ECE 1161/2161Embedded Computer System Design 2

Computing for Embedded Systems - II

Wei Gao

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How to Address the Local Resource Constraints? Local resource constraints at embedded systems Limited battery power Limited local computing capacity

Low-power designs Hardware

• Advanced VLSI manufacturing• New computing architecture

Software • DVFS• Duty cycling

May not fundamentally remove the limitation!

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Better Alternatives Cloud computing Offload the local computing workloads to the cloud

Problem: long latency for data transmission• Most embedded systems are delay-sensitive!

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Cloud processing Local processing

Wirelesstransmission

What can we do – Edge Computing

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Computing Storage

DATA CENTERS

END USERS

EDGECLOUD

Embedded Applications of Edge Computing

Cloud Gaming

Virtual Reality

Internet of Things

Smart Cities and Communities5

Challenges Adaptability Optimized performance? Minimized cost?

User mobility Minimized cost?

?Provisioning for the peak load

user mobility

?Complete move of data and program

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Hierarchical Architecture Adaptability Aggregation of

peak load

User mobility Partial migration

of data and programFlat Edge Cloud

Geo-distributed tree hierarchy 7

Optimal Workload Placement How to minimize the

response latency Where to place a workload How much capacity for a

workload

Challenge Delay tradeoff

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Computation delay

Communication delay

Computation Communication

Response latency

Low tiersHigh tiers

Supporting User Mobility

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A B

Virtual Machine Virtual Machine

BA

programbinarymemorydata

VM Migration

The Big Data Challenge Some embedded systems may be data intensive

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Cloud processing Local processing

Data partitioning

Wirelesstransmission

How to transmit? What to transmit?

What to Transmit? Dynamic data partitioning

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Existing work Assuming stationary and

fixed method transitions

Benefit of remote processing

Computation Cost Transmission Cost

Decisions over Program Methods

Modeling on Method Transitions?

ENERGY EFFICIENCY

Motivation Dynamic behaviors of run-time

program execution Input data User operation

Open-source Android applications Online profiling within source codes

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Firefox Chess game Barcode scanner

Dynamics of execution paths

Heterogeneity of method execution times

Modeling of Method Transitions

Transitions among program methods: semi-Markov model

Data partitioning approach: a stochastic framework

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Method execution times

Invocation dependency

System heterogeneity

Order-k

Arbitrary sojourn time distribution

Do We Have More Difficult Scenarios?

Data partitioning Move data-inexpensive computations to the cloud

What if the local computations are both data-intensive and computation-intensive?

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Virtual Reality

Solutions Exploit the redundancy in computations Whether we can reuse the previous computing results

• Within the same user• Across different users

Memoization

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Want to Use Edge Computing? You just need a server!

Existing VM solutions Virtual Box QEMU

Be careful about your programming models

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