OPSEL: optimal producer selection under data redundancy in wireless edge environments

OPSEL: optimal producer selection under data redundancy in wireless edge environments
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DOI:
10.1145/3517212.3558090
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发表时间:
2022-09
期刊:
Proceedings of the 9th ACM Conference on Information-Centric Networking
影响因子:
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通讯作者:
Mohammed Elbadry;Fan Ye;Peter Milder
Mohammed Elbadry;Fan Ye;Peter Milder
中科院分区:
其他
文献类型:
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作者:
Mohammed Elbadry;Fan Ye;Peter Milder

文献摘要

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在无线边缘环境中,由于需要支持应用程序性能、缓解故障或应用程序的固有性质(例如,AR/VR、边缘存储),多个相邻节点之间的数据冗余很常见。此外,在以数据为中心的范例(例如,命名数据联网(NDN))下,请求相同数据的消费者可以利用多播以使得数据仅被发送一次(例如,具有在多个边缘节点处高速缓存的数据的VR游戏)。天真的策略,如选择随机邻居或选择接收信号强度(RSSI)最强的策略(RSSI)会比其他可用的生产商造成更严重的损失。本文提出了一种单跳动态生产者(S)选择协议OPSEL,使单个和多个消费者能够在不断变化的介质条件下连续识别最优的生产者(S)(例如,最低损耗)。当数据是单跳时,OPSEL的目标是让最少数量的生产者向所有消费者发送数据,并在没有明确协调消息的情况下满足他们的性能需求。在真实原型上的实验表明,OPSEL的丢失率为3%,延迟与理论理想相同,而朴素计时器方法的丢失率和延迟可高达60%,延迟为理论的2-3倍。
In wireless edge environments, data redundancy among multiple neighboring nodes is common due to the need to support application performance, mitigate faults, or the intrinsic nature of applications (e.g., AR/VR, edge storage). Further, under data centric paradigms (e.g., Named Data Networking (NDN)), consumers that request the same data may leverage multicast so data are sent only once (e.g., VR games with data cached at multiple edge nodes). Naive strategies such as selecting a random neighbor or the prevailing wisdom of choosing the one with the strongest received signal strength (RSSI) cause more severe loss than other available producers. In this paper, we propose OPSEL, a single-hop dynamic producer(s) selection protocol that enables single and multiple consumers to continuously identify the optimal producer(s) (e.g., lowest loss) under constantly varying medium conditions. When Data is available single-hop, OPSEL's goal is to have the minimum number of producers sending to all consumers and meeting their performance needs without explicit coordination messages. Experiments on a real prototype show that OPSEL is 3% away in loss rate and has the same latency as the theoretical ideal, while naive timer methods can incur up to 60% more loss and 2-3× latency.