One-dimensional partitioning for heterogeneous systems: Theory and practice

We study the problem of one-dimensional partitioning of nonuniform workload arrays, with optimal load balancing for heterogeneous systems. We look at two cases: chain-on-chain partitioning, where the order of the processors is specified, and chain partitioning, where processor permutation is allowed. We present polynomial time algorithms to solve the chain-on-chain partitioning problem optimally, while we prove that the chain partitioning problem is NP-complete. Our empirical studies show that our proposed exact algorithms produce substantially better results than heuristics, while solution times remain comparable.     

Framework for Better Understanding a Face-to-Face Videoconferencing Using H.263 Codec

Face-to-face Videoconferencing is a popular option for many large organizations because it minimizes the need for travel. Instead of continually paying for traveling expenses, a company can either pay to set up a high speed network which has many usages (including videoconferencing) or they can rent time on an existing network. Employees will also no longer be burdened with the need to travel. While face-to-face videoconferencing performance is heavily influenced by the underlying hardware and software, a g...     

Earthquake onset detection using spectro-ratio on multi-threshold time–frequency sub-band

Automatic onset detection and picking algorithm has been proposed by applying the spectro-ratio on time–frequency sub-band. The proposed algorithm does not need any parameter settings as it will work on data generated by either short or very broad band seismometers. Our algorithm is applied on local events from Cairo region recorded by three stations of the Egyptian National Seismic Network (ENSN). Maximum standard deviation is observed to be 0.113 s of the corresponding manual picks made by analysts.     

Principles and performance analysis of SeCond: A system for epidemic peer-to-peer content distribution

We propose and design a peer-to-peer system, SeCond, addressing the distribution of large sized content to a large number of end systems in an efficient manner. In contrast to prior work, it employs a self-organizing epidemic dissemination scheme for state propagation of available blocks and initiation of block transmissions. In order to exploit heterogeneity of peers, enhance the utilization of system resources and for the ease of deployment, scalability, and adaptivity to dynamic peer arrivals/departures, we propose mechanisms for adjusting protocol parameters dynamically according to the bandwidth usages. We describe design and analysis details of our protocol SeCond. Comprehensive performance evaluations and comparison with the BitTorrent system model have been accomplished for a wide range of scenarios. Performance results include scalability analysis for different arrival/departure patterns, flash-crowd scenario, overhead analysis, and fairness ratio. The major metrics we study include the average file download time, load on the primary seed, uplink/downlink utilization, and communication overhead. We show that SeCond is a scalable and adaptive protocol which takes the heterogeneity of the peers into account. The protocol is as fair as BitTorrent although it has no explicit strategy addressing free-riding. We also illustrate the applicability of an analytical fluid model to the behavior of SeCond.     

Measuring robustness of computing systems

System builders are becoming increasingly interested in robust design. We believe that a methodology for generating robustness metrics will help the robust design research efforts and, in general, is an important step in the efforts to create robust computing systems. The purpose of the research in this paper is to quantify the robustness of a resource allocation, with the eventual objective of setting a standard that could easily be instantiated for a particular computing system to generate a robustness metric. The paper exposes how not considering the uncertainties can result in gross overestimation of the system capacity, and shows a method for reducing the impact of uncertainty, and even use it to our advantage if the uncertainties are correlated. We present our theoretical foundation for a robustness metric and give its instantiation for a particular system.     

Inertial microfluidics for continuous particle filtration and extraction

In this paper, we describe a simple passive microfluidic device with rectangular microchannel geometry for continuous particle filtration. The design takes advantage of preferential migration of particles in rectangular microchannels based on shear-induced inertial lift forces. These dominant inertial forces cause particles to move laterally and occupy equilibrium positions along the longer vertical microchannel walls. Using this principle, we demonstrate extraction of 590 nm particles from a mixture of 1.9 μm and 590 nm particles in a straight microfluidic channel with rectangular cross-section. Based on the theoretical analysis and experimental data, we describe conditions required for predicting the onset of particle equilibration in square and rectangular microchannels. The microfluidic channel design has a simple planar structure and can be easily integrated with on-chip microfluidic components for filtration and extraction of wide range of particle sizes. The ability to continuously and differentially equilibrate particles of different size without external forces in microchannels is expected to have numerous applications in filtration, cytometry, and bioseparations.     

Adaptive sorting: an information theoretic perspective

We present two algorithms that are near optimal with respect to the number of inversions present in the input. One of the algorithms is a variation of insertion sort, and the other is a variation of merge sort. The number of comparisons performed by our algorithms, on an input sequence of length n that has I inversions, is at most . Moreover, both algorithms have implementations that run in time . All previously published algorithms require at least comparisons for some c > 1. M. L. Fredman was supported in part by NSF grant CCR-9732689.     

Fuzzy-based hunger games search algorithm for global optimization and feature selection using medical data

Neural Computing and Applications - Feature selection (FS) is one of the basic data preprocessing steps in data mining and machine learning. It is used to reduce feature size and increase model...