Coding techniques for storage systems are gaining traction in data center (DC) applications, owing to their data survivability performance, and more recently, to their ability to mitigate traffic congestion. This paper considers stochastic allocation schedules in networks that admit bulk file requests, across three drive blocking models. We consider a block-based code and a stochastic scheduling algorithm which is beneficial in the case of continuous chunk read patterns. In particular, we demonstrate that in systems with continuous chunk reading patterns, when drive blocking is either independent or from traffic congestion, block coded storage can reduce average download time by 10 -- 66%, given modern system parameters. However, a distinction should be made between systems with continuous and those with interrupted chunk read patterns. For interrupted chunk read systems, given our allocation algorithm that performs well for continuous reads, block coded storage performance can be worse than replication, numerical illustrations show relative losses over 66%. These illustrations demonstrate that to harness the full benefits of coded storage and to avoid pitfalls, careful attention must be paid to continuous vs. Interrupted chunk reading patterns, codes other than block codes should be considered, as could joint code-scheduling design.

Over the coming decades, high-definition situationally-aware networks have the potential to create revolutionary applications in the social, scientific, commercial, and military sectors. Ultrawide bandwidth (UWB) technology is a viable candidate for enabling accurate localization capabilities through time-of-arrival (TOA)-based ranging techniques. These techniques exploit the fine delay resolution property of UWB signals by estimating the TOA of the first signal path. Exploiting the full capabilities of UWB TOA estimation can be challenging, especially when operating in harsh propagation environments, since the direct path may not exist or it may not be the strongest. In this paper, we first give an overview of ranging techniques together with the primary sources of TOA error (including propagation effects, clock drift, and interference). We then describe fundamental TOA bounds (such as the CramÉr–Rao bound and the tighter Ziv–Zakai bound) in both ideal and multipath environments. These bounds serve as useful benchmarks in assessing the performance of TOA estimation techniques. We also explore practical low-complexity TOA estimation techniques and analyze their performance in the presence of multipath and interference using IEEE 802.15.4a channel models as well as experimental data measured in indoor residential environments.