Data Transfer Management Research Articles

Genetic Cache: A Machine Learning Approach to Designing DRAM Cache Controllers in HBM Systems

DRAM memory controller plays a critical role in maximizing the performance of High Bandwidth Memory by efficiently managing data transfers between the CPU and the memory modules. Thus, they are suitable for low-power data-intensive applications. However, the complexity of DRAM command scheduling combined with tag management overheads in the cache makes the design of in-package cache controllers significantly challenging. Traditional memory controllers often face challenges with static, inflexible access scheduling designed for general applications, leading to suboptimal performance in dynamic environments. On the other hand, while some advanced controllers employing reinforcement learning offer adaptability to workload fluctuations, they tend to introduce hardware complexity and incur longer training latencies. Our approach aims to design low-power and efficient DRAM cache controllers using a machine learning model that dynamically adjusts to workload changes with optimized hardware efficiency and reduced training time. Therefore, we propose a machine learning approach to design low-power and efficient DRAM cache controllers that will leverage the trained model to produce optimal cache command schedules at runtime. The model considers several conditions for each request queue, and chooses the best response among the options. The simulation results show the superiority of our proposed design over the previous algorithms in a set of twelve data-intensive applications; our model is able to improve the performance up to 40% in some cases, and an average of 15% in performance and 10% in power consumption.

An HTTP REST API for Tape-backed Storage

The goal of the HTTP REST API for Tape project is to provide a simple, minimalistic and uniform interface to manage data transfers between Storage Endpoints (SEs) where the source file is on tape. The project is a collaboration between the developers of WLCG storage systems (EOS+CTA, dCache, StoRM) and data transfer clients (gfal2, FTS). For some years, HTTP has been growing in popularity as the preferred data transfer protocol between many WLCG SEs. However — unlike other protocols such as XRootD and SRM — HTTP does not include a method to stage files from tape to disk prior to transfer, forcing the use of workarounds such as hybrid protocols (different protocols used for the “stage” and “transfer” parts of the operation). The HTTP REST API offers a simple and consistent solution, by extending the HTTP protocol to include staging operations. It provides clients with a common and consistent API across different storage systems to manage and monitor the disk and tape residency of stored files. In this contribution, we present the history and motivation of the HTTP REST API project, the specification of version 1 of the API and implementation details in the various storage and data transfer systems. We also describe our experience of its deployment and use for LHC Run-3 operations. We conclude with a discussion of possible future work.

Energy-Efficient IoT-Based Light Control System in Smart Indoor Agriculture.

Indoor agriculture is emerging as a promising approach for increasing the efficiency and sustainability of agri-food production processes. It is currently evolving from a small-scale horticultural practice to a large-scale industry as a response to the increasing demand. This led to the appearance of plant factories where agri-food production is automated and continuous and the plant environment is fully controlled. While plant factories improve the productivity and sustainability of the process, they suffer from high energy consumption and the difficulty of providing the ideal environment for plants. As a small step to address these limitations, in this article we propose to use internet of things (IoT) technologies and automatic control algorithms to construct an energy-efficient remote control architecture for grow lights monitoring in indoor farming. The proposed architecture consists of using a master-slave device configuration in which the slave devices are used to control the local light conditions in growth chambers while the master device is used to monitor the plant factory through wireless communication with the slave devices. The devices all together make a 6LoWPAN network in which the RPL protocol is used to manage data transfer. This allows for the precise and centralized control of the growth conditions and the real-time monitoring of plants. The proposed control architecture can be associated with a decision support system to improve yields and quality at low costs. The developed method is evaluated in emulation software (Contiki-NG v4.7),its scalability to the case of large-scale production facilities is tested, and the obtained results are presented and discussed. The proposed approach is promising in dealing with control, cost, and scalability issues and can contribute to making smart indoor agriculture more effective and sustainable.

