Energy Efficiency Of Mobile Devices Research Articles

Energy Efficiency of Mobile Devices Using Fuzzy Logic Control by Exponential Weight with Priority-Based Rate Control in Multi-Radio Opportunistic Networks

The rapid development of mobile devices and wireless network technologies have made them indispensable. This has created a demand for faster networks and longer battery life. The assurance of a stable network service and the enhancement of network experiences for mobile devices is equally crucial to meeting these demands. To address these challenges, mobile devices employ various techniques to decrease power consumption when they connect to wireless networks. Moreover, enhancing the endurance of mobile devices to maintain stable network services is critical when using wireless networks. In this paper, we propose a dual-radio opportunistic network for energy efficiency (DRONEE)–exponential weight with priority-based on rate control (WPRC) method which can extend and enhance the DRONEE hybrid network. By leveraging fuzzy logic control (FLC) and quality of service (QoS), our proposed method effectively solves the weighting problem in the DRONEE–weight (DRONEE–W) method. Through efficient allocation of network resources within each cluster, we minimize resource wastage and maximize resource utilization. Simulation results demonstrate the superior performance of our DRONEE–WPRC method in terms of throughput, buffer size, delay time, and power consumption compared to other methods. Therefore, our proposed method achieves optimal network resource allocation and energy efficiency.

Utilizing Attitude Information for Efficient Multi-User Millimeter-Wave Communications

Sensing has played an important role in the 5G wireless network. It is well recognized that the energy efficiency of mobile devices can be further improved with the assistance of sensing. As an important sensing resource, attitude information is highly related to the angle of arrivals (AoAs) information when user equipments (UEs) rotate. It provides great potential to improve transceiver designs for multi-user millimeter-wave (mmWave) green communications. In this paper, we propose an attitude information aided block diagonalization receiver design algorithm. We first adopt angle of departure aided block diagonalization (AoD-BD) to eliminate inter-user interference (IUI). Then we compensate the rotation for each UE by only updating the receiver with attitude information from motion sensors. Compared to the joint transceiver design performance, we have theoretically proved that the sum spectral efficiency performance penalty of keeping transmitter unchanged is generally negligible. Furthermore, we consider the effect of imperfect attitude information, and derive a robust receiver by modeling the measurement error as Gaussian. Finally, the simulation results are presented to verify the effectiveness of the proposed design. It is noted that no feedback is required between the base station (BS) and UE during the rotation, which substantially reduces the system overhead.

Computation Offloading and User-Clustering Game in Multi-Channel Cellular Networks for Mobile Edge Computing.

Mobile devices may use mobile edge computing to improve energy efficiency and responsiveness by offloading computation tasks to edge servers. However, the transmissions of mobile devices may result in interference that decreases the upload rate and prolongs transmission delay. Clustering has been shown as an effective approach to improve the transmission efficiency for dense devices, but there is no distributed algorithm for the optimization of clustering and computation offloading. In this work, we study the optimization problem of computation offloading to minimize the energy consumption of mobile devices in mobile edge computing by adaptively clustering devices to improve the transmission efficiency. To address the optimization problem in a distributed manner, the decision problem of clustering and computation offloading for mobile devices is formulated as a potential game. We introduce the construction of the potential game and show the existence of Nash equilibrium in the game with a finite enhancement ability. Then, we propose a distributed algorithm of clustering and computation offloading based on game theory. We conducted a simulation to evaluate the proposed algorithm. The numerical results from our simulation show that our algorithm can improve offloading efficiency for mobile devices in mobile edge computing by improving transmission efficiency. By offloading more tasks to edge servers, both the energy efficiency of mobile devices and the responsiveness of computation-intensive applications can be improved simultaneously.

Energy Efficiency of Mobile Devices Using Fuzzy Logic Control by Exponential Weight with Priority-Based Rate Control in Multi-Radio Opportunistic Networks

Energy Efficiency of Mobile Devices Using Fuzzy Logic Control by Exponential Weight with Priority-Based Rate Control in Multi-Radio Opportunistic Networks

TOFFEE: Task Offloading and Frequency Scaling for Energy Efficiency of Mobile Devices in Mobile Edge Computing

