Booting, browsing and streaming time profiling, and bottleneck analysis on android-based systems

Lin, Ying-Dar; Ho, Cheng Yuan; Lai, Yuan Cheng; Du, Tzu Hsiung; Chang, Shun Lee

doi:10.1016/j.jnca.2013.02.024

Cited by 5 publications

(3 citation statements)

References 11 publications

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“…Note that about 72% of booting time is spent on setting up the environment and initializings the services for user programs to run on Android based devices [34]. It is not the boot of the kernel that takes most of the boot time, but it is software platform that is initialized after the kernel boot process.…”

Section: Problem Assessmentmentioning

confidence: 99%

LASER: Latency-Aware Segment Relocation for non-volatile memory

Kim

Lee

Shin³

et al. 2015

Journal of Systems Architecture

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Section: Problem Assessmentmentioning

confidence: 99%

LASER: Latency-Aware Segment Relocation for non-volatile memory

Kim

Lee

Shin³

et al. 2015

Journal of Systems Architecture

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“…EBL reviews smartphones and touchpads in terms of functionality, performance, power consumption, stability, and GUI smoothness. Another series of research works are being developed from EBL, which range from performance profiling (bottleneck analysis on Android applications [76], multi-resolution profiler on Android applications [77]), cloud offloading with time-and-energy awareness [78], Android malware detection [79], and smartphone GUI testing [80] [81]. This is a relatively young research area with potentials of good impact on embedded systems in general, smartphones, tablets, and other handheld or future wearable devices.…”

Section: Embedded Benchmarking Lab (Ebl)mentioning

confidence: 99%

Research Roadmap Driven by Network Benchmarking Lab (NBL): Deep Packet Inspection, Traffic Forensics, Embedded Benchmarking, Software Defined Networking and Beyond

Lin

2014

IJNC

Self Cite

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Most researchers look for topics from the literature. But our research derived mostly from development, in turn driven by industrial projects or product testing. We spanned into the areas of cable TV networks, multi-hop cellular, Internet QoS, deep packet inspection, traffic forensics, embedded benchmarking, and software defined networking. Among them, our multi-hop cellular work was the first along this line and has a high impact on both academia and industry, with over 600 citations and standardizations in WLAN mesh (IEEE 802.11s), WiMAX (IEEE 802.16j), Bluetooth (IEEE 802.15.5), and 3GPP LTE-advanced. Side products from our research include a startup (L7 Networks

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“…However, the enhanced air security increased the waiting time of passengers and bring inconvenience to them. To minimize inconvenience to passengers, we should identify the bottlenecks of the airport security process, which is critical [1].…”

Section: Introductionmentioning

confidence: 99%

Bottlenecks Identification - Airport Security Checkpoint Process Optimization based on the GSPN theory

Hu¹

2017

Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)

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Customers satisfaction degree is critical to airlines. Therefore, it is significant for airlines to provide a positive flying experience for passengers by minimizing the time they spend waiting in line at an airport security checkpoint. The key of this problem is to identify the bottlenecks of the airport security process. Based on the Generalized Stochastic Petri Net (GSPN) theory, this article build the bottlenecks identification model to achieve this goal.

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Booting, browsing and streaming time profiling, and bottleneck analysis on android-based systems

Cited by 5 publications

References 11 publications

LASER: Latency-Aware Segment Relocation for non-volatile memory

LASER: Latency-Aware Segment Relocation for non-volatile memory

Research Roadmap Driven by Network Benchmarking Lab (NBL): Deep Packet Inspection, Traffic Forensics, Embedded Benchmarking, Software Defined Networking and Beyond

Bottlenecks Identification - Airport Security Checkpoint Process Optimization based on the GSPN theory

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