HarvOS: Efficient code instrumentation for transiently-powered embedded sensing

We present code instrumentation strategies to allow transiently-powered embedded sensing devices efficiently checkpoint the system's state before energy is exhausted. Our solution, called HarvOS, operates at compile-time with limited developer intervention based on the control-flow graph of a program, while adapting to varying levels of remaining energy and possible program executions at run-time. In addition, the underlying design rationale allows the system to spare the energy-intensive probing of the energy buffer whenever possible. Compared to existing approaches, our evaluation indicates that HarvOS allows transiently-powered devices to complete a given workload with 68% fewer checkpoints, on average. Moreover, our performance in the number of required checkpoints rests only 19% far from that of an "oracle" that represents an ideal solution, yet unfeasible in practice, that knows exactly the last point in time when to checkpoint

Barriers for the Adoption of Professional Development Courses (PDCs) in Public Sector University Libraries

Objective: The purpose of the study was to explore the major problems of Library Professionals working in the academic libraries of public sector universities regarding participation in Professional Development Courses (PDCs). Methodology: Public sector Universities affiliated with Higher Education Commission (HEC) Pakistan, located in Lahore, Pakistan were the target population. The Census sampling technique was adopted to accomplish the objectives of the conducted study. 67 respondents participated in the study. A quantitative research technique was used in the study. A self-created questionnaire was used to collect the data. Key Findings: The findings of the study revealed that a good number of respondents were willing to participate in development activities. But, due to numerous hurdles included shortage of library staff, poor allocation of budget for development activities and non-interesting attitude of organizational administration towards the professional development of Library professionals were the major barriers towards professional development activities. Rationale and Significance: Past literature indicated that no study was conducted covering the objective of barriers in professional development. No researcher made the proper investigation in the local scenario. It was highly desired to explore the barriers in participating in professional development activities in the local context. Implication: This study would contribute to the professional literature. It will also assist policy makers to take initiatives for the capacity building of library professionals

Energy harvesting and wireless transfer in sensor network applications: Concepts and experiences

Advances in micro-electronics and miniaturized mechanical systems are redefining the scope and extent of the energy constraints found in battery-operated wireless sensor networks (WSNs). On one hand, ambient energy harvesting may prolong the systems lifetime or possibly enable perpetual operation. On the other hand, wireless energy transfer allows systems to decouple the energy sources from the sensing locations, enabling deployments previously unfeasible. As a result of applying these technologies to WSNs, the assumption of a finite energy budget is replaced with that of potentially infinite, yet intermittent, energy supply, profoundly impacting the design, implementation, and operation of WSNs. This article discusses these aspects by surveying paradigmatic examples of existing solutions in both fields and by reporting on real-world experiences found in the literature. The discussion is instrumental in providing a foundation for selecting the most appropriate energy harvesting or wireless transfer technology based on the application at hand. We conclude by outlining research directions originating from the fundamental change of perspective that energy harvesting and wireless transfer bring about

Towards soft real-time fault diagnosis for edge devices in industrial IoT using deep domain adaptation training strategy

Abstract: Artificial intelligence and industrial internet of things (IIoT) have been rejuvenating the fault diagnosis systems in Industry 4.0 for avoiding major financial losses caused by faults in rotating machines. Meanwhile, the diagnostic systems are provided with a number of sensory inputs that introduce variations in input space which causes difficulty for the algorithms in edge devices. This issue is generally dealt with bi-view cross-domain learning approach. We propose a soft real-time fault diagnosis system for edge devices using domain adaptation training strategy. The investigation is carried out using deep learning models that can learn representations irrespective of input dimensions. A comparative analysis is performed on a publicly available dataset to evaluate the efficacy of the proposed approach which achieved accuracy of 88.08%. The experimental results show that our method using long short-term memory network achieves the best results for the bearing fault detection in an IIoT environmental setting. © 2021 Elsevier Inc. All rights reserve

Laser Based Energy Distribution Architecture for Decoupling Energy and Sensing Planes in WSN

We propose decoupling energy and sensing planes in WSN. This decoupling represents a paradigm shift as it can alleviate the fundamental problem of energy depletion in WSN and can (in theory) offer a sensor network with infinite lifetime. We present energy transference as the mode of decoupling energy by allowing energy to move between energy-rich and energy-poor nodes. We present a first practical energy distribution architecture that allows us to decouple energy supply from sensing activities. Such a separation of responsibilities enables us to utilize abundant energy sources distant from the sensing location, allowing unrestricted lifetime and resolving unequal energy consumption in WSN. We demonstrate energy transfer for practical decoupling using low-cost and low-footprint, laser μ -power beaming that powers current WSN platforms at 100 m of range. We design and implement LAMP, a tiered architecture to manage energy supply to both mesh and clustered WSN deployments using an energy distribution protocol. We evaluate our system to show that, for an additional cost of $29 per mote, LAMP can support perpetual mesh functionality for up to 40 sensors or 120 nodes in clustered operation