As an emerging computing paradigm, mobile edge computing (MEC) can improve users’ service experience by provisioning the cloud resources close to the mobile devices. With MEC, computation-intensive tasks can be processed on the MEC servers, which can greatly decrease the mobile devices’ energy consumption and prolong their battery lifetime. However, the highly dynamic task arrival and wireless channel states pose great challenges on the computation task allocation in MEC. This paper jointly investigates the task allocation and CPU-cycle frequency, to achieve the minimum energy consumption while guaranteeing that the queue length is upper bounded. We formulate it as a stochastic optimization problem, and with the aid of stochastic optimization methods, we decouple the original problem into two deterministic optimization subproblems. An online Task Offloading and Frequency Scaling for Energy Efficiency (TOFFEE) algorithm is proposed to obtain the optimal solutions of these subproblems concurrently. TOFFEE can obtain the close-to-optimal energy consumption while bounding the applications’ queue length. Performance evaluation is conducted which verifies TOFFEE’s effectiveness. Experiment results indicate that TOFFEE can decrease the energy consumption by about 15 percent compared with the RLE algorithm, and by about 38 percent compared with the RME algorithm.

Failure-resilient DAG task scheduling in edge computing

Through placing computation, storage, and communications facilities near the data source, Edge Computing (EC) is anticipated to extend the intelligence from the central cloud to the network edge. The Quality of Experience (QoE) of user and energy efficiency of mobile device could be significantly improved through offloading their computation-intensive tasks to the network edge. With the increasing popularity of intelligent devices, tasks offloaded to the edge are becoming more complex, consisting of multiple sub-tasks with data dependency, which are typically modeled as a Directed Acyclic Graph (DAG). The scheduling of DAG tasks is more complex, which has been proved to be NP-hard. Traditional DAG scheduling algorithms developed in non-edge computing scenarios could not be directly applied due to their neglect of: (1) the competition of communication resources; and (2) the rescheduling requirement in case of edge server failure in dynamic edge network environment. In this backdrop, this paper presents a failure-resilient DAG task scheduling algorithm to minimize the response delay experienced by the tasks. After formulating the DAG task scheduling problem, a context-aware greedy task scheduling (CaGTS) algorithm is proposed. Then, to cope with the failure event of edge server, a dependency-aware task rescheduling (DaTR) algorithm is designed. To evaluate the performance of the proposed algorithms, extensive experiments have been conducted on a simulator developed using Python. Experimental results with diverse parameter settings have shown that CaGTS could reduce at least 10.47% average completion time than benchmarks, and DaTR can effectively avoid task scheduling interruption caused by server failure events.

Efficiently Sharing Remote Computing Resources for Mobile Devices

Computation offloading has been a trending technology in the last decade. Even though computation offloading provides great advantages in terms of performance and energy efficiency for mobile devices, it is inapplicable when an Internet connection is not present or unstable to provide remote executions. In this article, to address these limitations, we introduce a middleware system that can distribute CPU-intensive or commonly used functionality to mobile or edge/cloud devices. Our system enables peer-to-peer communications between nearby devices through a near communication technology. Moreover, one communication group can be connected to other groups, so that a mobile application can effectively utilize remote computing resources by extending its execution range. To realize our goal, we developed a proof-of-concept middleware system by employing a publish/subscribe communication pattern and the Wi-Fi Direct technology. Through various case studies, we demonstrate the effectiveness of the introduced system and easy development of complicated mobile applications in resource-constrained execution environments.

Energy Consumption Optimization by Increasing The Processor Speed of Moving Communication Devices in Transport Layer Protocol

The energy efficiency of mobile devices becomes very important, considering the development of mobile device technology starting to lead to smaller dimensions and with the higher processor speed of these mobile devices. Various studies have been conducted to grow energy-aware in hardware, middleware and application software. The step of optimizing energy consumption can be done at various layers of mobile communication network architecture. This study focuses on examining the energy consumption of mobile devices in the transport layer protocol, where the processor speed of the mobile devices used in this experiment is higher than the processor speed used in similar studies. The mobile device processor in this study has a speed of 1.5 GHz with 1 GHz RAM capacity. While in similar studies that have been carried out, mobile device processors have a speed of 369 MHz with a RAM capacity of less than 0.5 GHz. This study conducted an experiment in transmitting mobile data using TCP and UDP protocols. Because the video requires intensive delivery, so the video is the traffic that is being reviewed. Energy consumption is measured based on the amount of energy per transmission and the amount of energy per package. To complete the analysis, it can be seen the strengths and weaknesses of each protocol in the transport layer protocol, in this case the TCP and UDP protocols, also evaluated the network performance parameters such as delay and packet loss. The results showed that the UDP protocol consumes less energy and transmission delay compared to the TCP protocol. However, only about 22% of data packages can be transmitted. Therefore, the UDP protocol is only effective if the bit rate of data transmitted is close to the network speed. Conversely, despite consuming more energy and delay, the TCP protocol is able to transmit nearly 96% of data packets. On the other hand, when compared to mobile devices that have lower processor speeds, the mobile devices in this study consume more energy to transmit video data. However, transmission delay and packet loss can be suppressed. Thus, mobile devices that have higher processor speeds are able to optimize the energy consumed to improve transmission quality.Key words: energy consumption, processor, delay, packet loss, transport layer protocol

