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This work explores systems that deliver source updates requiring multiple sequential processing steps. We model and analyze the Age of Information (AoI) performance of various system designs under both parallel and series server setups. In parallel setups, each processor executes all computation steps with multiple processors working in parallel, while in series setups, each processor performs a specific step in sequence. In practice, processing faster is better in terms of age but it also consumes more power. To address this age-power trade-off, we formulate and solve an optimization problem to determine the optimal service rates for each processing step under a given power budget. Our analysis focuses on a special case where updates require two computational steps. The results show that the service rate of the second step should generally be faster than that of the first step to achieve minimum AoI and reduce power wastage. Furthermore, parallel processing is found to offer a better age-power trade-off compared to series processing. 

Dynamic Spectrum Access (DSA) is a key mechanism for meeting the ever-increasing demand for emerging wireless services. DSA involves managing and assigning available spectrum resources in a way that minimizes interference and allows RF coexistence between heterogeneous devices and systems. Spectrum Consumption Models (SCMs)- defined in the IEEE 1900.5.2 standard, offer a mechanism for RF devices to: (i) declare the characteristics of their intended spectrum use and their interference protection needs; and (ii) determine compatibility (non-interference) with existing devices. In this paper, we propose a novel SCM-based Spectrum Deconfliction (SD) algorithm that dynamically configures RF operational parameters (e.g., center frequency and transmission power) of a target transmitter-receiver pair aiming to minimize interference with existing devices/systems. We also propose sequential and distributed DSA methods that use the SD algorithm for assigning spectrum in large-scale networks. To evaluate the performance of our methods in terms of computation time, spectrum assignment efficiency, and overhead, we use two custom-made simulation platforms. Finally, to experimentally demonstrate the feasibility of our methods, we build a proof-of-concept implementation in the NSF PAWR COSMOS wireless testbed. The results reveal the advantages of using SCMs and their capabilities to conduct spectrum assignments in dynamic and congested communication environments. 

We consider a system where the updates from independent sources are disseminated via a publish-subscribe mechanism. The sources are the publishers and a decision process (DP), acting as a subscriber, derives decision updates from the source data. We derive the stationary expected age of information (AoI) of decision updates delivered to a monitor. We show that a lazy computation policy in which the DP may sit idle before computing its next decision update can reduce the average AoI at the monitor even though the DP exerts no control over the generation of source updates. This AoI reduction is shown to occur because lazy computation can offset the negative effect of high variance in the computation time.