scholarly journals Joint Power and Subchannel Allocation for Distributed Storage in Cellular-D2D Underlays

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8059
Author(s):  
Fengxia Han ◽  
Hao Deng ◽  
Jianfeng Shi ◽  
Hao Jiang
Keyword(s):  
Original Problem ◽  
Distributed Storage ◽  
Storage System ◽  
Low Complexity ◽  
Total Power ◽  
Joint Power ◽  
Storage Devices ◽  
Total Transmission ◽  
Total Power Consumption ◽  
Subchannel Allocation

Wireless distributed storage is beneficial in the provision of reliable content storage and offloading of cellular traffic. In this paper, we consider a cellular device-to-device (D2D) underlay-based wireless distributed storage system, in which the minimum storage regenerating (MSR) coding combined with the partial downloading scheme is employed. To alleviate burdens on insufficient cellular resources and improve spectral efficiency in densely deployed networks, multiple storage devices can simultaneously use the same uplink cellular subchannel under the non-orthogonal multiple access (NOMA) protocol. Our objective is to minimize the total transmission power for content reconstruction, while guaranteeing the signal-to-interference-plus-noise ratio (SINR) constraints for cellular users by jointly optimizing power and subchannel allocation. To tackle the non-convex combinational program, we decouple the original problem into two subproblems and propose two low-complexity algorithms to efficiently solve them, followed by a joint optimization, implemented by alternately updating the solutions to each subproblem. The numerical results illustrate that our proposed algorithms are capable of performing an exhaustive search with lower computation complexity, and the NOMA-enhanced scheme provides more transmission opportunities for neighbor storage devices, thus significantly reducing the total power consumption.

scholarly journals Supporting SLA via Adaptive Mapping and Heterogeneous Storage Devices in Ceph

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 847
Author(s):  
Sopanhapich Chum ◽  
Heekwon Park ◽  
Jongmoo Choi
Keyword(s):  
Positive Impact ◽  
Distributed Storage ◽  
Storage System ◽  
Hard Disk Drives ◽  
Service Level Agreement ◽  
Service Level ◽  
Cost Ratio ◽  
Solid State Drives ◽  
Storage Devices ◽  
Management Scheme

This paper proposes a new resource management scheme that supports SLA (Service-Level Agreement) in a bigdata distributed storage system. Basically, it makes use of two mapping modes, isolated mode and shared mode, in an adaptive manner. In specific, to ensure different QoS (Quality of Service) requirements among clients, it isolates storage devices so that urgent clients are not interfered by normal clients. When there is no urgent client, it switches to the shared mode so that normal clients can access all storage devices, thus achieving full performance. To provide this adaptability effectively, it devises two techniques, called logical cluster and normal inclusion. In addition, this paper explores how to exploit heterogeneous storage devices, HDDs (Hard Disk Drives) and SSDs (Solid State Drives), to support SLA. It examines two use cases and observes that separating data and metadata into different devices gives a positive impact on the performance per cost ratio. Real implementation-based evaluation results show that this proposal can satisfy the requirements of diverse clients and can provide better performance compared with a fixed mapping-based scheme.

scholarly journals Efficient Operation Method of Aquifer Thermal Energy Storage System Using Demand Response

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3129
Author(s):  
Jewon Oh ◽  
Daisuke Sumiyoshi ◽  
Masatoshi Nishioka ◽  
Hyunbae Kim
Keyword(s):  
Energy Storage ◽  
Power Consumption ◽  
Thermal Energy ◽  
Demand Response ◽  
Thermal Energy Storage ◽  
Heat Storage ◽  
Storage System ◽  
Total Power ◽  
Operation Method ◽  
Total Power Consumption

The mass introduction of renewable energy is essential to reduce carbon dioxide emissions. We examined an operation method that combines the surplus energy of photovoltaic power generation using demand response (DR), which recognizes the balance between power supply and demand, with an aquifer heat storage system. In the case that predicts the occurrence of DR and performs DR storage and heat dissipation operation, the result was an operation that can suppress daytime power consumption without increasing total power consumption. Case 1-2, which performs nighttime heat storage operation for about 6 h, has become an operation that suppresses daytime power consumption by more than 60%. Furthermore, the increase in total power consumption was suppressed by combining DR heat storage operation. The long night heat storage operation did not use up the heat storage amount. Therefore, it is recommended to the heat storage operation at night as much as possible before DR occurs. In the target area of this study, the underground temperature was 19.1 °C, the room temperature during cooling was about 25 °C and groundwater could be used as the heat source. The aquifer thermal energy storage (ATES) system in this study uses three wells, and consists of a well that pumps groundwater, a heat storage well that stores heat and a well that used heat and then returns it. Care must be taken using such an operation method depending on the layer configuration.

