymptotically optimal. The proposed distributed Online Algorithm is also practical and mitigates the user privacy issue by not sharing user utility functions. It is evaluated with trace-driven simulations and shown to outperform a benchmark scheme.
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Distributed Online Algorithm for Optimal Real-Time Energy Distribution in the Smart Grid
IEEE Internet of Things Journal, 2014Co-Authors: Yu Wang, Shiwen Mao, R.m. NelmsAbstract:In recent years, the smart grid has been recognized as an important form of the Internet of Things (IoT). The two-way energy and information flows in a smart gird, together with the smart devices, bring about new perspectives to energy management. This paper investigates a distributed Online Algorithm for electricity distribution in a smart grid environment. We first present a formulation that captures the key design factors such as user’s utility, grid load smoothing, and energy provisioning cost. The problem is shown to be convex and can be solved with a centralized Online Algorithm that only requires present information about users and the grid in our prior work. In this paper, we develop a distributed Online Algorithm that decomposes and solves the Online problem in a distributed manner, and prove that the distributed Online solution is asymptotically optimal. The proposed distributed Online Algorithm is also practical and mitigates the user privacy issue by not sharing user utility functions. It is evaluated with trace-driven simulations and shown to outperform a benchmark scheme.
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GLOBECOM - A distributed Online Algorithm for optimal real-time energy distribution in smart grid
2013 IEEE Global Communications Conference (GLOBECOM), 2013Co-Authors: Yu Wang, Shiwen Mao, R.m. NelmsAbstract:The two-way energy and information flows in a smart gird, together with the smart devices, bring new perspectives to energy management and demand response. This paper investigates a distributed Online Algorithm for electricity energy distribution in a smart grid environment. We first present a formulation that captures the key design factors such as user utility, grid load smoothing, and energy provisioning cost. The problem is shown to be convex and can be solved with an Online Algorithm that only requires present information about users and the grid in our prior work. In this paper, we develop a distributed Online Algorithm which decomposes and solves the Online problem in a distributed manner, and prove that the distributed Online solution is asymptotically optimal. The proposed distributed Online Algorithm is also practical and effective for user privacy protection. It is evaluated with trace-driven simulations and shown to outperform a benchmark scheme.
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Online Algorithm for Optimal Real-Time Energy Distribution in the Smart Grid
IEEE Transactions on Emerging Topics in Computing, 2013Co-Authors: Yu Wang, Shiwen Mao, R.m. NelmsAbstract:The two-way energy and information flows in a smart grid, together with the smart devices, bring new perspectives to energy management and demand response. This paper investigates an Online Algorithm for electricity energy distribution in a smart grid environment. We first present a formulation that captures the key design factors such as user's utility and cost, grid load smoothing, dynamic pricing, and energy provisioning cost. The problem is shown to be convex and can be solved with an offline Algorithm if future user and grid related information are known a priori. We then develop an Online Algorithm that only requires past and present information about users and the grid, and prove that the Online solution is asymptotically optimal. The proposed energy distribution framework and the Online Algorithm are quite general, suitable for a wide range of utility, cost, and pricing functions. It is evaluated with trace-driven simulations and shown to outperform a benchmark scheme.
Yu Wang - One of the best experts on this subject based on the ideXlab platform.
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Centralized Online Algorithm for Optimal Energy Distribution in Connected Microgrid
Online Algorithms for Optimal Energy Distribution in Microgrids, 2015Co-Authors: Yu Wang, Shiwen Mao, R.m. NelmsAbstract:This chapter investigates a distributed Online Algorithm for power distribution in a connected MG, based on the centralized Algorithm presented in Chap. 2. In this chapter, we take into account more practical factors, such as the user privacy and the distributed control manner. Based on the model introduced in National Institute of Standard and Technology, we first present a formulation that captures the key design factors such as user’s utility, grid load smoothing, and energy provisioning cost. The problem is shown to be convex and can be solved with a centralized Online Algorithm proposed in Chap. 2. We then develop a distributed Online Algorithm that decomposes and solves the Online problem in a distributed manner, and prove that the distributed Online solution is asymptotically optimal. The proposed distributed Online Algorithm is also practical and mitigates the user privacy issue by not sharing user utility functions. It is evaluated with trace-driven simulations and shown to outperform a benchmark scheme.
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Distributed Online Algorithm for Optimal Real-Time Energy Distribution in the Smart Grid
IEEE Internet of Things Journal, 2014Co-Authors: Yu Wang, Shiwen Mao, R.m. NelmsAbstract:In recent years, the smart grid has been recognized as an important form of the Internet of Things (IoT). The two-way energy and information flows in a smart gird, together with the smart devices, bring about new perspectives to energy management. This paper investigates a distributed Online Algorithm for electricity distribution in a smart grid environment. We first present a formulation that captures the key design factors such as user’s utility, grid load smoothing, and energy provisioning cost. The problem is shown to be convex and can be solved with a centralized Online Algorithm that only requires present information about users and the grid in our prior work. In this paper, we develop a distributed Online Algorithm that decomposes and solves the Online problem in a distributed manner, and prove that the distributed Online solution is asymptotically optimal. The proposed distributed Online Algorithm is also practical and mitigates the user privacy issue by not sharing user utility functions. It is evaluated with trace-driven simulations and shown to outperform a benchmark scheme.
