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Optimizing Video Application Design for Phase-Change RAM-Based Main Memory

IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS 2012年第11期20卷 2011-2019页

作者： Kwon, Suknam Yoo, Sungjoo Lee, Sunggu Park, Jinpyo Pohang Univ Sci & Technol POSTECH Dept Elect Engn Pohang 790784 South Korea Samsung Elect Syst LSI Yongin 446711 Gyeonggi South Korea

Video applications including video codecs place a large traffic demand on main memory. Emerging memory technology, such as phase-change RAM (PRAM) tends to suffer from the write endurance problem, in which the maximum number of writes is limited. Thus, it is required to improve video application designs to adapt to the new requirements of emerging memory technology, i.e., to minimize the number of writes in terms of bit updates. In this paper, we present a way to optimize video application design for PRAM-based main memory. We propose two methods to resolve the write endurance problem: inter-block differential data encoding and inter-frame multiple experts. Experimental results show an average of 18.4% reduction in bit updates when compared to the best existing data encoding methods for PRAM.

关键词： data encoding differential writes phase-change RAM (PRAM) write endurance

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Robot navigation based on view sequences stored in a sparse distributed memory

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ROBOTICA 2012年第4期30卷 571-581页

作者： Mendes, Mateus Paulo Coimbra, A. Crisostomo, Manuel M. Polytech Inst Coimbra ESTGOH P-3400124 Oliveira Do Hosp Portugal Inst Syst & Robot P-3030290 Coimbra Portugal

Robot navigation is a large area of research, where many different approaches have already been tried, including navigation based on visual memories. The Sparse Distributed Memory (SDM) is a kind of associative memory based on the properties of high-dimensional binary spaces. It exhibits characteristics, such as tolerance to noise and incomplete data, ability to work with sequences and the possibility of one-shot learning. Those characteristics make it appealing to use for robot navigation. The approach followed here was to navigate a robot using sequences of visual memories stored into a SDM. The robot makes intelligent decisions, such as selecting only relevant images to store, adjusting memory parameters to the level of noise and inferring new paths from the learnt trajectories. The method of encoding the information may influence the tolerance of the SDM to noise and saturation. This paper reports novel results of the limits of the model under different typical navigation problems. The SDM showed to be very robust to illumination and scenario changes, occlusion and saturation. An algorithm to build a topological map of the environment based on the visual memories is also described.

关键词： Sparse distributed memory SDM Robot navigation data encoding Vision-based navigation

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Incremental encoding for erasure-coded cross-datacenters cloud storage

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2018年 87卷 527-537页

作者： Xu, Fangliang Wang, Yijie Ma, Xingkong Natl Univ Def Technol Natl Lab Parallel & Distributed Proc Changsha 410073 Hunan Peoples R China Natl Univ Def Technol Coll Comp Changsha 410073 Hunan Peoples R China

As a storage efficient approach, erasure coding has been adopted by many large-scale cloud storage systems to protect data from server and datacenter failures. To erasure-coded storage systems, it is critical to encode newly written data blocks and generate parity blocks efficiently. Existing encoding approaches include Striping encoding and Replicating encoding. They either incur too high network traffic or seriously degrade the I/O performance. In this paper, we propose Incremental encoding, a decentralized encoding framework for all linear erasure codes. To achieve the optimal write performance, Incremental encoding forwards newly written data blocks to multiple servers in a pipelining manner. To reduce network traffic, Incremental encoding combines newly written data blocks together incrementally at the same time when they flow through servers to generate parity blocks. Incremental encoding also caches intermediate parity blocks into memory to further reduce disk I/O. We evaluate Incremental encoding by theoretically analyzing the encoding overheads and conducting a series of experiments in both a single-datacenter environment and a cross-datacenters environment. Analysis and experiments show that Incremental encoding can achieve a much better trade-off between network traffic and I/O performance. Specially, compared with Replicating encoding, which has the optimal I/O performance, Incremental encoding has nearly the same I/O performance with 44.5%-48.4% less encoding traffic. Compared with Striping encoding, Incremental encoding has up to 90% better write performance and up to 108% read performance with 56.25%-73.6% more encoding traffic. 2018 Elsevier B.V. All rights reserved.

