Difference between revisions of "Resource:Seminar"

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===Latest===
===Latest===
{{Latest_seminar
{{Latest_seminar
|abstract=Global-scale IPv6 scan, critical for network measurement and management, is still a mission to be accomplished due to its vast address space. To tackle this challenge, IPv6 scan generally leverages pre-defined seed addresses to guide search directions. Under this general principle, however, the core problem of effectively using the seeds is largely open. In this work, we propose a novel IPv6 active search strategy, namely HMap6, which significantly improves the use of seeds, w.r.t. the marginal benefit, for large-scale active address discovery in various prefixes. Using a heuristic search strategy for efficient seed collection and alias prefix detection under a wide range of BGP prefixes, HMap6 can greatly expand the scan coverage. Real-world experiments over the Internet in billion-scale scans show that HMap6 can discover 29.39M unique /80 prefixes with active addresses, an 11.88% improvement over the state-of-the-art methods. Furthermore, the IPv6 hitlists from HMap6 include all-responsive IPv6 addresses with rich information. This result sharply differs from existing public IPv6 hitlists, which contain non-responsive and filtered addresses, and pushes the IPv6 hitlists from quantity to quality. To encourage and benefit further IPv6 measurement studies, we released our tool along with our IPv6 hitlists and the detected alias prefixes.
|abstract=Versatile Internet of Things (IoT) applications call for re-configurable IoT devices that can easily extend new functionality on demand. However, the heterogeneity of functional chips brings difficulties in device customization, leading to inadequate flexibility. In this paper, we propose LEGO, a novel architecture for chip-level re-configurable IoT devices that supports plug-and-play with Commercial Off-The-Shelf (COTS) chips. To combat the heterogeneity of functional chips, we first design a novel Unified Chip Description Language (UCDL) with meta-operation and chip specifications to access various types of functional chips uniformly. Then, to achieve chips plug-and-play, we build up a novel platform and shift all chip control logic to the gateway, which makes IoT devices entirely decoupled from specific applications and does not need to make any changes when plugging in new functional chips. Finally, to handle communications overheads, we built up a novel orchestration architecture for gateway instructions, which minimizes instruction transmission frequency in remote chip control. We implement the prototype and conduct extensive evaluations with 100+ types of COTS functional chips. The results show that new functional chips can be automatically accessed by the system within 0.13 seconds after being plugged in, and only bringing 0.53 kb of communication load on average, demonstrating the efficacy of LEGO design.
|confname=INFOCOM '23
|confname=ASPLOS '23
|link=https://ieeexplore.ieee.org/abstract/document/10229089
|link=https://dl.acm.org/doi/10.1145/3582016.3582050
|title=Search in the Expanse: Towards Active and Global IPv6 Hitlists
|title=LEGO: Empowering Chip-Level Functionality Plug-and-Play for Next-Generation IoT Devices
|speaker=Xinyu
|speaker=Pengfei
|date=2023-11-2}}
|date=2023-11-09}}
{{Latest_seminar
{{Latest_seminar
|abstract=LoRa networks have been deployed in many orchards for environmental monitoring and crop management. An accurate propagation model is essential for efficiently deploying a LoRa network in orchards, e.g., determining gateway coverage and sensor placement. Although some propagation models have been studied for LoRa networks, they are not suitable for orchard environments, because they do not consider the shadowing effect on wireless propagation caused by the ground and tree canopies. This paper presents FLog, a propagation model for LoRa signals in orchard environments. FLog leverages a unique feature of orchards, i.e., all trees have similar shapes and are planted regularly in space. We develop a 3D model of the orchards. Once we have the location of a sensor and a gateway, we know the mediums that the wireless signal traverse. Based on this knowledge, we generate the First Fresnel Zone (FFZ) between the sender and the receiver. The intrinsic path loss exponents (PLE) of all mediums can be combined into a classic Log-Normal Shadowing model in the FFZ. Extensive experiments in almond orchards show that FLog reduces the link quality estimation error by 42.7% and improves gateway coverage estimation accuracy by 70.3%, compared with a widely-used propagation model.
