Abstract

Over the past decades, hardware and software technologies for wireless sensor networks (WSNs) have significantly progressed, and WSNs are widely used in various areas including Internet of Things (IoT). In general, existing WSNs are mainly used for applications that require delay-tolerance and low-computation due to the poor resources of traditional sensor nodes in WSNs. However, compared to the traditional sensor nodes, today’s devices for WSNs have more powerful resource. Thus, sensor nodes these days not only conduct sensing and transmitting data to servers but also are able to process many operations, so more diverse applications can be applied to WSNs. Especially, many applications using audio data have been proposed because audio is one of the most widely used data types, and many mobile devices already have a built-in microphone. However, many of the applications have a requirement that heavy-operations should be done by a tight deadline, so it is difficult for a single node in WSNs to run relatively heavy applications by itself. In this paper, to overcome this limitation of WSNs, we propose a new emerging system, HeaLow, a cooperative computing system for heavy-computation and low-latency processing in WSNs. We designed HeaLow and carried out the practical implementation on real devices. We confirmed the effectiveness of HeaLow through various experiments using the real devices and simulations. Using HeaLow, nodes in WSNs are able to perform heavy-computation processes while satisfying a completion time requirement.

Highlights

  • Supported by advancements of Micro Electro Mechanical Systems (MEMS), technologies of sensors have significantly progressed, and many various kinds of sensors have appeared [1]

  • We consider processing acoustic signals, which can be used for various services and applications in Wireless Sensor Networks (WSNs), as the target task in this paper

  • To overcome the aforementioned limitation, we propose the cooperative computing system, HeaLow, which enables nodes in WSNs to perform heavy-computation processing with meeting the deadline

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Summary

Introduction

Supported by advancements of Micro Electro Mechanical Systems (MEMS), technologies of sensors have significantly progressed, and many various kinds of sensors have appeared [1]. In addition to mobile devices, there have been significant developments on small-size and low-cost sensor platforms such as Arduino and WRTnode [16,17] Using these devices, users are able to gather many different sensor data and perform heavy-computation required processing. Users are able to gather many different sensor data and perform heavy-computation required processing Based on such advancement, the concept of edge computing was proposed. If sufficient resources are present in the multi-device system, utilizing free resources to improve the application performance is the secondary goal of HeaLow. As timeliness of heavy computation is a challenging task, the power efficiency issue is not considered in this paper.

Related Work
The Design of HeaLow and Implementation
Overall Design
Workflow of HeaLow
Implementation Details
Buffered Load Management
Work Queue Management
Communication Module and Delayed Response
Offloading Decision Process in Availability Checker
Fundamental Situation Assumed for Describing Offloading Decision Process
The Case When a Device Processes the Device’s Workload
The Case When a Device Is Requested to Process Another Device’s Workload
Performance Evaluation
Analysis on Effectiveness of Techniques Used for HeaLow
Analysis on Queue Length and Offloading
Simulations
Simulation on Effectiveness of HeaLow in WSNs
Analysis on Processing Capability of Nodes Using HeaLow
Analysis on Quality of Service Improved by Using HeaLow in WSNs
Findings
Conclusions
Full Text
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