Abstract

AbstractThis paper presents a new perspective to the design of wireless networks using the proposed dynamic data type refinement methodology. In the forthcoming years, new portable devices will execute wireless network applications with extensive computational demands (2 – 30 GOPS) with low energy consumption demands (0.3 – 2 Watts). Nowadays, in such dynamic applications the dynamic memory subsystem is one of the main sources of energy consumption and it can heavily affect the performance of the whole system, if it is not properly managed. The main objective is to arrive at energy efficient realizations of the dominant dynamic data types of this dynamic memory subsystem. The simulation results in real case studies show that our methodology reduces energy consumption 50% on average.KeywordsWireless NetworkMemory AccessRandom ElementMemory FootprintProfile ToolThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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