|abstract=In VANETs, it is important to support fast and reliable multi-hop broadcast for safety-related applications. The performance of multi-hop broadcast schemes is greatly affected by relay selection strategies. However, the relationship between the relay selection strategies and the expected broadcast performance has not been fully characterized yet. Furthermore, conventional broadcast schemes usually attempt to minimize the waiting time difference between adjacent relay candidates to reduce the waiting time overhead, which makes the relay selection process vulnerable to internal interference, occurring due to retransmissions from previous forwarders and transmissions from redundant relays. In this paper, we jointly take both of the relay selection and the internal interference mitigation into account and propose a fast, reliable, opportunistic multi-hop broadcast scheme, in which we utilize a novel metric called the expected broadcast speed in relay selection and propose a delayed retransmission mechanism to mitigate the adverse effect of retransmissions from previous forwarders and an expected redundancy probability based mechanism to mitigate the adverse effect of redundant relays. The performance evaluation results show that the proposed scheme yields the best broadcast performance among the four schemes in terms of the broadcast coverage ratio and the end-to-end delivery latency.
|confname=IPSN '23
|confname=TMC '23
|link=https://dl.acm.org/doi/10.1145/3583120.3586969
|link=https://ieeexplore.ieee.org/document/9566795
|title=Link Quality Modeling for LoRa Networks in Orchards
|title=A Fast, Reliable, Opportunistic Broadcast Scheme With Mitigation of Internal Interference in VANETs
|speaker=Jiacheng
|speaker=Luwei
|date=2023-11-02}}
|date=2023-11-09}}
{{Latest_seminar
{{Latest_seminar
|abstract=Quality of Experience (QoE) is one of the most important quality indicators for video streaming applications. But it is still an open question how to assess QoE value objectively and quantitatively over continuous time both for academia and industry. In this paper, we carry out an extensive data study on user behaviors in one of the largest short-video service providers. The measurement data reveals that the user’s exiting behavior in viewing video streams is an appropriate choice as a continuous-time QoE metric. Secondly, we build a quantitative QoE model to objectively assess the quality of video playback by discretizing the playback session into the Markov chain. By collecting 7 billion viewing session logs which cover users from 20 CDN providers and 40 Internet service providers, the proposed state-chain-based model of State-Exiting Ratio (SER) is validated. The experimental results show that the modeling error of SER and session duration are less than 2% and 10s respectively. By using the proposed scheme to optimize adaptive video streaming, the average session duration is improved up to 60% to baseline, and 20% to the existing black-box-like machine learning methods.
|abstract=With the explosive increment of computation requirements, the multiaccess edge computing (MEC) paradigm appears as an effective mechanism. Besides, as for the Internet of Things (IoT) in disasters or remote areas requiring MEC services, unmanned aerial vehicles (UAVs) and high altitude platforms (HAPs) are available to provide aerial computing services for these IoT devices. In this article, we develop the hierarchical aerial computing framework composed of HAPs and UAVs, to provide MEC services for various IoT applications. In particular, the problem is formulated to maximize the total IoT data computed by the aerial MEC platforms, restricted by the delay requirement of IoT and multiple resource constraints of UAVs and HAPs, which is an integer programming problem and intractable to solve. Due