Offload computation in cloud assisted Wireless Sensor Networks

Dattatraya, Patil Yogita; Agarkhed, Jayashree

doi:10.1109/aeeicb.2016.7538373

Cited by 3 publications

(1 citation statement)

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“…Their evaluation results show that the proposed partitioning algorithm outperformed existing algorithms. Unlike Wen [ 30 ] and Sinha [ 31 ], Dattatraya et al focused on the insufficient storage of sensor nodes [ 32 ]. In their system, sensor nodes store sensed data into servers, and the system provides access to authorized users for retrieval of sensor information stored in the servers.…”

Section: Related Workmentioning

confidence: 99%

Cooperative Computing System for Heavy-Computation and Low-Latency Processing in Wireless Sensor Networks

Jung

Lee

Kim

2018

Sensors

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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.

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Section: Related Workmentioning

confidence: 99%