11 research outputs found
Energy autonomous systems : future trends in devices, technology, and systems
The rapid evolution of electronic devices since the beginning of the nanoelectronics era has brought about exceptional computational power in an ever shrinking system footprint. This has enabled among others the wealth of nomadic battery powered wireless systems (smart phones, mp3 players, GPS, …) that society currently enjoys. Emerging integration technologies enabling even smaller volumes and the associated increased functional density may bring about a new revolution in systems targeting wearable healthcare, wellness, lifestyle and industrial monitoring applications
Variable length pattern coding for power reduction in off-chip data buses
Off-chip buses consume a huge fraction (20%-40%) of the system power. Hence, techniques
such as increasing bus widths, transition encoding etc. have been used for
power reduction on off-chip data buses. Since capacitances at the I/O pads and interwire
capacitances contribute significantly to increase in power, encoding/decoding
schemes have been developed to reduce switching activity of the off-chip bus lines,
thus reducing power. Frequent-Value Encoding(FVE) [1], Frequent Value Encoding
with Xor (FVExor) [1] and VALVE [2] are some of the better known encoding schemes
but they still have scope for improvement.
This thesis addresses the problem of power reduction in off-chip data buses by
encoding variable number (1 to 4) of fixed-size (32-bit) data values (variable length
patterns) which exhibit temporal locality. This characteristic enables us to cache
these patterns using 64-entry CAM at the encoder and 64-entry SRAM at the decoder.
Whenever a pattern match occurs a 2-bit code indicating the index of the match is
sent. If a variable length pattern match occurs then the code and unmatched portion
of data is sent.
We implemented our scheme, Variable Length Pattern Coding (VLPC) for various
integer and floating point benchmarks and have seen 6% to 49% encodable patterns
in these benchmarks. Based on the experiments on simplescalar and our analysis
in MATLAB, we obtained 4.88% to 40.11% reduction in transition activity for SPEC2000 benchmarks such as crafty, swim, mcf, applu, ammp etc. over unencoded
data. This is 0.3% to 38.9% higher than that obtained using FVE, FVExor [1] and
VALVE [2] encoding schemes. Finally, we have designed a low-power custom CAM
and SRAM using 45nm BSIM4 technology models which has been used to verify lower
latency of data matching and storing
In-Network Distributed Solar Current Prediction
Long-term sensor network deployments demand careful power management. While
managing power requires understanding the amount of energy harvestable from the
local environment, current solar prediction methods rely only on recent local
history, which makes them susceptible to high variability. In this paper, we
present a model and algorithms for distributed solar current prediction, based
on multiple linear regression to predict future solar current based on local,
in-situ climatic and solar measurements. These algorithms leverage spatial
information from neighbors and adapt to the changing local conditions not
captured by global climatic information. We implement these algorithms on our
Fleck platform and run a 7-week-long experiment validating our work. In
analyzing our results from this experiment, we determined that computing our
model requires an increased energy expenditure of 4.5mJ over simpler models (on
the order of 10^{-7}% of the harvested energy) to gain a prediction improvement
of 39.7%.Comment: 28 pages, accepted at TOSN and awaiting publicatio
A Survey of Green Networking Research
Reduction of unnecessary energy consumption is becoming a major concern in
wired networking, because of the potential economical benefits and of its
expected environmental impact. These issues, usually referred to as "green
networking", relate to embedding energy-awareness in the design, in the devices
and in the protocols of networks. In this work, we first formulate a more
precise definition of the "green" attribute. We furthermore identify a few
paradigms that are the key enablers of energy-aware networking research. We
then overview the current state of the art and provide a taxonomy of the
relevant work, with a special focus on wired networking. At a high level, we
identify four branches of green networking research that stem from different
observations on the root causes of energy waste, namely (i) Adaptive Link Rate,
(ii) Interface proxying, (iii) Energy-aware infrastructures and (iv)
Energy-aware applications. In this work, we do not only explore specific
proposals pertaining to each of the above branches, but also offer a
perspective for research.Comment: Index Terms: Green Networking; Wired Networks; Adaptive Link Rate;
Interface Proxying; Energy-aware Infrastructures; Energy-aware Applications.
