utilities for maximizing mac hard drive space

The work complements present decision monitoring and support tools and falls in the larger framework of decision-driven resource management. The paper introduces a new direction in quality-of-service-aware networked sensing that designs communication protocols and scheduling policies for data delivery that are optimized specifically for decision needs. Evaluation results show that the information funnel improves the utility of the collected data objects compared to other lossy protocols. This prioritization is achieved merely by comparing data name prefixes, without knowing application-level name semantics, which makes it generalizable across a wide range of applications. With a proper hierarchical name space design, our protocol prioritizes transmission of data objects over bottlenecks to maximize information utility, with very weak assumptions on the utility function.

This distance, in turn, can expose similarities between named objects that can be leveraged for minimizing redundancy among objects transmitted over bottlenecks, thereby maximizing their aggregate utility. We ar-gue that this paradigm is especially suited for utility-maximizing transport in resource constrained environments, because hier-archical data names give rise to a notion of distance between named objects that is a function of only the topology of the name tree. The abstraction leverages named-data networking, a communication paradigm where data objects are named instead of hosts. It encapsulates a data collection protocol for social sensing that maximizes a measure of delivered information utility, that is the minimized data redundancy, by diversifying the data objects to be collected. We describe a novel transport abstraction, called the information funnel. This paper describes the exploitation of hierarchical data names to achieve information-utility maximizing data collec-tion in social sensing applications.

Utilities for maximizing mac hard drive space