to the prohibitive complexity of the exhaustive search, we handle the problem by presenting the matching game theory-based algorithm to deal with the offloading decisions from IoT devices to UAVs, as well as a heuristic algorithm for the offloading decisions between UAVs and HAPs. The external effect affected by the interplay of different IoT devices in the matching is tackled by the externality elimination mechanism. Besides, an adjustment algorithm is also proposed to make the best of aerial resources. The complexity of proposed algorithms is analyzed and extensive simulation results verify the efficiency of the proposed algorithms, and the system performances are also analyzed by the numerical results.
|confname=INFOCOM '23
|confname=IoTJ '23
|link=https://ieeexplore.ieee.org/document/10228896
|link=https://ieeexplore.ieee.org/document/9714482?denied=
|title=Rebuffering but not Suffering: Exploring Continuous-Time Quantitative QoE by User’s Exiting Behaviors
|title=Hierarchical Aerial Computing for Internet of Things via Cooperation of HAPs and UAVs
|speaker=Jiajun
|speaker=Kun Wang
|date=2023-11-02}}
|date=2023-11-09}}
{{Latest_seminar
{{Latest_seminar
|abstract=The resource efficiency of video analytics workloads is critical for large-scale deployments on edge nodes and cloud clusters. Recent advanced systems have benefited from techniques including video compression, frame filtering, and deep model acceleration. However, based on our year-long experience of operating a real-time video analytics system on more than 1000 cameras, we identified a previously overlooked bottleneck of end- to-end concurrency: video decoding. To support concurrent video inference at scale, in this work, we investigate a new task, named video packet gating, which selectively filters packets before running a decoder. We propose a novel multi-view embedding approach for video packets and present PacketGame that has both theoretical performance guarantee and practical system designs. Experiments on both public datasets and a real system show PacketGame saves 52.0-79.3% decoding costs and achieves 2.1-4.8× concurrency compared to original workloads. Comparisons with four state-of-the-art complementary methods show the superiority of PacketGame in end-to-end concurrency.
|abstract=Serverless applications are typically composed of function workflows in which multiple short-lived functions are triggered to exchange data in response to events or state changes. Current serverless platforms coordinate and trigger functions by following high-level invocation dependencies but are oblivious to the underlying data exchanges between functions. This design is neither efficient nor easy to use in orchestrating complex workflows – developers often have to manage complex function interactions by themselves, with customized implementation and unsatisfactory performance. In this paper, we argue that function orchestration should follow a data-centric approach. In our design, the platform provides a data bucket abstraction to hold the intermediate data generated by functions. Developers can use a rich set of data trigger primitives to control when and how the output of each function should be passed to the next functions in a workflow. By making data consumption explicit and allowing it to trigger functions and drive the workflow, complex function interactions can be easily and efficiently supported. We present Pheromone – a scalable, low-latency serverless platform following this data-centric design. Compared to well-established commercial and open-source platforms, Pheromone cuts the latencies of function interactions and data exchanges by orders of magnitude, scales to large workflows, and enables easy implementation of complex applications.
|confname=SIGCOMM '23
|confname=NSDI '23
|link=https://yuanmu97.github.io/preprint/packetgame_sigcomm23.pdf
|link=https://www.usenix.org/conference/nsdi23/presentation/yu
|title=PacketGame: Multi-Stream Packet Gating for Concurrent Video Inference at Scale
|title=Following the Data, Not the Function: Rethinking Function Orchestration in Serverless Computing
|speaker=Shuhong
|speaker=Mengfan
|date=2023-11-02}}
|date=2023-11-09}}
{{Resource:Previous_Seminars}}
{{Resource:Previous_Seminars}}