scholarly journals Joint Power Allocation and Beamforming in Amplify-and-Forward Relay Networks under Per-Node Power Constraint

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Farzin Azami ◽  
Seyed Mostafa Safavi Hemami ◽  
Abbas Akbarpour-Kasgari
Keyword(s):  
Power Consumption ◽  
Relay Networks ◽  
Critical Issue ◽  
Total Power ◽  
Amplify And Forward ◽  
Joint Power ◽  
Total Power Consumption ◽  
Quadratically Constrained ◽  
Required Quality

Two-way relay networks (TWRN) have been intensively investigated over the past decade due to their ability to enhance the performance assessment of networks in terms of cellular coverage and spectral efficiency. Yet, power control in such systems is a nontrivial issue, particularly in multirelay networks where relays are deployed to ensure a required Quality of Service (QoS). In this paper, we envision to address this critical issue by minimizing the sum-power with respect to per-node power consumption and acceptable users’ rates. To tackle this, we employ a variable transformation to turn the fractional quadratically constrained quadratic problem (QCQP) into semidefinite programming (SDP). This algorithm is also extended to a distributed format. Simulation results of deploying 10 relay stations reveal that the total power consumption will decrease to approximately 8 dBW for 6 bps/Hz sum-rate.

scholarly journals Mapping Datasets to Object Storage System

2020 ◽  
Vol 245 ◽  
pp. 04037
Author(s):  
Xiaowei Aaron Chu ◽  
Jeff LeFevre ◽  
Aldrin Montana ◽  
Dana Robinson ◽  
Quincey Koziol ◽  
...  
Keyword(s):  
Storage Systems ◽  
Distributed Storage ◽  
Storage System ◽  
Random Access ◽  
Data Partitioning ◽  
Data Layout ◽  
Storage Devices ◽  
Storage Servers ◽  
Non Volatile Memory ◽  
Volatile Memory

Access libraries such as ROOT[1] and HDF5[2] allow users to interact with datasets using high level abstractions, like coordinate systems and associated slicing operations. Unfortunately, the implementations of access libraries are based on outdated assumptions about storage systems interfaces and are generally unable to fully benefit from modern fast storage devices. For example, access libraries often implement buffering and data layout that assume that large, single-threaded sequential access patterns are causing less overall latency than small parallel random access: while this is true for spinning media, it is not true for flash media. The situation is getting worse with rapidly evolving storage devices such as non-volatile memory and ever larger datasets. This project explores distributed dataset mapping infrastructures that can integrate and scale out existing access libraries using Ceph’s extensible object model, avoiding re-implementation or even modifications of these access libraries as much as possible. These programmable storage extensions coupled with our distributed dataset mapping techniques enable: 1) access library operations to be offloaded to storage system servers, 2) the independent evolution of access libraries and storage systems and 3) fully leveraging of the existing load balancing, elasticity, and failure management of distributed storage systems like Ceph. They also create more opportunities to conduct storage server-local optimizations specific to storage servers. For example, storage servers might include local key/value stores combined with chunk stores that require different optimizations than a local file system. As storage servers evolve to support new storage devices like non-volatile memory, these server-local optimizations can be implemented while minimizing disruptions to applications. We will report progress on the means by which distributed dataset mapping can be abstracted over particular access libraries, including access libraries for ROOT data, and how we address some of the challenges revolving around data partitioning and composability of access operations.

scholarly journals Simulating Efficient power Wireless Sensor Network over Smart University Campus

2015 ◽  
Vol 14 (10) ◽  
pp. 6168-6175
Author(s):  
Abbas Rushdi Kubba ◽  
Mahmood K. Al Shimmary ◽  
Muna M. Al Nayar
Keyword(s):  
Total Power ◽  
University Campus ◽  
Educational Organizations ◽  
Power Capacity ◽  
Processing Load ◽  
Total Transmission ◽  
Network Parameters ◽  
Total Power Consumption ◽  
Wireless Nodes ◽  
Efficient Power

Attendance is one of the important factors that determine the students activity in any educational organizations. Taking attendance manually is considered as a huge task, even if, it was done using traditional methods such as barcode or smart card technologies leading to congestion and waste of time. The motivation of this papper is  to simulate the wireless sensors network of a smart university (UOT) campus using OMNeT++ inorder to enhance the total power consumption of wireless nodes using several nodes scheduiling algorthim  . The proposed system has been tested, and the results show that, the processing load of central server is decreased and the total transmission load over the wireless network also enhanced with value of 83%. Different experiments applied over distributed ZigBee wireless nodes in order to enhance network parameters .finally, the network parameters such as total power capacity and number of received packets had been improved using a linear queue node scheduling as proposed method.