Improving energy efficiency of mobile devices by characterizing and exploring user behaviors

Nowadays, mobile devices have become the prevailing computation platform. Due to their battery-constraint nature, delivering excellent user experience with low energy consumption is highly desirable for mobile devices. Past researches on optimizing the energy efficiency for mobile devices are at either too high or too low levels. The former can explore different QoS requirements for applications, while the latter can model the interaction details. To get both advantages, we target a level in the middle, i.e., user behavior level. In this work, we characterize user behaviors, analyze their QoS requirements and propose corresponding QoS models for each behavior type. Then, we introduce U-ACT, a user behavior aware power management framework, which can optimize CPU frequencies for all different behavior types. Our evaluation shows the proposed framework can achieve up to 62% combined improvement, i.e., the summation of QoS and energy improvements in percentage, comparing with the state-of-the-art governors.

Pre-Grant Signaling for Energy-Efficient 5G and Beyond Mobile Devices: Method and Analysis

Due to the severely limited battery capacities, the energy efficiency of mobile devices plays an important role in their usability. In general, the cellular subsystem is one of the major contributors to the energy consumption of a mobile device, thus improving its energy efficiency is of paramount importance. In this paper, a new concept of pre-grant message together with associated control plane signaling is introduced, aiming to reduce the energy consumption of the cellular subsystem in the downlink, without notable increase in the buffering delay or latency. The proposed method is fully independent of the ordinary discontinuous reception (DRX) principle, which means that both methods can co-exist and act together to efficiently reduce the energy consumption of the user equipment. The performance of the proposed scheme in terms of the false alarm and misdetection rates are investigated and evaluated, in both additive white Gaussian noise and Rayleigh fading channels. The obtained numerical results show that the pre-grant message signaling can be decoded very reliably and can reduce the system power consumption, relative to an ordinary DRX-only reference system, by up to 70%, 68%, and 62% for FTP traffic, video streaming and VoIP, respectively, at the cost of negligible increase in the signaling overhead. The proposed method is also compared in terms of the energy consumption and energy efficiency against another state-of-the-art power-saving mechanism, namely the wake-up radio-based approach. The obtained results show that the pre-grant approach outperforms the wake-up-based system under broad range of traffic characteristics.

Energy saving strategies in the design of mobile device applications

As is well known, the main restriction in mobiles devices is battery duration, so strategies for energy saving in mobile devices should be designed and implemented. In this paper, key considerations in the design of mobile applications are studied from the energy consumption point of view. It has been found that rendering and processing tasks requiring high computational complexity entail increased consumption of energy. Consequently, different techniques, developed at the hardware and operating system levels, have been proposed to improve energy efficiency in mobile devices. On one hand, at the application level, there also exist some approaches, such as Mobile Computation Offloading (MCO) and Graphical User Interface (GUI) design. However, these approaches only consider connectivity and usability problems, putting battery management aspects aside. On the other hand, there are several surveys on saving energy in mobile devices, but many focus on some specific strategies, such as the use of wireless networks or MCO. The main contribution of this work is a literature review, analyzing various strategies for energy saving, emphasizing in those that deal with the development of applications. Unlike other similar articles, we have included several strategies from the literature and those developed and tested by our research group. As shown by our results, the studied strategies prevent energy consumption considerations from affecting other aspects of the application design, such as GUI adaptability and information management.

Energy efficiency of network-coding enabled mobile small cells

Energy efficiency becomes increasingly important due to the limited battery capacity in wireless devices while at the same time user throughput requirements are relentlessly increasing. In this paper, we study an energy efficient cooperation scheme which employs network coding to enhance the energy efficiency for mobile devices. Herein we propose that the mobile devices are clustered into mobile small cells with one of the mobile devices acting as a group head with basic transceiver, coding and relaying functionalities. Group heads coordinate the transmissions from the mobile devices in the mobile small cell to the network's base stations. The objective function of the cooperative scheme is to minimize mobile devices’ energy consumption subject to a certain bit error probability. The proposed network-coding based scheme has been evaluated by means of numerical simulations and compared to both a conventional direct transmit scheme, with no cooperation groups, and a cooperative relaying scheme. Results show that, with network-coded cooperation, energy efficiency may significantly increase provided the density of base stations and mobile devices is below a certain value. Above this value none of the compared cooperation schemes may improve energy efficiency, but rather power consumption is reduced only when mobile devices transmit via base stations in their close proximity.

