Eitan Bachmat

Spatial Aliasing in Spherical Microphone Arrays

Performance of microphone arrays at the high-frequency range is typically limited by aliasing, which is a result of the spatial sampling process. This paper presents analysis of aliasing for spherical microphone arrays, which have been recently studied for a range of applications. The paper presents theoretical analysis of spatial aliasing for various sphere sampling configurations, showing how high-order spherical harmonic coefficients are aliased into the lower orders. Spatial antialiasing filters on the sphere are then introduced, and the performance of spatially constrained filters is compared to that of the ideal antialiasing filter. A simulation example shows how the effect of aliasing on the beam pattern can be reduced by the use of the antialiasing filters

The design of a similarity based deduplication system

We describe some of the design choices that were made during the development of a fast, scalable, inline, deduplication device. The systems design goals and how they were achieved are presented. This is the firs deduplication device that uses similarity matching. The paper provides the following original research contributions: we show how similarity signatures can serve in a deduplication scheme; a novel type of similarity signatures is presented and its advantages in the context of deduplication requirements are explained. It is also shown how to combine similarity matching schemes with byte by byte comparison or hash based identity schemes.

Analysis of methods for scheduling low priority disk drive tasks

This paper analyzes various algorithms for scheduling low priority disk drive tasks. The derived closed form solution is applicable to class of greedy algorithms that include a variety of background disk scanning applications. By paying close attention to many characteristics of modern disk drives, the analytical solutions achieve very high accuracy---the difference between the predicted response times and the measurements on two different disks is only 3% for all but one examined workload. This paper also proves a theorem which shows that background tasks implemented by greedy algorithms can be accomplished with very little seek penalty. Using greedy algorithm gives a 10% shorter response time for the foreground application requests and up to a 20% decrease in total background task run time compared to results from previously published techniques.

Analysis of Airplane Boarding Times

We model and analyze the process of passengers boarding an airplane. We show how the model yields closed-form estimates for the expected boarding time in many cases of interest. Comparison of our computations with previous work, based on discrete-event simulations, shows a high degree of agreement. Analysis of the model reveals a clear link between the efficiency of various airline boarding policies and a congestion parameter that is related to interior airplane design parameters, such as distance between rows. In particular, as congestion increases, random boarding becomes more attractive among row-based policies.

Dynamic data reallocation in disk arrays

We present an application which optimizes the configuration of data in a disk array. The application relies on very little input data which is readily available from many storage devices. We validate the application in a controlled experiment and in a production environment. In both cases, the reconfiguration process led to a 20--30% improvement in response time.

Optimized view-dependent rendering for large polygonal datasets

In this paper we are presenting a novel approach for rendering large datasets in a view-dependent manner. In a typical view-dependent rendering framework, an appropriate level of detail is selected and sent to the graphics hardware for rendering at each frame. In our approach, we have successfully managed to speed up the selection of the level of detail as well as the rendering of the selected levels. We have accelerated the selection of the appropriate level of detail by not scanning active nodes that do not contribute to the incremental update of the selected level of detail. Our idea is based on imposing a spatial subdivision over the view-dependence trees data-structure, which allows spatial tree cells to refine and merge in real-time rendering to comply with the changes in the active nodes list. The rendering of the selected level of detail is accelerated by using vertex arrays. To overcome the dynamic changes in the selected levels of detail we use multiple small vertex arrays whose sizes depend on the memory on the graphics hardware. These multiple vertex arrays are attached to the active cells of the spatial tree and represent the active nodes of these cells. These vertex arrays, which are sent to the graphics hardware at each frame, merge and split with respect to the changes in the cells of the spatial tree.

Bounds on the performance of back-to-front airplane boarding policies

We provide bounds on the performance of back-to-front airplane boarding policies. In particular, we show that no back-to-front policy can be more than 20% better than the policy which boards passengers randomly.

Analysis of SITA policies

We analyze the performance of Size Interval Task Assignment (SITA) policies, for multi-host assignment in a non-preemptive environment. Assuming Poisson arrivals, we provide general bounds on the average waiting time independent of the job size distribution. We establish a general duality theory for the performance of SITA policies. We provide a detailed analysis of the performance of SITA systems when the job size distribution is Bounded Pareto and the range of job sizes tends to infinity. In particular, we determine asymptotically optimal cutoff values and provide asymptotic formulas for average waiting time and slowdown. We compare the results with the Least Work Remaining policy and compute which policy is asymptotically better for any given set of parameters. In the case of inhomogeneous hosts, we determine their optimal ordering.

The information entropy of quantum-mechanical states

It is well known that a Shannon-based definition of information entropy leads in the classical case to the Boltzmann entropy. It is tempting to regard the von Neumann entropy as the corresponding quantum-mechanical definition. But the latter is problematic from the quantum information point of view. Consequently, we introduce a new definition of entropy that reflects the inherent uncertainty of quantum-mechanical states. We derive for it an explicit expression, and discuss some of its general properties. We distinguish between the minimum uncertainty entropy of pure states, and the excess statistical entropy of mixtures.

Analysis of size interval task assignment policies

We analyze the performance of Size Interval task assignment (SITA) scheduling policies, for multi-host scheduling in a non-preemptive environment. We establish a general duality theory for the performance analysis of SITA policies. When the job size distribution is Bounded Pareto and the range of job sizes tends to infinity. we determine asymptotically optimal cutoff values and provide asymptotic formulas for average waiting time and slowdown. In the case of inhomogeneous hosts we determine their optimal ordering. We also consider TAGS policies. We provide a general formula that describes their load handling capabilities and examine their performance when the job size distribution is Bounded Pareto.