Abstract
It is increasingly common that computational devices with significant computing power are underexploited. Some of the reasons for that are due to frequent idle-time or to the low computational demand of the tasks they perform, either sporadically or in their regular duty. The exploitation of this (otherwise-wasted) computational power is a cost-effective solution for solving complex computational tasks. Individually (device-wise), this computational power can sometimes comprise a stable, long-lasting availability window but it will more frequently take the form of brief, ephemeral bursts. Then, in this context a highly dynamic and volatile computational landscape emerges from the collective contribution of such numerous devices. Algorithms consciously running on this kind of environment require specific properties in terms of flexibility, plasticity and robustness. Bioinspired algorithms are particularly well suited to this endeavor, thanks to some of the features they inherit from their biological sources of inspiration, namely decentralized functioning, intrinsic parallelism, resilience, and adaptiveness. Deploying bioinspired techniques on this scenario, and conducting analysis and modelling of the underlying Ephemeral Computing environment will also pave the way for the application of other non-bioinspired techniques on this computational domain. Computational creativity and content generation in video games are applications areas of the foremost economical interest and are well suited to Ephemeral Computing due to their intrinsic ephemeral nature and the widespread abundance of gaming applications in all kinds of devices. In this paper, we will explain why and how they can be adapted to this new environment.
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This work is supported by MINECO project EphemeCH (TIN2014-56494-C4-1-P, -2-P, -3-P and -4-P) – Check http://blog.epheme.ch.
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Cotta, C. et al. (2016). Application Areas of Ephemeral Computing: A Survey. In: Nguyen, N., Kowalczyk, R., Filipe, J. (eds) Transactions on Computational Collective Intelligence XXIV. Lecture Notes in Computer Science(), vol 9770. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-53525-7_9
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