&lt;italic&gt;AppATP&lt;/italic&gt;: An Energy Conserving Adaptive Mobile-Cloud Transmission Protocol

Liu, Fangming; Shu, Peng; Lui, John C. S.

doi:10.1109/tc.2015.2401032

Cited by 92 publications

(32 citation statements)

References 27 publications

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“…The work of Liu et al was to design and implement an application‐layer adaptive transmission protocol, AppATP , targeting energy‐efficient data transfers between mobile devices and the cloud platform. AppATP leveraged cloud computing to manage data transmissions for mobile applications, transferring data to and from mobile devices in an energy‐efficient manner.…”

Section: Related Workmentioning

confidence: 99%

“…AppATP leveraged cloud computing to manage data transmissions for mobile applications, transferring data to and from mobile devices in an energy‐efficient manner. Using the stochastic control framework, AppATP only relied on the current network information and data queue sizes to make an online decision on transmission scheduling, and it performed well under unpredictable wireless network conditions …”

Section: Related Workmentioning

confidence: 99%

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One‐on‐one contract game–based dynamic virtual machine migration scheme for Mobile Edge Computing

Kim

2017

Trans Emerging Tel Tech

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In the evolution toward fifth-generation networks, Mobile Edge Computing (MEC) is an emerging paradigm, conceived to meet the ever-increasing computational demands of mobile applications. Within the access range of mobile devices, the MEC technique promises the enablement of efficient Mobile Cloud Computing services.In an MEC system, virtual machine (VM) migration is a key issue; VM migration is the process of moving a VM from an edge node to another edge node. To improve service quality and system performance, the VM migration method has a dual focus on the MEC system's computation and communication resources. In this study, we formulate the VM migration problem as a one-on-one contract game model and develop a learning-based price control mechanism to effectively handle the MEC's resource.By using the game methodology and learning process, our approach is able to capture the dynamics of MEC systems, and it interacts continually with an unknown system environment. Finally, extensive simulation results are provided to demonstrate the capability of the proposed approach in achieving, with respect to existing MEC schemes, both higher resource utilization and system throughput, as well as reduced service drop ratio and reduced service delay.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

One‐on‐one contract game–based dynamic virtual machine migration scheme for Mobile Edge Computing

Kim

2017

Trans Emerging Tel Tech

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“…With respect to mobile-cloud paradigm, AppATP [23] leverages cloud computing to manage data transmissions for mobile apps, transferring data to and from mobile devices in an energy-efficient manner. Carat [24] presents a crowdsourcing approach for collection energy consumption data on smartphones and diagnosing energy anomalies from a community of clients.…”

Section: Related Workmentioning

confidence: 99%

Profiling Energy Efficiency and Data Communications for Mobile Internet of Things

Sathyamoorthy

Ngai

et al. 2017

Wireless Communications and Mobile Computing

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This paper proposes a novel power management solution for resource-constrained devices in the context of Internet of Things (IoT). We focus on smartphones in the IoT, as they are getting increasingly popular and equipped with strong sensing capabilities. Smartphones have complex and asynchronous power consumption incurred by heterogeneous components including their onboard sensors. Their interaction with the cloud allows them to offload computation tasks and access remote data storage. In this work, we aim at monitoring the power consumption behaviours of the smartphones, profiling both individual applications and the system as a whole, to make better decisions in power management. We design a cloud orchestration architecture as an epic predictor of behaviours of smart devices by extracting their application characteristics and resource utilization. We design and implement this architecture to perform energy profiling and data analysis on massive data logs. This cloud orchestration architecture coordinates a number of cloud-based services and supports dynamic workflows between service components, which can reduce energy consumption in the energy profiling process itself. Experimental results showed that small portion of applications dominate the energy consumption of smartphones. Heuristic profiling can effectively reduce energy consumption in data logging and communications without scarifying the accuracy of power monitoring.

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“…Instead, developers need to carefully restructure each application to schedule and aggregate I/O requests like [5], [24]. Besides, compared to other cloud computing based works in [25] and AppATP [26] which have to build a extra middleware in the cloud, eTrain is a more lightweight system which only works in mobile end.…”

Section: Related Workmentioning

confidence: 99%

eTrain: Making Wasted Energy Useful by Utilizing Heartbeats for Mobile Data Transmissions

Zhang

Liu

et al. 2015

2015 IEEE 35th International Conference on Distributed Computing Systems

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With the rapid proliferation of smartphones, hundreds of millions of mobile users are attracted to Instant Messaging (IM) apps. While such apps have brought convenience to our life, it comes with the price of great energy consumption, as these apps keep sending heartbeat messages to the server periodically in order to maintain an always-online connection. These frequent and fragmented transmissions result in a considerable amount of energy waste.In this paper, we investigate the "cost and potential of heartbeats". We quantify power consumption of heartbeats of real-world IM apps through extensive measurements. The measurement results confirm that huge power consumption is induced by heartbeats. The goal of this paper is to save energy by turning the energy wastage of heartbeats into transmitting useful data. Thus, we develop eTrain, a transmission management system running on Android phones, which takes advantage of IM heartbeats (as trains) to piggyback aggregated delay-tolerant apps' data such as e-mail and Weibo (as cargoes) via an online transmission strategy, so as to minimize the cumulative tail energy without sacrificing user-specified deadlines. Compared to other existing works, eTrain can reduce more energy consumption under the same settings. Experiments conducted on smartphones show that eTrain can achieve 12%-33% energy saving in various application scenarios.

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<italic>AppATP</italic>: An Energy Conserving Adaptive Mobile-Cloud Transmission Protocol

Cited by 92 publications

References 27 publications

One‐on‐one contract game–based dynamic virtual machine migration scheme for Mobile Edge Computing

One‐on‐one contract game–based dynamic virtual machine migration scheme for Mobile Edge Computing

Profiling Energy Efficiency and Data Communications for Mobile Internet of Things

eTrain: Making Wasted Energy Useful by Utilizing Heartbeats for Mobile Data Transmissions

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