Difference between revisions of "Resource:Seminar"

From MobiNetS
Jump to: navigation, search
(wenliang updates seminars)
 
(77 intermediate revisions by 3 users not shown)
Line 1: Line 1:
{{SemNote
{{SemNote
|time='''2022-10-10 9:00'''
|time='''Friday 10:30-12:00'''
|addr=4th Research Building A527-B
|addr=4th Research Building A518
|note=Useful links: [[Resource:Reading_List|Readling list]]; [[Resource:Seminar_schedules|Schedules]]; [[Resource:Previous_Seminars|Previous seminars]].
|note=Useful links: [[Resource:Reading_List|Readling list]]; [[Resource:Seminar_schedules|Schedules]]; [[Resource:Previous_Seminars|Previous seminars]].
}}
}}
Line 7: Line 7:
===Latest===
===Latest===
{{Latest_seminar
{{Latest_seminar
|abstract = Hidden screen-camera communication techniques emerge as a new paradigm that embeds data imperceptibly into regular videos while remaining unobtrusive to human viewers. Three key goals on imperceptible, high rate, and reliable communication are desirable but conflicting, and existing solutions usually made a trade-off among them. In this paper, we present the design and implementation of ChromaCode, a screen-camera communication system that achieves all three goals simultaneously. In our design, we consider for the first time color space for perceptually uniform lightness modifications. On this basis, we design an outcome-based adaptive embedding scheme, which adapts to both pixel lightness and regional texture. Last, we propose a concatenated code scheme for robust coding and devise multiple techniques to overcome various screen-camera channel errors. Our prototype and experiments demonstrate that ChromaCode achieves remarkable raw throughputs of >700 kbps, data goodputs of 120 kbps with BER of 0.05, and with fully imperceptible flicker for viewing proved by user study, which significantly outperforms previous works.  
|abstract=LoRa has emerged as one of the promising long-range and low-power wireless communication technologies for Internet of Things (IoT). With the massive deployment of LoRa networks, the ability to perform Firmware Update Over-The-Air (FUOTA) is becoming a necessity for unattended LoRa devices. LoRa Alliance has recently dedicated the specification for FUOTA, but the existing solution has several drawbacks, such as low energy efficiency, poor transmission reliability, and biased multicast grouping. In this paper, we propose a novel energy-efficient, reliable, and beamforming-assisted FUOTA system for LoRa networks named FLoRa, which is featured with several techniques, including delta scripting, channel coding, and beamforming. In particular, we first propose a novel joint differencing and compression algorithm to generate the delta script for processing gain, which unlocks the potential of incremental FUOTA in LoRa networks. Afterward, we design a concatenated channel coding scheme to enable reliable transmission against dynamic link quality. The proposed scheme uses a rateless code as outer code and an error detection code as inner code to achieve coding gain. Finally, we design a beamforming strategy to avoid biased multicast and compromised throughput for power gain. Experimental results on a 20-node testbed demonstrate that FLoRa improves network transmission reliability by up to 1.51 × and energy efficiency by up to 2.65 × compared with the existing solution in LoRaWAN.
|confname=TMC 2021
|confname=IPSN 2023
|link=https://dl.acm.org/doi/pdf/10.1145/3241539.3241543
|link=https://dl.acm.org/doi/10.1145/3583120.3586963
|title=ChromaCode: A Fully Imperceptible Screen-Camera Communication System
|title=FLoRa: Energy-Efficient, Reliable, and Beamforming-Assisted Over-The-Air Firmware Update in LoRa Networks
|speaker=Mengyu}}
|speaker=Kai Chen
 
