In this paper, we study the feasibility of a batteryless wireless sensor supplied with energy by using microwave power transmission (MPT). If we perform co-channel operation of MPT and wireless local area networks (WLANs) for the sake of spectral efficiency, a time division method for MPT and WLAN communications is required to avoid serious interference from MPT to WLAN data transmissions. In addition, to reduce the power consumption of a sensor, the use of power-save operation of the sensor is desirable. We proposed a scheduling scheme that allocates time for MPT and WLAN communications. Specifically, in the proposed scheduling system, an energy source transmits microwave power to a sensor station except when the sensor station transmits data frames or receives beacon frames. In addition, in the proposed scheduling system, we force the remaining energy of the sensor station to converge to a maximum value by adjusting the time interval of data transmission from the sensor station such that the power consumption of the sensor station is reduced. On the basis of the proposition, we implemented a scheduling system and then confirmed that it performed successfully in the conducted experiments. Finally, we discussed the feasibility of the proposed scheduling scheme by evaluating the coverage and then showed that the scheduling scheme can be applied to closed space or room.

Most of the previous work on power optimization regarded the capacity of battery power as an ideal constant value. In fact, experiments showed that 30% of the total battery capacity was wasted by improper discharge pattern [1]. In this letter, a battery-aware task scheduling protocol which harnesses one of the typical characteristics of batteries, i.e., battery recovery, is proposed to extend usage time for smart phones. The key idea is to adjust the working schedule of the components in smart phones for more energy recovering. Experiments show that when the proposed protocol is applied in an online music application, as much as 9% lifespan extension for batteries can be obtained.

In recent years, computation offloading, through which applications on a mobile device can offload their computations onto more resource-rich clouds, has emerged as a promising technique to reduce battery consumption as well as augment the devices' limited computation and memory capabilities. In order for computation offloading to be energy-efficient, an accurate estimate of battery consumption is required to decide between local processing and computation offloading. In this paper, we propose a novel technique for estimating battery consumption without requiring detailed information about the mobile application's internal structure or its execution behavior. In our approach, the relationship is derived between variables that affect battery consumption (i.e., the input to the application, the transmitted data, and resource status) and the actual consumed energy from the application's past run history. We evaluated the performance of the proposed technique using two different types of mobile applications over different wireless network environments such as 3G, Wi-Fi, and LTE. The experimental results show that our technique can provide tolerable estimation accuracy and thus make correct decisions between local processing and computation offloading.

A self-powered urinary-incontinence sensor with a flexible wire-type urine-activated battery has been developed as an application for wireless biosensor networks. It is disposable and can be embedded in a diaper. The battery consists of two long film-type line electrodes printed on a flexible plastic sheet that abuts the absorbent material of the diaper. It conforms to the shape of the diaper when the diaper is worn. The stress produced by the curvature of the diaper presses the electrodes firmly against the diaper material, providing greater contact with any urine present. Thus, the battery generates more power than when it is flat, as in an unworn diaper. To verify the effectiveness of the battery, we fabricated a battery and a prototype sensor, which consists of an intermittent-power-supply circuit and a wireless transmitter, and embedded the battery in a diaper. The anode of the battery also acts as a wide ground plane for the antenna of the wireless transmitter, which radiates a large amount of power. When 80cc of urine is poured onto the diaper, the battery outputs a voltage of around 1V, which allows the sensor to transmit an ID signal over a distance of 5m every 40 seconds or so.

Coarse-grained Reconfigurable Architecture (CGRA) is a parallel computing platform that provides both high performance of hardware and high flexibility of software. It is becoming a promising platform for embedded and mobile applications. Since the embedded and mobile devices are usually battery-powered, improving battery lifetime becomes one of the primary design issues in using CGRAs. In this paper, we propose a battery-aware task-mapping method to optimize energy consumption and improve battery lifetime. The proposed method mainly addresses two problems: task partitioning and task scheduling when mapping applications onto CGRA. The task partitioning and scheduling are formulated as a joint optimization problem of minimizing the energy consumption. The nonlinear effects of real battery are taken into account in problem formulation. Using the insights from the problem formulation, we design the task-mapping algorithm. We have used several real-world benchmarks to test the effectiveness of the proposed method. Experiment results show that our method can dramatically lower the energy consumption and prolong the battery-life.

