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Data and object clustering techniques are used in a wide variety of scientific applications such as biology, pattern recognition, information systems, etc. Traditionally, clustering methods have focused on optimizing a single metric, however, several multidisciplinary applications such as robot team deployment, ad hoc networks, facility location, etc.,(More)
The aggregation of robots into teams is necessitated due to the limited power and communication capabilities in emergency environments. The formation of robot teams significantly enhances the performance and efficiency of search and rescue missions in such environments. As opposed to the classical partitioning application domains, the robot aggregation(More)
Technology scaling has not only magnified the effects of device process variations, but it has also precipitated the need for simultaneous optimization of several performance metrics. In this paper, we propose a novel gate sizing approach for multi-metric optimization of delay, power, and crosstalk noise. The algorithm is based on the concepts of(More)
The aggressive scaling of technology has not only accentuated the effects of intradie parametric variations in devices, but it has also impacted the effects of optimizing a certain performance metric on the optimality of other metrics. Thus, there is a need for optimization methods that can perform the simultaneous optimization of multiple metrics(More)
The field of wireless sensor networks offers a rich, multi-disciplinary area of research, in which a variety of tools and concepts can be employed to address a diverse set of applications. As such, many potentials of this field have been under study both in academia and in the industry. Smart environments represent the next evolutionary development step in(More)
In this research, we propose a novel approach for simultaneous optimization of power, crosstalk noise and delay via gate sizing, in the presence of <i>scarce information</i> about the distribution of the variations. The methodology uses the concepts of utility theory and risk minimization to identify a <i>deterministic equivalent</i> model of the stochastic(More)
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