TY - JOUR
T1 - On-demand data broadcasting for mobile decision making
AU - Sharaf, Mohamed A.
AU - Chrysanthis, Panos K.
N1 - Funding Information:
∗This work is supported in part by NSF award ANI-0123705, the National Center for Disease Control and the Pennsylvania Department of Health Award ME-01-737. The first author is supported in part by the Andrew Mellon Predoctoral Fellowship.
PY - 2004/12
Y1 - 2004/12
N2 - The wide spread of mobile computing devices is transforming the newly emerged e-business world into a mobile e-business one, a world in which hand-held computers are the user's front-ends to access enterprise data. For good mobile decision making, users need to count on up-to-date, business-critical data. Such data are typically in the form of summarized information tailored to suit the user's analysis interests. In this paper, we are addressing the issue of time and energy efficient delivery of summary tables to mobile users with hand-held computers equipped with OLAP (On-Line Analytical Processing) front-end tools. Towards this, we propose a new on-demand scheduling algorithm, called STOBS, that exploits the derivation semantics among OLAP summary tables. It maximizes the aggregated data sharing between mobile users and reduces the broadcast length for satisfying a set of requests compared to the already existing techniques. The algorithm effectiveness with respect to access time and energy consumption is evaluated using simulation.
AB - The wide spread of mobile computing devices is transforming the newly emerged e-business world into a mobile e-business one, a world in which hand-held computers are the user's front-ends to access enterprise data. For good mobile decision making, users need to count on up-to-date, business-critical data. Such data are typically in the form of summarized information tailored to suit the user's analysis interests. In this paper, we are addressing the issue of time and energy efficient delivery of summary tables to mobile users with hand-held computers equipped with OLAP (On-Line Analytical Processing) front-end tools. Towards this, we propose a new on-demand scheduling algorithm, called STOBS, that exploits the derivation semantics among OLAP summary tables. It maximizes the aggregated data sharing between mobile users and reduces the broadcast length for satisfying a set of requests compared to the already existing techniques. The algorithm effectiveness with respect to access time and energy consumption is evaluated using simulation.
KW - Broadcast pull
KW - Broadcast scheduling
KW - Mobile commerce
KW - Mobile computing
KW - OLAP
KW - Power-aware computing
KW - Wireless communication
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U2 - 10.1023/B:MONE.0000042508.12154.51
DO - 10.1023/B:MONE.0000042508.12154.51
M3 - Article
AN - SCOPUS:4944254875
SN - 1383-469X
VL - 9
SP - 703
EP - 714
JO - Mobile Networks and Applications
JF - Mobile Networks and Applications
IS - 6 SPEC.ISS.
ER -