检索结果-内蒙古大学图书馆

Energy Conservation for Image Retrieval on Mobile Systems

ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS 2012年第3期11卷 66-66页

作者： Kumar, Karthik Nimmagadda, Yamini Lu, Yung-Hsiang Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA

Mobile systems such as PDAs and cell phones play an increasing role in handling visual contents such as images. Thousands of images can be stored in a mobile system with the advances in storage technology: this creates the need for better organization and retrieval of these images. Content Based Image Retrieval (CBIR) is a method to retrieve images based on their visual contents. In CBIR, images are compared by matching their numerical representations called features;CBIR is computation and memory intensive and consumes significant amounts of energy. This article examines energy conservation for CBIR on mobile systems. We present three improvements to save energy while performing the computation on the mobile system: selective loading, adaptive loading, and caching features in memory. Using these improvements adaptively reduces the features to be loaded into memory for each search. The reduction is achieved by estimating the difficulty of the search. If the images in the collection are dissimilar, fewer features are sufficient;less computation is performed and energy can be saved. We also consider the effect of consecutive user queries and show how features can be cached in memory to save energy. We implement a CBIR algorithm on an HP iPAQ hw6945 and show that these improvements can save energy and allow CBIR to scale up to 50,000 images on a mobile system. We further investigate if energy can be saved by migrating parts of the computation to a server, called computation offloading. We analyze the impact of the wireless bandwidth, server speed, number of indexed images, and the number of image queries on the energy consumption. Using our scheme, CBIR can be made energy efficient under all conditions.

关键词： Algorithms Design Measurement Performance Mobile content-based image retrieval energy saving adaptive feature reduction similarity index computation offloading

来源：评论

学校读者我要写书评

暂无评论

CLOUD COMPUTING FOR MOBILE USERS: CAN offloading computation SAVE ENERGY?

引用

COMPUTER 2010年第4期43卷 51-56页

作者： Kumar, Karthik Lu, Yung-Hsiang Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA

The cloud heralds a new era of computing where application services are provided through the Internet. Cloud computing can enhance the computing capability of mobile systems, but is it the ultimate solution for extend... 详细信息

关键词： Cloud computing Energy savings Internet Internet Mobile/wireless application services battery lifetimes cloud computing computation offloading energy conservation mobile computing mobile systems mobile users

来源：评论

学校读者我要写书评

暂无评论

Adaptive computation offloading for energy conservation on battery-powered systems

Adaptive computation offloading for energy conservation on b...

引用

International Conference on Parallel and Distributed Systems

作者： Xian, Changjiu Lu, Yung-Hsiang Li, Zhiyuan Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA

ISBN: (纸本)9781424418893

This paper considers the problem of extending the battery lifetime for a portable computer by offloading its computation to a server Depending on the inputs, computation time for different instances of a program can vary significantly and they are often difficult to predict. Different from previous studies on computation offloading, our approach does not require estimating the computation time before the execution. We execute the program initially on the portable client with a timeout. If the computation is not completed after the timeout, it is offloaded to the server We first set the timeout to be the minimum computation time that can benefit from offloading. This method is proved to be 2-competitive. We further consider collecting online statistics of the computation time and find the statistically optimal timeout. Finally, we provide guidelines to construct programs with computation offloading. Experiments show that our methods can save up to 17% more energy than existing approaches.

关键词： computation offloading

来源：评论

学校读者我要写书评

暂无评论

Optimal resource allocation in mobile cloud computing network

引用

Tongxin Xuebao/Journal on Communications 2011年第9 A期32卷 42-48页

作者： Cao, Yang Jiang, Tao Yang, Shi-Yong Qu, Dai-Ming Department of Electronics and Information Engineering Huazhong University of Science and Technology Wuhan 430074 China Department of Electronics and Information Engineering Wuzhou University Wuzhou 543002 China

To reduce the aggravated communication overhead of the computation offloading in the mobile cloud computing network, a novel scheme of optimal resource allocation was proposed to minimize the total completion time of remote tasks offloaded by multiple mobile terminals with the constraint of that the task completion time of each remote task is less than a preset threshold. Firstly, the optimization problem of resource allocation for multiple mobile terminals was formulated. Then, an algorithm was presented in detail to test the feasibility of satisfying the task completion time constraint for each remote task simultaneously. Moreover, an efficient scheme was developed to search the optimal solution of the resource allocation problem. Conducted simulation results show the validity of the proposed optimal resource allocation scheme.