A fuzzy logic and DEEC protocol-based clustering routing method for wireless sensor networks

<abstract> <p>Power-efficient wireless sensor network routing techniques (WSN). Clustering is used to extend WSNs' lifetimes. One node act as the cluster head (CH) to represent the others in communications. The member nodes are less important than the cluster hub (CH) in the clustering procedure. Fuzzy techniques based on clustering theory may provide evenly distributed loads. In this study, we provide a fuzzy-logic-based solution that factors in distance to base station (BS), number of nodes, remaining energy, compactness, distance to communicate within a cluster, number of CH, and remaining energy. Fuzzy clustering has a preliminary and final step. First, we select CH based on distance to the base station (BS), remaining node vigor, and node compactness. In the second phase, clusters are created by combining nodes that aren't already in a CH, using density, outstanding vigor, and detachment as limitations. The proposed solution increases load balancing and node longevity. This work provides a unique hybrid routing technique for forming clusters and managing data transfer to the base station. Simulation findings confirm the protocol's functionality and competence. Reduced energy use keeps network sensor nodes online longer. The framework outperforms Stable Election Protocol (SEP), hybrid energy-efficient distributed clustering (HEED), and Low Energy Adaptive Clustering Hierarchy (LEACH). Using the nodes' energy levels to create a grid pattern for the clusters gave four clusters. In addition, the proposed method has a 4347%, 41.46%, 39.26%, 37.57% and 35.67% reduction in average energy consumption when compared with the conventional algorithms. The proposed technologies could increase the network's lifetime, stability interval, packet transfer rate (throughput), and average energy. The suggested protocol is at least 50% better in every statistic that was looked at, such as network lifetime, stability interval, packet transmission rate (throughput), and average energy use.</p> </abstract>

A dynamic key management and secure data transfer based on m-tree structure with multi-level security framework for Internet of vehicles

Nowadays, broadband wireless networks and 5G have improvements in the quality and dependability of network services for high-speed mobile vehicles. Within an open communication environment on the Internet of vehicles named IoV, personal details will be revealed on the Wi-Fi network. Considering information security and privacy, this research concentrates on how to protect secure information transmission in real time through IoV, and also wants to avoid illegal vehicles, passers-by or drivers from joining connection and planting or altering significant data. This research provides a multilevel security infrastructure with M-tree based elliptic curve digital signature algorithm (ECDSA) for securing data transmission in both IoV and cloud environments. While transmitting, this study provides several flexible and scalable schemes to manage security issues, which dynamically adjust the framework depending on the rapidly changing IoV topology and speed up the time to synchronise the reconstruction of the system key, and decrease the quantity of phases to resynchronise the system key. Moreover, most research of key management without secure data transmission, we integrate the M-tree key management with secure data transmission to achieve the secure IoV. Simultaneously, the provided key management for the multi-level security is quite appropriate to adaptable and expandable IoV.

The significance of the Tactile Internet and 5G for digital agriculture

Abstract The demand for internet access and data transfer is the key driver of mobile communications technologies. The next step is wireless real-time networking. The “Tactile Internet” demands completely new technologies. Low latency, short response times, high reliability and resilience, a network of edge clouds and security are basic requirements. Therefore, 5G is developed. Novel use cases are industrial automation, autonomous vehicles, e-health, and the Internet of Things. For agriculture, 5G is a crucial technology enabler for robotization and Smart Farming processes. Agriculture needs own ad-hoc radio network solutions to efficiently provide coverage and manage data transfer, privacy and flexibility. The synergy of cellular and local mesh communications can solve the problem of unreliable communication and allows farmers to take full control of their data.

Design and Implementation of Basic Data Platform for University Library

Considering the problems existing in the data management and use of university library, this paper puts forward the concept of constructing “basic data platform”, which can provide the guarantee for the production and business data of library and university. The system includes data acquisition system, library data exchange system, data access API interface, cold data transfer system, data visualization and management platform, data analysis and mining modules, forming a complete system of data storage, management and use.

