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An Upgrading Algorithm with Optimal Power Law

Or Ordentlich, Ido Tal, Amos Lapidoth, Stefan M. Moser
2020
This power law of L is optimal.  ...  In this paper, we present an algorithm that produces an upgraded channel Q from W , as a function of PX and the required output alphabet size of Q, denoted L.  ...  Our method produces such a Q for which I(P X , Q) − I(P X , W ) = O(L −2/(|X |−1) ) . (2) By [3, Section IV], the above power law of L is optimal. III.  ... 
doi:10.3929/ethz-b-000402700 fatcat:qthq4axbwffwjpfnd5yiekgd3u

Tunable QoS-aware network survivability

Jose Yallouz, Ariel Orda
2013 2013 Proceedings IEEE INFOCOM  
Coping with network failures has been recognized as an issue of major importance in terms of social security, stability and prosperity.  ...  Then, we establish efficient algorithmic schemes for optimizing the level of survivability under additive end-to-end QoS bounds.  ...  For each generated network and survivability level constraint S in the range of [0.9, 1] with intervals of 0.005, we employed the CT-TSMQ Algorithm for the Power-Law class and for the Waxman class.  ... 
doi:10.1109/infcom.2013.6566883 dblp:conf/infocom/YallouzO13 fatcat:gwpx4ojjz5erxbgv3gzoku3bci

Minimizing the Total Cost of WAMS Using Artificial Electric Field Algorithm

Batool. B. Al-Khraisat, Ali. S. AL-Dmour, Khaled. S. Al Maitah
2021 International Journal of Energy  
However, there are several approaches to solve the optimal PMU placement (OPP) with various optimization algorithms.  ...  Additionally, the results have been compared with other optimization algorithm, and it demonstrates that the AEFA is efficient to solve the OPP problem.  ...  In this paper, the total installation cost of WAMS is considered as objective function to determine the optimal number and location of PMUs in an electrical power system.  ... 
doi:10.46300/91010.2021.15.9 fatcat:s5oqmbnawffdvcnros3mcpsgbm

Tunable QoS-Aware Network Survivability

Jose Yallouz, Ariel Orda
2017 IEEE/ACM Transactions on Networking  
Coping with network failures has been recognized as an issue of major importance in terms of social security, stability and prosperity.  ...  Then, we establish efficient algorithmic schemes for optimizing the level of survivability under additive end-to-end QoS bounds.  ...  For each generated network and survivability level constraint S in the range of [0.9, 1] with intervals of 0.005, we employed the CT-TSMQ Algorithm for the Power-Law class and for the Waxman class.  ... 
doi:10.1109/tnet.2016.2606342 fatcat:6gkfy4qsqvhhhnmgqio336apuy

Resilient Transmission Grid Design: AC Relaxation vs. DC approximation [article]

Harsha Nagarajan, Russell Bent, Pascal Van Hentenryck, Scott Backhaus, Emre Yamangil
2017 arXiv   pre-print
.), extreme weather events pose an enormous threat to the electric power transmission systems and the associated socio-economic systems that depend on reliable delivery of electric power.  ...  In this paper, we develop a model and tractable methods for optimizing the upgrade of transmission systems through a combination of hardening existing components, adding redundant lines, switches, generators  ...  Comparison of total upgrade costs and ψ for optimal upgrade solutions with and without FACTS devices. TABLE II COMPARISON II OF WALL TIME (SEC.)  ... 
arXiv:1703.05893v1 fatcat:jplkzumuwvcovnu7r4of5tfera

Communication-Constrained Expansion Planning for Resilient Distribution Systems [article]

Geunyeong Byeon and Pascal Van Hentenryck and Russell Bent and Harsha Nagarajan
2018 arXiv   pre-print
The ORDPDC model and branch-and-price algorithm were evaluated on a variety of test cases with varying disaster inten- sities and network topologies.  ...  The paper proposes an exact branch-and-price algorithm for the ORDPDC which features a strong lower bound and a variety of acceleration schemes to address degeneracy.  ...  The goal of the ORDPDC is to find an optimal upgrade profile for the cyber-physical system G that is resilient with respect to the damage scenarios in D.  ... 
arXiv:1801.03520v1 fatcat:6wdixktecbgjdlcce2zfp2cbaq

Tunable QoS-Aware Network Survivability [article]

Jose Yallouz, Ariel Orda
2016 arXiv   pre-print
Coping with network failures has been recognized as an issue of major importance in terms of social security, stability and prosperity.  ...  Then, we establish efficient algorithmic schemes for optimizing the level of survivability under additive end-to-end QoS bounds.  ...  For each generated network and survivability level constraint S in the range of [0.9, 1] with intervals of 0.005, we employed the CT-TSMQ Algorithm for the Power-Law class and for the Waxman class.  ... 
arXiv:1608.08660v1 fatcat:irr3kx6sqnh7lhnc7kwkdutrg4