scholarly journals Dynamic resource allocation for opportunistic software-defined IoT networks: stochastic optimization framework

2020 ◽  
Vol 10 (4) ◽  
pp. 3854
Author(s):  
Sharhabeel H. Alnabelsi ◽  
Haythem A. Bany Salameh ◽  
Zaid M. Albataineh
Keyword(s):  
Demand Uncertainty ◽  
Random Variable ◽  
Total Power ◽  
Traffic Demand ◽  
Total Transmission ◽  
Total Power Consumption ◽  
Important Challenge ◽  
Iot Devices ◽  
Highly Correlated ◽  
Dynamic Bandwidth

Several wireless technologies have recently emerged to enable efficient and scalable internet-of-things (IoT) networking. Cognitive radio (CR) technology, enabled by software-defined radios, is considered one of the main IoT-enabling technologies that can provide opportunistic wireless access to a large number of connected IoT devices. An important challenge in this domain is how to dynamically enable IoT transmissions while achieving efficient spectrum usage with a minimum total power consumption under interference and traffic demand uncertainty. Toward this end, we propose a dynamic bandwidth/channel/power allocation algorithm that aims at maximizing the overall network’s throughput while selecting the set of power resulting in the minimum total transmission power. This problem can be formulated as a two-stage binary linear stochastic programming. Because the interference over different channels is a continuous random variable and noting that the interference statistics are highly correlated, a suboptimal sampling solution is proposed. Our proposed algorithm is an adaptive algorithm that is to be periodically conducted over time to consider the changes of the channel and interference conditions. Numerical results indicate that our proposed algorithm significantly increases the number of simultaneous IoT transmissions compared to a typical algorithm, and hence, the achieved throughput is improved.

scholarly journals An Economical and Precise Cooling Model and Its Application in a Single-Cylinder Diesel Engine

2021 ◽  
Vol 11 (15) ◽  
pp. 6749
Author(s):  
Zhifeng Xie ◽  
Ao Wang ◽  
Zhuoran Liu
Keyword(s):  
Diesel Engine ◽  
Cooling System ◽  
Combustion Engine ◽  
Electronic Control Unit ◽  
Total Power ◽  
Dynamical Characteristic ◽  
Water Jacket ◽  
Single Cylinder ◽  
Pump Speed ◽  
Total Power Consumption

The cooling system is an important subsystem of an internal combustion engine, which plays a vital role in the engine’s dynamical characteristic, the fuel economy, and emission output performance at each speed and load. This paper proposes an economical and precise model for an electric cooling system, including the modeling of engine heat rejection, water jacket temperature, and other parts of the cooling system. This model ensures that the engine operates precisely at the designated temperature and the total power consumption of the cooling system takes the minimum value at some power proportion of fan and pump. Speed maps for the cooling fan and pump at different speeds and loads of engine are predicted, which can be stored in the electronic control unit (ECU). This model was validated on a single-cylinder diesel engine, called the DK32. Furthermore, it was used to tune the temperature of the water jacket precisely. The results show that in the common use case, the electric cooling system can save the power of 255 W in contrast with the mechanical cooling system, which is about 1.9% of the engine’s power output. In addition, the validation results of the DK32 engine meet the non-road mobile machinery China-IV emission standards.

scholarly journals On-CMOS Image Sensor Processing for Lane Detection

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3713
Author(s):  
Soyeon Lee ◽  
Bohyeok Jeong ◽  
Keunyeol Park ◽  
Minkyu Song ◽  
Soo Youn Kim
Keyword(s):  
Edge Detection ◽  
High Speed ◽  
Cmos Image Sensor ◽  
Image Sensor ◽  
Image Resolution ◽  
Lane Detection ◽  
Frame Rate ◽  
Total Power ◽  
Detection Accuracy ◽  
Total Power Consumption

This paper presents a CMOS image sensor (CIS) with built-in lane detection computing circuits for automotive applications. We propose on-CIS processing with an edge detection mask used in the readout circuit of the conventional CIS structure for high-speed lane detection. Furthermore, the edge detection mask can detect the edges of slanting lanes to improve accuracy. A prototype of the proposed CIS was fabricated using a 110 nm CIS process. It has an image resolution of 160 (H) × 120 (V) and a frame rate of 113, and it occupies an area of 5900 μm × 5240 μm. A comparison of its lane detection accuracy with that of existing edge detection algorithms shows that it achieves an acceptable accuracy. Moreover, the total power consumption of the proposed CIS is 9.7 mW at pixel, analog, and digital supply voltages of 3.3, 3.3, and 1.5 V, respectively.

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