Lingering issues in distributed scheduling

Recent advances have resulted in queue-based algorithms for medium access control which operate in a distributed fashion, and yet achieve the optimal throughput performance of centralized scheduling algorithms. However, fundamental performance bounds reveal that the "cautious" activation rules involved in establishing throughput optimality tend to produce extremely large delays, typically growing exponentially in 1/(1-r), with r the load of the system, in contrast to the usual linear growth. Motivated by that issue, we explore to what extent more "aggressive" schemes can improve the delay performance. Our main finding is that aggressive activation rules induce a lingering effect, where individual nodes retain possession of a shared resource for excessive lengths of time even while a majority of other nodes idle. Using central limit theorem type arguments, we prove that the idleness induced by the lingering effect may cause the delays to grow with 1/(1-r) at a quadratic rate. To the best of our knowledge, these are the first mathematical results illuminating the lingering effect and quantifying the performance impact. In addition extensive simulation experiments are conducted to illustrate and validate the various analytical results

Stability of random admissible-set scheduling in spatial wireless systems

We examine the stability of wireless networks whose users are distributed over a compact space. Users arrive at spatially uniform locations with intensity \lambda and each user has a random number of packets to transmit with mean ??\beta. In each time slot, an admissible subset of users is selected uniformly at random to transmit one packet. A subset of users is called admissible when their simultaneous activity obeys the prevailing interference constraints. We consider a wide class of interference constraints, including the SINR model and the protocol model. Denote by \mu?? the maximum number of users in an admissible subset for the model under consideration. We will show that the necessary condition \lamba \beta <\mu is also su??fficient for random admissible-set scheduling to achieve stability. Thus random admissible-set scheduling achieves stability, if feasible to do so at all, for a broad class of interference scenarios. The proof relies on a description of the system as a measure-valued process and the identi??cation of a Lyapunov function

Stability of spatial wireless systems with random admissible-set scheduling

We examine the stability of wireless networks whose users are distributed over a compact space. Users arrive at spatially uniform locations with intensity \lambda and each user has a random number of packets to transmit with mean \beta. In each time slot, an admissible subset of users is selected uniformly at random to transmit one packet. A subset of users is called admissible when their simultaneous activity obeys the prevailing interference constraints. We consider a wide class of interference constraints, including the SINR model and the protocol model. Denote by \mu the maximum number of users in an admissible subset for the model under consideration. We will show that the necessary condition \lamba \beta <\mu is also sufficient for random admissible-set scheduling to achieve stability. Thus random admissible-set scheduling achieves stability, if feasible to do so at all, for a broad class of interference scenarios. The proof relies on a description of the system as a measure-valued process and the identi??cation of a Lyapunov function. Keywords: Wireless networks, stability, Foster-Lyapunov, Harris recurrent, measure-valued process, interference constraints, SINR requirements, protocol mode

Backlog-based random access in wireless networks : fluid limits and delay issues

We explore the spatio-temporal congestion dynamics of wireless networks with backlog-based random-access mechanisms. While relatively simple and inherently distributed in nature, suitably designed backlog-based access schemes provide the striking capability to match the optimal throughput performance of centralized scheduling algorithms in a wide range of scenarios. In the present paper, we show that the specific activity functions for which maximum stability has been established, may however yield excessive queue lengths and delays. The results reveal that more aggressive/persistent access schemes can improve the delay performance, while retaining the maximum stability guarantees in a rich set of scenarios. In order to gain qualitative insights and examine stability properties we will investigate fluid limits where the system dynamics are scaled in space and time. As it turns out, several distinct types of fluid limits can arise, exhibiting various degrees of randomness, depending on the structure of the network, in conjunction with the form of the activity functions. We further demonstrate that, counter to intuition, additional interference may improve the delay performance in certain cases. Simulation experiments are conducted to illustrate and validate the analytical findings