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GLOBECOM - A distributed Online Algorithm for optimal real-time energy distribution in smart grid
2013 IEEE Global Communications Conference (GLOBECOM), 2013Co-Authors: Yu Wang, Shiwen Mao, R.m. NelmsAbstract:The two-way energy and information flows in a smart gird, together with the smart devices, bring new perspectives to energy management and demand response. This paper investigates a distributed Online Algorithm for electricity energy distribution in a smart grid environment. We first present a formulation that captures the key design factors such as user utility, grid load smoothing, and energy provisioning cost. The problem is shown to be convex and can be solved with an Online Algorithm that only requires present information about users and the grid in our prior work. In this paper, we develop a distributed Online Algorithm which decomposes and solves the Online problem in a distributed manner, and prove that the distributed Online solution is asymptotically optimal. The proposed distributed Online Algorithm is also practical and effective for user privacy protection. It is evaluated with trace-driven simulations and shown to outperform a benchmark scheme.
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Online Algorithm for Optimal Real-Time Energy Distribution in the Smart Grid
IEEE Transactions on Emerging Topics in Computing, 2013Co-Authors: Yu Wang, Shiwen Mao, R.m. NelmsAbstract:The two-way energy and information flows in a smart grid, together with the smart devices, bring new perspectives to energy management and demand response. This paper investigates an Online Algorithm for electricity energy distribution in a smart grid environment. We first present a formulation that captures the key design factors such as user's utility and cost, grid load smoothing, dynamic pricing, and energy provisioning cost. The problem is shown to be convex and can be solved with an offline Algorithm if future user and grid related information are known a priori. We then develop an Online Algorithm that only requires past and present information about users and the grid, and prove that the Online solution is asymptotically optimal. The proposed energy distribution framework and the Online Algorithm are quite general, suitable for a wide range of utility, cost, and pricing functions. It is evaluated with trace-driven simulations and shown to outperform a benchmark scheme.
Shiwen Mao - One of the best experts on this subject based on the ideXlab platform.
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Centralized Online Algorithm for Optimal Energy Distribution in Connected Microgrid
Online Algorithms for Optimal Energy Distribution in Microgrids, 2015Co-Authors: Yu Wang, Shiwen Mao, R.m. NelmsAbstract:This chapter investigates a distributed Online Algorithm for power distribution in a connected MG, based on the centralized Algorithm presented in Chap. 2. In this chapter, we take into account more practical factors, such as the user privacy and the distributed control manner. Based on the model introduced in National Institute of Standard and Technology, we first present a formulation that captures the key design factors such as user’s utility, grid load smoothing, and energy provisioning cost. The problem is shown to be convex and can be solved with a centralized Online Algorithm proposed in Chap. 2. We then develop a distributed Online Algorithm that decomposes and solves the Online problem in a distributed manner, and prove that the distributed Online solution is asymptotically optimal. The proposed distributed Online Algorithm is also practical and mitigates the user privacy issue by not sharing user utility functions. It is evaluated with trace-driven simulations and shown to outperform a benchmark scheme.
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Distributed Online Algorithm for Optimal Real-Time Energy Distribution in the Smart Grid
IEEE Internet of Things Journal, 2014Co-Authors: Yu Wang, Shiwen Mao, R.m. NelmsAbstract:In recent years, the smart grid has been recognized as an important form of the Internet of Things (IoT). The two-way energy and information flows in a smart gird, together with the smart devices, bring about new perspectives to energy management. This paper investigates a distributed Online Algorithm for electricity distribution in a smart grid environment. We first present a formulation that captures the key design factors such as user’s utility, grid load smoothing, and energy provisioning cost. The problem is shown to be convex and can be solved with a centralized Online Algorithm that only requires present information about users and the grid in our prior work. In this paper, we develop a distributed Online Algorithm that decomposes and solves the Online problem in a distributed manner, and prove that the distributed Online solution is asymptotically optimal. The proposed distributed Online Algorithm is also practical and mitigates the user privacy issue by not sharing user utility functions. It is evaluated with trace-driven simulations and shown to outperform a benchmark scheme.
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GLOBECOM - A distributed Online Algorithm for optimal real-time energy distribution in smart grid
2013 IEEE Global Communications Conference (GLOBECOM), 2013Co-Authors: Yu Wang, Shiwen Mao, R.m. NelmsAbstract:The two-way energy and information flows in a smart gird, together with the smart devices, bring new perspectives to energy management and demand response. This paper investigates a distributed Online Algorithm for electricity energy distribution in a smart grid environment. We first present a formulation that captures the key design factors such as user utility, grid load smoothing, and energy provisioning cost. The problem is shown to be convex and can be solved with an Online Algorithm that only requires present information about users and the grid in our prior work. In this paper, we develop a distributed Online Algorithm which decomposes and solves the Online problem in a distributed manner, and prove that the distributed Online solution is asymptotically optimal. The proposed distributed Online Algorithm is also practical and effective for user privacy protection. It is evaluated with trace-driven simulations and shown to outperform a benchmark scheme.
