TY - GEN
T1 - Performance analysis of data management in sensor data storage via stochastic petri nets
AU - Zeng, Rongfei
AU - Lin, Chuang
AU - Jiang, Yixin
AU - Chu, Xiaowen
AU - Liu, Fangqin
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - Recently, sensor data storage has gained increasing popularity for reliable access to data through redundancy spread over unreliable nodes in wireless sensor networks. In storage-centric sensor networks, several schemes have been proposed to optimize the performance of data management in terms of data availability, repair bandwidth, etc. However, few works have been undertaken to study the performance of these data management schemes from a comprehensive point of view. In this paper, we adopt a concise graphic model, i.e., Stochastic Petri Nets (SPNs), to analyze the performance of three representative data management schemes. From the steady state probability matrix of the SPNs models, we can easily get the average energy consumption, repair bandwidth, reliability and data availability. Based on numerical results, we provide guidelines for designing sensor data storage systems. The results also demonstrate that our proposed models are suitable for analyzing data management schemes in sensor data storage.
AB - Recently, sensor data storage has gained increasing popularity for reliable access to data through redundancy spread over unreliable nodes in wireless sensor networks. In storage-centric sensor networks, several schemes have been proposed to optimize the performance of data management in terms of data availability, repair bandwidth, etc. However, few works have been undertaken to study the performance of these data management schemes from a comprehensive point of view. In this paper, we adopt a concise graphic model, i.e., Stochastic Petri Nets (SPNs), to analyze the performance of three representative data management schemes. From the steady state probability matrix of the SPNs models, we can easily get the average energy consumption, repair bandwidth, reliability and data availability. Based on numerical results, we provide guidelines for designing sensor data storage systems. The results also demonstrate that our proposed models are suitable for analyzing data management schemes in sensor data storage.
KW - Data management
KW - Performance evaluation
KW - Sensor data storage
KW - Stochastic petri nets
UR - http://www.scopus.com/inward/record.url?scp=79551618439&partnerID=8YFLogxK
U2 - 10.1109/GLOCOM.2010.5683539
DO - 10.1109/GLOCOM.2010.5683539
M3 - Conference proceeding
AN - SCOPUS:79551618439
SN - 9781424456383
T3 - GLOBECOM - IEEE Global Telecommunications Conference
BT - 2010 IEEE Global Telecommunications Conference, GLOBECOM 2010
PB - IEEE
T2 - 53rd IEEE Global Communications Conference, GLOBECOM 2010
Y2 - 6 December 2010 through 10 December 2010
ER -