OpenRaiser/Intern-Atlas huggingface dataset:
Enhancing the Error Correction of Finite Alphabet Iterative Decoders via Adaptive Decimation
Venue: arXiv cs.IT 2012
Year: 2012

Finite alphabet iterative decoders (FAIDs) for LDPC codes were recently shown to be capable of surpassing the Belief Propagation (BP) decoder in the error floor region on the Binary Symmetric channel (BSC). More recently, the technique of decimation which involves fixing the values of certain bits during decoding, was proposed for FAIDs in order to make them more amenable to analysis while maintaining their good performance. In this paper, we show how decimation can be used adaptively to further enhance the guaranteed error correction capability of FAIDs that are already good on a given code. The new adaptive decimation scheme proposed has marginally added complexity but can significantly improve the slope of the error floor performance of a particular FAID. We describe the adaptive decimation scheme particularly for 7-level FAIDs which propagate only 3-bit messages and provide numerical results for column-weight three codes. Analysis suggests that the failures of the new decoders are linked to stopping sets of the code.
Selecting Two-Bit Bit Flipping Algorithms for Collective Error Correction
Venue: arXiv cs.IT 2012
Year: 2012

A class of two-bit bit flipping algorithms for decoding low-density parity-check codes over the binary symmetric channel was proposed in [1]. Initial results showed that decoders which employ a group of these algorithms operating in parallel can offer low error floor decoding for high-speed applications. As the number of two-bit bit flipping algorithms is large, designing such a decoder is not a trivial task. In this paper, we describe a procedure to select collections of algorithms that work well together. This procedure relies on a recursive process which enumerates error configurations that are uncorrectable by a given algorithm. The error configurations uncorrectable by a given algorithm form its trapping set profile. Based on their trapping set profiles, algorithms are selected so that in parallel, they can correct a fixed number of errors with high probability.
Classical and Bayesian Linear Data Estimators for Unique Word OFDM
Venue: arXiv cs.IT 2012
Year: 2012

Unique word - orthogonal frequency division multiplexing (UW-OFDM) is a novel OFDM signaling concept, where the guard interval is built of a deterministic sequence - the so-called unique word - instead of the conventional random cyclic prefix. In contrast to previous attempts with deterministic sequences in the guard interval the addressed UW-OFDM signaling approach introduces correlations between the subcarrier symbols, which can be exploited by the receiver in order to improve the bit error ratio performance. In this paper we develop several linear data estimators specifically designed for UW-OFDM, some based on classical and some based on Bayesian estimation theory. Furthermore, we derive complexity optimized versions of these estimators, and we study their individual complex multiplication count in detail. Finally, we evaluate the estimators' performance for the additive white Gaussian noise channel as well as for selected indoor multipath channel scenarios.
Content-aware Traffic Engineering
Venue: arXiv cs.NI 2012
Year: 2012

Today, a large fraction of Internet traffic is originated by Content Providers (CPs) such as content distribution networks and hyper-giants. To cope with the increasing demand for content, CPs deploy massively distributed infrastructures. This poses new challenges for CPs as they have to dynamically map end-users to appropriate servers, without being fully aware of network conditions within an ISP as well as the end-users network locations. Furthermore, ISPs struggle to cope with rapid traffic shifts caused by the dynamic server selection process of CPs. In this paper, we argue that the challenges that CPs and ISPs face separately today can be turned into an opportunity. We show how they can jointly take advantage of the deployed distributed infrastructures to improve their operation and end-user performance. We propose Content-aware Traffic Engineering (CaTE), which dynamically adapts the traffic demand for content hosted on CPs by utilizing ISP network information and end-user location during the server selection process. As a result, CPs enhance their end-user to server mapping and improve end-user experience, thanks to the ability of network-informed server selection to circumvent network bottlenecks. In addition, ISPs gain the ability to partially influence the traffic demands in their networks. Our results with operational data show improvements in path length and delay between end-user and the assigned CP server, network wide traffic reduction of up to 15%, and a decrease in ISP link utilization of up to 40% when applying CaTE to traffic delivered by a small number of major CPs.
On the Performance of Maximum Likelihood Inverse Reinforcement Learning
Venue: arXiv cs.LG 2012
Year: 2012

