Abstract
Novel algorithmic ideas for big data have not been accompanied by advances in the way central memory is allocated to concurrently running programs. Commonly, RAM is poorly managed since the programs’ trade offs between speed of execution and RAM consumption are ignored. This trade off is, however, well known to the programmers. We adopt mechanism design tools to truthfully elicit this (multidimensional) information with the aim of designing more clever RAM allocation algorithms. We introduce a novel paradigm wherein programs are bound to overbidding declarations of their running times. We show the limitations of this paradigm in the absence of transfers and prove how to leverage waiting times, as a currency, to obtain optimal money burning mechanisms for the makespan.
Partially supported by the DFG grant ME 2088/3-1, EPSRC grant EP/M018113/1, and by MADALGO – Center for Massive Data Algorithmics, a Center of the Danish National Research Foundation.
Notes
- 1.
For simplicity, throughout the paper we use ‘decreasing’ with the meaning ‘non-increasing’, and similarly we use ‘increasing’ instead of ‘non-decreasing’.
- 2.
When these functions have a “large” representation, oracle queries are used just like in the Combinatorial Auctions (CA) literature [3], see preliminaries for a discussion.
- 3.
This might be implemented by letting the mechanism hold back the results of the computation whenever the program terminates before the reported time.
- 4.
Specifically, Nisan and Ronen embedded the monitoring assumption in their ‘mechanisms with verification’, but here we use the term verification in a different sense.
- 5.
- 6.
For the definition of ‘minimally implements’, see the Preliminaries.
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Kovács, A., Meyer, U., Ventre, C. (2015). Mechanisms with Monitoring for Truthful RAM Allocation. In: Markakis, E., Schäfer, G. (eds) Web and Internet Economics. WINE 2015. Lecture Notes in Computer Science(), vol 9470. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48995-6_29
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