This dissertation focuses on linear packet combining (coding) strategies for bulk content data distribution in packet-switching networks and their effects on transmission cost. The employment of packet level codes aims to reduce the communication overhead needed to exchange real-time network states to restore packet losses, or to plan for efficient sharing of communication links. The aim is achievable due to the additional diversity introduced by coding, which increases the possibility of extracting innovative information by receivers. Nevertheless, increased computational complexity is entailed and may lower the throughput of network node processors and hence the communication throughput. This dissertation, in particular, studies coding strategies generating linear combinations of packets that are decodable with reduced complexity. Major efforts to reduce computational complexity include limiting the number of packets combined in each coded packet and working with simple operations such as xoring. Two representative classes of codes are LT codes and coding with generations (hyperblocks). LT codes are the first class of fountain codes, especially suitable for multicast applications. Coding with generations is also of interest due to other practical reasons, such as source clustering. We study these codes in two settings: (1) Content delivery to heterogeneous users experiencing varied channel conditions and having diverse demand volumes; (2) One or more users collecting packets from a ``cloud'' of source nodes storing the content. Throughput performance is characterized analytically and optimized or improved by parameter selection and code design. In particular, with scenario (2), a probability analysis is conducted using balls-into-bins models. We show that (1) the achievable throughput and energy performance with coding and without receiver feedback can beat that achievable with receiver feedback but without coding; (2) fast encoding and decoding is essential to increasing the throughput limits; (3) employing coding such as LT codes with optimized degree distribution can increase the efficiency of a simultaneous service to heterogeneous users; (4) coding with generations compensates for the lack of coordination between sources or between collectors; and (5) the proposed random annex codes based on coding with generations effectively reduces transmission redundancy by introducing overlaps between generations.
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Electrical and Computer Engineering
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Rutgers University Electronic Theses and Dissertations
Rutgers University. Graduate School - New Brunswick
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