|date=2024-05-10}}
{{Latest_seminar
|abstract = We present MVPose, a novel system designed to enable real-time multi-person pose estimation (PE) on commodity mobile devices, which consists of three novel techniques. First, MVPose takes a motion-vector-based approach to fast and accurately track the human keypoints across consecutive frames, rather than running expensive human-detection model and pose-estimation model for every frame. Second, MVPose designs a mobile-friendly PE model that uses lightweight feature extractors and multi-stage network to significantly reduce the latency of pose estimation without compromising the model accuracy. Third, MVPose leverages the heterogeneous computing resources of both CPU and GPU to execute the pose estimation model for multiple persons in parallel, which further reduces the total latency. We present extensive experiments to evaluate the effectiveness of the proposed tecniques by implemented the MVPose on five off-the-shelf commercial smartphones. Evaluation results show that MVPose achieves over 30 frames per second PE with 4 persons per frame, which significantly outperforms the state-of-the-art baseline, with a speedup of up to 5.7 and 3.8 in latency on CPU and GPU, respectively. Compared with baseline, MVPose achieves an improvement of 10.1% in multi-person PE accuracy. Furthermore, MVPose achieves up to 74.3% and 57.6% energy-per-frame saving on average.
|confname=TMC 2021
|link=https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9673682
|title=MVPose:Realtime Multi-Person Pose Estimation using Motion Vector on Mobile Devices
|speaker=Silence}}
 
{{Latest_seminar
{{Latest_seminar
|abstract = Games are energy-intensive applications on mobile devices. Optimizing the energy efficiency of games is hence critical for battery-limited mobile devices. Although the advent of energy-aware scheduling (EAS) integrated in recent devices has provided opportunities for improved energy management, the framework is not specifically tuned for game applications. In this paper, we aim to improve the energy efficiency of game applications running on EAS-enabled mobile devices. To this end, we first analyze the functional characteristics of games, and investigate the source of the energy inefficiency. We then propose a scheme, called System-level Energy-optimization for Game Applications (SEGA), to improve the energy efficiency of games. SEGA governs CPU and GPU power consumption in a tightly coupled manner by employing three key techniques: (1) Lsync-aware GPU DVFS governor, (2) adaptive capacity clamping, and (3) on-demand touch boosting. We implemented SEGA on the latest Android-based smartphones. The evaluation results for 23 popular games showed that SEGA reduced the energy consumption of the Google Pixel 2 XL and Samsung Galaxy S9 Plus smartphones, at the device level, by 6.1–22.3 and 4.0–11.7 percent, respectively, with a quality of service (QoS) degradation of 1.1 and 0.5 percent, on average.
|abstract=As a promising infrastructure, edge storage systems have drawn many attempts to efficiently distribute and share data among edge servers. However, it remains open to meeting the increasing demand for similarity retrieval across servers. The intrinsic reason is that the existing solutions can only return an exact data match for a query while more general edge applications require the data similar to a query input from any server. To fill this gap, this paper pioneers a new paradigm to support high-dimensional similarity search at network edges. Specifically, we propose Prophet, the first known architecture for similarity data indexing. We first divide the feature space of data into plenty of subareas, then project both subareas and edge servers into a virtual plane where the distances between any two points can reflect not only data similarity but also network latency. When any edge server submits a request for data insert, delete, or query, it computes the data feature and the virtual coordinates; then iteratively forwards the request through greedy routing based on the forwarding tables and the virtual coordinates. By Prophet, similar high-dimensional features would be stored by a common server or several nearby servers. Compared with distributed hash tables in P2P networks, Prophet requires logarithmic servers to access for a data request and reduces the network latency from the logarithmic to the constant level of the server number. Experimental results indicate that Prophet achieves comparable retrieval accuracy and shortens the query latency by 55%~70% compared with centralized schemes.
|confname=TMC 2021
|confname=INFOCOM 2023
|link=https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9352566
|link=https://ieeexplore.ieee.org/abstract/document/10228941/
|title=Optimizing Energy Consumption of Mobile Games
|title=Prophet: An Efficient Feature Indexing Mechanism for Similarity Data Sharing at Network Edge
|speaker=Luwei}}
|speaker=Rong Cong
 
|date=2024-05-10}}
 
 
=== History ===
 
{{Resource:Previous_Seminars}}
{{Resource:Previous_Seminars}}

Latest revision as of 20:19, 6 May 2024

Time: Friday 10:30-12:00
Address: 4th Research Building A518
Useful links: Readling list; Schedules; Previous seminars.

