Difference between revisions of "Resource:Seminar"

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{{SemNote
{{SemNote
|time=2021-10-22 8:40
|time='''Friday 10:30-12:00'''
|addr=Main Building B1-612
|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]].
}}
}}


===Latest===
===Latest===
{{Latest_seminar
|abstract=In this paper, an enhanced flooding-based routing protocol is designed based on random network coding (RNC) and clustering for swarm UAV networks, enabling the efficient routing process without any routing path discovery or network topology information. RNC can naturally accelerate the routing process, with which in some hops fewer generations need to be transmitted. To address the issue of numerous hops and further expedite routing process, a clustering method is leveraged, where UAV networks are partitioned into multiple clusters and generations are only flooded from representatives of each cluster rather than flooded from each UAV. By this way, the amount of hops can be significantly reduced. The technical details of the introduced routing protocol are designed. Moreover, to capture the dynamic network topology, the Poisson cluster process is employed to model UAV networks. Afterwards, stochastic geometry tools are utilized to derive the distance distribution between two random selected UAVs and analytically evaluate performance. Extensive simulation studies are conducted to prove the validation of performance analysis, demonstrate the effectiveness of our designed routing protocol, and reveal its design insight.
|confname=INFOCOM 2021
|link=https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9488721
|title=Enhanced Flooding-Based Routing Protocol for Swarm UAV Networks: Random Network Coding Meets Clustering
|speaker=Luwei
}}
{{Latest_seminar
{{Latest_seminar
|abstract=In recent years, device-to-device (D2D) communication has attained significant attention in the research community. The advantages of D2D communication can be fully realized in multi-hop communication scenario. The integration of cellular and multi-hop networks not only provides guaranteed quality of service and reliability as a traditional cellular network, but also has the flexibility and adaptability as a multi-hop network. Routing in such multi-hop cellular D2D networks is a critical issue, since the multi-hop network can perform worse than a traditional cellular network if wrong routing decisions are made. This is because routing in these multi-hop networks needs to take care of the node mobility, dynamic network topology, and network fragmentation, which did not exist in traditional cellular networking. This paper provides a comprehensive survey of routing in multi-hop D2D networks. Some future research directions for the routing in D2D networks are also discussed at the end of this paper.
|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=IEEE Communications Surveys & Tutorials 2018
|confname=IPSN 2023
|link=https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8386758
|link=https://dl.acm.org/doi/10.1145/3583120.3586963
|title=Routing in Multi-Hop Cellular Device-to-Device(D2D) Networks: A Survey
|title=FLoRa: Energy-Efficient, Reliable, and Beamforming-Assisted Over-The-Air Firmware Update in LoRa Networks
|speaker=Wenjie
|speaker=Kai Chen
}}
|date=2024-05-10}}
 
{{Latest_seminar
{{Latest_seminar
|abstract=Internet path failure recovery relies on routing protocols, such as BGP. However, routing can take minutes to detect failures and reconverge; in some cases, like partial failures or severe performance degradation, it may never intervene. For large scale network outages, such as those caused by route leaks, bypassing the affected party completely may be the only effective solution. This paper presents Connection Path Reselection (CPR), a novel system that operates on edge networks such as Content Delivery Networks and edge peering facilities and augments TCP to deliver transparent, scalable, multipath-aware end-to-end path failure recovery. The key intuition behind it is that edge networks need not rely on BGP to learn of path impairments: they can infer the status of a path by monitoring transport-layer forward progress, and then reroute stalled flows onto healthy paths. Unlike routing protocols such as BGP, CPR operates at the timescale of round-trip times, providing connection recovery in seconds rather than minutes. By delegating routing responsibilities to the edge hosts themselves, CPR achieves per-connection re-routing protection for all destination prefixes without incurring additional costs reconstructing transport protocol state within the network. Unlike previous multipath-aware transport protocols, CPR is unilaterally deployable and has been running in production at a large edge network for over two years.
|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=NSDI 2021
|confname=INFOCOM 2023
|link=https://www.usenix.org/system/files/nsdi21-landa.pdf
|link=https://ieeexplore.ieee.org/abstract/document/10228941/
|title=Staying Alive: Connection Path Reselection at the Edge
|title=Prophet: An Efficient Feature Indexing Mechanism for Similarity Data Sharing at Network Edge
|speaker=Zhuoliu
|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

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