Inverse reinforcement learning (IRL) addresses the problem of recovering a task description given a demonstration of the optimal policy used to solve such a task. The optimal policy is usually provided by an expert or teacher, making IRL specially suitable for the problem of apprenticeship learning. The task description is encoded in the form of a reward function of a Markov decision process (MDP). Several algorithms have been proposed to find the reward function corresponding to a set of demonstrations. One of the algorithms that has provided best results in different applications is a gradient method to optimize a policy squared error criterion. On a parallel line of research, other authors have presented recently a gradient approximation of the maximum likelihood estimate of the reward signal. In general, both approaches approximate the gradient estimate and the criteria at different stages to make the algorithm tractable and efficient. In this work, we provide a detailed description of the different methods to highlight differences in terms of reward estimation, policy similarity and computational costs. We also provide experimental results to evaluate the differences in performance of the methods.
Signaling Schemes for Revenue Maximization
Venue: arXiv cs.GT 2012
Year: 2012

Signaling is an important topic in the study of asymmetric information in economic settings. In particular, the transparency of information available to a seller in an auction setting is a question of major interest. We introduce the study of signaling when conducting a second price auction of a probabilistic good whose actual instantiation is known to the auctioneer but not to the bidders. This framework can be used to model impressions selling in display advertising. We study the problem of computing a signaling scheme that maximizes the auctioneer's revenue in a Bayesian setting. While the general case is proved to be computationally hard, several cases of interest are shown to be polynomially solvable. In addition, we establish a tight bound on the minimum number of signals required to implement an optimal signaling scheme and show that at least half of the maximum social welfare can be preserved within such a scheme.
The impact of propagation environment and traffic load on the performance of routing protocols in ad hoc networks
Venue: arXiv cs.NI 2012
Year: 2012

Wireless networks are characterized by a dynamic topology triggered by the nodes mobility. Thus, the wireless multi-hops connection and the channel do not have a determinist behaviour such as: interference or multiple paths. Moreover, the nodes' invisibility makes the wireless channel difficult to detect. This wireless networks' behaviour should be scrutinized. In our study, we mainly focus on radio propagation models by observing the evolution of the routing layer's performances in terms of the characteristics of the physical layer. For this purpose, we first examine and then display the simulation findings of the impact of different radio propagation models on the performance of ad hoc networks. To fully understand how these various radio models influence the networks performance, we have compared the performances of several routing protocols (DSR, AODV, and DSDV) for each propagation model. To complete our study, a comparison of energy performance based routing protocols and propagation models are presented. In order to reach credible results, we focused on the notion of nodes' speed and the number of connections by using the well known network simulator NS-2.
User profile based proportional share scheduling and mac protocol for manets
Venue: arXiv cs.NI 2012
Year: 2012

Quality of Service(QoS) in Mobile Ad Hoc Networks (MANETs) though a challenge, becomes a necessity because of its applications in critical scenarios. Providing QoS for users belonging to various profiles and playing different roles, becomes the need of the hour. In this paper, we propose proportional share scheduling and MAC protocol (PS2-MAC) model. It classifies users based on their profile as High Profiled users (HP), Medium Profiled users (MP) and Low profiled users (LP) and assigns proportional weights. Service Differentiation for these three service classes is achieved through, rationed dequeuing algorithm, variable inter frame space, proportionate prioritized backoff timers and enhanced RTS/CTS control packets. Differentiated services is simulated in ns2 and results show that 9.5% control overhead is reduced in our proposed scheme than the existing scheme and results also justify that, differentiated services have been achieved for the different profiles of users with proportionate shares and thereby reducing starvation.
Multi-outcome and Multidimensional Market Scoring Rules
Venue: arXiv cs.GT 2012
Year: 2012

Hanson's market scoring rules allow us to design a prediction market that still gives useful information even if we have an illiquid market with a limited number of budget-constrained agents. Each agent can "move" the current price of a market towards their prediction. While this movement still occurs in multi-outcome or multidimensional markets we show that no market-scoring rule, under reasonable conditions, always moves the price directly towards beliefs of the agents. We present a modified version of a market scoring rule for budget-limited traders, and show that it does have the property that, from any starting position, optimal trade by a budget-limited trader will result in the market being moved towards the trader's true belief. This mechanism also retains several attractive strategic properties of the market scoring rule.
Stabilizing sliding mode control design and application for a dc motor: Speed control
Venue: arXiv cs.SY 2012
Year: 2012

The regulation by sliding mode control (SMC) is recognized for its qualities of robustness and dynamic response. This article will briefly talk about the regulation principles by sliding mode as well as the application of this approach to the adjustment of a speed control DC motor bench using the TY36A/EV unit. This unit, from Electronica Veneta products, uses a PID controller to control the speed and position of the DC motor. Our purpose is to improve the set time answer and the robustness of the system when disturbances take place. The experimental results show very good performances of the proposed approach relatively to the PID.
Personalised product design using virtual interactive techniques
Venue: arXiv cs.MM 2012
Year: 2012

