Limited Battery Life Research Articles

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Wireless sensor network is an emerging technology which has an immense scope of research and development. It has the potential of quick capturing, processing and transferring data with high resolution to the base station. WSN consists of multiple sensor nodes, these nodes have low storage capability and limited battery life which dies due to the computation and transmission of data. It is not feasible to replace these batteries due to their placement in isolated areas. In this paper we will emphasize on maximizing energy efficiency and improvement of life span of network. Clustering is the technique which balances the load on sensor network and reduces energy dissipation. LEACH is one of the self- organized clustering routing protocols which will be explored and modified. Further we will compare various LEACH protocols on the basis of their features and we will throw some light on future possibilities and outdo.

Modal Identification of a Full-Scale Building Under Seismic Excitation Using the Fast Mode Identification Technique

The sensors used in structural monitoring systems have becomemore affordable in the last few decades. The number of sensors used for monitoring is expected to grow, creating the need for new algorithms for online modal identification of structural systems. The fast mode identification (FMI) technique uses experimental data from ambient vibration tests to identify operational modal shapes at a fraction of the time used by traditional modal identification techniques. This paper discusses the mathematical formulation and experimental validation of the FMI technique on a full-scale building under earthquake excitation. The method consists of two steps: (1) the identification of natural frequencies and modal damping ratios using traditional techniques, and (2) the identification of operational mode shapes using the FMI technique. Dividing the process in two reduces the computational time required for modal identification. Experimental results show good agreement between the results of FMI and those of other widely used modal identification methods on a full-scale building submitted to seismic excitation. Furthermore, FMI shows a higher consistency on the identified mode coordinates and lower processing time than traditional methods. FMI is envisioned to be used on dense wireless intelligent sensor with limited processing capabilities and battery life.

An empirical study on green practices of mobile phone users

Given the market's saturation with smartphones and the increased power needs that these have as compared with older feature phones, the users' green practices and behavior is emerging as an important research topic. The environmental aspects and general awareness issues are not addressed in this study; however, the limited battery life of smartphones is a decisive factor that shapes the users' behavior, practices and preferences. As such, the users need to follow green practices and carefully assess the energy related characteristics (speed, screen size, weight, and price) that they value the most in a smartphone, to maximize their experience. Based on our previous work that gathered relevant data from 313 users, we extended the analysis in order to examine the user battery life and charging practices, buying habits, green practices and preferences. To that end, we used quantitative statistics and Fuzzy Decision Tree analysis to propose relevant Fuzzy Decision Rules that can classify the results and profile the users.

A comparative analysis of energy conservation approaches in hybrid wireless sensor networks data collection protocols

Wireless sensor network (WSN) has become part of human life as it is used in several applications including healthcare, environment and agricultural, public safety, military, transportation as well as in the industry. In spite of its usefulness, it is challenging to maintain long-term operations due to limited battery life. Several energy efficient protocols have been designed to prolong the network lifetime. The integration of mobility technology with the conventional static sensor network, described as hybrid WSN, promises a new solution that balances energy consumption among sensor nodes and extends the network lifetime. To the best of our knowledge, there has not been as yet an evaluation of the energy-efficiency of the data collection approaches in terms of the energy conservation techniques adopted. In this paper, the architecture of data collection approaches in WSN is discussed. Then, we propose and discuss a taxonomy of types of data collection in WSN. We further present and discuss in details a thematic taxonomy of energy conservation techniques adopted in the various hybrid WSN data collection approaches. Consequently, we compare the different energy conservation approaches that minimize energy consumption in hybrid WSN, highlighting their pros and cons. In conclusion, we point out open research challenges and future directions in the field.

A Comparative Review on Routing Protocols in Wireless Sensor Networks

Networking is a technology in which number of mobile nodes can communicate with each other directly or indirectly through wireless links. A sensor network is composed of a large number of sensor nodes and a sink. In the wireless sensor networks the main problem is limited battery life used by sensor nodes because the size of sensor nodes is small so constraints are there like battery size, processor, storage for data, these all are small as sensor nodes Routing protocols of sensor networks are dependable for handles the routes in the networks. This paper surveys current routing protocols for sensor networks and present a categorization for the various approaches pursued and contrast their strength and constraint.

