Abstract: Semiconductor technology has been
evolving rapidly over the past several
decades, introducing a new breed of
embedded systems that are tiny,
efficient, and pervasive. These
embedded systems are the backbone
of the ubiquitous and pervasive
computing revolution, embedded
intelligence all around us. Often, such
embedded intelligence for pervasive
computing must be deployed at
remote locations, for purposes of
environment sensing, data processing,
information transmission, etc.
Compared to current mobile devices,
which are mostly supported by
rechargeable and exchangeable
batteries, emerging embedded
systems for pervasive computing favor
a self-sustainable energy supply, as
their remote and mass deployment
makes it impractical to change or
charge their batteries. The ability to
sustain systems by scavenging energy
from ambient sources is called energy
harvesting, which is gaining monument
for its potential to enable energy
autonomy in the era of pervasive
computing. Among various energy
harvesting techniques, solar energy
harvesting has attracted the most
attention due to its high power density
Another impact of semiconductor
technology scaling into the deep
submicron level is the shifting of
design focus from performance to
energy efficiency as power dissipation
on a chip cannot increase indefinitely.
Due to unacceptable power
consumption at high clock rate, it is
desirable for computing systems to
distribute workload on multiple cores
with reduced execution frequencies so
that overall system energy efficiency
improves while meeting performance
goals. Thus it is necessary to adopt
the design paradigm of
multiprocessing for low-power
embedded systems due to the ever-
increasing demands for application
performance and stringent limitations
on power dissipation.
In this dissertation we focus on the
problem of resource management for
multicore embedded systems powered
by solar energy harvesting. We have
conducted a substantial amount of
research on this topic, which has led to
the design of a semi-dynamic resource
management framework designed with
emphasis on efficiency and flexibility
that can be applied to energy
harvesting-powered systems with a
variety of functionality, performance,
energy, and reliability goals. The
capability and flexibility of the
proposed semi-dynamic framework are
verified by issues we have addressed
with it, including: (i) minimizing miss
rate/miss penalty of systems with
energy harvesting, (ii) run-time thermal
control, (iii) coping with process
variation induced core-to-core
heterogeneity, (iv) management of
hybrid energy storage, (v) scheduling
of task graphs with inter-node
dependencies, (vi) addressing soft
errors during execution, (vii) mitigating
aging effects across the chip over
time, and (vii) supporting mixed-
criticality scheduling on heterogeneous
Adviser: Dr. Sudeep Pasricha Co-Adviser: N/A Non-ECE Member: Dr. Michelle Mills Strout Member 3: Dr. H. J. Siegel Addional Members: Dr. Anura Jayasumana
Publications: Y. Xiang, S. Pasricha, "Run-Time Management for Multi-Core Embedded Systems with Energy Harvesting", IEEE Transactions on Very Large Scale Integration Systems (TVLSI), 2014.
Y. Xiang, S. Pasricha, "Fault-Aware Application Scheduling in Low Power Embedded Systems with Energy Harvesting", ACM/IEEE International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS), 2014.
Y. Xiang, S. Pasricha, "A Hybrid Framework for Application Allocation and Scheduling in Multicore Systems with Energy Harvesting", ACM Great Lakes Symposium on VLSI (GLSVLSI), 2014.
B. Donohoo, C. Ohlsen, S. Pasricha, C. Anderson, Y. Xiang, "Context-Aware Energy Enhancements for Smart Mobile Devices", IEEE Transactions on Mobile Computing (TMC), 2013.
Y. Xiang, S. Pasricha, "Harvesting-Aware Energy Management for Multicore Platforms with Hybrid Energy Storage", ACM Great Lakes Symposium on VLSI (GLSVLSI), 2013.
Y. Xiang, S. Pasricha, "Thermal-Aware Semi-Dynamic Power Management for Multicore Systems with Energy Harvesting", IEEE International Symposium on Quality Electronic Design (ISQED), 2013.
Y. Zou, Y. Xiang, S. Pasricha, "Characterizing Vulnerability of Network Interfaces in Embedded Chip Multiprocessors", IEEE Embedded System Letters, 4(2), Jun 2012.
Y. Zou, Y. Xiang, S. Pasricha, “Analysis of On-chip Interconnection Network Interface Reliability in Multicore Systems”, IEEE International Conference on Computer Design (ICCD), 2011.
Program of Study: ECE 658 CS 545 ECE 514 CS 575 ECE 661 GRAD 511 CS 475 ECE 561