Latest

  1. [IPSN 2023] FLoRa: Energy-Efficient, Reliable, and Beamforming-Assisted Over-The-Air Firmware Update in LoRa Networks, Kai Chen
    Abstract: LoRa has emerged as one of the promising long-range and low-power wireless communication technologies for Internet of Things (IoT). With the massive deployment of LoRa networks, the ability to perform Firmware Update Over-The-Air (FUOTA) is becoming a necessity for unattended LoRa devices. LoRa Alliance has recently dedicated the specification for FUOTA, but the existing solution has several drawbacks, such as low energy efficiency, poor transmission reliability, and biased multicast grouping. In this paper, we propose a novel energy-efficient, reliable, and beamforming-assisted FUOTA system for LoRa networks named FLoRa, which is featured with several techniques, including delta scripting, channel coding, and beamforming. In particular, we first propose a novel joint differencing and compression algorithm to generate the delta script for processing gain, which unlocks the potential of incremental FUOTA in LoRa networks. Afterward, we design a concatenated channel coding scheme to enable reliable transmission against dynamic link quality. The proposed scheme uses a rateless code as outer code and an error detection code as inner code to achieve coding gain. Finally, we design a beamforming strategy to avoid biased multicast and compromised throughput for power gain. Experimental results on a 20-node testbed demonstrate that FLoRa improves network transmission reliability by up to 1.51 × and energy efficiency by up to 2.65 × compared with the existing solution in LoRaWAN.
  2. [INFOCOM 2023] Prophet: An Efficient Feature Indexing Mechanism for Similarity Data Sharing at Network Edge, Rong Cong
    Abstract: As a promising infrastructure, edge storage systems have drawn many attempts to efficiently distribute and share data among edge servers. However, it remains open to meeting the increasing demand for similarity retrieval across servers. The intrinsic reason is that the existing solutions can only return an exact data match for a query while more general edge applications require the data similar to a query input from any server. To fill this gap, this paper pioneers a new paradigm to support high-dimensional similarity search at network edges. Specifically, we propose Prophet, the first known architecture for similarity data indexing. We first divide the feature space of data into plenty of subareas, then project both subareas and edge servers into a virtual plane where the distances between any two points can reflect not only data similarity but also network latency. When any edge server submits a request for data insert, delete, or query, it computes the data feature and the virtual coordinates; then iteratively forwards the request through greedy routing based on the forwarding tables and the virtual coordinates. By Prophet, similar high-dimensional features would be stored by a common server or several nearby servers. Compared with distributed hash tables in P2P networks, Prophet requires logarithmic servers to access for a data request and reduces the network latency from the logarithmic to the constant level of the server number. Experimental results indicate that Prophet achieves comparable retrieval accuracy and shortens the query latency by 55%~70% compared with centralized schemes.

History

2024

2023

2022

2021

2020

  • [Topic] [ The path planning algorithm for multiple mobile edge servers in EdgeGO], Rong Cong, 2020-11-18

2019

2018

2017

Template loop detected: Resource:Previous Seminars

Instructions

请使用Latest_seminar和Hist_seminar模板更新本页信息.

    • 修改时间和地点信息
    • 将当前latest seminar部分的code复制到这个页面中
    • 将{{Latest_seminar... 修改为 {{Hist_seminar...，并增加对应的日期信息|date=
    • 填入latest seminar各字段信息
    • link请务必不要留空，如果没有link则填本页地址 https://mobinets.org/index.php?title=Resource:Seminar
  • 格式说明
    • Latest_seminar:

{{Latest_seminar
|confname=
|link=
|title=
|speaker=
}}

    • Hist_seminar

{{Hist_seminar
|confname=
|link=
|title=
|speaker=
|date=
}}

Retrieved from "http://mobinets.cn/site/index.php?title=Resource:Seminar&oldid=2813"