Efficient Intermittent Computing with Differential Checkpointing

Embedded devices running on ambient energy perform computations intermittently, depending upon energy availability. System support ensures forward progress of programs through state checkpointing in non-volatile memory. Checkpointing is, however, expensive in energy and adds to execution times. To reduce this overhead, we present DICE, a system design that efficiently achieves differential checkpointing in intermittent computing. Distinctive traits of DICE are its software-only nature and its ability to only operate in volatile main memory to determine differentials. DICE works with arbitrary programs using automatic code instrumentation, thus requiring no programmer intervention, and can be integrated with both reactive (Hibernus) or proactive (MementOS, HarvOS) checkpointing systems. By reducing the cost of checkpoints, performance markedly improves. For example, using DICE, Hibernus requires one order of magnitude shorter time to complete a fixed workload in real-world settings

Fast and Energy-efficient State Checkpointing for Intermittent Computing

Intermittently powered embedded devices ensure forward progress of programs through state checkpointing in non-volatile memory. Checkpointing is, however, expensive in energy and adds to the execution times. To minimize this overhead, we present DICE, a system that renders differential checkpointing profitable on these devices. DICE is unique because it is a software-only technique and efficient because it only operates in volatile main memory to evaluate the differential. DICE may be integrated with reactive (Hibernus) or proactive (MementOS, HarvOS) checkpointing systems, and arbitrary code can be enabled with DICE using automatic code-instrumentation requiring no additional programmer effort. By reducing the cost of checkpoints, DICE cuts the peak energy demand of these devices, allowing operation with energy buffers that are one-eighth of the size originally required, thus leading to benefits such as smaller device footprints and faster recharging to operational voltage level. The impact on final performance is striking: with DICE, Hibernus requires one order of magnitude fewer checkpoints and one order of magnitude shorter time to complete a workload in real-world settings

The Betrayal of Constant Power × Time: Finding the Missing Joules of Transiently-powered Computers

Transiently-powered computers (TPCs) lay the basis for a battery-less Internet of Things, using energy harvesting and small capacitors to power their operation. This power supply is characterized by extreme variations in supply voltage, as capacitors charge when harvesting energy and discharge when computing. We experimentally find that these variations cause marked fluctuations in clock speed and power consumption, which determine energy efficiency. We demonstrate that it is possible to accurately model and concretely capitalize on these fluctuations. We derive an energy model as a function of supply voltage and develop EPIC, a compile-time energy analysis tool. We use EPIC to substitute for the constant power assumption in existing analysis techniques, giving programmers accurate information on worst-case energy consumption of programs. When using EPIC with existing TPC system support, run-time energy efficiency drastically improves, eventually leading up to a 350% speedup in the time to complete a fixed workload. Further, when using EPIC with existing debugging tools, programmers avoid unnecessary program changes that hurt energy efficiency

Demystifying Energy Consumption Dynamics in Transiently powered Computers

Transiently powered computers (TPCs) form the foundation of the battery-less Internet of Things, using energy harvesting and small capacitors to power their operation. This kind of power supply is characterized by extreme variations in supply voltage, as capacitors charge when harvesting energy and discharge when computing. We experimentally find that these variations cause marked fluctuations in clock speed and power consumption. Such a deceptively minor observation is overlooked in existing literature. Systems are thus designed and parameterized in overly conservative ways, missing on a number of optimizations. We rather demonstrate that it is possible to accurately model and concretely capitalize on these fluctuations. We derive an energy model as a function of supply voltage and prove its use in two settings. First, we develop EPIC, a compile-time energy analysis tool. We use it to substitute for the constant power assumption in existing analysis techniques, giving programmers accurate information on worst-case energy consumption of programs. When using EPIC with existing TPC system support, run-time energy efficiency drastically improves, eventually leading up to a 350% speedup in the time to complete a fixed workload. Further, when using EPIC with existing debugging tools, it avoids unnecessary program changes that hurt energy efficiency. Next, we extend the MSPsim emulator and explore its use in parameterizing a different TPC system support. The improvements in energy efficiency yield up to more than 1000% time speedup to complete a fixed workload