By Ramesh Karri, David J. Goodman
This publication specializes in rising concerns in power-aware transportable multimedia communications units past low-power digital layout. It compiles system-level strength administration methods, from theoretical and simulation experiences to experimental try out beds relating to low energy computing, cellular verbal exchange and networking.
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Additional info for System-Level Power Optimization for Wireless Multimedia Communication: Power Aware Computing
Example text
In this chapter, we focus, for illustrative purposes, on the center-of-sets defuzzifier [ME01]. It computes a crisp output for the FLS by first computing the centroid, of every consequent set and, then computing a weighted average of these centroids. The weight corresponding to the l th rule consequent centroid is the degree of firing associated with the l th rule, so that , where M is the number of rules in the FLS. In the next section, we define a FLS for power control and management of ad hoc wireless networks.
Examples of sensor deployment organization for a target-tracking oriented mission can be found in B198]. Sensors have limited energy resources and their functionality continues until their energy drains. Therefore, energy resources for sensor networks should be managed wisely to extend the lifetime of sensors. The sensing element of a sensor probes the surrounding environment. After performing signal processing of the observed data, sensors communicate this data, typically using a radio-based short-haul links, to a command center usually through a relay or a data concentrator called the gateway.
It can be calculated as: where the block error density denotes the probability of k symbol errors within a block of n symbols and depends on the parameters of the Markov channel the distance d between mobile and receiver and the radiated energy per bit The derivation of can be found in [BF92]. 4 Distortion at the video decoder While motion compensation yields significant gains in coding efficiency, any residual transmission error will cause interframe error propagation. Hence increasing intra frame rate also increases the error resilience of the video coder.