Wireless sensor nodes are becoming more and more common in various settings and require a long battery life for better maintainability. Since most sensor nodes are powered by batteries, energy efficiency is a critical problem. In an experiment, we observed that when peak power consumption is high, battery voltage drops quickly, and the sensor stops working even though some useful charge remains in the battery. We propose three off-line algorithms that extend battery life by scheduling sensors' execution time that is able to reduce peak power consumption as much as possible under a deadline constraint. We also developed a simulator to evaluate the effectiveness of these algorithms. The simulation results showed that one of the three algorithms dramatically can extend battery life approximately three time as long as in simultaneous sensor activation.

Solid-state disks (SSDs) have received much attention as replacements for hard disk drives (HDDs). One of their noticeable advantages is their high-speed read/write operation. To achieve good performance, SSDs have an internal memory hierarchy which includes several volatile memories, such as DRAMs and SRAMs. Furthermore, many SSDs adopt aggressive memory management schemes under the assumption of stable power supply. Unfortunately, the data stored in the volatile memories are lost when the power supplied to SSDs is abruptly shut off. Such power failure is often observed in portable devices. For this reason, it is critical to provide a power failure protection scheme for reliable SSDs. In this work, we propose a power-failure protection scheme for SSDs to increase their reliability. The contribution of our work is three-fold. First, we design a power failure protection circuit which incorporates super-capacitors as well as rechargeable batteries. Second, we provide a method to determine the capacity of backup power sources. Third, we propose a data backup procedure when the power failure occurs. We implemented our method on a real board and applied it to a notebook PC with a contemporary SSD. The board measurement and simulation results prove that our method is robust in cases of sudden power failure.

In this paper, a wide input range CMOS multi-mode active rectifier is presented for a magnetic resonant wireless battery charging system. The configuration is automatically changed with respect to the magnitude of the input AC voltage. The output voltage of the multi-mode rectifier is sensed by a comparator. Furthermore, the mode of the multi-mode rectifier is automatically selected by switches among the original rectifier mode, 1-stage voltage multiplier mode, and 2-stage voltage multiplier mode. In the original rectifier, the range of the rectified output DC voltage is from 9 V to 19 V for an input AC voltage from 10 V to 20 V. In the multi-mode rectifier, the input-range is wider compared to the original rectifier by 5 V. As a result, the rectified output DC voltage ranges from 7.5 V to 19 V for an input AC voltage from 5 V to 20 V. The proposed multi-mode rectifier is fabricated in a 0.35 µm CMOS process with an active area of around 2500 µm 1750 µm. When the magnitude of the input AC voltage is 10 V, the power conversion efficiency is about 94%.

More and more mobile devices adopt multi-battery and dynamic voltage scaling policy (DVS) to reduce the energy consumption and extend the battery runtime. However, since the nonlinear characteristics of the multi-battery are not considered, the practical efficiency is not good enough. In order to reduce the energy consumption and extend the battery runtime, this paper proposes an approach based on the battery characteristics to implement the co-optimization of the multi-battery scheduling and dynamic voltage scaling on multi-battery powered systems. In this work, considering the nonlinear discharging characteristics of the existing batteries, we use the Markov process to depict the multi-battery discharging behavior, and build a multi-objective optimal model to denote the energy consumption and battery states, then propose a binary tree based algorithm to solve this model. By means of this method, we get an optimal and applicable scheme about multi-battery scheduling and dynamic voltage scaling. Experimental results show that this approach achieves an average improvement in battery runtime of 17.5% over the current methods in physical implementation.