Load balancing maximal minimal nodal residual energy ad hoc on-demand multipath distance vector routing protocol (LBMMRE-AOMDV)

Mobile ad hoc multipath routing protocols have attracted considerable research attention over the past decade, but the limited battery life of nodes remains a significant obstacle. Many researchers have designed multipath routing protocols that balance the data load between the generated paths, but there is always some tradeoff between conserving the nodes' energy and delivering data. In this paper, I introduce a load balancing (LB) multipath routing protocol based on maximal minimal nodal residual energy (MMRE) in the ad hoc on-demand multipath distance vector (AOMDV) protocol. The proposed LBMMRE-AOMDV protocol evaluates the generated paths based on the maximal nodal residual energy and the actual number of packets that could be transmitted over that path without depleting the nodes' energy. The performance of the proposed protocol was tested and evaluated using different scenarios and performance metrics, and achieved good results compared with MMRE-AOMDV and AOMDV. In particular, the proposed method can increase packet delivery and decrease the number of dead nodes, thus reducing the probability of network portioning.

Evaluation of a novel canine activity monitor for at-home physical activity analysis.

BackgroundAccelerometers are motion-sensing devices that have been used to assess physical activity in dogs. However, the lack of a user-friendly, inexpensive accelerometer has hindered the widespread use of this objective outcome measure in veterinary research. Recently, a smartphone-based, affordable activity monitor (Whistle) has become available for measurement of at-home physical activity in dogs. The aim of this research was to evaluate this novel accelerometer. Eleven large breed, privately owned dogs wore a collar fitted with both the Whistle device and a previously validated accelerometer-based activity monitor (Actical) for a 24-h time period. Owners were asked to have their dogs resume normal daily activities. Total activity time obtained from the Whistle device in minutes was compared to the total activity count from the Actical device. Activity intensity from the Whistle device was calculated manually from screenshots of the activity bars displayed in the smartphone-application and compared to the activity count recorded by the Actical in the same 3-min time period.ResultsA total of 3740 time points were compared. There was a strong correlation between activity intensity of both devices for individual time points (Pearson’s correlation coefficient 0.81, p < 0.0001). An even stronger correlation was observed between the total activity data between the two devices (Pearson’s correlation coefficient 0.925, p < 0.0001).ConclusionsActivity data provided by the Whistle activity monitor may be used as an objective outcome measurement in dogs. The total activity time provided by the Whistle application offers an inexpensive method for obtaining at-home, canine, real-time physical activity data. Limitations of the Whistle device include the limited battery life, the need for manual derivation of activity intensity data and data transfer, and the requirement of Wi-Fi and Bluetooth availability for data transmission.

Distributed Algorithms for Multirobot Task Assignment With Task Deadline Constraints

We present distributed algorithms for multirobot task assignment where the tasks have to be completed within given deadlines. Each robot has a limited battery life and thus there is an upper limit on the amount of time that it has to perform tasks. Performing each task requires certain amount of time (called the task duration) and each robot can have different payoffs for the tasks. Our problem is to assign the tasks to the robots such that the total payoff is maximized while respecting the task deadline constraints and the robot's battery life constraints. Our problem is NP-hard since a special case of our problem is the classical generalized assignment problem (which is NP-hard). There are no known algorithms (distributed or centralized) for this problem with provably good guarantees of performance. We present a distributed algorithm for solving this problem and prove that our algorithm has an approximation ratio of 2. For the special case of constant task duration we present a distributed algorithm that is provably almost optimal. Our distributed algorithms are polynomial in the number of robots and the number of tasks. We also present simulation results to depict the performance of our algorithms. Note to Practitioners-In this paper, we present provably good multirobot task assignment algorithms, while considering practical constraints like task deadlines and limited battery life of robots. Such constraints are relevant in many applications including parts movement by robots in manufacturing, delivery of goods by unmanned vehicles, and search and rescue operations. Our solution is applicable to a group of heterogeneous robots with different suitability (i.e., payoffs) for different tasks. Our distributed approach is independent of the underlying robot communication network topology, and thus can be applied to a wide range of robot network deployments. Finally, our approach is easy to implement, has low communication requirements, and it is scalable, since its running time is linear in the number of robots and tasks.