关键词： computation offloading

来源：评论

学校读者我要写书评

暂无评论

NWSLite: A general-purpose, Nonparametric prediction utility for embedded systems

引用

ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS 2008年第3期7卷 32-32页

作者： Gurun, Selim Krintz, Chandra Wolski, Rich Univ Calif Santa Barbara Santa Barbara CA 93106 USA

Time series-based prediction methods have a wide range of uses in embedded systems. Many OS algorithms and applications require accurate prediction of demand and supply of resources. However, configuring prediction algorithms is not easy, since the dynamics of the underlying data requires continuous observation of the prediction error and dynamic adaptation of the parameters to achieve high accuracy. Current prediction methods are either too costly to implement on resource-constrained devices or their parameterization is static, making them inappropriate and inaccurate for a wide range of datasets. This paper presents NWSLite, a prediction utility that addresses these shortcomings on resource-restricted platforms.

关键词： measurement performance computation offloading CPU availability estimation embedded systems network performance estimation prediction algorithms

来源：评论

学校读者我要写书评

暂无评论

Parametric analysis for adaptive computation offloading

Parametric analysis for adaptive computation offloading

引用

Conference on Programming Language Design and Implementation

作者： Wang, C Li, ZY Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA

Many programs can be invoked under different execution options;input parameters and data files. Such different execution contexts may lead to strikingly different execution instances. The optimal code generation may be sensitive to the execution instances. In this paper, we show how to use parametric program analysis to deal with this issue for the optimization problem of computation offloading. computation offloading has been shown to be an effective way to improve performance and energy saving on mobile devices. Optimal program partitioning for computation offloading depends on the tradeoff between the computation workload and the communication cost. The computation workload and communication requirement may change with different execution instances. Optimal decisions on program partitioning must be made at run time when sufficient information about workload and communication requirement becomes available. Our cost analysis obtains program computation workload and communication cost expressed as functions of run-time parameters, and our parametric partitioning algorithm finds the optimal program partitioning corresponding to different ranges of run-time parameters. At run time, the transformed program self-schedules its tasks on either the mobile device or the server, based on the optimal program partitioning that corresponds to the current values of run-time parameters. Experimental results on an HP IPAQ handheld device show that different run-time parameters can lead to quite different program partitioning decisions.

关键词： algorithms design experimentation measurement performance program partitioning program analysis program transformation computation offloading program profiling handheld devices adaptive optimization distributed system

来源：评论

学校读者我要写书评

暂无评论

Resource aware media framework for mobile ad hoc networks

Resource aware media framework for mobile ad hoc networks

引用

International Conference on Telecommunications and Networking (TeNe)/International Conference on Industrial Electronics, Technology and Automation (IETA)

作者： Akram, Adeel Pervez, Shahbaz Khan, Shoab A. Univ Engn & Technol Taxila Pakistan

ISBN: (纸本)9781402062650

In this paper we present a framework that acts as a distributed media encoder/decoder for real-time multimedia streams. The paper proposes an implementation of a Multimedia encoder/decoder that works by partitioning and distributing various tasks allocated to different stages of the encoder/decoder to different computers having the minimum required capabilities for that task. At the end the combined work by these different nodes creates the actual encoded/decoded multimedia stream. As encoding is a resource hungry process, we divide it into separable stages and perform their tasks on multiple nodes, while decoding is performed on the single intended target device if it is capable to do so. In case of less capable target device, the Middleware can convert the encoded video into a format suitable for the client node.

关键词： computation offloading task partitioning time-constrained task scheduling multimedia over ad hoc networks OMAP architecture

来源：评论

学校读者我要写书评

暂无评论

Software architecture exploration for high-performance security processing on a multiprocessor mobile SoC

Software architecture exploration for high-performance secur...