Management of Django Web Development in Python

Application Development is not only limited to the business or promotional field, but it also helps to provide the necessary services to the common people across the world by creating an interaction between the companies and the customers through the website. It also creates a platform for the common people who have the ability to attract the audience using their talent. We can take the example of various blog writers, online councilors and fashion influencers who have a large audience because of their quality content and knowledge in their field. We have generally seen how the electronic companies have marked their presence on the online platform via the website which enables the users to contact the company easily. Online retail companies interact with the users via website and provide the orders at the doorsteps of the people. There are various news agencies which had created their website which keeps the users updated with the latest national and international articles. The website development has helped to create a link between the people and the companies, but behind all these facilities there is a powerful language and commands that holds these computational activities and data transfers which helps to create a good interaction between the users and the website owners. Web developers are classified into Front-end and Back-end web developers, Front-end developers help to create an interactive interface that can be easily accessed by the users, whereas Back-end development deals with the main work that is done behind the screens. We can say that it helps to power the website by managing data transfer and other computational activities. In this project, the importance of Django and back-end web development is explained. Using the tools and commands of these languages we can make an interactive and user-friendly interface that can be easily accessed by people. Back-end was earlier known for limited purposes but now when it is explored thoroughly proved to be one of the best languages for website development, gaming, Artificial Intelligence, and highly advanced mobile applications.

DySHARQ: Dynamic Software-Defined Hardware-Managed Queues for Tile-Based Architectures

The recent trend towards tile-based manycore architectures has helped to tackle the memory wall by physically distributing memories and processing nodes. However, this introduced a data-to-task locality challenge and inter-tile communication thus often imposes significant software overhead. Thus, we proposed software-defined hardware-managed SHARQ queues that enable efficient inter-tile communication by leveraging user-defined queues with arbitrarily sized elements. To ensure (remote) processing of queued elements, SHARQ introduces an optional handler task, which is scheduled by hardware on demand. Queue management, intra- and inter-tile data transfer, and handler task invocation are entirely handled by hardware. Only rare tasks, like the dynamic queue creation at run-time, are performed in software. DySHARQ, an extension of SHARQ, enables dynamic and concurrent queue memory management and queue length adjustments to be able to adapt to application and resource requirement changes. The DySHARQ hardware is able to monitor the queue memory requirements at run-time and conditionally schedules a software-defined memory management task. It further optimizes the hardware-software interaction for local queue operations. We integrated DySHARQ into the MPI library used by the NAS benchmarks. The evaluation shows a reduction in execution time by up to 43% (compared to software) for the communication intense IS kernel in a 4 $$\times$$ 4 tile design on an FPGA platform with a total of 80 LEON3 cores. The dynamic memory management reduces the memory footprint by 3.75 $$\times$$ in a 2 $$\times$$ 2 design.

Method of developing machine learning architecture for IoT­devices based on serverless architecture

With the advent of IoT and microservice architectures, a multitude of intelligent distributed applications have emerged in which IoT devices collect, transform, and analyze data in large volumes and at high speed. A large number of these programs require robust, predictive analytics in real time, which require threading workflows closer to the data source, as well as dynamic resource management decisions. Moreover, predictive analytics requires the developer to create robust deep learning models, which, in turn, requires them to develop functions, find and configure parameters, and select machine learning models, which takes not only time, but also requires high experience level. The proliferation of machine learning libraries and frameworks, data ingestion tools, streaming and batch processing engines, rendering techniques, and the myriad of available hardware platforms further exacerbate these challenges. To overcome these complex challenges faced by developers of intelligent IoT applications, this article proposes a method for deploying machine learning architecture for IoT devices based on a serverless architecture called MLAbosa. The MLAbosa method can deploy, plan and dynamically manage data transfer tools, streaming software, batch analytics tools, and visualization tools across the cloud spectrum. This article describes the architecture of the MLAbosa method, highlighting the problems it solves.

