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Mar 11, 2024 446 likes •537 views

Adaptive Data Replication in Real-Time Reliable Edge Computing for Internet of Things + Chao Wang, * Christopher Gill, * Chenyang Lu + Department of Computer Science and Information Engineering, National Taiwan Normal University * Department of

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Adaptive Data Replication in Real-Time Reliable Edge Computing for Internet of Things

+Chao Wang, *Christopher Gill, *Chenyang Lu + Department of Computer Science and Information Engineering, National Taiwan Normal University * Department of Computer Science and Engineering, Washington University in St. Louis, USA

SLIDE 2

Challenges in performant IoT edge computing

Reliable and timely computing

at a resource-constraint network waist

Example: structural health inference and control

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an IoT gateway

Single point of failure
Traffic congestion and delay
Limited network bandwidth

SLIDE 3

Specific IoT gateway requirements

Quantitative requirements
Data subscriber cannot accept more than

Li consecutive losses for data topic i

Data subscriber imposes an end-to-end

soft deadline for data

Qualitative requirements
The gateway should not consume too

much local network bandwidth

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SLIDE 4

System model

Publish-subscribe data model
with a minimum inter-publishing

time for each topic

Each embedded sensing device can
nly keep Ni latest data elements
Primary-backup fault tolerance
consider the crash failure (fail-stop)
data replication to backup

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Networked Cyber-Physical Systems Laboratory

SLIDE 5

Key idea for adaptive data replication

In the IoT gateway, once data is processed/delivered, it is irrelevant
Therefore, for each data, we may postpone replication activities to

reduce the need of actually performing the replication!

Only start to replicate an arrival of data at the last starting time
Once start, perform a batch of pending replications

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Networked Cyber-Physical Systems Laboratory

SLIDE 6

Adaptive data replication architecture

Edge computing engine

schedules both computing tasks and replication tasks using the EDF policy

Replication handler decides

the intended rate of replication:

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Networked Cyber-Physical Systems Laboratory

Lower intended rate -> tighter replication deadline

(see the paper for the analysis)

SLIDE 7

Empirical performance: efficiency in network bandwidth usage

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Networked Cyber-Physical Systems Laboratory

88% saving in bandwidth. A higher intended replication rate is preferred, because it permits a longer replication deadline, which in turn would allow the system to skip many more replication activities.

(Payload size = 512 bytes)

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Concluding remarks

Performant IoT edge computing is challenging
Reliability, timeliness, and resource constraints
In this work we addressed the challenges for the case of IoT gateways
Key idea: adaptive data replication
Our empirical validation shows that the proposed architecture can
meet the required levels of data-loss tolerance
save network bandwidth consumption
meet application-specific end-to-end deadlines
Email us for further discussion: cw@ntnu.edu.tw

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Networked Cyber-Physical Systems Laboratory