18 pages, 6 figures, 2 table
SIVEH: numerical computing simulation of wireless energy-harvesting sensor nodes
[EN] The paper presents a numerical energy harvesting model for sensor nodes, SIVEH (Simulator I–V for EH), based on I–V hardware tracking. I–V tracking is demonstrated to be more accurate than traditional energy modeling techniques when some of the components present different power dissipation at either different operating voltages or drawn currents. SIVEH numerical computing allows fast simulation of long periods of time—days, weeks, months or years—using real solar radiation curves. Moreover, SIVEH modeling has been enhanced with sleep time rate dynamic adjustment, while seeking energy-neutral operation. This paper presents the model description, a functional verification and a critical comparison with the classic energy approachThe authors gratefully acknowledge financial support from CICYT. ANDREA: Automated Inspection and Remote Performance of Marine Fish Farms (CTM2011-29691-C02-01); and RIDeWAM: Research on Improvement of the Dependability of WSN-based Applications by Developing a Hybrid Monitoring Platform. (TIN2011-28435-C03-01).Sánchez MatĂas, AM.; Blanc Clavero, S.; Climent, S.; Yuste PĂ©rez, P.; Ors Carot, R. (2013). SIVEH: numerical computing simulation of wireless energy-harvesting sensor nodes. Sensors. 13(9):11750-11771. https://doi.org/10.3390/s130911750S1175011771139Akyildiz, I., Melodia, T., & Chowdury, K. (2007). Wireless multimedia sensor networks: A survey. IEEE Wireless Communications, 14(6), 32-39. doi:10.1109/mwc.2007.4407225Madan, R., Cui, S., Lall, S., & Goldsmith, A. (2006). Cross-Layer Design for Lifetime Maximization in Interference-Limited Wireless Sensor Networks. IEEE Transactions on Wireless Communications, 5(11), 3142-3152. doi:10.1109/twc.2006.04770Wang, Z. L., & Wu, W. (2012). Nanotechnology-Enabled Energy Harvesting for Self-Powered Micro-/Nanosystems. Angewandte Chemie International Edition, 51(47), 11700-11721. doi:10.1002/anie.201201656Riemer, R., & Shapiro, A. (2011). Biomechanical energy harvesting from human motion: theory, state of the art, design guidelines, and future directions. Journal of NeuroEngineering and Rehabilitation, 8(1), 22. doi:10.1186/1743-0003-8-22Sudevalayam, S., & Kulkarni, P. (2011). Energy Harvesting Sensor Nodes: Survey and Implications. IEEE Communications Surveys & Tutorials, 13(3), 443-461. doi:10.1109/surv.2011.060710.00094Alippi, C., & Galperti, C. (2008). An Adaptive System for Optimal Solar Energy Harvesting in Wireless Sensor Network Nodes. IEEE Transactions on Circuits and Systems I: Regular Papers, 55(6), 1742-1750. doi:10.1109/tcsi.2008.922023Alippi, C., Camplani, R., Galperti, C., & Roveri, M. (2011). A Robust, Adaptive, Solar-Powered WSN Framework for Aquatic Environmental Monitoring. IEEE Sensors Journal, 11(1), 45-55. doi:10.1109/jsen.2010.2051539Lopez-Lapena, O., Penella, M. T., & Gasulla, M. (2010). A New MPPT Method for Low-Power Solar Energy Harvesting. IEEE Transactions on Industrial Electronics, 57(9), 3129-3138. doi:10.1109/tie.2009.2037653Kansal, A., Hsu, J., Zahedi, S., & Srivastava, M. B. (2007). Power management in energy harvesting sensor networks. ACM Transactions on Embedded Computing Systems, 6(4), 32-es. doi:10.1145/1274858.1274870Niyato, D., Hossain, E., Rashid, M., & Bhargava, V. (2007). Wireless sensor networks with energy harvesting technologies: a game-theoretic approach to optimal energy management. IEEE Wireless Communications, 14(4), 90-96. doi:10.1109/mwc.2007.4300988EECS Department of the University of California at Berkleyhttp://bwrc.eecs.berkeley.edu/Classes/IcBook/SPICE/http://www.panasonic.com/industrial/components/pdf/goldcap_tech-guide_052505.pdfAnalog, Embedded Processing, Semiconductor Company, Texas Instrumentshttp://www.ti.comST Microelectronicshttp://www.st.comHome Pagehttp://www.linear.com/ns-3http://www.nsnam.orgSánchez, A., Blanc, S., Yuste, P., Perles, A., & Serrano, J. J. (2012). An Ultra-Low Power and Flexible Acoustic Modem Design to Develop Energy-Efficient Underwater Sensor Networks. Sensors, 12(6), 6837-6856. doi:10.3390/s12060683
HOLLOWS: A Power-Aware Task Scheduler for Energy Harvesting Sensor Nodes
