Piggybacking (data transmission)

About: Piggybacking (data transmission) is a research topic. Over the lifetime, 394 publications have been published within this topic receiving 5044 citations.

Adaptive piggybacking: a novel technique for data sharing in video-on-demand storage servers

Abstract: Recent technology advances have made multimedia on-demand services, such as home entertainment and home-shopping, important to the consumer market. One of the most challenging aspects of this type of service is providing access either instantaneously or within a small and reasonable latency upon request. We consider improvements in the performance of multimedia storage servers through data sharing between requests for popular objects, assuming that the I/O bandwidth is the critical resource in the system. We discuss a novel approach to data sharing, termed adaptive piggybacking, which can be used to reduce the aggregate I/O demand on the multimedia storage server and thus reduce latency for servicing new requests.

A Solution to the Network Challenges of Data Recovery in Erasure-coded Distributed Storage Systems: A Study on the Facebook Warehouse Cluster

Abstract: Erasure codes, such as Reed-Solomon (RS) codes, are being increasingly employed in data centers to combat the cost of reliably storing large amounts of data. Although these codes provide optimal storage efficiency, they require significantly high network and disk usage during recovery of missing data. In this paper, we first present a study on the impact of recovery operations of erasure-coded data on the data-center network, based on measurements from Facebook's warehouse cluster in production. To the best of our knowledge, this is the first study of its kind available in the literature. Our study reveals that recovery of RS-coded data results in a significant increase in network traffic, more than a hundred terabytes per day, in a cluster storing multiple petabytes of RS-coded data. To address this issue, we present a new storage code using our recently proposed "Piggybacking" framework, that reduces the network and disk usage during recovery by 30% in theory, while also being storage optimal and supporting arbitrary design parameters. The implementation of the proposed code in the Hadoop Distributed File System (HDFS) is underway. We use the measurements from the warehouse cluster to show that the proposed code would lead to a reduction of close to fifty terabytes of cross-rack traffic per day.

A solution to the network challenges of data recovery in erasure-coded distributed storage systems: a study on the Facebook warehouse cluster

Abstract: Erasure codes, such as Reed-Solomon (RS) codes, are being increasingly employed in data centers to combat the cost of reliably storing large amounts of data. Although these codes provide optimal storage efficiency, they require significantly high network and disk usage during recovery of missing data. In this paper, we first present a study on the impact of recovery operations of erasure-coded data on the data-center network, based on measurements from Facebook's warehouse cluster in production. To the best of our knowledge, this is the first study of its kind available in the literature. Our study reveals that recovery of RS-coded data results in a significant increase in network traffic, more than a hundred terabytes per day, in a cluster storing multiple petabytes of RS-coded data. To address this issue, we present a new storage code using our recently proposed Piggybacking framework, that reduces the network and disk usage during recovery by 30% in theory, while also being storage optimal and supporting arbitrary design parameters. The implementation of the proposed code in the Hadoop Distributed File System (HDFS) is underway. We use the measurements from the warehouse cluster to show that the proposed code would lead to a reduction of close to fifty terabytes of cross-rack traffic per day.

Transmitting sequence numbers of information in a packet data transmission system

Abstract: In a packet data transmission system, correctly received information packets are acknowledged by piggybacking their sequence numbers onto information packets being transmitted. The control field of each information packet includes a bit which indicates whether or not there is a piggybacked acknowledgement. Acknowledgements can also be transmitted separately in control packets having no information field. Each acknowledgement consists of not only the sequence number of a correctly received information packet, but also the acknowledgement status of a plurality of preceding information packets whereby these can be negatively acknowledged if necessary. The sequence numbers can have any one of three different sizes, for efficient transmission of sequence numbers on transmission links of arbitrary transmission speed and length (and hence delay), The sequence number size which is used on any particular transmission link is determined on set-up of the link in dependence upon the transmission speed and the round-trip delay of the link.

Understanding Android App Piggybacking: A Systematic Study of Malicious Code Grafting

Abstract: The Android packaging model offers ample opportunities for malware writers to piggyback malicious code in popular apps, which can then be easily spread to a large user base. Although recent research has produced approaches and tools to identify piggybacked apps, the literature lacks a comprehensive investigation into such phenomenon. We fill this gap by: 1) systematically building a large set of piggybacked and benign apps pairs, which we release to the community; 2) empirically studying the characteristics of malicious piggybacked apps in comparison with their benign counterparts; and 3) providing insights on piggybacking processes. Among several findings providing insights analysis techniques should build upon to improve the overall detection and classification accuracy of piggybacked apps, we show that piggybacking operations not only concern app code, but also extensively manipulates app resource files, largely contradicting common beliefs. We also find that piggybacking is done with little sophistication, in many cases automatically, and often via library code.