Recent evolutions in the LTDP CDF project

In the latest years, CNAF (the national center of the Italian Institute for Nuclear Physics INFN dedicated to Research and Development on Information and Communication Technologies) has been working on the Long Term Data Preservation (LTDP) project for the CDF experiment, active at Fermilab from 1990 to 2011. The main aims of the project are to protect the most relevant part of the CDF RUN-2 data collected between 2001 and 2011 and already stored on tape at CNAF (4 PB), as well as to ensure the availability and the access to the analysis facility to those data over time. Lately, the CDF database, hosting information about CDF datasets such as their structure, file locations and metadata, has been imported from Fermilab to CNAF. Also, the Sequential Access via Metadata (SAM) station data handling tool for CDF data management, that allows to manage data transfers and to retrieve information from the CDF database, has been properly installed and configured at CNAF. This was a fundamental step in the perspective of a complete decommissioning of CDF services on Fermilab side. An access system has been designed and tested to submit CDF analysis jobs, using CDF software distributed via CERN Virtual Machine File System (CVMFS) and requesting delivery of CDF files stored on CNAF tapes, as well as data present only on Fermilab storage archive. Moreover, the availability and the correctness of all CDF data stored on CNAF tapes has been verified. This paper describes all these recent evolutions in detail, presenting the future plans for the LTDP project at CNAF.

Enhancing the SDTMA-NDN architecture for transferring the scientific data software using named data networking

Named Data Networking (NDN) is one of the promising future internet architectures, which focuses on the data rather than its location (IP/host-based system). NDN has several characteristics which facilitate addressing and routing the data: fail-over, in-network caching and load balancing. This makes it useful in areas such as managing scientific data across a distributed infrastructure. The Compact Muon Solenoid (CMS) experiment on the Large Hadron Collider (LHC) runs such an infrastructure and has a data access pattern amenable to Information-Centric Networking (ICN).In this paper, we propose SDTMA-NDN (Scientific Data Transfer Management Architecture using NDN) to distribute CMS’s software to worker-nodes and end-users. We provide several strategies to enhance the performance of NDN in transferring the scientific data. We build this on top of CERN Virtual Machine File System (CVMFS), a global, distributed filesystem designed to be used with cache-friendly workloads. CVMFS maintains its data by using content-addressable storage, which makes it suitable for NDN and a reasonable starting point for CMS. We examine the effect of in-network caching of NDN on the latency, how NDN provides transparent path selection to avoid high latency in the path, and how it balances several paths for retrieving the data. We compare SDTMA-NDN to the HTTP proxies used in the existing CVMFS-Content Distribution Network (CDN). Also, we propose two NDN forwarding strategies for retrieving the data; NDN Best-Path strategy (NDN-BP) and NDN Multi-path strategy (NDN-MP). SDTMA-NDN shows a better performance than the existing HTTP protocol in transferring the data. Further, it shows more resiliency and outperforms CVMFS-CDN under different network conditions.

An Ultrasonically Powered Wireless System for In Vivo Gastric Slow-Wave Recording.

This paper summarizes our recent progress towards Gastric Seed which is an ultrasonically interrogated millimeter-sized implant for gastric electrical activity (also known as slow waves, SWs) recording. We present a proof-of-concept wireless system designed to collect, transmit, and store in vivo SW signals by integrating a prototype Gastric Seed chip, fabricated in a 0.35-μm 2P4M CMOS process, with a commercial-off-the-shelf (COTS) amplifier, 10-bit analog-to-digital converter (ADC), and pair of microcontrollers (MCU) as radio-frequency (RF) transceivers. The chip includes ultrasonic self-regulated power management and addressable pulse-based data transfer. Utilizing two pairs of millimeter-sized stacked power/data ultrasonic transducers spaced by 6 cm in a water tank, the chip achieved a regulated voltage of 2.5 V and a data rate of 16 kbps. The amplifier was configured to have a gain of 60 dB with a 3-dB bandwidth of 18 mHz to 500 mHz. The MCU's built-in 10-bit ADC and RF transceiver were used to digitize the SW signal and transmit the data to a computer. In vivo, SW was recorded wirelessly from the stomach of an anesthetized rat. The recorded SWs showed a frequency of 1.5 cycle-per-minute (cpm) and maximum and minimum amplitudes of 1.03 mV and 0.28 mV peak-to-peak, respectively.

