OpenRaiser/Intern-Atlas huggingface dataset:
Effect of Fast Moving Object on RSSI in WSN: An Experimental Approach
Venue: arXiv cs.NI 2012
Year: 2012

In this paper, we experimentally investigate the effect of fast moving object on the RSSI in the wireless sensor networks in presence of the ground effect and antenna orientation in elevation direction. In experimental setup, MICAz mote pair was placed on the ground, where one mote acts as a transmitter and the other as a receiver. The trans- mitter mote's antenna was oriented in elevation direction with respect to the receiver mote's antenna. The fast moving object i.e. car, was passed between the motes and the fluctuations in the RSSI are observed. The experimental results show some sequential pattern in RSSI fluctuations when car moves at some relatively slow speed. However, some irregu- larities were also observed when antenna was oriented at 45 and 90 in elevation direction.
On Finding Sub-optimum Signature Matrices for Overloaded CDMA Systems
Venue: arXiv cs.IT 2012
Year: 2012

The objective of this paper is to design optimal signature matrices for binary inputs. For the determination of such optimal codes, we need certain measures as objective functions. The sum-channel capacity and Bit Error Rate (BER) measures are typical methods for the evaluation of signature matrices. In this paper, in addition to these measures, we use distance criteria to evaluate the optimality of signature matrices. The Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to search the optimum signature matrices based on these three measures (Sum channel capacity, BER and Distance). Since the GA and PSO algorithms become computationally expensive for large signature matrices, we propose suboptimal large signature matrices that can be derived from small suboptimal matrices.
When Should I Make Preservation Copies of Myself?
Venue: arXiv cs.DL 2012
Year: 2012

We investigate how different preservation policies ranging from least aggressive to Most aggressive affect the level of preservation achieved by autonomic processes used by smart digital objects (DOs). The mechanisms used to support preservation across different hosts can be used for automatic link generation and support preservation activities by moving data preservation from an archive centric perspective to a data centric preservation. Based on simulations of small-world graphs of DOs created using the Unsupervised Small-World algorithm, we report quantitative and qualitative results for graphs ranging in size from 10 to 5000 DOs. Our results show that a Most aggressive preservation policy makes the best use of distributed host resources while using one half of the number of messages of a Moderately aggressive preservation policy.
Coalitional Beliefs of Cournot Network Agents
Venue: arXiv cs.GT 2012
Year: 2012

In Network cooperative games, due to computational complexity issues, agents are not able to base their behavior on the "whole network status" but have to follow certain "beliefs" as to how it is in their strategic interest to act. This behavior constitutes the main interest of this paper. To this end, we quantify and characterize the set of beliefs that support cooperation of such agents. Assuming that they are engaged in a differentiated Cournot competition and that they equally split the worth produced, we characterize the set of coalitional beliefs that support core non-emptiness and thus guarantee stability of the Network.
Linear approach to the orbiting spacecraft thermal problem
Venue: arXiv cs.CE 2012
Year: 2012

We develop a linear method for solving the nonlinear differential equations of a lumped-parameter thermal model of a spacecraft moving in a closed orbit. Our method, based on perturbation theory, is compared with heuristic linearizations of the same equations. The essential feature of the linear approach is that it provides a decomposition in thermal modes, like the decomposition of mechanical vibrations in normal modes. The stationary periodic solution of the linear equations can be alternately expressed as an explicit integral or as a Fourier series. We apply our method to a minimal thermal model of a satellite with ten isothermal parts (nodes) and we compare the method with direct numerical integration of the nonlinear equations. We briefly study the computational complexity of our method for general thermal models of orbiting spacecraft and conclude that it is certainly useful for reduced models and conceptual design but it can also be more efficient than the direct integration of the equations for large models. The results of the Fourier series computations for the ten-node satellite model show that the periodic solution at the second perturbative order is sufficiently accurate.
An Overview of Local Capacity in Wireless Networks
Venue: arXiv cs.IT 2012
Year: 2012

This article introduces a metric for performance evaluation of medium access schemes in wireless ad hoc networks known as local capacity. Although deriving the end-to-end capacity of wireless ad hoc networks is a difficult problem, the local capacity framework allows us to quantify the average information rate received by a receiver node randomly located in the network. In this article, the basic network model and analytical tools are first discussed and applied to a simple network to derive the local capacity of various medium access schemes. Our goal is to identify the most optimal scheme and also to see how does it compare with more practical medium access schemes. We analyzed grid pattern schemes where simultaneous transmitters are positioned in a regular grid pattern, ALOHA schemes where simultaneous transmitters are dispatched according to a uniform Poisson distribution and exclusion schemes where simultaneous transmitters are dispatched according to an exclusion rule such as node coloring and carrier sense schemes. Our analysis shows that local capacity is optimal when simultaneous transmitters are positioned in a grid pattern based on equilateral triangles and our results show that this optimal local capacity is at most double the local capacity of ALOHA based scheme. Our results also show that node coloring and carrier sense schemes approach the optimal local capacity by an almost negligible difference. At the end, we also discuss the shortcomings in our model as well as future research directions.
On the Reliability of RAID Systems: An Argument for More Check Drives
Venue: arXiv cs.PF 2012
Year: 2012

