Dissertation/Thesis Abstract

When in-network processing meets time: Complexity and effects of joint optimization in wireless sensor networks
by Xiang, Qiao, M.S., Wayne State University, 2011, 82; 1507002
Abstract (Summary)

Towards understanding the complexity of joint QoS and in-network processing (INP) optimization in sensornets, we study the problem of jointly optimizing packet packing 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 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. We design a distributed, online protocol tPack that schedules packet transmissions to maximize the local utility of packet packing at each node. We evaluate the properties of tPack in NetEye testbed. We find that jointly optimizing data delivery timeliness and packet packing and considering real-world aggregation constraints significantly improve network performance.

Indexing (document details)
Advisor: Zhang, Hongwei
Commitee: Fisher, Nathan, Xu, Lihao
School: Wayne State University
Department: Computer Science
School Location: United States -- Michigan
Source: MAI 50/04M, Masters Abstracts International
Subjects: Computer science
Keywords: In-network processing, Packet packing, Real-time, Sensor network, Wireless network
Publication Number: 1507002
ISBN: 978-1-267-21322-8
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