The Best Data Integration Method by Using SAW Technique in Ministry of Science, Research and Technology (MSRT)

Many computer systems are usually used by organizations. The data within different systems should be integrated in order to analyze and provide a report. Methodology: The method of saving data and files often focused in the past, the data structure and flow received little attention, therefore, the large volume of data and data transfer management carry into account as a big challenge. Results: Since information systems are growing in the organizations, the number and entanglement of interfaces will increase. If the data integration strategy is disregarded, the organization will meet numerous problems. Conclusion: There are 4 different data integration methods which have their special usage. This article concentrates on the process of data integration and aims to understand the meaning and methods of data integration, to identify variables and effective factors on data integration, to rank the variables of data integration and to provide the best method of data integration by SAW Technique for the Ministry of Science, Research and Technology.

A security-based asymmetric cryptographic algorithm to improve IEEE802.11i protocol

Today, wireless networks are significantly expanding in the current world, various security protocols have been introduced to secure the transmission of information, such as IEEE802.11i protocol. In data transfer management, only the 32-bit Cyclic Redundancy Check (CRC) algorithm has been used, which is only applied to detect the error in the transmission of data. Therefore, the unsafe data transfer allows attackers to perform different types of attacks and destructive efforts, particularly in Denial-Of-Service (DOS) and Man-In-Middle (MitM) attacks. In this paper, a new asymmetric cryptographic algorithm is presented to improve the security of the IEEE802.11i protocol. The experimental results showed that the proposed method has optimal performance than other approaches such as a fuzzy method.

Gastric Seed: Toward Distributed Ultrasonically Interrogated Millimeter-Sized Implants for Large-Scale Gastric Electrical-Wave Recording

This paper presents the concept of Gastric Seed, which is an ultrasonically interrogated millimeter-sized implant for gastric electrical-wave (also known as slow waves, SWs) recording. A network of Gastric Seeds can be endoscopically implanted within the stomach submucosal space for large-scale SW recording. This paper also summarizes our recent effort towards Gastric Seed development including ultrasonic self-regulated power management and addressable ultrasonic pulse-based data transfer. The proposed power management in the form of a voltage doubler only requires a single off-chip capacitor for simultaneous rectification, regulation and over-voltage protection (OVP) by utilizing ultrasonic transducer's internal capacitance and reverse current. For data transfer, sharp ultrasonic pulses are transmitted to reduce the implant's power consumption. A proof-of-concept addressable chip was fabricated in a 0.35-μm standard CMOS process. Utilizing two pairs of millimeter-sized stacked power/data ultrasonic transducers spaced by 3.75 cm in a water tank, the chip achieved measured regulated voltage of 3 V and data rate of 75 kbps with the data transmitter energy consumption of 440 pJ/bit.

The onboard software of the EUSO‐SPB pathfinder experiment

SummaryIn this paper, the flight software architecture of the EUSO‐SPB mission is described. The JEM‐EUSO program aims at developing an advanced large space‐borne UV telescope designed to detect ultra high energy cosmic rays. In this framework, the EUSO‐SPB experiment is the third pathfinder mission of the JEM‐EUSO program, the second that has been launched on a stratospheric balloon to test the technological readiness of the detectors and to carry out some preliminary scientific observations. The EUSO‐SPB software has a modular structure conceived to control all the instruments and the ancillary subsystems, to acquire data, and to manage data transfer to ground. System programming in C and C++ languages and Bash scripts have been used to implement and run the modules. The software runs on the data processor, an onboard computer that communicates with several payload blocks, the UV sensor, and the synchronization and time tagging board. The control software module controls all the subsystems, provides communication to ground through the NASA telemetry or the Internet, runs the acquisition control and download software, and manages the execution of the acquisition software. The acquisition software module directly operates the subsystems for the data acquisition activity. The acquisition control and download software module runs the acquisition software upon request of the control software and transfers scientific data to ground. The software system performed as expected during the flight on April 2017.

