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Computation Partitioning in Mobile Cloud Computing： A Survey 总被引：1，自引：0，他引：1
Mobile devices are increasingly interacting with clouds,and mobile cloud computing has emerged as a new paradigm.An central topic in mobile cloud computing is computation partitioning,which involves partitioning the execution of applications between the mobile side and cloud side so that execution cost is minimized.This paper discusses computation partitioning in mobile cloud computing.We first present the background and system models of mobile cloud computation partitioning systems.We then describe and compare state-of-the-art mobile computation partitioning in terms of application modeling,profiling,optimization,and implementation.We point out the main research issues and directions and summarize our own works. 相似文献
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There is a good opportunity for enlightening the services of the mobile devices by introducing computational offloading using cloud technology. Offloading is a process for managing the complexity of the mobile environment by migrating computational load to the cloud. The mobile devices oblige the quick response for the offloading requests; it is dependent on network connectivity. The cloud services take long set‐up time irrespective of network connectivity. In this paper, new system architecture for the dynamic task offloading in the mobile cloud environment is proposed. The architecture includes the offloading algorithm that concentrates on energy consumption of the tasks both in the local and remote environment. The proposed algorithm formulates a collective task execution model for minimizing the energy consumption. The architecture concentrates on the network model by considering the task completion time in three different network scenarios. The experimental results show the efficiency of the suggested architecture in reducing the energy consumption and completion time of the tasks. 相似文献
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Hoang T. Dinh Chonho Lee Dusit Niyato Ping Wang 《Wireless Communications and Mobile Computing》2013,13(18):1587-1611
Together with an explosive growth of the mobile applications and emerging of cloud computing concept, mobile cloud computing (MCC) has been introduced to be a potential technology for mobile services. MCC integrates the cloud computing into the mobile environment and overcomes obstacles related to the performance (e.g., battery life, storage, and bandwidth), environment (e.g., heterogeneity, scalability, and availability), and security (e.g., reliability and privacy) discussed in mobile computing. This paper gives a survey of MCC, which helps general readers have an overview of the MCC including the definition, architecture, and applications. The issues, existing solutions, and approaches are presented. In addition, the future research directions of MCC are discussed. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
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Higinio Mora;Francisco A. Pujol;Tamai Ramirez-Gordillo;Antonio Jimeno; 《Transactions on Emerging Telecommunications Technologies》2024,35(12):e70020
The Mobile Cloud Computing paradigm has revolutionized the concepts of mobile computing and the Internet of Things (IoT). This paradigm allows outsourcing the workload of mobile devices, or other connected “things,” to be computed in the Cloud. Currently, outsourcing possibilities have been widely developed making available computing platforms at different network layers. In a consequence of that, a virtual increasing of the performance and a homogenization of the computing capabilities of the devices are produced. The research described in this work presents a review of the state of the art about recent works, the main operational concerns, challenges, and open issues of this paradigm in order to update the border of knowledge on this topic. As a result, a critical analysis is conducted, and new research directions are discussed. The findings provide value-added to the scientific community and, therefore it could be helpful for other researches in these topics, especially given the rising popularity of IoT platforms. 相似文献
