TY - GEN
T1 - Publish/Subscribe for Mobile Applications Using Shared Dictionary Compression
AU - Doblander, Christoph
AU - Zhang, Kaiwen
AU - Jacobsen, Hans Arno
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/8/8
Y1 - 2016/8/8
N2 - Publish/Subscribe is known as a scalable and efficient data dissemination mechanism. In a mobile environment, there is an added challenge for the pub/sub system to economizemobile bandwidth, which is especially precious in areas not wellcovered by mobile providers. While well-known compressionmethods such as GZip or Deflate are generally useful in suchsituations, we propose using Shared Dictionary Compression(SDC) to achieve a greater level of bandwidth efficiency. SDCrequires a dictionary, generated upfront, to be shared betweentwo communicating peers before it can be used. We proposea design where brokers forming the pub/sub overlay can be incharge of generating and propagating the shared dictionary. Oursolution employs an adaptive algorithm, executed at the brokers, which creates and maintains the dictionaries over time. Withthis approach, it is possible to reduce the required bandwidth byup to 88% including the introduced dictionary overhead. Ourdemo shows this approach applied to a smartphone applicationcommunicating with a publish/subscribe broker using the MQTTprotocol.
AB - Publish/Subscribe is known as a scalable and efficient data dissemination mechanism. In a mobile environment, there is an added challenge for the pub/sub system to economizemobile bandwidth, which is especially precious in areas not wellcovered by mobile providers. While well-known compressionmethods such as GZip or Deflate are generally useful in suchsituations, we propose using Shared Dictionary Compression(SDC) to achieve a greater level of bandwidth efficiency. SDCrequires a dictionary, generated upfront, to be shared betweentwo communicating peers before it can be used. We proposea design where brokers forming the pub/sub overlay can be incharge of generating and propagating the shared dictionary. Oursolution employs an adaptive algorithm, executed at the brokers, which creates and maintains the dictionaries over time. Withthis approach, it is possible to reduce the required bandwidth byup to 88% including the introduced dictionary overhead. Ourdemo shows this approach applied to a smartphone applicationcommunicating with a publish/subscribe broker using the MQTTprotocol.
KW - compression
KW - publish/subscribe
KW - pubsub
KW - shared dictionary compression
UR - http://www.scopus.com/inward/record.url?scp=84985910997&partnerID=8YFLogxK
U2 - 10.1109/ICDCS.2016.70
DO - 10.1109/ICDCS.2016.70
M3 - Conference contribution
AN - SCOPUS:84985910997
T3 - Proceedings - International Conference on Distributed Computing Systems
SP - 775
EP - 776
BT - Proceedings - 2016 IEEE 36th International Conference on Distributed Computing Systems, ICDCS 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 36th IEEE International Conference on Distributed Computing Systems, ICDCS 2016
Y2 - 27 June 2016 through 30 June 2016
ER -