Revision as of 15:16, 6 November 2023

Time: Thursday 16:20-18:00
Address: 4th Research Building A518
Useful links: Readling list; Schedules; Previous seminars.

Latest

  1. [ASPLOS '23] LEGO: Empowering Chip-Level Functionality Plug-and-Play for Next-Generation IoT Devices, Pengfei
    Abstract: Versatile Internet of Things (IoT) applications call for re-configurable IoT devices that can easily extend new functionality on demand. However, the heterogeneity of functional chips brings difficulties in device customization, leading to inadequate flexibility. In this paper, we propose LEGO, a novel architecture for chip-level re-configurable IoT devices that supports plug-and-play with Commercial Off-The-Shelf (COTS) chips. To combat the heterogeneity of functional chips, we first design a novel Unified Chip Description Language (UCDL) with meta-operation and chip specifications to access various types of functional chips uniformly. Then, to achieve chips plug-and-play, we build up a novel platform and shift all chip control logic to the gateway, which makes IoT devices entirely decoupled from specific applications and does not need to make any changes when plugging in new functional chips. Finally, to handle communications overheads, we built up a novel orchestration architecture for gateway instructions, which minimizes instruction transmission frequency in remote chip control. We implement the prototype and conduct extensive evaluations with 100+ types of COTS functional chips. The results show that new functional chips can be automatically accessed by the system within 0.13 seconds after being plugged in, and only bringing 0.53 kb of communication load on average, demonstrating the efficacy of LEGO design.
  2. [TMC '23] A Fast, Reliable, Opportunistic Broadcast Scheme With Mitigation of Internal Interference in VANETs, Luwei
    Abstract: In VANETs, it is important to support fast and reliable multi-hop broadcast for safety-related applications. The performance of multi-hop broadcast schemes is greatly affected by relay selection strategies. However, the relationship between the relay selection strategies and the expected broadcast performance has not been fully characterized yet. Furthermore, conventional broadcast schemes usually attempt to minimize the waiting time difference between adjacent relay candidates to reduce the waiting time overhead, which makes the relay selection process vulnerable to internal interference, occurring due to retransmissions from previous forwarders and transmissions from redundant relays. In this paper, we jointly take both of the relay selection and the internal interference mitigation into account and propose a fast, reliable, opportunistic multi-hop broadcast scheme, in which we utilize a novel metric called the expected broadcast speed in relay selection and propose a delayed retransmission mechanism to mitigate the adverse effect of retransmissions from previous forwarders and an expected redundancy probability based mechanism to mitigate the adverse effect of redundant relays. The performance evaluation results show that the proposed scheme yields the best broadcast performance among the four schemes in terms of the broadcast coverage ratio and the end-to-end delivery latency.
  3. [IoTJ '23] Hierarchical Aerial Computing for Internet of Things via Cooperation of HAPs and UAVs, Kun Wang
    Abstract: With the explosive increment of computation requirements, the multiaccess edge computing (MEC) paradigm appears as an effective mechanism. Besides, as for the Internet of Things (IoT) in disasters or remote areas requiring MEC services, unmanned aerial vehicles (UAVs) and high altitude platforms (HAPs) are available to provide aerial computing services for these IoT devices. In this article, we develop the hierarchical aerial computing framework composed of HAPs and UAVs, to provide MEC services for various IoT applications. In particular, the problem is formulated to maximize the total IoT data computed by the aerial MEC platforms, restricted by the delay requirement of IoT and multiple resource constraints of UAVs and HAPs, which is an integer programming problem and intractable to solve. Due to the prohibitive complexity of the exhaustive search, we handle the problem by presenting the matching game theory-based algorithm to deal with the offloading decisions from IoT devices to UAVs, as well as a heuristic algorithm for the offloading decisions between UAVs and HAPs. The external effect affected by the interplay of different IoT devices in the matching is tackled by the externality elimination mechanism. Besides, an adjustment algorithm is also proposed to make the best of aerial resources. The complexity of proposed algorithms is analyzed and extensive simulation results verify the efficiency of the proposed algorithms, and the system performances are also analyzed by the numerical results.
  4. [NSDI '23] Following the Data, Not the Function: Rethinking Function Orchestration in Serverless Computing, Mengfan
    Abstract: Serverless applications are typically composed of function workflows in which multiple short-lived functions are triggered to exchange data in response to events or state changes. Current serverless platforms coordinate and trigger functions by following high-level invocation dependencies but are oblivious to the underlying data exchanges between functions. This design is neither efficient nor easy to use in orchestrating complex workflows – developers often have to manage complex function interactions by themselves, with customized implementation and unsatisfactory performance. In this paper, we argue that function orchestration should follow a data-centric approach. In our design, the platform provides a data bucket abstraction to hold the intermediate data generated by functions. Developers can use a rich set of data trigger primitives to control when and how the output of each function should be passed to the next functions in a workflow. By making data consumption explicit and allowing it to trigger functions and drive the workflow, complex function interactions can be easily and efficiently supported. We present Pheromone – a scalable, low-latency serverless platform following this data-centric design. Compared to well-established commercial and open-source platforms, Pheromone cuts the latencies of function interactions and data exchanges by orders of magnitude, scales to large workflows, and enables easy implementation of complex applications.

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

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