Smartphone Energy Drain in the Wild

The limited battery life of modern smartphones remains a leading factor adversely affecting the mobile experience of millions of smartphone users. In order to extend battery life, it is critical to understand where and how is energy drain happening on users' phones under normal usage, for example, in a one-day cycle. In this paper, we conduct the first extensive measurement and modeling of energy drain of 1520 smartphone in the wild. We make two primary contributions. First, we develop a hybrid power model that integrates utilization-based models and FSM-based models for different phone components with a novel technique that estimates the triggers for the FSM-based network power model based on network utilization. Second, through analyzing traces collected on 1520 Galaxy S3 and S4 devices in the wild, we present detailed analysis of where the CPU time and energy are spent across the 1520 devices, inside the 800 apps, as well as along several evolution dimensions, including hardware, Android, cellular, and app updates. Our findings of smartphone energy drain in the wild have significant implications to the various key players of the Android phone eco-system, including phone vendors Samsung , Android developers, app developers, and ultimately millions of smartphone users, towards the common goal of extending smartphone battery life and improving the user mobile experience.

Early Stage Automatic Strategy for Power-Aware Signal Processing Systems Design

Complexity management, portability and long term adaptivity are common challenges in different fields of embedded systems, normally colliding with the needs of efficient resource utilization and power balance. Image/signal processing systems, though required to offer a large variety of complex functions, have also to deal with battery-life limitations. Wearable signal processing systems, for example, should provide high performance and support new generation standards without compromising their portability and their long-term usability. These constraints challenge hardware designers: early stage trade-off analysis and power management automated techniques are helpful to guarantee a reasonable time-to-market. In the field of video codec specifications, the MPEG standard known as Reconfigurable Video Coding (RVC) framework addresses functional complexity and adaptivity leveraging on the intrinsic modularity of the dataflow model of computation, but it still lacks in offering power management support. The main contribution of this work is providing an automatic early-stage power management methodology to be adopted within the MPEG-RVC context. Starting from different high-level specifications, our mapping methodology identifies directly on the high-level models disjointed homogeneous logic clock regions, where the platform resources can be enabled/disabled together without affecting the overall system performance. To extend its usability to the RVC community, we have integrated this methodology within the Multi-Dataflow Composer (MDC) tool. MDC is a tool for on-the-fly reconfigurable signal processing platforms deployment. In this paper, we extended MDC to address power-aware multi-context systems. To prove the effectiveness of our work, a coprocessor for image and video processing acceleration has been assembled. This latter has been synthesized on a 90 nm ASIC technology, where demonstrated up to 90 % of reduction in the dynamic power consumption on different dataflow-intensive applications. The coprocessor has been implemented also on FPGA, confirming, partially, the benefits of adopting the proposed methodology.

Highly Secure Mobile Devices Assisted with Trusted Cloud Computing Environments

Mobile devices have been widespread and become very popular with connectivity to the Internet, and a lot of desktop PC applications are now aggressively ported to them. Unfortunately, mobile devices are often vulnerable to malicious attacks due to their common usage and connectivity to the Internet. Therefore, the demands on the development of mobile security systems increase in accordance with advances in mobile computing. However, it is very hard to run a security program on a mobile device all of the time due the device's limited computational power and battery life. To overcome these problems, we propose a novel mobile security scheme that migrates heavy computations on mobile devices to cloud servers. An efficient data transmission scheme for reducing data traffic between devices and servers over networks is introduced. We have evaluated the proposed scheme with a mobile device in a cloud environment, whereby it achieved a maximum speedup of 13.4 compared to a traditional algorithm.

Autonomous Soft-Error Tolerance of FPGA Configuration Bits

Field-programmable gate arrays (FPGAs) are increasingly susceptible to radiation-induced single event upsets (SEUs). These upsets are predominant in a space environment; however, with increasing use of static RAM (SRAM) in modern FPGAs, these SEUs are gaining prominence even in a terrestrial environment. SEUs can flip SRAM bits of FPGA, potentially altering the functionality of the implemented design. This has motivated FPGA designers to investigate techniques to protect the FPGA configuration bits against such inadvertent bit flips (soft error). Traditionally, triple modular redundancy (TMR) is used to protect the FPGA bit flips. Increasing design complexity and limited battery life motivate for alternative approaches for soft-error tolerance. In this article, we propose a technique to improve autonomous fault-masking capabilities of a design by maximizing the number of zeros or ones in lookup tables (LUTs). The technique analyzes critical configuration bits and utilizes spare resources (XOR gates and carry chains) of FPGAs to selectively manipulate the logic implemented in LUTs using two operations: LUT restructuring and LUT decomposition. We implemented the proposed approach for Xilinx Virtex-6 FPGAs and validated the same with a wide set of designs from the MCNC, IWLS 2005, and ITC99 benchmark suites. Results demonstrate that the proposed logic restructuring maximizes logic 0 (or 1) of LUTs by an average of 20%, achieving 80% fault masking with no area overhead. The fault rate of the entire design is reduced by 60% on average as compared to the existing techniques. Furthermore, the logic decomposition algorithm provides incremental fault-tolerance capabilities and achieves an additional 5% fault masking with an average 7% increase in slice usage. The complete methodology is implemented into a tool for Xilinx FPGA and is made available online for the benefit of the research community. The algorithms are lightweight, and the whole design flow (including Xilinx Place and Route) was completed in 75 minutes for the largest benchmark in the set.

