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Recently, energy harvesting systems that utilize hybrid NVM-SRAM memory in their designs are introduced as a promising alternative for battery-operated systems. Since the ambient input power of an energy harvesting system fluctuates as the environmental conditions change, the system may stop the execution of programs until it receives enough energy to continue the execution. Resuming the execution of a program after the suspension may lead to data inconsistency in an energy harvesting system and threatens the correct functionality of the programs. In this paper, we propose COACH, an energy-efficient consistency-aware memory scheme which guarantees the correct functionality and consistency of... 

Recently, energy harvesting systems that utilize hybrid NVM-SRAM memory in their designs are introduced as a promising alternative for battery-operated systems. Since the ambient input power of an energy harvesting system fluctuates as the environmental conditions change, the system may stop the execution of programs until it receives enough energy to continue the execution. Resuming the execution of a program after the suspension may lead to data inconsistency in an energy harvesting system and threatens the correct functionality of the programs. In this paper, we propose COACH, an energy-efficient consistency-aware memory scheme which guarantees the correct functionality and consistency of... 

Energy harvesting has been developed as an effective technology for communication systems in order to extend their lifetime. In this paper, we consider a single-user energy harvesting wireless communication system, in which arrival data and harvested energy curves are modeled as continuous functions. Our first goal is to find an offline algorithm, which maximizes the amount of data, which is transmitted to the receiver node by a given deadline. If more than one scheme exists that transmits the maximum data, we choose the one with minimum utilized energy at the transmitter node. We find this optimal algorithm, by showing its properties. Next, we propose an online algorithm for this system and... 

Energy harvesting has been developed as an effective technology for communication systems in order to extend the lifetime of these systems. In this work, we consider a single-user energy harvesting wireless communication system, in which both of the arrival data and the harvested energy curves are modeled as continuous functions. Our goal is to find an offline algorithm, which maximizes the amount of data which is transmitted to the receiver node by a given deadline. If more than one scheme exist that transmit the maximum data, we choose the one with minimum utilized energy at the transmitter node  

Energy harvesting (EH) has been developed to extend the lifetimes of energy-limited communication systems. In this letter, we consider a single-user EH communication system, in which both of the arrival data and the harvested energy curves are modeled as general functions. Unlike most of the works in the field, we investigate the online algorithms which only acquire the causal information of the arrival data and the harvested energy processes. We study how well the optimal online algorithm works compared with the optimal offline algorithm, and thus our goal is to find the lower and upper bounds for the ratio of the completion time in the optimal online algorithm to the optimal offline... 

Recently, energy harvesting systems that utilize hybrid NVM-SRAM memory in their designs are introduced as a promising alternative for battery-operated systems. Since the ambient input power of an energy harvesting system fluctuates as the environmental conditions change, the system may stop the execution of programs until it receives enough energy to continue the execution. Resuming the execution of a program after the suspension may lead to data inconsistency in an energy harvesting system and threatens the correct functionality of the programs. In this article, we propose COACH, an energy-efficient consistency-aware memory scheme which guarantees the correct functionality and consistency... 

Energy harvesting systems powered by renewable energy sources employ hybrid volatile-nonvolatile memory to enhance energy efficiency and forward progress. These systems have unreliable power sources and energy buffers with limited capacity, so they complete long-running applications across multiple power outages. However, a power outage might cause data inconsistency, because the data in nonvolatile memories are persistent, while the data in volatile memories are unsteady. State of the art studies proposed various memory architectures and compiler-based techniques to tackle the data inconsistency in these systems. These approaches impose too many unnecessary check-points on the system to... 

The energy efficiency of emerging nonvolatile processors equipped with FRAM-SRAM memory makes them a promising solution for energy harvesting systems. To enable correct functionality and forward progress with an unreliable power supply, the system must accumulate sufficient energy in the capacitor to execute tasks atomically, even in the worst case scenario. Due to the large gap between the average and worst case energy consumption of tasks, state of the art approaches like eM-map require a large capacitor to execute tasks on the SRAM. However, the size, cost, and charging time of the capacitor are major concerns in the energy harvesting systems. In this paper, we proposed CHANCE, a... 