In this paper we address issues of reliability of RAID systems. We focus on "big data" systems with a large number of drives and advanced error correction schemes beyond \RAID{6}. Our RAID paradigm is based on Reed-Solomon codes, and thus we assume that the RAID consists of $N$ data drives and $M$ check drives. The RAID fails only if the combined number of failed drives and sector errors exceeds $M$, a property of Reed-Solomon codes. We review a number of models considered in the literature and build upon them to construct models usable for a large number of data and check drives. We attempt to account for a significant number of factors that affect RAID reliability, such as drive replacement or lack thereof, mistakes during service such as replacing the wrong drive, delayed repair, and the finite duration of RAID reconstruction. We evaluate the impact of sector failures that do not result in drive replacement. The reader who needs to consider large $M$ and $N$ will find applicable mathematical techniques concisely summarized here, and should be able to apply them to similar problems. Most methods are based on the theory of continuous time Markov chains, but we move beyond this framework when we consider the fixed time to rebuild broken hard drives, which we model using systems of delay and partial differential equations. One universal statement is applicable across various models: increasing the number of check drives in all cases increases the reliability of the system, and is vastly superior to other approaches of ensuring reliability such as mirroring.
MAV Stabilization using Machine Learning and Onboard Sensors
Venue: arXiv cs.RO 2012
Year: 2012

In many situations, Miniature Aerial Vehicles (MAVs) are limited to using only on-board sensors for navigation. This limits the data available to algorithms used for stabilization and localization, and current control methods are often insufficient to allow reliable hovering in place or trajectory following. In this research, we explore using machine learning to predict the drift (flight path errors) of an MAV while executing a desired flight path. This predicted drift will allow the MAV to adjust it's flightpath to maintain a desired course.
A Cryptographic Moving-Knife Cake-Cutting Protocol
Venue: arXiv cs.GT 2012
Year: 2012

This paper proposes a cake-cutting protocol using cryptography when the cake is a heterogeneous good that is represented by an interval on a real line. Although the Dubins-Spanier moving-knife protocol with one knife achieves simple fairness, all players must execute the protocol synchronously. Thus, the protocol cannot be executed on asynchronous networks such as the Internet. We show that the moving-knife protocol can be executed asynchronously by a discrete protocol using a secure auction protocol. The number of cuts is n-1 where n is the number of players, which is the minimum.
IP Traceback for Flooding attacks on Internet Threat Monitors (ITM) Using Honeypots
Venue: arXiv cs.NI 2012
Year: 2012

The Internet Threat Monitoring (ITM) is an efficient monitoring system used globally to measure, detect, characterize and track threats such as denial of service (DoS) and distributed Denial of Service (DDoS) attacks and worms. . To block the monitoring system in the internet the attackers are targeted the ITM system. In this paper we address the flooding attack of DDoS against ITM monitors to exhaust the network resources, such as bandwidth, computing power, or operating system data structures by sending the malicious traffic. We propose an information-theoretic frame work that models the flooding attacks using Botnet on ITM. One possible way to counter DDoS attacks is to trace the attack sources and punish the perpetrators. we propose a novel traceback method for DDoS using Honeypots. IP tracing through honeypot is a single packet tracing method and is more efficient than commonly used packet marking techniques.
Compressive Principal Component Pursuit
Venue: arXiv cs.IT 2012
Year: 2012

We consider the problem of recovering a target matrix that is a superposition of low-rank and sparse components, from a small set of linear measurements. This problem arises in compressed sensing of structured high-dimensional signals such as videos and hyperspectral images, as well as in the analysis of transformation invariant low-rank recovery. We analyze the performance of the natural convex heuristic for solving this problem, under the assumption that measurements are chosen uniformly at random. We prove that this heuristic exactly recovers low-rank and sparse terms, provided the number of observations exceeds the number of intrinsic degrees of freedom of the component signals by a polylogarithmic factor. Our analysis introduces several ideas that may be of independent interest for the more general problem of compressed sensing and decomposing superpositions of multiple structured signals.
Delay Asymptotics with Retransmissions and Incremental Redundancy Codes over Erasure Channels
Venue: arXiv cs.IT 2012
Year: 2012