Game‐theoretic approach to energy‐efficient resource allocation in device‐to‐device underlay communications

Despite the numerous benefits brought by Device-to-Device (D2D) communications, the introduction of D2D into cellular networks poses many new challenges in the resource allocation design due to the co-channel interference caused by spectrum reuse and limited battery life of User Equipments (UEs). Most of the previous studies mainly focus on how to maximize the Spectral Efficiency (SE) and ignore the energy consumption of UEs. In this paper, we study how to maximize each UE's Energy Efficiency (EE) in an interference-limited environment subject to its specific Quality of Service (QoS) and maximum transmission power constraints. We model the resource allocation problem as a noncooperative game, in which each player is self-interested and wants to maximize its own EE. A distributed interference-aware energy-efficient resource allocation algorithm is proposed by exploiting the properties of the nonlinear fractional programming. We prove that the optimum solution obtained by the proposed algorithm is the Nash equilibrium of the noncooperative game. We also analyze the tradeoff between EE and SE and derive closed-form expressions for EE and SE gaps.

Effective and efficient neighbor detection for proximity-based mobile applications

We consider the problem of maximizing both effectiveness and efficiency of the detection of a device by another device in a mobile ad hoc network, given a maximum amount of time that they remain in the proximity of each other. Effectiveness refers to the degree to which the detection is successful, while efficiency refers to the degree to which the detection is energy saving. Our motivation lies in the emergence of a new trend of mobile applications known as proximity-based mobile applications which enable a user to communicate with other users in some defined range and for a certain amount of time. The highly dynamic nature of these applications makes neighbor detection time-constrained, i.e., even if a device remains in proximity for a limited amount of time, it should be detected with a high probability as a neighbor. In addition, the limited battery life of mobile devices requires the neighbor-detection to be performed by consuming as little energy as possible. To address this problem, we perform a realistic simulation-based study in mobile ad hoc networks and we consider three typical urban environments where proximity-based mobile applications are used, namely indoor with hard partitions, indoor with soft partitions and outdoor urban areas. In our study, a node periodically broadcasts a message in order to be detected as a neighbor. Thus, we study the effect of parameters that we believe could influence effectiveness and efficiency, i.e., the transmission power and the time interval between two consecutive broadcasts. Our results show that regardless of the environment, effectiveness and efficiency are in conflict with each other. Thus, we propose a metric that can be used to make good tradeoffs between effectiveness and efficiency.

The effective intrusion detection system using optimal feature selection algorithm

Wireless mobile networks consist of autonomous with a limited battery life; there are many challenges in identifying false data. False data is generally detected and dropped by the sink, but the false data travelling in the network causes a lot of battery wastage. The work presented in this paper concerns about filtering the false data in the routing nodes before it reaches the sink and saves the resources. The proposed solution involves using advanced encryption standard (AES) by deploying keys to the mobile ad hoc nodes when the network is first deployed. The data is verified by usage of message authentication code. Location and the time stamp of the forwarding nodes is monitored to detect unusual activity by the forwarding nodes.

Wireless powered communication: opportunities and challenges

The performance of wireless communication is fundamentally constrained by the limited battery life of wireless devices, the operations of which are frequently disrupted due to the need of manual battery replacement/recharging. The recent advance in RF-enabled wireless energy transfer (WET) technology provides an attractive solution named wireless powered communication (WPC), where the wireless devices are powered by dedicated wireless power transmitters to provide continuous and stable microwave energy over the air. As a key enabling technology for truly perpetual communications, WPC opens up the potential to build a network with larger throughput, higher robustness, and increased flexibility compared to its battery-powered counterpart. However, the combination of wireless energy and information transmissions also raises many new research problems and implementation issues that need to be addressed. In this article, we provide an overview of state-of- the-art RF-enabled WET technologies and their applications to wireless communications, highlighting the key design challenges, solutions, and opportunities ahead.

