In drive-thru internet, road side units (RSUs) are deployed along the road, which facilitate content dissemination to the vehicles on the go through vehicle to infrastructure (V2I) communications. Due to many factors including short and intermittent connections, the fading nature of wireless channel, and relatively fast speed of the vehicle, the vehicles might not be able to receive the complete content file successfully. Therefore, caching a file at multiple RSUs along the road in a collaborative manner is needed. To this end, the combination property (CP) is desired for caching the content: if $k$ source packets are mapped into $n \geq k$ packets and with any $k$ out of these $n$ packets are able to recover all the information. Reed-Solomon (RS) codes possess CP and have been widely adopted in distributed storage (DS) systems. RS codes operating within a large size finite field have high encoding/decoding complexity, which dramatically increase the computation burden and prolong the processing delay. By introducing several overhead bits and by smart design, binary zigzag decoding (BZD) can significantly reduce the decoding complexity, and CP-BZD codes that possess both CP and BZD have been proposed recently. For CP-BZD structured drive-thru internet system, packets delivered over the air might encounter errors in certain bits. In this work, without adding extra checking bits, existing overhead bits in CP-BZD is used instead, and a novel decoding method that reaps error correction ability is proposed. In other words, our method has self-error correction ability. Complexity analysis of this proposed method is performed and a low complexity algorithm is designed. This error correction module is completely optional, adaptable, and flexible to be deployed to various environments. Numerical studies show that the proposed method can achieve CP with both low decoding complexity and self-error correction.


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    Title :

    Error Correction CP-BZD Storage Codes for Content Delivery in Drive-Thru Internet


    Contributors:
    Dai, Mingjun (author) / Lu, Shuangshuang (author) / Zhang, Ning (author) / Li, Xiaofeng (author) / Wang, Hui (author)


    Publication date :

    2020-11-01


    Size :

    2086751 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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