Recent studies have shown that retransmissions can cause heavy-tailed transmission delays even when packet sizes are light-tailed. Moreover, the impact of heavy-tailed delays persists even when packets size are upper bounded. The key question we study in this paper is how the use of coding techniques to transmit information, together with different system configurations, would affect the distribution of delay. To investigate this problem, we model the underlying channel as a Markov modulated binary erasure channel, where transmitted bits are either received successfully or erased. Erasure codes are used to encode information prior to transmission, which ensures that a fixed fraction of the bits in the codeword can lead to successful decoding. We use incremental redundancy codes, where the codeword is divided into codeword trunks and these trunks are transmitted one at a time to provide incremental redundancies to the receiver until the information is recovered. We characterize the distribution of delay under two different scenarios: (I) Decoder uses memory to cache all previously successfully received bits. (II) Decoder does not use memory, where received bits are discarded if the corresponding information cannot be decoded. In both cases, we consider codeword length with infinite and finite support. From a theoretical perspective, our results provide a benchmark to quantify the tradeoff between system complexity and the distribution of delay.
Performance Evaluation of the Random Replacement Policy for Networks of Caches
Venue: arXiv cs.PF 2012
Year: 2012

The overall performance of content distribution networks as well as recently proposed information-centric networks rely on both memory and bandwidth capacities. In this framework, the hit ratio is the key performance indicator which captures the bandwidth / memory tradeoff for a given global performance.This paper focuses on the estimation of the hit ratio in a network of caches that employ the Random replacement policy. Assuming that requests are independent and identically distributed, general expressions of miss probabilities for a single Random cache are provided as well as exact results for specific popularity distributions. Moreover, for any Zipf popularity distribution with exponent $α$ > 1, we obtain asymptotic equivalents for the miss probability in the case of large cache size. We extend the analysis to networks of Random caches, when the topology is either a line or a homogeneous tree. In that case, approximations for miss probabilities across the network are derived by assuming that miss events at any node occur independently in time; the obtained results are compared to the same network using the Least-Recently-Used discipline, already addressed in the literature. We further analyze the case of a mixed tandem cache network where the two nodes employ either Random or Least-Recently-Used policies. In all scenarios, asymptotic formulas and approximations are extensively compared to simulations and shown to perform very well. Finally, our results enable us to propose recommendations for cache replacement disciplines in a network dedicated to content distribution. These results also hold for a cache using the First-In-First-Out policy.
The Price of Anarchy for Network Formation in an Adversary Model
Venue: arXiv cs.GT 2012
Year: 2012

We study network formation with n players and link cost α> 0. After the network is built, an adversary randomly deletes one link according to a certain probability distribution. Cost for player v incorporates the expected number of players to which v will become disconnected. We show existence of equilibria and a price of stability of 1+o(1) under moderate assumptions on the adversary and n \geq 9. As the main result, we prove bounds on the price of anarchy for two special adversaries: one removes a link chosen uniformly at random, while the other removes a link that causes a maximum number of player pairs to be separated. For unilateral link formation we show a bound of O(1) on the price of anarchy for both adversaries, the constant being bounded by 10+o(1) and 8+o(1), respectively. For bilateral link formation we show O(1+\sqrt{n/α}) for one adversary (if α> 1/2), and Θ(n) for the other (if α> 2 considered constant and n \geq 9). The latter is the worst that can happen for any adversary in this model (if α= Ω(1)). This points out substantial differences between unilateral and bilateral link formation.
Triadic Measures on Graphs: The Power of Wedge Sampling
Venue: arXiv cs.SI 2012
Year: 2012

Graphs are used to model interactions in a variety of contexts, and there is a growing need to quickly assess the structure of a graph. Some of the most useful graph metrics, especially those measuring social cohesion, are based on triangles. Despite the importance of these triadic measures, associated algorithms can be extremely expensive. We propose a new method based on wedge sampling. This versatile technique allows for the fast and accurate approximation of all current variants of clustering coefficients and enables rapid uniform sampling of the triangles of a graph. Our methods come with provable and practical time-approximation tradeoffs for all computations. We provide extensive results that show our methods are orders of magnitude faster than the state-of-the-art, while providing nearly the accuracy of full enumeration. Our results will enable more wide-scale adoption of triadic measures for analysis of extremely large graphs, as demonstrated on several real-world examples.
Efficient and Effective Volume Visualization with Enhanced Isosurface Rendering
Venue: arXiv cs.GR 2012
Year: 2012

