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Area Computation by the Alternative Coordinate Method01:24

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The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...
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Cross-Device Computation Coordination for Mobile Collocated Interactions with Wearables.

Hyoseok Yoon1, Choonsung Shin2

  • 1Korea Electronics Technology Institute, Mapo-gu, Seoul 03924, Korea. hyoon@keti.re.kr.

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|February 21, 2019
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Summary

Mobile devices face demanding tasks like big data analysis. This study introduces a cross-device computation coordination method to share workloads and conserve energy among connected devices, enhancing performance.

Keywords:
Internet-of-Thingscomputation offloadingcontext-awarenesscross-devicemachine learningmobile interactionwearables

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Area of Science:

  • Computer Science
  • Ubiquitous Computing
  • Mobile Computing

Background:

  • Modern mobile devices, wearables, and Internet-of-Things (IoT) devices are increasingly powerful yet constrained by form factor and battery life.
  • Demanding applications like big data analysis, machine learning, and virtual reality require significant computational resources.
  • Existing multi-device ecosystems often struggle with efficient resource allocation and energy management for complex tasks.

Purpose of the Study:

  • To address the computational and energy demands of modern applications on resource-constrained mobile and wearable devices.
  • To propose a novel method for coordinating computation across multiple collocated devices.
  • To formally define and solve the cross-device computation coordination problem in mobile interaction scenarios.

Main Methods:

  • Formal definition of the cross-device computation coordination problem.
  • Development of a coordination method to distribute computational tasks among collocated mobile and wearable devices.
  • Experimental validation using 12 commercial Android devices with diverse computational capabilities.

Main Results:

  • Demonstrated the feasibility of the proposed cross-device computation coordination method.
  • Showcased the ability of multiple devices to collectively share computation burdens.
  • Achieved improved energy efficiency through coordinated task distribution.

Conclusions:

  • The proposed method effectively coordinates computation across mobile and wearable devices.
  • Cross-device collaboration is a viable strategy for meeting the demands of intensive applications.
  • This approach enhances the performance and energy efficiency of multi-device ecosystems.