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人们对后3G的要求是:在全球范围内实现无缝覆盖,进行包括语音、文本、图像、视频等在内的高速多媒体通信。为此,在有限频谱资源条件下,必须缩短无线信号的传输半径,极大限度地复用频谱资源,提高单位空间的信道容量。采用各种先进的无线传输技术的无线传输网络则在中、小范围内提供高速率、高质量的无线移动通信服务。因而WLAN和WPAN的需求和应用在不断增长,超宽带(UWB,ultra wide-band)等短距离、高空间容量的技术日益兴起,成为目前无线通信领域的热点。UWB的核心是冲激无线电技术,即利用持续时间非常短(纳秒、亚纳秒级)的脉冲波形来… 相似文献
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Zhigang Zhou Hongli Zhang Lin Ye Xiaojiang Du 《Wireless Communications and Mobile Computing》2016,16(18):3256-3268
Mobile cloud computing (MCC) is an emerging technology to facilitate complex application execution on mobile devices. Mobile users are motivated to implement various tasks using their mobile devices for great flexibility and portability. However, such advantages are challenged by the limited battery life of mobile devices. This paper presents Cuckoo, a scheme of flexible compute‐intensive task offloading in MCC for energy saving. Cuckoo seeks to balance the key design goals: maximize energy saving (technical feasibility) and minimize the impact on user experience with limited cost for offloading (realistic feasibility). Specifically, using a combination of static analysis and dynamic profiling, compute‐intensive tasks are fine‐grained marked from mobile application codes offline. According to the network transmission technologies supported in mobile devices and the runtime network conditions, adopting “task‐bundled” strategy online offloads these tasks to MCC. In the task‐hosted stage, we propose a skyline‐based online resource scheduling strategy to satisfy the realistic feasibility of MCC. In addition, we adopt resource reservation to reduce the extra energy consumption caused by the task multi‐offloading phenomenon. Further, we evaluate the performance of Cuckoo using real‐life data sets on our MCC testbed. Our extensive experiments demonstrate that Cuckoo is able to balance energy consumption and execution performance. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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Ibrar Yaqoob Ejaz Ahmed Abdullah Gani Salimah Mokhtar Muhammad Imran Sghaier Guizani 《Wireless Communications and Mobile Computing》2016,16(16):2572-2589
The unabated flurry of research activities to augment various mobile devices in terms of compute‐intensive task execution by leveraging heterogeneous resources of available devices in the local vicinity has created a new research domain called mobile ad hoc cloud (MAC) or mobile cloud. It is a new type of mobile cloud computing (MCC). MAC is deemed to be a candidate blueprint for future compute‐intensive applications with the aim of delivering high functionalities and rich impressive experience to mobile users. However, MAC is yet in its infancy, and a comprehensive survey of the domain is still lacking. In this paper, we survey the state‐of‐the‐art research efforts carried out in the MAC domain. We analyze several problems inhibiting the adoption of MAC and review corresponding solutions by devising a taxonomy. Moreover, MAC roots are analyzed and taxonomized as architectural components, applications, objectives, characteristics, execution model, scheduling type, formation technologies, and node types. The similarities and differences among existing proposed solutions by highlighting the advantages and disadvantages are also investigated. We also compare the literature based on objectives. Furthermore, our study advocates that the problems stem from the intrinsic characteristics of MAC by identifying several new principles. Lastly, several open research challenges such as incentives, heterogeneity‐ware task allocation, mobility, minimal data exchange, and security and privacy are presented as future research directions. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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It is a visible fact that the growth of mobile devices is enormous. More computations are required to be carried out for various applications in these mobile devices. But the drawback of the mobile devices is less computation power and low available energy. The mobile cloud computing helps in resolving these issues by integrating the mobile devices with cloud technology. Again, the issue is increased in the latency as the task and data to be offloaded to the cloud environment uses WAN. Hence, to decrease the latency, this paper proposes cloudlet‐based dynamic task offloading (CDTO) algorithm where the task can be executed in device environment, cloudlet environment, cloud server environment, and integrated environment. The proposed algorithm, CDTO, is tested in terms of energy consumption and completion time. 相似文献