Energy-harvesting sensor nodes (EHSNs) have stringent low-energy consumption requirements, but they need to concurrently execute several types of tasks (processing, sensing, actuation, etc). Furthermore, no accurate models exist to predict the energy harvesting income in order to adapt at run-time the executing set of prioritized tasks. In this paper, we propose a novel power-aware task scheduler for EHSNs, namely, HOLLOWS: Head-of-Line Low-Overhead Wide-priority Service. HOLLOWS uses an energy-constrained prioritized queue model to describe the residence time of tasks entering the system and dynamically selects the set of tasks to execute, according to system accuracy requirements and expected energy. Moreover, HOLLOWS includes a new energy harvesting prediction algorithm, i.e., Weather-Conditioned Moving Average (WCMA), which we have developed to estimate the solar panel energy income. We have tested HOLLOWS using the real-life working conditions of Shimmer, a sensor node for structural health monitoring. Our results indicate that HOLLOWS accurately predicts the energy available in Shimmer to guarantee a certain damage monitoring quality for long-term autonomous scenarios. Also, HOLLOWS is able to adjust the use of the incoming energy harvesting to achieve high accuracy for rapid event damage assessment (after earthquakes, fires, etc.)
Urubu: energy scavenging in wireless sensor networks
For the past years wireless sensor networks (WSNs) have been coined as one of the most
promising technologies for supporting a wide range of applications. However, outside the
research community, few are the people who know what they are and what they can offer.
Even fewer are the ones that have seen these networks used in real world applications. The
main obstacle for the proliferation of these networks is energy, or the lack of it. Even
though renewable energy sources are always present in the networks environment,
designing devices that can efficiently scavenge that energy in order to sustain the operation
of these networks is still an open challenge.
Energy scavenging, along with energy efficiency and energy conservation, are the current
available means to sustain the operation of these networks, and can all be framed within
the broader concept of “Energetic Sustainability”. A comprehensive study of the several
issues related to the energetic sustainability of WSNs is presented in this thesis, with a
special focus in today’s applicable energy harvesting techniques and devices, and in the
energy consumption of commercially available WSN hardware platforms.
This work allows the understanding of the different energy concepts involving WSNs and
the evaluation of the presented energy harvesting techniques for sustaining wireless sensor
nodes. This survey is supported by a novel experimental analysis of the energy
consumption of the most widespread commercially available WSN hardware platforms.Há já alguns anos que as redes de sensores sem fios (do Inglês Wireless Sensor Networks -
WSNs) tĂŞm sido apontadas como uma das mais promissoras tecnologias de suporte a uma
vasta gama de aplicações. No entanto, fora da comunidade cientĂfica, poucas sĂŁo as
pessoas que sabem o que elas sĂŁo e o que tĂŞm para oferecer. Ainda menos sĂŁo aquelas que
já viram a sua utilização em aplicações do dia-a-dia. O principal obstáculo para a
proliferação destas redes é a energia, ou a falta dela. Apesar da existência de fontes de
energia renováveis no local de operação destas redes, continua a ser um desafio construir
dispositivos capazes de aproveitar eficientemente essa energia para suportar a operação
permanente das mesmas.
A colheita de energia juntamente com a eficiência energética e a conservação de energia,
sĂŁo os meios disponĂveis actualmente que permitem a operação permanente destas redes e
podem ser todos englobados no conceito mais amplo de “Sustentabilidade Energética”.
Esta tese apresenta um estudo extensivo das várias questões relacionadas com a
sustentabilidade energética das redes de sensores sem fios, com especial foco nas
tecnologias e dispositivos explorados actualmente na colheita de energia e no consumo
energético de algumas plataformas comercias de redes de sensores sem fios.
Este trabalho permite compreender os diferentes conceitos energéticos relacionados com as
redes de sensores sem fios e avaliar a capacidade das tecnologias apresentadas em suportar
a operação permanente das redes sem fios. Este estudo é suportado por uma inovadora
análise experimental do consumo energético de algumas das mais difundidas plataformas
comerciais de redes de sensores sem fios
Driving the Network-on-Chip Revolution to Remove the Interconnect Bottleneck in Nanoscale Multi-Processor Systems-on-Chip
The sustained demand for faster, more powerful chips has been met by the
availability of chip manufacturing processes allowing for the integration of increasing
numbers of computation units onto a single die. The resulting outcome,
especially in the embedded domain, has often been called SYSTEM-ON-CHIP
(SoC) or MULTI-PROCESSOR SYSTEM-ON-CHIP (MP-SoC).