Energy Optimized Ad hoc on-Demand Multipath Routing Protocol for Mobile Ad hoc Networks

As the wireless nodes are having limited battery life, energy efficiency is the most important design consideration in mobile ad hoc networks. Many multipath routing schemes are possibly exploiting multiple disjoint routes between any pair of source and destination in order to provide aggregated bandwidth, fault-tolerance and load-balancing properties. Hence we propose an optimized energy efficient routing scheme by slightly modifying MMRE-AOMDV route update rules in order to generate more energy efficient routes than MMRE-AOMDV routing protocol, called an Optimized Minimal Maximal nodal Residual Energy AOMDV (OMMRE-AOMDV) protocol. It reduces the energy consumption, average end to end delay, routing overhead and normalized routing overhead. It also improves packet delivery ratio and throughput. Simulation results show that the OMMRE-AOMDV routing protocol has performed better than AOMDV and MMRE-AOMDV routing protocols.

Automatic offloading of mobile applications into the cloud by means of genetic programming

The limited battery life of modern mobile devices is one of the key problems limiting their use. Even if the offloading of computation onto cloud computing platforms can considerably extend battery duration, it is really hard not only to evaluate the cases where offloading guarantees real advantages on the basis of the requirements of the application in terms of data transfer, computing power needed, etc., but also to evaluate whether user requirements (i.e. the costs of using the cloud services, a determined QoS required, etc.) are satisfied. To this aim, this paper presents a framework for generating models to make automatic decisions on the offloading of mobile applications using a genetic programming (GP) approach. The GP system is designed using a taxonomy of the properties useful to the offloading process concerning the user, the network, the data and the application. The fitness function adopted permits different weights to be given to the four categories considered during the process of building the model. Experimental results, conducted on datasets representing different categories of mobile applications, permit the analysis of the behavior of our algorithm in different applicative contexts. Finally, a comparison with the state of the art of the classification algorithm establishes the goodness of the approach in modeling the offloading process.

Two time-delay dynamic model on the transmission of malicious signals in wireless sensor network

Deployed in a hostile environment, motes of a Wireless sensor network (WSN) could be easily compromised by the attackers because of several constraints such as limited processing capabilities, memory space, and limited battery life time etc. While transmitting the data to their neighbour motes within the network, motes are easily compromised due to resource constraints. Here time delay can play an efficient role to reduce the adversary effect on motes. In this paper, we propose an epidemic model SEIR (Susceptible–Exposed–Infectious–Recovered) with two time delays to describe the transmission dynamics of malicious signals in wireless sensor network. The first delay accounts for an exposed (latent) period while the second delay is for the temporary immunity period due to multiple worm outbreaks. The dynamical behaviour of worm-free equilibrium and endemic equilibrium is shown from the point of stability which switches under some threshold condition specified by the basic reproduction number. Our results show that the global properties of equilibria also depends on the threshold condition and that latent and temporary immunity period in a mote does not affect the stability, but they play a positive role to control malicious attack. Moreover, numerical simulations are given to support the theoretical analysis.

Compact Switched-Beam Antennas Enabling Novel Power-Efficient Wireless Sensor Networks

Energy saving is one of the most important issues in wireless sensor network (WSN) context. The bottleneck of WSN nodes is the limited battery life and, in most cases, it is inconvenient or even impossible to replace the energetic module. Since the communication task is highly most power consuming, it is quite important to achieve an energy efficient communication in order to increase the lifetime of the devices through an intelligent use of the power transmission. In this paper, the integration of WSN nodes with switched-beam antennas is becoming more and more appealing due to the possibility to extend sensor node lifetime by optimizing the transmitted power. In this paper, a switched-beam antenna for WSNs nodes in the ISM band is proposed. The radiating structure consists of four identical antennas, composed of an array of two L-shaped quarter-wavelength slot antenna elements arranged in a compact and symmetrical planar structure. Thanks to a properly designed switching circuit which controls the feeding of the antenna elements, one among eight possible different radiation patterns in the azimuth plane (horizontal plane) can be selected on the basis of specific needs. Simulations and experimental results, referred to a prototype realized on an FR-4 substrate, demonstrate the appropriateness of the proposed switched-beam antenna system as hardware element enabling new power saving strategies in WSN contexts.