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A computation offloading scheme based on edge-cloud computing was proposed to improve the system utility of multiuser computation offloading.This scheme improved the system utility while considering the optimization of edge-cloud resources.In order to tackle the problems of computation offloading mode selection and edge-cloud resource allocation,a greedy algorithm based on submodular theory was developed by fully exploiting the computing and communication resources of cloud and edge.The simulation results demonstrate that the proposed scheme effectively reduces the delay and energy consumption of computing tasks.Additionally,when computing tasks are offloaded to edge and cloud from devices,the proposed scheme still maintains stable system utilities under ultra-limited resources. 相似文献
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An ad hoc mobile cloud had been proposed to offload workload to neighboring mobile devices for resource sharing.The issues that whether to offload or not was addressed,how to select the suitable mobile device to offload,and how to assign workload.Game theoretic approach was used to formulate this problem,and then,a distributed scheme was designed to achieve the optimal solution.The experimental results validate the rightness and effectiveness of proposed scheme. 相似文献
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针对具有依赖关系的计算密集型应用任务面临的卸载决策难题,提出了一种基于优先级的深度优先搜索调度策略。考虑到用户能量受限和移动性,构建了一种联合用户下行能量捕获和上行计算任务卸载的网络模型,并在此基础上建立了端到端优化目标函数。结合任务优先级及时延约束,利用深度强化学习自学习的优势,将任务卸载决策问题建模为马尔科夫模型,并设计了基于任务相关性的Dueling Double DQN(D3QN)算法对问题进行求解。仿真数据表明,所提算法较其他算法能够满足更多用户的时延要求,并能减少9%～10%的任务执行时延。 相似文献
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A Survey of Mobile Cloud Computing 总被引：1，自引：0，他引：1
Mobile Cloud Computing (MCC) is emerging as one of the most important branches of cloud computing. In this paper, MCC is defined as cloud computing extended by mobility, and a new ad-hoc infrastructure based on mobile devices. It provides mobile users with data storage and processing services on a cloud computing platform. Because mobile cloud computing is still in its infancy, we aim to clarify confusion that has arisen from different views. Existing works are reviewed, and an overview of recent advances in mobile cloud computing is provided. We investigate representative infrastructures of mobile cloud computing and analyze key components. Moreover, emerging MCC models and services are discussed, and challenging issues are identified that will need to be addressed in future work. 相似文献
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随着智能交通的快速发展和车联网中数据流量爆炸式的增长,汽车终端请求卸载的任务对时延和带宽有了更加严苛的要求。在现有的云计算服务模式中,车辆可以访问云服务器来获得强大的计算、存储和网络资源,但缺点是通信传输时延较大,仅依靠云计算可能会导致过度的延迟。为了更加合理利用资源、减小时延、优化卸载策略,提出了一种基于粒子群优化算法的“车-边-云”协同卸载方案。首先通过接入点附近的软件定义网络（Software Define Network,SDN)控制器根据终端用户附近边缘节点、本地终端和云计算节点的计算资源和容量情况得出最优的卸载策略,充分利用本地、移动边缘计算（Mobile Edge Computing,MEC）设备、云端的计算资源,然后通过粒子群优化算法得出“车-边-云”各计算节点的卸载系数,即最优卸载策略。实验结果表明,相比于其他卸载策略,所提的卸载机制对时延优化效果明显,提高了计算资源的利用率。 相似文献
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随着云计算方式的发展,移动互联网的不断优化和智能终端的逐渐普及,移动云计算势必成为移动互联网未来发展趋势。文中结合移动互联网的现状分析了目前移动云计算的主要应用研究,并总结了移动云计算的特点与发展过程中面临的主要问题,同时对其研究方向提出了展望 相似文献
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移动边缘计算(MEC)通过将计算任务卸载到MEC服务器上,在缓解智能移动设备计算负载的同时,可以降低服务时延。然而目前在MEC系统中,关于任务卸载和资源分配仍然存在以下问题：1)边缘节点间缺乏协作;2)计算任务到达与实际环境中动态变化的特征不匹配;3)协作式任务卸载和资源分配动态联合优化问题。为解决上述问题,文章在协作式MEC架构的基础上,提出了一种基于多智能体的深度确定性策略梯度算法(MADDPG)的任务卸载和资源分配算法,最小化系统中所有用户的长期平均成本。仿真结果表明,该算法可以有效降低系统的时延及能耗。 相似文献