Use of Virtual Interactive Techniques for personalized product design is described in this paper. Usually products are designed and built by considering general usage patterns and Prototyping is used to mimic the static or working behaviour of an actual product before manufacturing the product. The user does not have any control on the design of the product. Personalized design postpones design to a later stage. It allows for personalized selection of individual components by the user. This is implemented by displaying the individual components over a physical model constructed using Cardboard or Thermocol in the actual size and shape of the original product. The components of the equipment or product such as screen, buttons etc. are then projected using a projector connected to the computer into the physical model. Users can interact with the prototype like the original working equipment and they can select, shape, position the individual components displayed on the interaction panel using simple hand gestures. Computer Vision techniques as well as sound processing techniques are used to detect and recognize the user gestures captured using a web camera and microphone.
Network Backbone Discovery Using Edge Clustering
Venue: arXiv cs.SI 2012
Year: 2012

In this paper, we investigate the problem of network backbone discovery. In complex systems, a "backbone" takes a central role in carrying out the system functionality and carries the bulk of system traffic. It also both simplifies and highlight underlying networking structure. Here, we propose an integrated graph theoretical and information theoretical network backbone model. We develop an efficient mining algorithm based on Kullback-Leibler divergence optimization procedure and maximal weight connected subgraph discovery procedure. A detailed experimental evaluation demonstrates both the effectiveness and efficiency of our approach. The case studies in the real world domain further illustrates the usefulness of the discovered network backbones.
Classification of artificial intelligence ids for smurf attack
Venue: arXiv cs.AI 2012
Year: 2012

Many methods have been developed to secure the network infrastructure and communication over the Internet. Intrusion detection is a relatively new addition to such techniques. Intrusion detection systems (IDS) are used to find out if someone has intrusion into or is trying to get it the network. One big problem is amount of Intrusion which is increasing day by day. We need to know about network attack information using IDS, then analysing the effect. Due to the nature of IDSs which are solely signature based, every new intrusion cannot be detected; so it is important to introduce artificial intelligence (AI) methods / techniques in IDS. Introduction of AI necessitates the importance of normalization in intrusions. This work is focused on classification of AI based IDS techniques which will help better design intrusion detection systems in the future. We have also proposed a support vector machine for IDS to detect Smurf attack with much reliable accuracy.
Equivalence of SLNR Precoder and RZF Precoder in Downlink MU-MIMO Systems
Venue: arXiv cs.IT 2012
Year: 2012

The signal-to-leakage-and-noise ratio (SLNR) precoder is widely used for MU-MIMO systems in many works, and observed with improved performance from zeroforcing (ZF) precoder. Our work proofs SLNR precoder is completely equivalent to conventional regulated ZF (RZF) precoder, which has significant gain over ZF precoder at low SNRs. Therefore, with our conclusion, the existing performance analysis about RZF precoder can be readily applicable to SLNR precoder.
Improving energy efficiency in wireless sensor networks through scheduling and routing
Venue: arXiv cs.NI 2012
Year: 2012

This paper is about the wireless sensor network in environmental monitoring applications. A Wireless Sensor Network consists of many sensor nodes and a base station. The number and type of sensor nodes and the design protocols for any wireless sensor network is application specific. The sensor data in this application may be light intensity, temperature, pressure, humidity and their variations .Clustering and routing are the two areas which are given more attention in this paper.
A Block Cipher using Rotation and Logical XOR Operations
Venue: arXiv cs.CR 2012
Year: 2012

Cryptography is the study of methods of sending messages in disguised form so that only the intended recipients can remove the disguise and read the messages. Information security has become a very critical aspect of modern communication systems. With the global acceptance of the Internet as a medium of communication, virtually every computer in the world is connected to every other. It has created a new risk for the users of the computers with a constant threat of being hacked and being victims of data theft. In this connection data encryption has become an essential part of secure communication of the messages. In the present paper we propose a new method of encryption of data in blocks using the operations Rotation and Logical XOR
Smoothed Complexity Theory
Venue: arXiv cs.CC 2012
Year: 2012

Smoothed analysis is a new way of analyzing algorithms introduced by Spielman and Teng (J. ACM, 2004). Classical methods like worst-case or average-case analysis have accompanying complexity classes, like P and AvgP, respectively. While worst-case or average-case analysis give us a means to talk about the running time of a particular algorithm, complexity classes allows us to talk about the inherent difficulty of problems. Smoothed analysis is a hybrid of worst-case and average-case analysis and compensates some of their drawbacks. Despite its success for the analysis of single algorithms and problems, there is no embedding of smoothed analysis into computational complexity theory, which is necessary to classify problems according to their intrinsic difficulty. We propose a framework for smoothed complexity theory, define the relevant classes, and prove some first hardness results (of bounded halting and tiling) and tractability results (binary optimization problems, graph coloring, satisfiability). Furthermore, we discuss extensions and shortcomings of our model and relate it to semi-random models.
An Intelligent Mobile-Agent Based Scalable Network Management Architecture for Large-Scale Enterprise System
Venue: arXiv cs.NI 2012
Year: 2012