引用

43rd Design Automation Conference

作者： Arora, Divya Raghunathan, Anand Ravi, Srivaths Sankaradass, Murugan Jha, Niraj K. Chakradhar, Srimat T. Princeton Univ Dept Elect Engn Princeton NJ 08544 USA NEC Labs Amer Princeton NJ 08540 USA

ISBN: (纸本)1595933816

We present a systematic methodology for exploring the security processing software architecture for a commercial heterogeneous multiprocessor system-on-chip (SoC) for mobile devices. The SoC contains multiple host processors executing applications and a dedicated programmable security processing engine. We developed an exploration methodology to map the code and data of security software libraries onto the platform, with the objective of maximizing the overall application-visible performance. The salient features of the methodology include (i) the use of real performance measurements from a prototyping board that contains the target platform to drive the exploration, (ii) a new data structure access profiling framework that allows us to accurately model the communication overheads involved in offloading a given set of functions to the security processor, and (iii) an exact branch-and-bound based design space exploration algorithm that determines the best mapping of security library functions and data structures to the host and security processors. We used the proposed framework to map a commercial security library to the target mobile application SoC. The resulting optimized software architecture outperformed several manually-designed software architectures, resulting in upto 12.5X speedup for individual cryptographic operations (encryption, hashing) and 2.2X-6.2X speedup for applications such as a Digital Rights Management (DRM) agent and Secure Sockets Layer (SSL) client. We also demonstrate the applicability of our framework to software architecture exploration in other multiprocessor scenarios.

关键词： security performance software partitioning computation offloading

来源：评论

学校读者我要写书评

暂无评论

computation offloading to save energy on handheld devices: A partition scheme 2

Computation offloading to save energy on handheld devices: A...

引用

2nd International Conference on Compilers, Architecture, and Synthesis for Embedded Systems, CASES 2001

作者： Li, Zhiyuan Wang, Cheng Xu, Rong Department of Computer Sciences Purdue University West LafayetteIN United States

ISBN: (纸本)1581133995

We consider handheld computing devices which are connected to a server (or a powerful desktop machine) via a wireless LAN. On such devices, it is often possible to save the energyon the handheld byoffloading its computation to the server. In this work, based on profiling information on computation time and data sharing at the filevel of procedure calls, we construct a cost graph for a given application program. We then applya partition scheme to statically divide the program into server tasks and client tasks such that the energyconsumed bythe program is minimized. Experiments are performed on a suite of multimedia benchmarks. Results show considerable energysa ving for several programs through offloading. Copyright 2001 ACM.

关键词： computation offloading

来源：评论

学校读者我要写书评

暂无评论

DNN Inference Acceleration Based on Adaptive Task Partitioning and offloading in Embedded VEC

引用

ACM Transactions on Embedded Computing Systems 1000年

作者： Chunlin Li Sen Liu Kun Jiang Mengjie Yang Zihao Zhang Bingxin Wang Liang Zhao Chen Chen Shaohua Wan Wuhan University of Technology Wuhan China School of Computer and Artificial Intelligence Wuhan University of Technology Wuhan China Shenyang Aerospace University Shenyang China University of Electronic Science and Technology of China Shenzhen China

As a distributed embedded system, vehicular edge computing (VEC) completes various complex Deep neural network (DNN) tasks through network collaboration and communication. However,due to the limited computing power of vehicle processors, vehicles cannot handle increasingly complex DNN tasks. To accurately estimate the execution latency of each layer across different DNN models on heterogeneous devices, we proposed the Extreme Gradient Boosting Tree (XGBoost) algorithm to predict DNN task inference latency. Furthermore, we proposed partitioning and offloading algorithms for both chained DNN tasks and Directed Acyclic Graph (DAG)-type DNN tasks, addressing their unique computational characteristics. For chained DNN tasks, we employ a linear search to determine optimal partitioning points based on predictions from the DNN latency prediction model. For the partitioning and offloading of DAG-type DNN tasks, we construct it as a minimum cut problem under the network flow graph and propose a DNN task partitioning and offloading algorithm based on the highest label pre-stream push (HLPP) algorithm to effectively reduce the cost of task partitioning and offloading. Finally, we used an experimental vehicle equipped with Raspberry and a RSU equipped with Jetson Nano to verify the results. The experiment shows that the DNN latency prediction model based on the XGBoost we proposed can effectively improve the latency prediction accuracy of DNN layer-by-layer execution. At the same time, the division and offloading algorithms for different types of DNN inference tasks can achieve higher task completion rate, lower latency, and lower energy consumption.

关键词： Vehicular edge computing (VEC) Deep neural network (DNN) DNN partition computation offloading

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：