scholarly journals Data-Sharing Method for Multi-Smart Devices at Close Range

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Myoungbeom Chung ◽  
Ilju Ko
Keyword(s):  
Performance Evaluation ◽  
Success Rate ◽  
Data Sharing ◽  
Operating Systems ◽  
Smart Devices ◽  
Smart Device ◽  
Shared Data ◽  
Close Range ◽  
A Performance

We proposed a useful data-sharing method among multi-smart devices at close range using inaudible frequencies and Wi-Fi. The existing near data-sharing methods mostly use Bluetooth technology, but these methods have the problem of being unable to be operated using different operating systems. To correct this flaw, the proposed method that uses inaudible frequencies through the inner speaker and microphone of smart device can solve the problems of the existing methods. Using the proposed method, the sending device generates trigger signals composed of inaudible sound. Moreover, smart devices that receive the signals obtain the shared data from the sending device through Wi-Fi. To evaluate the efficacy of the proposed method, we developed a near data-sharing application based on the trigger signals and conducted a performance evaluation experiment. The success rate of the proposed method was 98.8%. Furthermore, we tested the user usability of the Bump application and the proposed method and found that the proposed method is more useful than Bump. Therefore, the proposed method is an effective approach for sharing data practically among multi-smart devices at close range.

scholarly journals Vibration-based Key Exchange among Multiple Smart Devices on the Desk

2016 ◽  
Vol 21 (2) ◽  
pp. 33-43
Author(s):  
Alisa Arno ◽  
Kentaroh Toyoda ◽  
Yuji Watanabe ◽  
Iwao Sasase ◽  
P. Takis Mathiopoulos
Keyword(s):  
Performance Evaluation ◽  
Data Sharing ◽  
Key Exchange ◽  
Smart Devices ◽  
Secure Communications ◽  
Indoor Environments ◽  
Experimental Performance ◽  
Diffie Hellman ◽  
Man In The Middle

Abstract Eavesdropping is an important and real concern in mobile NFC (Near Filed Communication) payment and data sharing applications. Although the DH (Diffie-Hellman) scheme has been widely used in key exchange for secure communications, it may fail in indoor environments due to its vulnerability against man-in-the-middle attack. In this paper, we propose a new vibration-based key exchange among multiple smart devices which are placed on a desk. In this scheme, devices are assumed to be located next to each other with each of them vibrating with patterns converted from a key to be exchanged. The vibration patterns are measured by an accelerometer and each key is recovered from the measured acceleration. The proposed scheme has been implemented using Android smartphones and various experimental performance evaluation results have validated its effectiveness.

A performance evaluation and modification of the UNICEF upward-flow water filter

Waterlines ◽  
1993 ◽  
Vol 12 (2) ◽  
pp. 29-31 ◽  
Author(s):  
Vinay Pratap Singh ◽  
Malay Chaudhuri
Keyword(s):  
Performance Evaluation ◽  
Upward Flow ◽  
Water Filter ◽  
A Performance

scholarly journals SRPerf: a Performance Evaluation Framework for IPv6 Segment Routing

2020 ◽  
pp. 1-1
Author(s):  
Ahmed Abdelsalam ◽  
Pier Luigi Ventre ◽  
Carmine Scarpitta ◽  
Andrea Mayer ◽  
Stefano Salsano ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Evaluation Framework ◽  
A Performance

scholarly journals Latency-Optimal Computational Offloading Strategy for Sensitive Tasks in Smart Homes

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2347
Author(s):  
Yanyan Wang ◽  
Lin Wang ◽  
Ruijuan Zheng ◽  
Xuhui Zhao ◽  
Muhua Liu
Keyword(s):  
Queue Length ◽  
Optimization Problem ◽  
Time Slot ◽  
Smart Homes ◽  
Back Pressure ◽  
Smart Devices ◽  
Smart Device ◽  
Simulation Results ◽  
Computational Offloading ◽  
The Stability

In smart homes, the computational offloading technology of edge cloud computing (ECC) can effectively deal with the large amount of computation generated by smart devices. In this paper, we propose a computational offloading strategy for minimizing delay based on the back-pressure algorithm (BMDCO) to get the offloading decision and the number of tasks that can be offloaded. Specifically, we first construct a system with multiple local smart device task queues and multiple edge processor task queues. Then, we formulate an offloading strategy to minimize the queue length of tasks in each time slot by minimizing the Lyapunov drift optimization problem, so as to realize the stability of queues and improve the offloading performance. In addition, we give a theoretical analysis on the stability of the BMDCO algorithm by deducing the upper bound of all queues in this system. The simulation results show the stability of the proposed algorithm, and demonstrate that the BMDCO algorithm is superior to other alternatives. Compared with other algorithms, this algorithm can effectively reduce the computation delay.

scholarly journals Getting Started Creating Data Dictionaries: How to Create a Shareable Data Set

2021 ◽  
Vol 4 (1) ◽  
pp. 251524592092800
Author(s):  
Erin M. Buchanan ◽  
Sarah E. Crain ◽  
Ari L. Cunningham ◽  
Hannah R. Johnson ◽  
Hannah Stash ◽  
...  
Keyword(s):  
Data Collection ◽  
Data Sharing ◽  
Search Engine ◽  
Web Applications ◽  
Data Sets ◽  
Data Dictionary ◽  
Data Set ◽  
Entire Process ◽  
Shared Data ◽  
Source Data

As researchers embrace open and transparent data sharing, they will need to provide information about their data that effectively helps others understand their data sets’ contents. Without proper documentation, data stored in online repositories such as OSF will often be rendered unfindable and unreadable by other researchers and indexing search engines. Data dictionaries and codebooks provide a wealth of information about variables, data collection, and other important facets of a data set. This information, called metadata, provides key insights into how the data might be further used in research and facilitates search-engine indexing to reach a broader audience of interested parties. This Tutorial first explains terminology and standards relevant to data dictionaries and codebooks. Accompanying information on OSF presents a guided workflow of the entire process from source data (e.g., survey answers on Qualtrics) to an openly shared data set accompanied by a data dictionary or codebook that follows an agreed-upon standard. Finally, we discuss freely available Web applications to assist this process of ensuring that psychology data are findable, accessible, interoperable, and reusable.

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