Compared with full volume rendering, isosurface rendering has several well recognized advantages in efficiency and accuracy. However, standard isosurface rendering has some limitations in effectiveness. First, it uses a monotone colored approach and can only visualize the geometry features of an isosurface. The lack of the capability to illustrate the material property and the internal structures behind an isosurface has been a big limitation of this method in applications. Another limitation of isosurface rendering is the difficulty to reveal physically meaningful structures, which are hidden in one or multiple isosurfaces. As such, the application requirements of extract and recombine structures of interest can not be implemented effectively with isosurface rendering. In this work, we develop an enhanced isosurface rendering technique to improve the effectiveness while maintaining the performance efficiency of the standard isosurface rendering. First, an isosurface color enhancement method is proposed to illustrate the neighborhood density and to reveal some of the internal structures. Second, we extend the structure extraction capability of isosurface rendering by enabling explicit scene exploration within a 3D-view, using surface peeling, voxel-selecting, isosurface segmentation, and multi-surface-structure visualization. Our experiments show that the color enhancement not only improves the visual fidelity of the rendering, but also reveals the internal structures without significant increase of the computational cost. Explicit scene exploration is also demonstrated as a powerful tool in some application scenarios, such as displaying multiple abdominal organs.
Analyzing Tag Distributions in Folksonomies for Resource Classification
Venue: arXiv cs.DL 2012
Year: 2012

Recent research has shown the usefulness of social tags as a data source to feed resource classification. Little is known about the effect of settings on folksonomies created on social tagging systems. In this work, we consider the settings of social tagging systems to further understand tag distributions in folksonomies. We analyze in depth the tag distributions on three large-scale social tagging datasets, and analyze the effect on a resource classification task. To this end, we study the appropriateness of applying weighting schemes based on the well-known TF-IDF for resource classification. We show the great importance of settings as to altering tag distributions. Among those settings, tag suggestions produce very different folksonomies, which condition the success of the employed weighting schemes. Our findings and analyses are relevant for researchers studying tag-based resource classification, user behavior in social networks, the structure of folksonomies and tag distributions, as well as for developers of social tagging systems in search of an appropriate setting.
Interaction Histories and Short Term Memory: Enactive Development of Turn-taking Behaviors in a Childlike Humanoid Robot
Venue: arXiv cs.AI 2012
Year: 2012

In this article, an enactive architecture is described that allows a humanoid robot to learn to compose simple actions into turn-taking behaviors while playing interaction games with a human partner. The robot's action choices are reinforced by social feedback from the human in the form of visual attention and measures of behavioral synchronization. We demonstrate that the system can acquire and switch between behaviors learned through interaction based on social feedback from the human partner. The role of reinforcement based on a short term memory of the interaction is experimentally investigated. Results indicate that feedback based only on the immediate state is insufficient to learn certain turn-taking behaviors. Therefore some history of the interaction must be considered in the acquisition of turn-taking, which can be efficiently handled through the use of short term memory.
q-Gaussian based Smoothed Functional Algorithm for Stochastic Optimization
Venue: arXiv cs.SY 2012
Year: 2012

The q-Gaussian distribution results from maximizing certain generalizations of Shannon entropy under some constraints. The importance of q-Gaussian distributions stems from the fact that they exhibit power-law behavior, and also generalize Gaussian distributions. In this paper, we propose a Smoothed Functional (SF) scheme for gradient estimation using q-Gaussian distribution, and also propose an algorithm for optimization based on the above scheme. Convergence results of the algorithm are presented. Performance of the proposed algorithm is shown by simulation results on a queuing model.
Fractional Order Modeling of a PHWR Under Step-Back Condition and Control of Its Global Power with a Robust PIλDμ Controller
Venue: arXiv cs.SY 2012
Year: 2012

Bulk reduction of reactor power within a small finite time interval under abnormal conditions is referred to as step-back. In this paper, a 500MWe Canadian Deuterium Uranium (CANDU) type Pressurized Heavy Water Reactor (PHWR) is modeled using few variants of Least Square Estimator (LSE) from practical test data under a control rod drop scenario in order to design a control system to achieve a dead-beat response during a stepped reduction of its global power. A new fractional order (FO) model reduction technique is attempted which increases the parametric robustness of the control loop due to lesser modeling error and ensures iso-damped closed loop response with a PIλDμ or FOPID controller. Such a controller can, therefore, be used to achieve active step-back under varying load conditions for which the system dynamics change significantly. For closed loop active control of the reduced FO reactor models, the PIλDμ controller is shown to perform better than the classical integer order PID controllers and present operating Reactor Regulating System (RRS) due to its robustness against shift in system parameters.
Embedded Network Test-Bed for Validating Real-Time Control Algorithms to Ensure Optimal Time Domain Performance
Venue: arXiv cs.SY 2012
Year: 2012

The paper presents a Stateflow based network test-bed to validate real-time optimal control algorithms. Genetic Algorithm (GA) based time domain performance index minimization is attempted for tuning of PI controller to handle a balanced lag and delay type First Order Plus Time Delay (FOPTD) process over network. The tuning performance is validated on a real-time communication network with artificially simulated stochastic delay, packet loss and out-of order packets characterizing the network.