Backlog-based random access in wireless networks : fluid limits and delay issues

We explore the spatio-temporal congestion dynamics of wireless networks with backlog-based random-access mechanisms. While relatively simple and inherently distributed in nature, suitably designed backlog-based access schemes provide the striking capability to match the optimal throughput performance of centralized scheduling algorithms in a wide range of scenarios. In the present paper, we show that the specific activity functions for which maximum stability has been established, may however yield excessive queue lengths and delays. The results reveal that more aggressive/persistent access schemes can improve the delay performance, while retaining the maximum stability guarantees in a rich set of scenarios. In order to gain qualitative insights and examine stability properties we will investigate fluid limits where the system dynamics are scaled in space and time. As it turns out, several distinct types of fluid limits can arise, exhibiting various degrees of randomness, depending on the structure of the network, in conjunction with the form of the activity functions. We further demonstrate that, counter to intuition, additional interference may improve the delay performance in certain cases. Simulation experiments are conducted to illustrate and validate the analytical findings

Fast secure comparison for medium-sized integers and its application in binarized neural networks

In 1994, Feige, Kilian, and Naor proposed a simple protocol for secure 3-way comparison of integers a and b from the range [0, 2]. Their observation is that for p=7, the Legendre symbol (x∣p) coincides with the sign of x for x=a−b∈[−2,2], thus reducing secure comparison to secure evaluation of the Legendre symbol. More recently, in 2011, Yu generalized this idea to handle secure comparisons for integers from substantially larger ranges [0, d], essentially by searching for primes for which the Legendre symbol coincides with the sign function on [−d,d]. In this paper, we present new comparison protocols based on the Legendre symbol that additionally employ some form of error correction. We relax the prime search by requiring that the Legendre symbol encodes the sign function in a noisy fashion only. Practically, we use the majority vote over a window of 2k+1 adjacent Legendre symbols, for small positive integers k. Our technique significantly increases the comparison range: e.g., for a modulus of 60 bits, d increases by a factor of 2.8 (for k=1) and 3.8 (for k=2) respectively. We give a practical method to find primes with suitable noisy encodings.We demonstrate the practical relevance of our comparison protocol by applying it in a secure neural network classifier for the MNIST dataset. Concretely, we discuss a secure multiparty computation based on the binarized multi-layer perceptron of Hubara et al., using our comparison for the second and third layers.</p

Tuning dissipation dilution in 2D material resonators by MEMS-induced tension

Resonators based on two-dimensional (2D) materials have exceptional properties for application as nanomechanical sensors, which allows them to operate at high frequencies with high sensitivity. However, their performance as nanomechanical sensors is currently limited by their low quality ($Q$)-factor. Here, we make use of micro-electromechanical systems (MEMS) to apply pure in-plane mechanical strain, enhancing both their resonance frequency and Q-factor. In contrast to earlier work, the 2D material resonators are fabricated on the MEMS actuators without any wet processing steps, using a dry-transfer method. A platinum clamp, that is deposited by electron beam-induced deposition, is shown to be effective in fixing the 2D membrane to the MEMS and preventing slippage. By in-plane straining the membranes in a purely mechanical fashion, we increase the tensile energy, thereby diluting dissipation. This way, we show how dissipation dilution can increase the $Q$-factor of 2D material resonators by 91\%. The presented MEMS actuated dissipation dilution method does not only pave the way towards higher $Q$-factors in resonators based on 2D materials, but also provides a route toward studies of the intrinsic loss mechanisms of 2D materials in the monolayer limit.Comment: 20 pages, 15 figure

Multiscale Discriminant Saliency for Visual Attention

The bottom-up saliency, an early stage of humans' visual attention, can be considered as a binary classification problem between center and surround classes. Discriminant power of features for the classification is measured as mutual information between features and two classes distribution. The estimated discrepancy of two feature classes very much depends on considered scale levels; then, multi-scale structure and discriminant power are integrated by employing discrete wavelet features and Hidden markov tree (HMT). With wavelet coefficients and Hidden Markov Tree parameters, quad-tree like label structures are constructed and utilized in maximum a posterior probability (MAP) of hidden class variables at corresponding dyadic sub-squares. Then, saliency value for each dyadic square at each scale level is computed with discriminant power principle and the MAP. Finally, across multiple scales is integrated the final saliency map by an information maximization rule. Both standard quantitative tools such as NSS, LCC, AUC and qualitative assessments are used for evaluating the proposed multiscale discriminant saliency method (MDIS) against the well-know information-based saliency method AIM on its Bruce Database wity eye-tracking data. Simulation results are presented and analyzed to verify the validity of MDIS as well as point out its disadvantages for further research direction.Comment: 16 pages, ICCSA 2013 - BIOCA sessio