Battery-powered wireless sensor networks are prone to premature failures because some nodes deplete their batteries more rapidly than others due to workload variations, the many-to-one traffic pattern, and heterogeneous hardware. Most previous sensor network lifetime enhancement techniques focused on balancing the power distribution, assuming the usage of the identical battery. This paper proposes a novel fine-grained cost-constrained lifetime-aware battery allocation solution for sensor networks with arbitrary topologies and heterogeneous power distributions. Based on an energy–cost battery pack model and optimal node partitioning algorithm, a rapid battery pack selection heuristic is developed and its deviation from optimality is quantified. Furthermore, we investigate the impacts of the power variations on the lifetime extension by battery allocation. We prove a theorem to show that power variations of nodes are more likely to reduce the lifetime than to increase it. Experimental results indicate that the proposed technique achieves network lifetime improvements ranging from 4–13 over the uniform battery allocation, with no more than 10 battery pack levels and 2-5 orders of magnitudes speedup compared with a standard integer nonlinear program solver (INLP).

In wireless sensor networks constructed from battery driven nodes, it is difficult to supply electric power to the nodes. Because of this, the power consumption must be reduced. To cope with this problem, clustering techniques have been proposed. EACLE is a method that uses a clustering technique. In EACLE, route selection is executed independently after the CH (Cluster Head) selection. This two-phase control approach increases overheads and reduces the battery power, which shortens the lifetime of wireless sensor networks. To cope with this problem, we have proposed a novel routing and clustering method called PARC for wireless sensor networks that reduces these overheads by integrating the cluster selection phase and the route construction phase into a single phase. However, PARC has a weak point in that the batteries of CHs around the sink node are depleted earlier than the other nodes and the sink node cannot collect sensing data. This phenomenon is called the hot spot problem. In order to cope with this problem of PARC, we propose PARC+, which extends the CH selection method of PARC such as more nodes around the sink can be selected as a CH node. We evaluate our proposed methods by simulation experiments and show its effectiveness.

The principles for good design of battery-aware voltage scheduling algorithms for both aperiodic and periodic task sets on dynamic voltage scaling (DVS) systems are presented. The proposed algorithms are based on greedy heuristics suggested by several battery characteristics and Lagrange multipliers. To construct the proposed algorithms, we use the battery characteristics in the early stage of scheduling more properly. As a consequence, the proposed algorithms show superior results on synthetic examples of periodic and aperiodic tasks from the task sets which are excerpted from the comparative work, on uni- and multi-processor platforms, respectively. In particular, for some large task sets, the proposed algorithms enable previously unschedulable task sets due to battery exhaustion to be schedulable.

This paper describes diffusion of electric vehicles and novel social infrastructure from the viewpoint of systems innovation theory considering both human society aspects and elemental technological aspects. Firstly, fundamentals of the systems innovation theory and the platform theory are mentioned. Secondly, discussion on mobility from the viewpoint of the human-society layer and discussion of electrical vehicles from the viewpoint of the elemental techniques are carried out. Thirdly, based on those, R & D, measures are argued such as establishment of the ubiquitous noncontact feeding and authentication payment system is important. Finally, it is also insisted that after the establishment of this system the super smart grid with temporal and spatial control including demand itself with the low social cost will be expected.

The security level of an internet protocol television (IPTV) digital right management (DRM) system ultimately relies on protection of secret keys. Well known devices for the key protection include smartcards and battery backup SRAMs (BB-SRAMs); however, these devices could be vulnerable to various physical attacks. In this paper, we propose a secure and cost-effective design of a cryptographic system on chip (SoC) that integrates the BB-SRAM with a cell-based design technique. The proposed SoC provides robust safeguard against the physical attacks, and satisfies high-speed and low-price requirements of IPTV set-top boxes. Our implementation results show that the maximum encryption rate of the SoC is 633 Mb/s. In order to verify the data retention capabilities, we made a prototype chip using 0.18 µm standard cell technology. The experimental results show that the integrated BB-SRAM can reliably retain data with a 1.4 µA leakage current.