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Online Algorithm for Optimal Real-Time Energy Distribution in the Smart Grid
IEEE Transactions on Emerging Topics in Computing, 2013Co-Authors: Yu Wang, Shiwen Mao, R.m. NelmsAbstract:The two-way energy and information flows in a smart grid, together with the smart devices, bring new perspectives to energy management and demand response. This paper investigates an Online Algorithm for electricity energy distribution in a smart grid environment. We first present a formulation that captures the key design factors such as user's utility and cost, grid load smoothing, dynamic pricing, and energy provisioning cost. The problem is shown to be convex and can be solved with an offline Algorithm if future user and grid related information are known a priori. We then develop an Online Algorithm that only requires past and present information about users and the grid, and prove that the Online solution is asymptotically optimal. The proposed energy distribution framework and the Online Algorithm are quite general, suitable for a wide range of utility, cost, and pricing functions. It is evaluated with trace-driven simulations and shown to outperform a benchmark scheme.
Jiming Chen - One of the best experts on this subject based on the ideXlab platform.
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An Online Algorithm for Data Collection by Multiple Sinks in Wireless-Sensor Networks
IEEE Transactions on Control of Network Systems, 2018Co-Authors: Ruilong Deng, Jiming ChenAbstract:Data collection by multiple sinks is a fundamental problem in wireless-sensor networks. Existing works focused on designing the optimal offline methods provided that the number and positions of sensors and sinks (or trajectories of mobile sinks) are predetermined. This may not be practical, because although sensors are cheap, sinks are quite expensive in reality. A more practical scenario is that sinks are deployed step by step during the network operation due budget constraints, and we do not know the number, positions, and capacities of sinks a priori. In this paper, we investigate the problem of data collection with multiple sinks, and design a suboptimal Online Algorithm via a primal-dual approach, requiring very little priori knowledge. We theoretically derive the competitive ratio of the Online Algorithm, and further improve it by finding the optimal sink location with an approximation ratio. We also analyze the computational complexity of the improved approach. Extensive simulations are conducted to demonstrate the performance of the proposed Online Algorithm and performance-complexity tradeoff.
Andrea Giovannucci - One of the best experts on this subject based on the ideXlab platform.
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normcorre an Online Algorithm for piecewise rigid motion correction of calcium imaging data
Journal of Neuroscience Methods, 2017Co-Authors: Eftychios A Pnevmatikakis, Andrea GiovannucciAbstract:Abstract Background Motion correction is a challenging pre-processing problem that arises early in the analysis pipeline of calcium imaging data sequences. The motion artifacts in two-photon microscopy recordings can be non-rigid, arising from the finite time of raster scanning and non-uniform deformations of the brain medium. New method We introduce an Algorithm for fast Non-Rigid Motion Correction (NoRMCorre) based on template matching. NoRMCorre operates by splitting the field of view (FOV) into overlapping spatial patches along all directions. The patches are registered at a sub-pixel resolution for rigid translation against a regularly updated template. The estimated alignments are subsequently up-sampled to create a smooth motion field for each frame that can efficiently approximate non-rigid artifacts in a piecewise-rigid manner. Existing methods Existing approaches either do not scale well in terms of computational performance or are targeted to non-rigid artifacts arising just from the finite speed of raster scanning, and thus cannot correct for non-rigid motion observable in datasets from a large FOV. Results NoRMCorre can be run in an Online mode resulting in comparable to or even faster than real time motion registration of streaming data. We evaluate its performance with simple yet intuitive metrics and compare against other non-rigid registration methods on simulated data and in vivo two-photon calcium imaging datasets. Open source Matlab and Python code is also made available. Conclusions The proposed method and accompanying code can be useful for solving large scale image registration problems in calcium imaging, especially in the presence of non-rigid deformations.
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normcorre an Online Algorithm for piecewise rigid motion correction of calcium imaging data
bioRxiv, 2017Co-Authors: Eftychios A Pnevmatikakis, Andrea GiovannucciAbstract:Motion correction is a challenging pre-processing problem that arises early in the analysis pipeline of calcium imaging data sequences. Here we introduce an Algorithm for fast Non-Rigid Motion Correction (NoRMCorre) based on template matching. \norm operates by splitting the field of view into overlapping spatial patches that are registered for rigid translation against a continuously updated template. The estimated alignments are subsequently up-sampled to create a smooth motion field for each frame that can efficiently approximate non-rigid motion in a piecewise-rigid manner. \norm allows for subpixel registration and can be run in an Online mode resulting in comparable to or even faster than real time motion registration on streaming data. We evaluate the performance of the proposed method with simple yet intuitive metrics and compare against other non-rigid registration methods on two-photon calcium imaging datasets. Open source Matlab and Python code is also made available.