Several Mobile Agent based distributed network management models have been proposed in recent times to address the scalability and flexibility problems of centralized (SNMP or CMIP management models) models. Though the use of Mobile Agents to distribute and delegate management tasks comes handy in dealing with the previously stated issues, many of the agent-based management frameworks like initial flat bed models and static mid-level managers employing mobile agents models cannot efficiently meet the demands of current networks which are growing in size and complexity. Moreover, varied technologies, such as SONET, ATM, Ethernet, DWDM etc., present at different layers of the Access, Metro and Core (long haul) sections of the network, have contributed to the complexity in terms of their own framing and protocol structures. Thus, controlling and managing the traffic in these networks is a challenging task. This paper presents an intelligent scalable hierarchical agent based model for the management of large-scale complex networks to address aforesaid issues. The cost estimation, carried out with a view to compute the overall management cost in terms of management data overhead, is being presented. The results obtained thereafter establish the usefulness of the presented architecture as compare to centralized and flat bed agent based models.
Arduino Tool: For Interactive Artwork Installations
Venue: arXiv cs.SE 2012
Year: 2012

The emergence of the digital media and computational tools has widened the doors for creativity. The cutting edge in the digital arts and role of new technologies can be explored for the possible creativity. This gives an opportunity to involve arts with technologies to make creative works. The interactive artworks are often installed in the places where multiple people can interact with the installation, which allows the art to achieve its purpose by allowing the people to observe and involve with the installation. The level of engagement of the audience depends on the various factors such as aesthetic satisfaction, how the audience constructs meaning, pleasure and enjoyment. The method to evaluate these experiences is challenging as it depends on integration between the artificial life and real life by means of human computer interaction. This research investigates "How Adriano fits for creative and interactive artwork installations?" using an artwork installation in the campus of NTNU (Norwegian University of Science & Technology). The main focus of this investigation has been to get an overview on the intersection between information technology and Arts. This gives an opportunity to understand various attributes like creativity, cooperation and openness of processes influencing the creative Artworks. The artwork is combination of Adriano and other auxiliary components such as sensors, LED's and speakers.
Cryptanalysis and enhancement of two low cost rfid authentication protocols
Venue: arXiv cs.CR 2012
Year: 2012

Widespread attention is recently paid upon RFID system structure considering its ease of deployment over an extensive range of applications. Due to its several advantages, many technical articles are published to improve its capabilities over specific system implementations. Recently, a lightweight anti-de-synchronization RFID authentication protocol and a lightweight binding proof protocol to guard patient safety are proposed. This contribution provides enough evidence to prove the first introduced protocol vulnerability to de-synchronization attack. It also provides the other protocol's suffering from de-synchronization attack as well as tracking the movements of the tags. This paper also addresses appropriate solutions to fix the security flaws concerning the two described protocols for secure RFID applications.
A New Type of Cipher
Venue: arXiv cs.CR 2012
Year: 2012

We will define a new type of cipher that doesn't use neither an easy to calcualate and hard to invert matematical function like RSA nor a classical mono or polyalphabetic cipher.
Informed Source Separation using Iterative Reconstruction
Venue: arXiv cs.ET 2012
Year: 2012

This paper presents a technique for Informed Source Separation (ISS) of a single channel mixture, based on the Multiple Input Spectrogram Inversion method. The reconstruction of the source signals is iterative, alternating between a time- frequency consistency enforcement and a re-mixing constraint. A dual resolution technique is also proposed, for sharper transients reconstruction. The two algorithms are compared to a state-of-the-art Wiener-based ISS technique, on a database of fourteen monophonic mixtures, with standard source separation objective measures. Experimental results show that the proposed algorithms outperform both this reference technique and the oracle Wiener filter by up to 3dB in distortion, at the cost of a significantly heavier computation.
Typing Copyless Message Passing
Venue: arXiv cs.PL 2012
Year: 2012

We present a calculus that models a form of process interaction based on copyless message passing, in the style of Singularity OS. The calculus is equipped with a type system ensuring that well-typed processes are free from memory faults, memory leaks, and communication errors. The type system is essentially linear, but we show that linearity alone is inadequate, because it leaves room for scenarios where well-typed processes leak significant amounts of memory. We address these problems basing the type system upon an original variant of session types.