Optimizing the Date of an Upgrading Investment in a Data Network

F. Morlot, B. Fourestie, S.-E. Elayoubi
2007 Vehicular Technology Conference-Fall (VTC-FALL), Proceedings, IEEE  
Such upgrades allow them to increase the capacity, and provide adequate Quality of Service (QoS). In this paper we propose a general framework for deriving the optimal date for a network upgrade.  ...  The upgrade should hence be performed when the loss of profit, derived using analytical capacity expressions, exceeds the expected discount.  ...  The strategy we adopted is: • first, analytically model the operator profit and the customer satisfaction; • second, compute the optimal upgrading date with an actualization algorithm.  ... 
doi:10.1109/vetecf.2007.40 dblp:conf/vtc/MorlotFE07 fatcat:tar2ze5verasteqi3763ug6x7e

Greedy-Merge Degrading has Optimal Power-Law [article]

Assaf Kartowsky, Ido Tal
2017 arXiv   pre-print
This upper bound is within a constant factor of an algorithm-independent lower bound. Thus, we establish that greedy-merge is optimal in the power-law sense.  ...  The third result is an efficient algorithm for optimal upgrading, in the binary-input case. That is, we are given a channel and an input distribution.  ...  Implicitly, we apply the optimal upgrading algorithm, to get from an alphabet of |Y| output letters to one with |Y| − 1 output letters.  ... 
arXiv:1703.04923v1 fatcat:6d5mrlz2ffgr7g4czmbkievc3i

It's not easy being green

Peter Xiang Gao, Andrew R. Curtis, Bernard Wong, Srinivasan Keshav
2012 Computer communication review  
It allows an operator to navigate the threeway tradeoff between access latency, carbon footprint, and electricity costs and to determine an optimal datacenter upgrade plan in response to increases in traffic  ...  In this paper, we describe FORTE: Flow Optimization based framework for request-Routing and Traffic Engineering.  ...  Such providers can use FORTE as-is to optimize their request-routing algorithms and datacenter upgrades.  ... 
doi:10.1145/2377677.2377719 fatcat:sd3ayu4kxjhsjgqcuojfirysuy

An Extensive Study on Gravitational Search Algorithm

2022 Materials and its Characterization  
Gravitational search algorithm is a naturally occurring algorithm based on Newton's mathematical model of the law of gravitation and motion.  ...  Over the course of a decade, researchers have provided many variants of the gravitational search algorithm by modifying its parameters to effectively solve complex optimization problems.  ...  The gravitational search algorithm is a recent natural-inspired algorithm proposed to solve upgrade Problems based on the law of gravity.  ... 
doi:10.46632/mc/1/1/2 fatcat:n7z6uvvstvfqho2gfyxfwgezb4

Towards self-predicting systems: What if you could ask 'what-if'?

ENO THERESKA, DUSHYANTH NARAYANAN, GREGORY R. GANGER
2006 Knowledge engineering review (Print)  
This reactive approach requires expertise regarding of system behavior, making it difficult to deal with unforeseen uses of a system's resources and leading to system unpredictability and large system  ...  Through two concrete management problems, automating system upgrades and deciding on service migrations, we identify system design changes that enable a system to answer What...if... questions about itself  ...  Operational laws should be used when a new system is built, together with simulation of internal algorithms.  ... 
doi:10.1017/s0269888906000920 fatcat:h7w2o2z4brelncw5zvrjjg7pne

Forecasting Carbon Emissions Related to Energy Consumption in Beijing-Tianjin-Hebei Region Based on Grey Prediction Theory and Extreme Learning Machine Optimized by Support Vector Machine Algorithm

Menglu Li, Wei Wang, Gejirifu De, Xionghua Ji, Zhongfu Tan
2018 Energies  
The result of SVM-ELM model was compared with the forecasting results of SVM (Support Vector Machine Algorithm) and ELM (Extreme Learning Machine) algorithm.  ...  Secondly, the kernel function of the support vector machine was applied to the extreme learning machine algorithm to optimize the connection weight matrix between the original hidden layer and the output  ...  [24] used an improved Gaussian process regression method and particle swarm algorithm to predict carbon emissions.  ... 
doi:10.3390/en11092475 fatcat:zn3akkqctng53ncc5lldjy3hh4

Housing peak shaving algorithm (HPSA) with plug-in hybrid electric vehicles (PHEVs): Vehicle-to-Home (V2H) and Vehicle-to-Grid (V2G) concepts

Harun Turker, Ahmad Hably, Seddik Bacha
2013 4th International Conference on Power Engineering, Energy and Electrical Drives  
In this paper we use Dynamic Programming (DP) algorithm for optimal charged the PEV.  ...  This vast deployment will create challenges of integration in the power system. Especially in the residential areas where mostly charging will take place.  ...  Offline Online Optimization problem formulation Consistent with the intended application, the DP algorithm determines the optimal charge power that meets the constraints of the system.  ... 
doi:10.1109/powereng.2013.6635704 fatcat:5tnoa3yfl5cmhfvtnlv2e3nak4

Chapter 3: Plasma Control in ASDEX Upgrade

Vitus Mertens, Gerhard Raupp, Wolfgang Treutterer
2003 Fusion science and technology  
The supervisor is fully integrated with a layered machine protection system.  ...  The feedback control algorithm is based on a matrix proportional-integralderivative method, adapted to handle saturation of coil currents, excess of coil forces, or to balance loads among coils.  ...  Finally, 14 signals were selected empirically as inputs for statistically determined power law scalings and classification boundaries. An example is given in Fig. 7 .  ... 
doi:10.13182/fst03-a401 fatcat:bl2vo36lm5eh3mwk4ppax2bzqu
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