CETM: a conflict-free energy efficient transmission policy in mobile cloud computing

The rapid advancement of mobile devices creates huge interest to the users for performing various applications. For running those applications, sufficient energy is required which can fulfil the user requirements. To accommodate this challenge, in this work an energy optimal scheduling policy for mobile cloud computing (MCC) named as CETM has been proposed. There are a number of work have been proposed in the literature which focus on energy efficiency of mobile devices but they do not support conflict-free scheduling. In CETM, the applications of mobile devices are split into a number of tasks and the inter release time of two consecutive tasks maintain atleast δ steps. The CETM also supports offloading scheme to reduce the consumption of energy of mobile devices. The simulation results indicate that the proposed approach performs better as compared to the existing approaches such as eTime and ThinkAir.

CETM: a conflict-free energy efficient transmission policy in mobile cloud computing

The rapid advancement of mobile devices creates huge interest to the users for performing various applications. For running those applications, sufficient energy is required which can fulfil the user requirements. To accommodate this challenge, in this work an energy optimal scheduling policy for mobile cloud computing (MCC) named as CETM has been proposed. There are a number of work have been proposed in the literature which focus on energy efficiency of mobile devices but they do not support conflict-free scheduling. In CETM, the applications of mobile devices are split into a number of tasks and the inter release time of two consecutive tasks maintain atleast δ steps. The CETM also supports offloading scheme to reduce the consumption of energy of mobile devices. The simulation results indicate that the proposed approach performs better as compared to the existing approaches such as eTime and ThinkAir.

A Peer Management Policy for Energy Efficiency in Mobile P2P Networks

Recently, mobile devices with multiple network interfaces are not only being used in the daily life but also across the entire industry in diverse ways and in many different sectors, including medical, health, education, business, and entertainment. Especially, analyzing the mobile usage patterns of users, there's been an increasing number of services that provide diverse types of content on an Internet-based environment, including video conferencing and VOD streaming services. For these kinds of services, due to the limitations imposed by the client/server architecture which involves going by a base station, the need for P2P is currently being emphasized, which allows direct communication between mobile devices. In order to improve the stability of mobile P2P services, however, there are challenges to overcome, including constraints of wireless communication (such as irregular bandwidth and frequent interrupts in the connection) as well as limitations of the mobile devices themselves (such as limited CPU and battery capabilities), which are classical mobile computing problems. Accordingly, this paper suggests a peer management policy for mobile P2P environments with high degrees of mobility which is designed to increase the efficiency of data transmission by taking sufficiently into account network characteristics and energy efficiency of mobile devices.

FSLRU: a page cache algorithm for mobile devices with hybrid memory architecture

Even though page cache layer of operating system enhances the performance of mobile devices by reducing the number of write requests issued to the underlying mobile storage, the mobile devices still suffer from the excessive write requests. This is because mobile applications frequently trigger synchronous writes with fsync() system call to guarantee the reliability of each application. Unfortunately, these synchronous writes significantly draw both performance and battery power of mobile devices. This paper proposes a novel page cache algorithm, called fsync-aware LRU (FSLRU), that adopts hybrid memory architecture, which is composed of DRAM and emerging nonvolatile memory (NVM). In particular, the proposed algorithm is designed to overcome the negative performance effect of NVM writes, which is measured on a real board. In order to improve performance and energy efficiency of mobile devices, FSLRU integrates the durability function into page cache layer and provides atomic update operations that are necessary to support strong durability. For detailed performance analyses, the proposed algorithm is implemented on a trace-driven simulator and is evaluated on a real board by replaying the results of the simulator. The evaluation results clearly present that FSLRU outperforms the conventional LRU algorithm by up to 3.2 times under three real world workloads while reducing power consumption by up to 99%1.