关键词： Cloud storage systems Cross datacenters Erasure code data encoding

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Replication vs erasure coding in data centric storage for wireless sensor networks

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COMPUTER NETWORKS 2015年第Feb.11期77卷 42-55页

作者： Albano, Michele Chessa, Stefano Polytech Inst Porto CISTER ISEP INESC TEC P-4200072 Oporto Portugal Univ Pisa Dept Comp Sci I-56127 Pisa Italy

In-network storage of data in wireless sensor networks contributes to reduce the communications inside the network and to favor data aggregation. In this paper, we consider the use of n out of m codes and data dispersal in combination to in-network storage. In particular, we provide an abstract model of in-network storage to show how n out of m codes can be used, and we discuss how this can be achieved in five cases of study. We also define a model aimed at evaluating the probability of correct data encoding and decoding, we exploit this model and simulations to show how, in the cases of study, the parameters of the n out of m codes and the network should be configured in order to achieve correct data coding and decoding with high probability. (C) 2014 Elsevier B.V. All rights reserved.

关键词： data availability data encoding In-network storage Redundant Residue Number Systems Wireless ad hoc networks

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Modulating Intelligent Surfaces for Multiuser MIMO Systems: Beamforming and Modulation Design

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IEEE TRANSACTIONS ON COMMUNICATIONS 2022年第5期70卷 3234-3249页

作者： Rehman, Haseeb Ur Bellili, Faouzi Mezghani, Amine Hossain, Ekram Univ Manitoba Dept Elect & Comp Engn Winnipeg MB R3T 2N2 Canada

This paper introduces a novel approach of utilizing the reconfigurable intelligent surface (RIS) for joint data modulation and signal beamforming in a multi-user downlink cellular network by leveraging the idea of backscatter communication. We present a general framework in which the RIS, referred to as modulating intelligent surface (MIS) in this paper, is used to: i) beamform the signals for a set of users whose data modulation is already performed by the base station (BS), and at the same time, ii) embed the data of a different set of users by passively modulating the deliberately sent carrier signals from the BS to the RIS. To maximize each user's spectral efficiency, a joint non-convex optimization problem is formulated under the sum minimum mean-square error (MMSE) criterion. Alternating optimization is used to divide the original joint problem into two tasks of: i) separately optimizing the MIS phase-shifts for passive beamforming along with data embedding for the BS- and MIS-served users, respectively, and ii) jointly optimizing the active precoder and the receive scaling factor for the BS- and MIS-served users, respectively. While the solution to the latter joint problem is found in closed-form using traditional optimization techniques, the optimal phase-shifts at the MIS are obtained by deriving the appropriate optimization-oriented vector approximate message passing (OOVAMP) algorithm. Moreover, the original joint problem is solved under both ideal and practical constraints on the MIS phase shifts, namely, the unimodular constraint and assuming each MIS element to be terminated by a variable reactive load. The proposed MIS-assisted scheme is compared against state-of-the-art RIS-assisted wireless communication schemes and simulation results reveal that it brings substantial improvements in terms of system throughput while supporting a much higher number of users.

关键词： Reconfigurable intelligent surface (RIS) RIS-assisted multi-user MIMO active and passive beamforming modulation data encoding backscatter communication modulating intelligent surface (MIS)

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Improved associative recall of binary data in volume holographic memories

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OPTICS COMMUNICATIONS 1999年第1-3期171卷 37-44页

作者： Betzos, GA Laisné, A Mitkas, PA Colorado State Univ Dept Elect & Comp Engn Ft Collins CO 80523 USA Colorado State Univ Ctr Optoelect Comp Syst Ft Collins CO 80523 USA

A new technique is presented that improves the results of associative recall in a volume holographic memory system A background is added to the normal search argument to increase the amount of optical power that is used to reconstruct the reference beams in the crystal. This is combined with post-processing of the captured image of the reference beams. The use of both the background and post-processing greatly improves the results by allowing associative recall using small arguments. In addition, the number of false hits is reduced and misses are virtually eliminated. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： volume holographic memories associative recall content-based search optical data storage data encoding

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Online Pricing and Resource Scheduling for Profit Maximization of Cloud Storage Providers

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IEEE TRANSACTIONS ON CLOUD COMPUTING 2024年第4期12卷 1186-1199页

作者： Lee, Kyungtae Kim, Yeongjin Inha Univ Dept Elect & Comp Engn Incheon 22212 South Korea