The proposed quasi-resonant (QR) zero current switching (ZCS) switched-capacitor (SC) converter is a new type of bidirectional power flow control conversion scheme. The proposed converter is able to provide voltage conversion ratios from -3/- (triple-mode/ trisection-mode) to -n/- (-n-mode/--mode) by adding a different number of switched-capacitors and power MOSFET switches with a small series connected resonant inductor for forward and reverse power flow control schemes. It possesses the advantages of low switching losses and current stress in this QR ZCS SC converter. The principle of operation, theoretical analysis of the proposed triple-mode/ trisection-mode bidirectional power conversion scheme is described in detail with circuit model analysis. Simulation and experimental studies are carried out to verify the performance of the proposed inverting type ZCS SC QR bidirectional converter. The proposed converters can be applied to battery equalization for battery management system (BMS).

The redox (Reduction-Oxidation) flow battery is one of the most promising rechargeable batteries due to its ability to average loads and output of power sources. The transient characteristics are well known as the remarkable feature of the battery. Then it can also compensate for a sudden voltage drop. The dynamics are governed by the chemical reactions, fluid flow, and electrical circuit of its structure. This causes the difficulty of the analysis at transient state. This paper discusses the transient behavior of the redox flow battery based on chemical reactions. The concentration change of vanadium ions depends on the chemical reactions and the flow of electrolysis solution. The chemical reaction rate is restricted by the attached external electric circuit. In this paper, a model of the transient behavior is introduced. The validity of the derived model is examined based on experiments for a tested micro-redox flow battery system.

A fuzzy logic control battery equalizing controller (FLC-BEC) is adopted to control the cell voltage balancing process for a series connected Li-ion battery string. The proposed individual cell equalizer (ICE) is based on the bidirectional Cuk converter operated in the discontinuous capacitor voltage mode (DCVM) to reduce the switching loss and improve equalization efficiency. The ICE with the proposed FLC-BEC can reduce the equalizing time, maintain safe operations during the charge/discharge state and increase the battery string capacity.

For the success of a large deployment of UHF RFID, easy-to-use and low-cost engineering tools to facilitate the performance evaluation are demanded particularly in installations and for trouble shooting. The measurement of interrogation area is one of the most typical industrial demands to establish the stable readability of UHF RFID. Exhaustive repetition of tag position change with a read operation and a usage of expensive measurement equipment or special interrogators are common practices to measure the interrogation area. In this paper, a practical method to measure the interrogation area of a UHF RFID by using a battery assisted passive tag (BAP) is presented. After introducing the fundamental design and performances of the BAP that we have developed, we introduce the measurement method. In the method, the target tag in the target installation is continuously traversed either manually or automatically while it is subjected to a repetitive read of a commercial interrogator. During the target tag traversal, the interrogator's commands are continuously monitored by a BAP. With an extensive analysis on interrogator commands, the BAP can differentiate between its own read timings and those of the target tag. The read timings of the target tag collected by the BAP are recorded synchronously with the target tag position, yielding a map of the interrogation area. The present method does not entail a measurement burden. It is also independent of the choice of interrogator and tag. The method is demonstrated in a practical UHF RFID installation to show that the method can measure a 40 mm resolution interrogation area measurement just by traversing the target tag at a slow walking speed, 300 mm/sec.

An energy management circuit is proposed for self-powered ubiquitous sensor modules using vibration-based energy. With the proposed circuit, the sensor modules work with low duty cycle operation. Moreover, a two-tank circuit as a part of the energy management circuit is utilized to solve the problem that the average power density of ambient energy always varies with time while the power consumption of the sensor modules is constant and larger than it. In addition, the long start-up time problem is also avoided with the timing control of the proposed energy management circuit. The CMOS implementation and silicon verification results of the proposed circuit are also presented. Its validity is further confirmed with a vibration-based energy generation. The sensor module is used to supervise the vibration of machines and transfer the vibration signal discontinuously. A piezoelectric element acts as the vibration-to-electricity converter to realize battery-free operation.

Accompanying with the rapid popularization of portable equipments, it becomes very important to make the battery lifetime longer without increasing the battery size. Especially toward the ubiquitous computing age, long battery lifetime in a tight size limitation will be highly demanded. It will be invaluable for intelligent sensor for cars and robots, too. This paper proposes an algorithm to optimize the battery lifetime in the restriction of total size, by simultaneous analysis of operation condition of battery, buck converter, and LSI. We discuss accurate design models of those components at the same time.