Energy consumption and privacy in mobile Web browsing: Individual issues and connected solutions

Providing mechanisms to improve energy efficiency of mobile devices is, in the past few years, one of the important objectives in the field of green computing and energy savings. Several studies have addressed this issue from different point of views, i.e., hardware, software, as well as by analyzing the energy drained by different mobile applications. On the other hand, the energy consumption of Web browsing activities has been poorly addressed, given the lack of analysis about users’ real browsing sessions. In this paper we explore how energy savings in mobile devices can be effectively tackled by switching on/off filtering techniques offered by a privacy-enhancing technology. We present first, results about a survey that we conducted to understand the beliefs, attitudes, behaviors, and expectations of mobile users towards privacy and energy issues, and their behavioral intention on what kind of countermeasures adopt to reduce their privacy leakage. Then, we present a tool, mNoTrace, that allows to protect privacy during Web Navigation and prove, by an experimental study, that, by helping users in protecting their privacy, mNoTrace also achieves a significant reduction in terms of communication and computation overhead and thus battery consumption. Conclusions, remarks and lessons learned on our experimental methodology, that employs hardware-based instrumentation, real workloads, and testing on real sites, will conclude the paper.

Analyzing Assisted Offloading of Cellular User Sessions onto D2D Links in Unlicensed Bands

For the past years, the analysts have been predicting a tremendous and continuous increase in mobile traffic, causing much of industry and academia to seek out any and all methods to increase wireless network capacity. In this paper, we investigate one such method, cellular data offloading onto direct connections between proximate user devices, which has been shown to provide significant wireless capacity gains. To do so, we formulate a new system model that couples a cellular network in licensed bands and a device-to-device (D2D) network in unlicensed bands. We propose that devices be continually associated with the cellular base station and use this connectivity to help manage their direct connections in unlicensed spectrum. In particular, we demonstrate that assisted offloading of cellular user sessions onto the D2D links improves the degree of spatial reuse and reduces the impact of interference. In this study, a session is a real-time flow of data from one user to another, which adheres to a Poisson point process (PPP). By contrast to a throughput- or capacity-centric system view, the application of PPP enables formulations where entire user sessions, rather than singular data packets, are arriving at random and leaving the system after being served. The proposed methodology is flexible enough to accommodate practical offloading scenarios, network selection algorithms, quality of service measures, and advanced wireless technologies. In this study, we are primarily interested in evaluating the data session blocking probability in dynamically loaded cellular and D2D networks, but given the importance of energy efficiency for mobile devices, we are also interested in characterizing the energy expenditure of a typical data session in these different networks. First with our advanced analytical methodology and then with our detailed system-level simulator, we evaluate the performance of network-assisted data session offloading from cellular to D2D connections under a variety of conditions. This analysis represents a useful tool in the development of practical offloading schemes and ongoing standardization efforts.

Optimizing energy efficiency of a multi-radio mobile device in heterogeneous beyond-4G networks

In this paper, we address the operation of a multi-radio mobile device in heterogeneous wireless deployments. We assume that such a device may efficiently control its radio interfaces when using the available radio access technologies. In particular, we investigate the potential of flexible transmit power allocation and develop a provably optimal power control scheme that strictly maximizes the energy efficiency of the mobile device, while at the same time satisfies the minimum required level of the user data rate. When compared against simpler (heuristic) power control strategies, our solution always demonstrates the best energy efficiency of the multi-radio device by enabling collaborative operation between several radio technologies, which makes it a useful benchmark for the future integrated beyond-4G wireless networks.

Toward Environmentally Sustainable Mobile Computing Through an Economic Framework

Amid the plethora of initiatives and research endeavors targeting the minimization of power and energy consumption of information and communication technologies, what has been largely missing is an effort to reduce the energy consumption and electronic waste generated by the rapidly growing segment of mobile computing and communication devices. Prior work with energy efficiency in mobile devices has primarily focused on the goal of maximizing battery life of these devices and not on the broader concept of environmentally sustainable mobile computing. This paper provides an overview of the concept of environmentally sustainable mobile computing and identifies reduction in manufacturing energy costs and electronic waste generated as two important outcomes that can be achieved by increasing device lifespan. Increased device lifespans, however, are possible only if the underlying market forces support such a paradigm shift. This paper develops an analytical economic framework as it applies to mobile phones by analyzing a market scenario of two firms competing under a differentiated Bertrand duopoly model. The framework and its analysis helps verify intuitions about the reasons that affect a firm's decision to offer an environmentally sustainable choice for consumers and considers the feasibility, possible benefits, and challenges in increasing device lifespan, including technical challenges. The results of this paper also provide guidance on the relative impacts of various factors involved on device lifespan such as user-experience, subsidies, and differences in underlying costs to providers.