There is increasing competition among cloud object storage service (COSS) providers as the demand for COSSs grows. However, existing pricing models offered by commercial COSS providers fail to effectively adapt to changing client demand and resource supply. Consequently, many COSS providers are still grappling with operational challenges in maximizing their profits, such as pricing policy, load balancing, server scheduling, and energy management. In this paper, we propose a novel approach called time-dependent pricing and scheduling (TD-PnS), which is based on the Lyapunov-drift-minus-profit technique. To maximize the profits of COSS providers, TD-PnS enables joint and dynamic decision-making across several key factors that have been dealt with separately so far: (i) service pricing, (ii) CPU clock scaling and encoding scheduling, (iii) network scheduling, and (iv) energy storage management. We propose an enhanced version of TD-PnS, called TD-PnS-Adv, further to improve other aspects, such as system stabilization. Finally, through trace-driven simulations utilizing a real dataset, we demonstrate the superior performance of the proposed algorithms compared to existing algorithms and pricing models in terms of profit maximization.

关键词： Cloud computing Pricing Servers encoding Energy storage Renewable energy sources Electricity data encoding energy storage system object storage service provider time-dependent pricing

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Improved spiking neural network for intershaft bearing fault diagnosis

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JOURNAL OF MANUFACTURING SYSTEMS 2022年 65卷 208-219页

作者： Wang, Jun Li, Tianfu Sun, Chuang Yan, Ruqiang Chen, Xuefeng Xi An Jiao Tong Univ Dept Mech Engn Xian 710049 Shaanxi Peoples R China Ecole Polytech Fed Lausanne Lab Intelligent Maintenance & Operat Syst CH-1015 Lausanne Switzerland

The intershaft bearing is located between the high and low-pressure rotors of the aero-engine, where the working environment is harsh, the load variation range is large, and the lubrication and heat dissipation are poor. The fault of the intershaft bearing is sudden and will cause the engine to hold the shaft and break the shaft, which is more harmful than the ordinary bearings. In recent years, bearing intelligent fault diagnosis methods based on deep learning have been widely applied. However, most of the existing methods are mainly proposed based on second-generation neural networks. Spiking neural network (SNN), also known as the third-generation neural network, mimics the dynamics of the biological brain and is more powerful for processing time-series information. As we know, vibration data is a typical time-series data, SNN would have stronger feature extraction potential for it. In this paper, we propose an improved spiking neural network (ISNN) for intershaft bearing fault diagnosis. Specifically, we propose an encoding method to encode raw data into spike sequences and demonstrate that the encoding method is accurate and efficient. Then we derive the gradient relation in the ISNN and mathematically prove the replacement of invalid gradients in it. Furthermore, we compensate for the loss of information in forward propagation and simplify the process of backpropagation by constructing suitable spiking neurons. Finally, we test the ISNN on the fault dataset of intershaft bearings, and the results show that the proposed ISNN outperforms previous SNNs and typical second-generation neural networks.

关键词： Spiking neural network Intershaft bearing Fault diagnosis data encoding Surrogate gradient

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Use of MATLAB neural networks toolbox in a character recognition problem

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COMPUTER APPLICATIONS IN ENGINEERING EDUCATION 2005年第1期13卷 66-71页

作者： Trebar, M Univ Ljubljana Fac Chem & Informat Sci Dhaka 1000 Bangladesh

We present the use of the MATLAB Neural Network Toolbox (NN Toolbox) in simulations of neural networks. We suggest ways for undergraduate students to solve a character recognition problem with feed-forward neural networks. The software provides the user with a very simple way to define several neural network architectures with different parameters, The solution of the character recognition problem is described from the beginning: collecting the data, data encoding, defining the input-output mapping architecture to the training, and testing the neural networks with the NN Toolbox. (c) 2005 Wiley Periodicals, Inc.

关键词： character recognition input-output mapping data encoding neural networks

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Predictive vector quantisation for image compression

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ELECTRONICS LETTERS 1998年第24期34卷 2325-2326页

作者： Tsai, JC Hsieh, CH Chinese Army Acad Dept Elect Engn Kaohsiung 830 Taiwan I Shou Univ Dept Informat Engn Kaohsiung 840 Taiwan

A new vector quantisation algorithm is presented which fully exploits the interblock correlation of an image. For an input block, a predicted block from the previously encoded data is searched. If the prediction is good enough, only a Bag code is sent to the receiver. The algorithm results in a significant reduction in bit rate with better picture quality, as compared to the conventional full-search VQ.

关键词： predictive algorithm picture quality Image and video coding flag code vector quantisation image coding prediction theory image compression bit rate data encoding interblock correlation

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