METHOD OF MULTI-CRITERIA EVALUATION OF INTEGRATION OPTIONS FOR LOCAL ATCS

For the English abstract and full text of the article please see the attached PDF-File (English version follows Russian version). АBSTRACT The methodological basis for management decisions and data transfer between local automated road traffic control systems (ATCS) is now constituted by the concept of scenarios, based on the object-relational approach. However, the disadvantage of this approach is the lack of the system’s ability to adapt to changes in input information without completely reworking the structure of the original requirements. One of the options for correcting the situation is integration of existing ATCS within a single information platform. To effectively implement such a task, it is necessary to develop a methodology for multicriteria evaluation of options for integrating local control systems with the help of formal logistical analytical methods that were tested and now are used in the theory of decision making. Keywords: automated traffic control system, decision theory, multi-criteria task, integration, analytical methods, single information platform.

Application of a new integrated optimization approach in sheet hydroforming process

The purpose of this study is to produce a desired hydroformed product under the optimal pressure profile. To achieve this purpose, a new adaptive optimization approach is proposed based on fuzzy logic control (FLC) integrated with simulated annealing (SA) optimization technique and ANSYS parametric design language (APDL). An intermediate MATLAB code was developed and used to manage data transfer automatically between FLC, SA and APDL, in which there would be no need for any interaction of user/designer during the optimization process execution. This method aims to find the optimal pressure loading profile, prevent wrinkling and necking failures, reduce unsuccessful iterations, and enhance convergence precision. This method is capable of adaptively changing the process parameters in order to reach the optimized values with higher accuracy in a more reasonable time. The results show a good agreement between the proposed optimization approach and experiments. The developed optimization approach is a practical and reliable design tool for industrial production of any symmetric shell cups using hydroforming process.

RT-CUDA: A Software Tool for CUDA Code Restructuring

Recent development in graphic processing units (GPUs) has opened a new challenge in harnessing their computing power as a new general purpose computing paradigm. However, porting applications to CUDA remains a challenge to average programmers, which have to package code in separate functions, explicitly manage data transfers between the host and device memories, and manually optimize GPU memory utilization. In this paper, we propose a restructuring tool (RT-CUDA) that takes a C-like program and some user directives as compiler hints to produce an optimized CUDA code. The tool strategy is based on efficient management of the memory system to minimize data motion by managing the transfer between host and device, maximizing bandwidth for device memory accesses, and enhancing data locality and re-use of cached data using shared-memory and registers. Enhanced resource utilization is implemented by re-writing code as parametric kernels and use of efficient auto-tuning. The tool enables calling numerical libraries (CuBLAS, CuSPARSE, etc.) to help implement applications in science simulation like iterative linear algebra solvers. For the above applications, the tool implement an inter-block global synchronization which allow the execution overall among a few iterations which is helpful to balance load and to avoid polling. Evaluation of RT-CUDA has been performed using a variety of basic linear algebra operators (Madd, MM, MV, VV, etc.) as well as the programming of iterative solvers for systems of linear equations like Jacobi and Conjugate Gradient algorithms. Significant speedup has been achieved over other compilers like PGI OpenACC and GPGPU compilers for the above applications. Evaluation shows that generated kernels efficiently call math libraries and enable implementing complete iterative solvers. The tool help scientists developing parallel simulators like reservoir simulators, molecular dynamics, etc. without exposing to complexity of GPU and CUDA programming. We have partnership with a group of researchers at the Saudi Aramco, a national company in Saudi Arabia. RT-CUDA is currently explored as a potential development tool for applications involving linear algebra solvers by the above group. In addition, RT-CUDA is being used by Senior and Graduate students at King Fahd University of Petroleum and Minerals in their projects as part of RT-CUDA continuous enhancement.