Abstract

Abstract

Abstract
Version vectors (VV) are used pervasively to track dependencies between replica versions in multi-version distributed storage systems. In these systems, VV tend to have a dual functionality: identify a version and encode causal dependencies. In this paper, we show that by maintaining the identifier of the version separate from the causal past, it is possible to verify causality in constant time (instead of O(n) for VV) and to precisely track causality with information with size bounded by the degree of replication, and not by the number of concurrent writers. © 2012 Authors.

Abstract
A new type of irrigation system is being developed in the context of the research project 02/SAICT/2017-28247-FCT-TO-CHAIR. The output are irrigation plans based on optimal control theory that minimize water usage and keep crops safe. In this paper, we present the main features of the system prototype. The system uses soil moisture sensors in the field, weather forecasts and parameters that the farmer provides. This data is input to an Octave/Matlab program that implements an Optimal Control algorithm to compute the irrigation plan for the crop field. The system consists of an electronic device that interfaces the sensors in the field and a server computer. The field device reads data from any analogue sensors and uses mobile communications to upload the data to the server computer. The server provides a website for users to insert data about their crops and fields and it retrieves weather forecast data from a freely available service. Once a day the server runs the Optimal Control irrigation-planning algorithm and the result is provided on the user web page using both numerical and graphical formats. Due to the diversity of irrigation infrastructures installed in crop fields and water availability for irrigation, the system does not automatically control/actuate the irrigation. That task is left on the hands of the farmer.