In this paper, a common energy harvester is investigated which uses a specimen of magnetic shape memory alloy (MSMA). The aim of this study is to improve system performance and to evaluate the magneto-mechanical loading on the MSMA material. Since demagnetization effect is not included in the employed original MSMA model, a method to incorporate this effect is proposed which has a good performance for the specific magneto-mechanical loading of this problem. In order to decrease the need for bias magnetic field and increase system efficiency, a new return mechanism for the MSMA specimen is proposed. The results indicate that the maximum harvested power from the improved system is obtained at... 

Energy harvesting systems powered by renewable energy sources employ hybrid volatile-nonvolatile memory to enhance energy efficiency and forward progress. These systems have unreliable power sources and energy buffers with limited capacity, so they complete long-running applications across multiple power outages. However, a power outage might cause data inconsistency, because the data in nonvolatile memories are persistent, while the data in volatile memories are unsteady. State of the art studies proposed various memory architectures and compiler-based techniques to tackle the data inconsistency in these systems. These approaches impose too many unnecessary check-points on the system to... 

In communications, the nodes with the ability of harvesting energy potentially can prolong the overall network lifetime. In this paper, we consider a single-user energy harvesting wireless communication system, in which arrival data and harvested energy curves are modeled as continuous functions. Our goal is to find an online algorithm for the throughput maximization problem, which only needs the causal information of the arrival processes. We propose a heuristic online algorithm which is efficient for both discrete and continuous models, even when the distributions of harvested energy and arrival data are unknown  

In this paper, a common energy harvester is investigated which uses a specimen of magnetic shape memory alloy (MSMA). The aim of this study is to improve system performance and to evaluate the magneto-mechanical loading on the MSMA material. Since demagnetization effect is not included in the employed original MSMA model, a method to incorporate this effect is proposed which has a good performance for the specific magneto-mechanical loading of this problem. In order to decrease the need for bias magnetic field and increase system efficiency, a new return mechanism for the MSMA specimen is proposed. The results indicate that the maximum harvested power from the improved system is obtained at... 

This article introduces an architecture exploration tool to study and understand the tradeoffs of future processor systems using nonvolatile memory and help guide the design of the future. Energy efficiency serves as a critical factor in designing embedded systems. Furthermore, the growing dominance of energy harvesting systems (EHSs) in sensor-rich applications has eventuated an emerging trend in wearable-systems and IoT devices as an alternative to battery-powered embedded systems. In this article, researchers have presented CATNAP-Sim, a simulator for EHSs, with NVP and hybrid NVM-SRAM memory  

Energy harvesters are used in today's Wireless Sensor Networks (WSNs) to harvest energy from the environment. Although an energy harvester can provide a supply source with a much greater lifetime than a battery, the amount of available energy for an energy harvesting system is a random variable. Furthermore, the proper management of energy harvesters has a considerable impact on reliability. It has been observed that cooperative error control mechanisms like Cooperative Automatic Repeat Request (C-ARQ) and Cooperative Hybrid ARQ (C-HARQ) can be used for improving the energy management and reliability in Energy Harvesting WSNs (EH-WSNs). Recently, the impact of C-ARC mechanism has been... 

Energy consumption and predictability are two important constraints in designing real-time embedded systems and one of the recently proposed solutions for the energy consumption problem is the use of non-volatile memories due to their lower leakage power consumption. Furthermore, because of their non-volatile nature, the use of these memories helps normally-off computing and energy harvesting systems. However, the write access latency of non-volatile memories is considerably more than that of SRAM which can decrease the performance and predictability of the system. We present a predictable non-volatile data memory for real-time embedded systems which improves both worst-case execution time... 

Stirling engines operate in a variety of temperatures and the electric power production via dish Stirling systems could be considered as an appropriate alternative for high-temperature solar concentrator energy harvesting systems. To this end, by performing various studies and analyses on the engine, Stirling cycle, and heat exchangers while utilizing the solar energy as the input thermal energy of the Stirling engine, parameters with the highest effect on the output power and engine stability are detected and considered as optimization variables. In this case, output power, thermal efficiency, and economic evaluation are taken to be the three suitable objective functions for multi-objective...