scholarly journals CFedAvg: Achieving Efficient Communication and Fast Convergence in Non-IID Federated Learning

Author(s):  
Haibo Yang ◽  
Jia Liu ◽  
Elizabeth S. Bentley
2021 ◽  
Vol 11 (3) ◽  
pp. 1211
Author(s):  
En-Chih Chang ◽  
Chun-An Cheng ◽  
Rong-Ching Wu

This paper develops a full-bridge DC-AC converter, which uses a robust optimal tracking control strategy to procure a high-quality sine output waveshape even in the presence of unpredictable intermissions. The proposed strategy brings out the advantages of non-singular fast convergent terminal attractor (NFCTA) and chaos particle swarm optimization (CPSO). Compared with a typical TA, the NFCTA affords fast convergence within a limited time to the steady-state situation, and keeps away from the possibility of singularity through its sliding surface design. It is worth noting that once the NFCTA-controlled DC-AC converter encounters drastic changes in internal parameters or the influence of external non-linear loads, the trembling with low-control precision will occur and the aggravation of transient and steady-state performance yields. Although the traditional PSO algorithm has the characteristics of simple implementation and fast convergence, the search process lacks diversity and converges prematurely. So, it is impossible to deviate from the local extreme value, resulting in poor solution quality or search stagnation. Thereby, an improved version of traditional PSO called CPSO is used to discover global optimal NFCTA parameters, which can preclude precocious convergence to local solutions, mitigating the tremor as well as enhancing DC-AC converter performance. By using the proposed stable closed-loop full-bridge DC-AC converter with a hybrid strategy integrating NFCTA and CPSO, low total harmonic distortion (THD) output-voltage and fast dynamic load response are generated under nonlinear rectifier-type load situations and during sudden load changes, respectively. Simulation results are done by the Matlab/Simulink environment, and experimental results of a digital signal processor (DSP) controlled full-bridge DC-AC converter prototype confirm the usefulness of the proposed strategy.


2011 ◽  
Vol 63 (3) ◽  
pp. 691-709 ◽  
Author(s):  
Abhinav Vishnu ◽  
Shuaiwen Song ◽  
Andres Marquez ◽  
Kevin Barker ◽  
Darren Kerbyson ◽  
...  

2021 ◽  
Vol 104 (2) ◽  
pp. 003685042110254
Author(s):  
Armaghan Mohsin ◽  
Yazan Alsmadi ◽  
Ali Arshad Uppal ◽  
Sardar Muhammad Gulfam

In this paper, a novel modified optimization algorithm is presented, which combines Nelder-Mead (NM) method with a gradient-based approach. The well-known Nelder Mead optimization technique is widely used but it suffers from convergence issues in higher dimensional complex problems. Unlike the NM, in this proposed technique we have focused on two issues of the NM approach, one is shape of the simplex which is reshaped at each iteration according to the objective function, so we used a fixed shape of the simplex and we regenerate the simplex at each iteration and the second issue is related to reflection and expansion steps of the NM technique in each iteration, NM used fixed value of [Formula: see text], that is, [Formula: see text]  = 1 for reflection and [Formula: see text]  = 2 for expansion and replace the worst point of the simplex with that new point in each iteration. In this way NM search the optimum point. In proposed algorithm the optimum value of the parameter [Formula: see text] is computed and then centroid of new simplex is originated at this optimum point and regenerate the simplex with this centroid in each iteration that optimum value of [Formula: see text] will ensure the fast convergence of the proposed technique. The proposed algorithm has been applied to the real time implementation of the transversal adaptive filter. The application used to demonstrate the performance of the proposed technique is a well-known convex optimization problem having quadratic cost function, and results show that the proposed technique shows fast convergence than the Nelder-Mead method for lower dimension problems and the proposed technique has also good convergence for higher dimensions, that is, for higher filter taps problem. The proposed technique has also been compared with stochastic techniques like LMS and NLMS (benchmark) techniques. The proposed technique shows good results against LMS. The comparison shows that the modified algorithm guarantees quite acceptable convergence with improved accuracy for higher dimensional identification problems.


Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 461
Author(s):  
Yongbin Yim ◽  
Euisin Lee ◽  
Seungmin Oh

Recently, the demand for monitoring a certain object covering large and dynamic scopes such as wildfires, glaciers, and radioactive contaminations, called large-scale fluid objects (LFOs), is coming to the fore due to disasters and catastrophes that lately happened. This article provides an analytic comparison of such LFOs and typical individual mobile objects (IMOs), namely animals, humans, vehicles, etc., to figure out inherent characteristics of LFOs. Since energy-efficient monitoring of IMOs has been intensively researched so far, but such inherent properties of LFOs hinder the direct adaptation of legacy technologies for IMOs, this article surveys technological evolution and advances of LFOs along with ones of IMOs. Based on the communication cost perspective correlated to energy efficiency, three technological phases, namely concentration, integration, and abbreviation, are defined in this article. By reviewing various methods and strategies employed by existing works with the three phases, this article concludes that LFO monitoring should achieve not only decoupling from node density and network structure but also trading off quantitative reduction against qualitative loss as architectural principles of energy-efficient communication to break through inherent properties of LFOs. Future research challenges related to this topic are also discussed.


2021 ◽  
Vol 11 (2) ◽  
pp. 25
Author(s):  
Evelina Forno ◽  
Alessandro Salvato ◽  
Enrico Macii ◽  
Gianvito Urgese

SpiNNaker is a neuromorphic hardware platform, especially designed for the simulation of Spiking Neural Networks (SNNs). To this end, the platform features massively parallel computation and an efficient communication infrastructure based on the transmission of small packets. The effectiveness of SpiNNaker in the parallel execution of the PageRank (PR) algorithm has been tested by the realization of a custom SNN implementation. In this work, we propose a PageRank implementation fully realized with the MPI programming paradigm ported to the SpiNNaker platform. We compare the scalability of the proposed program with the equivalent SNN implementation, and we leverage the characteristics of the PageRank algorithm to benchmark our implementation of MPI on SpiNNaker when faced with massive communication requirements. Experimental results show that the algorithm exhibits favorable scaling for a mid-sized execution context, while highlighting that the performance of MPI-PageRank on SpiNNaker is bounded by memory size and speed limitations on the current version of the hardware.


2016 ◽  
Vol 45 (2) ◽  
pp. 233-252
Author(s):  
Pepijn Viaene ◽  
Alain De Wulf ◽  
Philippe De Maeyer

Landmarks are ideal wayfinding tools to guide a person from A to B as they allow fast reasoning and efficient communication. However, very few path-finding algorithms start from the availability of landmarks to generate a path. In this paper, which focuses on indoor wayfinding, a landmark-based path-finding algorithm is presented in which the endpoint partition is proposed as spatial model of the environment. In this model, the indoor environment is divided into convex sub-shapes, called e-spaces, that are stable with respect to the visual information provided by a person’s surroundings (e.g. walls, landmarks). The algorithm itself implements a breadth-first search on a graph in which mutually visible e-spaces suited for wayfinding are connected. The results of a case study, in which the calculated paths were compared with their corresponding shortest paths, show that the proposed algorithm is a valuable alternative for Dijkstra’s shortest path algorithm. It is able to calculate a path with a minimal amount of actions that are linked to landmarks, while the path length increase is comparable to the increase observed when applying other path algorithms that adhere to natural wayfinding behaviour. However, the practicability of the proposed algorithm is highly dependent on the availability of landmarks and on the spatial configuration of the building.


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