MPSoC design brings to the foreground a large number of challenges, one of
the most prominent of which is the design of the chip interconnection. With a
number of on-chip blocks presently ranging in the tens, and quickly approaching
the hundreds, the novel issue of how to best provide on-chip communication
resources is clearly felt.
NETWORKS-ON-CHIPS (NoCs) are the most comprehensive and scalable
answer to this design concern. By bringing large-scale networking concepts to
the on-chip domain, they guarantee a structured answer to present and future
communication requirements. The point-to-point connection and packet switching
paradigms they involve are also of great help in minimizing wiring overhead
and physical routing issues. However, as with any technology of recent inception,
NoC design is still an evolving discipline. Several main areas of interest
require deep investigation for NoCs to become viable solutions:
• The design of the NoC architecture needs to strike the best tradeoff among
performance, features and the tight area and power constraints of the onchip
domain.
• Simulation and verification infrastructure must be put in place to explore,
validate and optimize the NoC performance.
• NoCs offer a huge design space, thanks to their extreme customizability in
terms of topology and architectural parameters. Design tools are needed
to prune this space and pick the best solutions.
• Even more so given their global, distributed nature, it is essential to evaluate
the physical implementation of NoCs to evaluate their suitability for
next-generation designs and their area and power costs.
This dissertation performs a design space exploration of network-on-chip architectures,
in order to point-out the trade-offs associated with the design of
each individual network building blocks and with the design of network topology
overall. The design space exploration is preceded by a comparative analysis
of state-of-the-art interconnect fabrics with themselves and with early networkon-
chip prototypes. The ultimate objective is to point out the key advantages
that NoC realizations provide with respect to state-of-the-art communication
infrastructures and to point out the challenges that lie ahead in order to make
this new interconnect technology come true. Among these latter, technologyrelated
challenges are emerging that call for dedicated design techniques at all
levels of the design hierarchy. In particular, leakage power dissipation, containment
of process variations and of their effects. The achievement of the above
objectives was enabled by means of a NoC simulation environment for cycleaccurate
modelling and simulation and by means of a back-end facility for the
study of NoC physical implementation effects. Overall, all the results provided
by this work have been validated on actual silicon layout
DISK DESIGN-SPACE EXPLORATION IN TERMS OF SYSTEM-LEVEL PERFORMANCE, POWER, AND ENERGY CONSUMPTION
To make the common case fast, most studies focus on the computation phase of applications in which most instructions are executed. However, many programs spend significant time in the I/O intensive phase due to the I/O latency. To obtain a system with more balanced phases, we require greater insight into the effects of the I/O configurations to the entire system in both performance and power dissipation domains.
Due to lack of public tools with the complete picture of the entire memory hierarchy, we developed SYSim. SYSim is a complete-system simulator aiming at complete memory hierarchy studies in both performance and power consumption domains.
In this dissertation, we used SYSim to investigate the system-level impacts of several disk enhancements and technology improvements to the detailed interaction in memory hierarchy during the I/O-intensive phase. The experimental results are reported in terms of both total system performance and power/energy consumption. With SYSim, we conducted the complete-system experiments and revealed intriguing behaviors including, but not limited to, the following:
During the I/O intensive phase which consists of both disk reads and writes, the average system CPI tracks only average disk read response time, and not overall average disk response time, which is the widely-accepted metric in disk drive research.
In disk read-dominating applications, Disk Prefetching is more important than increasing the disk RPM. On the other hand, in applications with both disk reads and writes, the disk RPM matters.
The execution time can be improved to an order of magnitude by applying some disk enhancements. Using disk caching and prefetching can improve the performance by the factor of 2, and write-buffering can improve the performance by the factor of 10. Moreover, using disk caching/prefetching and the write-buffering techniques in conjunction can improve the total system performance by at least an order of magnitude.
Increasing the disk RPM and the number of disks in RAID disk system also have an impressive improvement over the total system performance. However, employing such techniques requires careful consideration for trade-offs in power/energy consumption