Mobile devices have increasingly been used to run multimedia applications which are extremely downlink-intensive. The conventional rate adaptive and/or margin adaptive approach for radio resource allocation may result in unnecessary energy consumption on mobile devices, which will not be energy efficient for mobile multimedia applications. In this paper, we develop an energy adaptive approach and design an energy-efficient downlink resource allocation scheme to support multimedia applications. The objective is to minimize the total energy consumption of mobile devices for data reception while meeting the data rate requirements at mobile devices and the transmit power constraint at the base station. We show that the optimization problem is NP -hard and then propose an efficient algorithm that has a provable performance guarantee under a certain condition. We have conducted extensive simulations to evaluate the efficacy of the proposed algorithm and our results provide useful insights into the design of energy-efficient resource allocation for wireless systems.
This paper studies joint subchannel allocation, power allocation, and beamforming for simultaneous wireless information and power transfer (SWIPT) in multiuser downlink orthogonal frequency-division multiple access (OFDMA) systems. We formulate a multi-objective optimization (MOO) problem where the objectives are to maximize both the information rate and the harvested power for all users in the system. We approach the MOO problem with two proposed methods, i.e., semidefinite relaxation based weighted aggregation (SDR-WA) and multi-objective genetic algorithm (MOGA). Simulation compares the achievable Pareto optimal solution set yielded by these methods, and illustrates the tradeoffs of the sum information rate vs. the sum harvested power in the system.
Graphics-intensive mobile games are becoming increasingly popular, but such applications place high demand on device CPUs and GPUs. The design of current mobile systems results in unnecessary energy waste due to lack of consideration of application phases and user attention (a “demand-level” gap) and because each processor administers power management autonomously (a “processor-level” gap). This paper proposes a user-centric CPU-GPU governing framework which aims to reduce energy consumption without significantly impacting the user experience. To bridge the gap at the demand level, we identify the user demand at runtime and accordingly determine appropriate governing policies for the respective processors. On the other hand, to bridge the gap at the processor level, the proposed framework interprets the frequency scaling intents of processors based on the observation of the CPU-GPU interaction and the processor status. We implemented our framework on a Samsung Galaxy S4, and conducted extensive experiments with real-world 3D gaming apps. Experimental results showed that, for an application being highly interactive and frequent phase changing, our proposed framework can reduce energy consumption by 45.1% compared with state-of-the-art policy without significantly impacting the user experience.
This paper studies the information-theoretic secrecy rates of wireless two-way relay systems where two users wish to exchange information through a single relay with an eavesdropper observing all communications. We formulate and compare the achievable secrecy rates of the system that employs one of the three common relay protocols: conventional decode-and-forward (DF), DF with network coding (NC), and compute-and-forward (CF) based on physical-layer network coding (PNC). We show that CF based on PNC achieves the highest secrecy rate at high signal-to-noise ratio (SNR), while, interestingly, the other two protocols have mixed performance depending on the power allocation scheme and the network topology. Our study offers insights into designing wireless two-way relay protocols from a secrecy perspective.
Understanding the implications in smartphone usage and the power breakdown among hardware components has led to various energy-efficient designs for mobile systems. While energy consumption has been extensively explored, one critical dimension is often overlooked - unperceived activities that could steal a significant amount of energy behind users' back potentially. In this paper, we conduct the first exploration of unperceived activities in mobile systems. Specifically, we design a series of experiments to reveal, characterize, and analyze unperceived activities invoked by popular resident applications when an Android smartphone is left unused. We draw possible solutions inspired by the exploration and demonstrate that even an immediate remedy can mitigate energy dissipation to some extent.
Mobile systems will increasingly feature emerging OLED displays, whose power consumption is highly dependent on the image content. Existing OLED power-saving techniques change users' visual experience or degrade images' visual quality in exchange for power reduction, or seek a chance to also enhance image quality by employing a compound objective function. This paper presents a win-win scheme that always enhances image quality and reduces power consumption simultaneously. We define metrics to assess the profit and the cost for potential image enhancement and power reduction. Then, we propose algorithms that ensure the transformation of images into their quality-enhanced power-saving versions. Finally, the proposed scheme is realized as a practical camera application on mobile devices. The results of experiments conducted on a commercial tablet with a popular image database are very encouraging and provide valuable insights for future research and practices.
Reducing the communication energy is essential to facilitate the growth of emerging mobile applications. In this paper, we introduce signal strength into location-based applications to reduce the energy consumption of mobile devices for data reception. First, we model the problem of data fetch scheduling, with the objective of minimizing the energy required to fetch location-based information without impacting the application's semantics adversely. To solve the fundamental problem, we propose a dynamic-programming algorithm and prove its optimality in terms of energy savings. Then, we perform postoptimal analysis to explore the tolerance of the algorithm to signal strength fluctuations. Finally, based on the algorithm, we consider implementation issues. We have also developed a virtual tour system integrated with existing Web applications to validate the practicability of the proposed concept. The results of experiments conducted based on real-world case studies are very encouraging and demonstrate the applicability of the proposed algorithm toward signal strength fluctuations.
Improving the performance of storage systems without losing the reliability and sanity/integrity of file systems is a major issue in storage system designs. In contrast to existing storage architectures, we consider a PCM-based storage architecture to enhance the reliability of storage systems. In PCM-based storage systems, the major challenge falls on how to prevent the frequently updated (meta)data from wearing out their residing PCM cells without excessively searching and moving metadata around the PCM space and without extensively updating the index structures of file systems. In this work, we propose an adaptive wear-leveling mechanism to prevent any PCM cell from being worn out prematurely by selecting appropriate data for swapping with constant search/sort cost. Meanwhile, the concept of indirect pointers is designed in the proposed mechanism to swap data without any modification to the file system's indexes. Experiments were conducted based on well-known benchmarks and realistic workloads to evaluate the effectiveness of the proposed design, for which the results are encouraging.
This paper considers a noncoherent distributed space-frequency coded (SFC) wireless relay system with multiple relays. Each relay adopts a censoring scheme to determine whether the relay will decode and forward the source's information towards the destination. We analytically obtain the achievable diversity for both cases of perfect and imperfect relay censoring. With perfect censoring, we show that the same diversity of a conventional noncoherent SFC MIMO-OFDM system is achievable in the considered noncoherent distributed SFC system with maximum likelihood (ML) decoding, regardless of whether partial information of channel statistics and relay decoding status is available at the destination. With imperfect censoring, we analytically investigate how censoring errors affect the achievability of the system's diversity. We show that the two types of censoring errors, which correspond to useless and harmful relays, respectively, can decrease the achievable diversity significantly. Our analytical insights and numerical simulations demonstrate that the noncoherent distributed system can offer a comparable diversity as the conventional MIMO-OFDM system if relay censoring is carefully implemented.
In recent years, advances in virtualization technology have enabled multiple virtual machines to run on a physical machine, such that each virtual machine can perform independently with its own operating system. The IT industry has adopted virtualization technology because of its ability to improve hardware resource utilization, achieve low-power consumption, support concurrent applications, simplify device management, and reduce maintenance costs. However, because of the hardware limitation of storage devices, the I/O capacity could cause performance bottlenecks. To address the problem, we propose a hybrid storage access framework that exploits solid-state drives (SSDs) to improve the I/O performance in a virtualization environment.