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Crowd-Sourced Centralized Thermal Imaging for Isolation and Quarantine
Published in Chhabi Rani Panigrahi, Bibudhendu Pati, Mamata Rath, Rajkumar Buyya, Computational Modeling and Data Analysis in COVID-19 Research, 2021
Sudershan Kumar, Prabuddha Sinha, Sujata Pal
Cristian’s algorithm is a relative time synchronization algorithm. It is mainly a server-client model in which there is only a one-time server. Every time the client node requests the server to synchronize the time. The client node requests periodically and the time server responds with the current UTC (Universal Time Coordinated). Then the client sets its time according to UTC. The client calculates some overhead involved during the communication and adjusts the new time (Varma et al., 2013). The new time is: Tclientnew=Tserver+(averageoverheadtime)
The System of the Supervision and the Visualization of Multimedia Data for BG
Published in Adam Weintrit, Marine Navigation, 2017
M. Blok, B. Czaplewski, S. Kaczmarek, J. Litka, M. Narloch, M. Sac
Usage of an universal IP network in the proposed system allows application of respective protocols from TCP/IP family for communication between particular elements. Regarding data communication between consoles, the EVP and Mapservers a concept of communication based on Message Oriented Middleware is concerned. Particularly an ISO/ECMA standard protocol named Advance Message Queuing Protocol (AMQP) is applied. Moreover the AMQP and HTTP are used for communication with Archive Servers. Regarding interactive VoIP communication the SIP is used as signaling (control) protocol between terminal and telecommunication servers. In the proposed system media (voice and video) are carried by the Real-time Transport Protocol/Real-time Transport Control Protocol (RTP/RTCP). This concept allows application of Real Time Streaming Protocol (RTSP) for control of multimedia sessions, particularly video from surveillance cameras and video recordings stored in Archive Servers. The elements of the whole system are synchronized with the aid of the Network Time Protocol (NTP) and a central time server. Application of GPS in time synchronization is possible as a backup in the case of isolation of particular, mainly mobile, units.
Internet of Things for Structural Health Monitoring
Published in Jayantha Ananda Epaarachchi, Gayan Chanaka Kahandawa, Structural Health Monitoring Technologies and Next-Generation Smart Composite Structures, 2016
Aravinda S. Rao, Jayavardhana Gubbi, Tuan Ngo, Priyan Mendis, Marimuthu Palaniswami
Time synchronization is an inherent problem in any communication network; for instance, two computers connected to a common local area network will have a difference in their clock timings if both are left untethered to the Internet for a significant amount of time (a few days). This may be attributed to physical, mechanical, and electrical properties of the quartz crystal oscillators residing in each of the computers. However, computers connected to the Internet maintain their timings equal, as they are synchronized to higher level stratum time server using network time protocol [34]. To maintain accurate timings with moveable devices, global positioning system (GPS) can be used. GPS consists of a constellation of 27 satellites positioned in geosynchronous orbits such that at least three satellites are visible for a device on any geographical position on the Earth. These satellites use atomic clocks to maintain accuracy of 10 ns [3]. In case of low-cost and low-power networks such as WSN, sensor nodes use lower end quartz crystal oscillators as their clock source. As a consequence, the clocks experience time drifts and also skewness.
Power and Energy-efficient VM scheduling in OpenStack Cloud Through Migration and Consolidation using Wake-on-LAN
Published in IETE Journal of Research, 2022
Krishan Kumar, Kunal Patange, Pushkar Pete, Manjiri Wankhade, Arpitrama Chatterjee, Manish Kurhekar
Suppose S1 is an active Server. Hence new requests will be designed on it if they can be accommodated on S1, else hibernated server says S2 will be woken up, and this new VM is scheduled on it. In case of deletion, the controller deletes the required VM and checks if migration of remaining VMs is possible such that a server becomes idle and can be shut down. Suppose at any instant of time, server S1 contains 5 VMs, and server S2 contains only 1 VM. When the work on VM3 at server S1 is completed, it is deleted. In this case, server S1 can accommodate one more VM, so for ensuring server consolidation, VM6 from server S2 is migrated on server S1. Server S2 becomes idle and can be shut down. Server S1 is the only active server now. In this way, the server consolidation is performed, and energy is saved.
An effective scheduling in data centres for efficient CPU usage and service level agreement fulfilment using machine learning
Published in Connection Science, 2021
Rohit Daid, Yogesh Kumar, Yu-Chen Hu, Wu-Lin Chen
The problem so far is the cost in terms of energy consumption which is increasing day by day and equipment in the data centres needs low power and cooling structures, and the main issue is not the existing volume of data centre discharges but the point that these discharges are growing faster than any additional emission (Oró et al., 2015). Accordingly, data centres are growing; moreover, the cost and resources are increasing due to there is a huge problem in the infrastructure-based organisation. Quite less work is done on data centres maintenance because of complex structures and high demand in real-time environments and most of the work is done on its usage. Consequently, the primary objective of the work includes the efficient scheduling of the power levels, loads of the CPU using artificial intelligence and machine learning based on past behaviours of the system to improve the scheduling decision, and the cost of the resources required to operate the data centres. These days, energy efficiency turns out to be an important scenario in cloud computing and real-time server handling systems which are managed by data centres.
Development of Real-Time Software for Thomson Scattering Analysis at NSTX-U
Published in Fusion Science and Technology, 2019
Roman Rozenblat, Egemen Kolemen, Florian M. Laggner, Christopher Freeman, Greg Tchilinguirian, Paul Sichta, Gretchen Zimmer
The real-time hardware can acquire data of eight polychromators, i.e., eight spatial channels. Each polychromator is equipped with up to six spectral filters and associated avalanche photodiodes (APDs) to measure the spectrum of the scattered light. The signals of the APD detectors are digitized with an SIS3316-250–14 analog-to-digital converter (ADC) that operates at 250 Msamples s−1 with 14-bit resolution.15 The ADC is connected to a server via a Solarflare16 Ethernet card. There are four SIS3316 cards with 16 channels each, which allows for the digitization of the eight spatial channels and other required signals for the TS analysis. The cards continuously digitize to a circular buffer, whose readout is triggered by laser pulses. When the cards are triggered, the peak values of the detected pulse are extracted in the first step of the real-time Multi-Pulse Thomson Scattering (MPTS) analysis software. The real-time server that is used to process the TS calculation is a ServeDirect server with 32 Gbytes Memory, Intel Xeon 2.2 GHz with 20 cores. The output of the real-time MPTS server is done through an analog output (AO) 16AO64 PCIE card, which has up to 64 channels with 16-bit resolution.17