Date of Award
Master of Science
Electrical and Computer Engineering
Arun K. Somani
Network coding improves throughput in wireless networks. When applied to battery driven devices, like wireless sensor nodes, it extends the network lifetime. Network coding reduces the energy consumption by minimizing the number of transmissions required to communicate a given amount of information across the network. However, aggressive application of network coding adversely aects the network lifetime. We illustrate this trade o in this paper, and
show that the existing throughput based network coding approaches cannot be applied to energy-constrained networks. Specically, we address the following routing problem. Given a set of trac demands the goal is to route the demands across the network with the objective of minimizing the total energy consumption while providing guarantees on the lifetime of individual nodes. This work studies both multi-path and single-path variations of the above routing prob-
lem. We present analytical formulations to solve the problems optimally. Evaluation of the multi-path problem indicates that the proposed solution is 35% more energy efficient than no-network-coding solution while still meeting required lifetime constraints.
However, network coding is a costly technique to apply. This technique involves extra over- head in terms of control message transmissions, and may result into unbounded delays. These
factors oset the performance enhancements that are otherwise achievable through network coding. In this work, we characterize a network to determine regions (nodes), where applica-
tion of coding can be advantageous. This serves two purposes. First, if a network is well suited to eectively use coding then performance enhancement would dominate instead of latency and
additional overhead issues. Second, coding-aware routing protocols can be designed, which use topology information to route the packets eectively in the network.
Nishanth Reddy Gaddam
Gaddam, Nishanth Reddy, "Network coding in wireless networks" (2009). Graduate Theses and Dissertations. 10844.