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When In-Network Processing Meets Time: Complexity and Effects of Joint Optimization in Wireless Sensor Networks
October 2011 (vol. 10 no. 10)
pp. 1488-1502
ASCII Text
x 
 
Qiao Xiang, Hongwei Zhang, Jinhong Xu, Xiaohui Liu, Loren J. Rittle, "When In-Network Processing Meets Time: Complexity and Effects of Joint Optimization in Wireless Sensor Networks," IEEE Transactions on Mobile Computing, vol. 10, no. 10, pp. 1488-1502, October, 2011.
 
 
BibTex
x
 
@article{ 10.1109/TMC.2011.81,
author = {Qiao Xiang and Hongwei Zhang and Jinhong Xu and Xiaohui Liu and Loren J. Rittle},
title = {When In-Network Processing Meets Time: Complexity and Effects of Joint Optimization in Wireless Sensor Networks},
journal ={IEEE Transactions on Mobile Computing},
volume = {10},
number = {10},
issn = {1536-1233},
year = {2011},
pages = {1488-1502},
doi = {http://doi.ieeecomputersociety.org/10.1109/TMC.2011.81},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Mobile Computing
TI - When In-Network Processing Meets Time: Complexity and Effects of Joint Optimization in Wireless Sensor Networks
IS - 10
SN - 1536-1233
SP1488
EP1502
EPD - 1488-1502
A1 - Qiao Xiang,
A1 - Hongwei Zhang,
A1 - Jinhong Xu,
A1 - Xiaohui Liu,
A1 - Loren J. Rittle,
PY - 2011
KW - Wireless network
KW - sensor network
KW - real-time
KW - packet packing
KW - in-network processing.
VL - 10
JA - IEEE Transactions on Mobile Computing
ER -
 
Qiao Xiang, Wayne State University, Detroit
Hongwei Zhang, Wayne State University, Detroit
Jinhong Xu, Indiana University
Xiaohui Liu, Wayne State University, Detroit
Loren J. Rittle, Content and Context-aware Solutions group, Applied Research, Motorola Mobility, Schaumburg
As sensornets are increasingly being deployed in mission-critical applications, it becomes imperative that we consider application QoS requirements in in-network processing (INP). Toward understanding the complexity of joint QoS and INP optimization, we study the problem of jointly optimizing packet packing (i.e., aggregating shorter packets into longer ones) and the timeliness of data delivery. We identify the conditions under which the problem is strong NP-hard, and we find that the problem complexity heavily depends on aggregation constraints (in particular, maximum packet size and reaggregation tolerance) instead of network and traffic properties. For cases when the problem is NP-hard, we show that there is no polynomial-time approximation scheme (PTAS); for cases when the problem can be solved in polynomial time, we design polynomial time, offline algorithms for finding the optimal packet packing schemes. To understand the impact of joint QoS and INP optimization on sensornet performance, we design a distributed, online protocol tPack that schedules packet transmissions to maximize the local utility of packet packing at each node. Using a testbed of 130 TelosB motes, we experimentally evaluate the properties of tPack. We find that jointly optimizing data delivery timeliness and packet packing and considering real-world aggregation constraints significantly improve network performance. Our findings shed light on the challenges, benefits, and solutions of joint QoS and INP optimization, and they also suggest open problems for future research.

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Index Terms:
Wireless network, sensor network, real-time, packet packing, in-network processing.
Citation:
Qiao Xiang, Hongwei Zhang, Jinhong Xu, Xiaohui Liu, Loren J. Rittle, "When In-Network Processing Meets Time: Complexity and Effects of Joint Optimization in Wireless Sensor Networks," IEEE Transactions on Mobile Computing, vol. 10, no. 10, pp. 1488-1502, Oct. 2011, doi:10.1109/TMC.2011.81
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