OpenRaiser/Intern-Atlas huggingface dataset:
A Traffic Load Balancing Framework for Software-defined Radio Access Networks Powered by Hybrid Energy Sources
Venue: arXiv cs.NI 2014
Year: 2014

Dramatic mobile data traffic growth has spurred a dense deployment of small cell base stations (SCBSs). Small cells enhance the spectrum efficiency and thus enlarge the capacity of mobile networks. Although SCBSs consume much less power than macro BSs (MBSs) do, the overall power consumption of a large number of SCBSs is phenomenal. As the energy harvesting technology advances, base stations (BSs) can be powered by green energy to alleviate the on-grid power consumption. For mobile networks with high BS density, traffic load balancing is critical in order to exploit the capacity of SCBSs. To fully utilize harvested energy, it is desirable to incorporate the green energy utilization as a performance metric in traffic load balancing strategies. In this paper, we have proposed a traffic load balancing framework that strives a balance between network utilities, e.g., the average traffic delivery latency, and the green energy utilization. Various properties of the proposed framework have been derived. Leveraging the software-defined radio access network architecture, the proposed scheme is implemented as a virtually distributed algorithm, which significantly reduces the communication overheads between users and BSs. The simulation results show that the proposed traffic load balancing framework enables an adjustable trade-off between the on-grid power consumption and the average traffic delivery latency, and saves a considerable amount of on-grid power, e.g., 30%, at a cost of only a small increase, e.g., 8%, of the average traffic delivery latency.
Caching and Auditing in the RPPM Model
Venue: arXiv cs.CR 2014
Year: 2014

Crampton and Sellwood recently introduced a variant of relationship-based access control based on the concepts of relationships, paths and principal matching, to which we will refer as the RPPM model. In this paper, we show that the RPPM model can be extended to provide support for caching of authorization decisions and enforcement of separation of duty policies. We show that these extensions are natural and powerful. Indeed, caching provides far greater advantages in RPPM than it does in most other access control models and we are able to support a wide range of separation of duty policies.
Generating and Solving Symbolic Parity Games
Venue: arXiv cs.LO 2014
Year: 2014

We present a new tool for verification of modal mu-calculus formulae for process specifications, based on symbolic parity games. It enhances an existing method, that first encodes the problem to a Parameterised Boolean Equation System (PBES) and then instantiates the PBES to a parity game. We improved the translation from specification to PBES to preserve the structure of the specification in the PBES, we extended LTSmin to instantiate PBESs to symbolic parity games, and implemented the recursive parity game solving algorithm by Zielonka for symbolic parity games. We use Multi-valued Decision Diagrams (MDDs) to represent sets and relations, thus enabling the tools to deal with very large systems. The transition relation is partitioned based on the structure of the specification, which allows for efficient manipulation of the MDDs. We performed two case studies on modular specifications, that demonstrate that the new method has better time and memory performance than existing PBES based tools and can be faster (but slightly less memory efficient) than the symbolic model checker NuSMV.
Specifying and Executing Optimizations for Parallel Programs
Venue: arXiv cs.PL 2014
Year: 2014

Compiler optimizations, usually expressed as rewrites on program graphs, are a core part of all modern compilers. However, even production compilers have bugs, and these bugs are difficult to detect and resolve. The problem only becomes more complex when compiling parallel programs; from the choice of graph representation to the possibility of race conditions, optimization designers have a range of factors to consider that do not appear when dealing with single-threaded programs. In this paper we present PTRANS, a domain-specific language for formal specification of compiler transformations, and describe its executable semantics. The fundamental approach of PTRANS is to describe program transformations as rewrites on control flow graphs with temporal logic side conditions. The syntax of PTRANS allows cleaner, more comprehensible specification of program optimizations; its executable semantics allows these specifications to act as prototypes for the optimizations themselves, so that candidate optimizations can be tested and refined before going on to include them in a compiler. We demonstrate the use of PTRANS to state, test, and refine the specification of a redundant store elimination optimization on parallel programs.
On the Degrees of Freedom of SISO X-Channel with Alternating CSIT
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, we establish the degrees of freedom (DoF) of the two-user single input single output (SISO) X-channel with alternating channel state information at the transmitters (CSIT). Three cases are considered for the availability of CSIT; perfect, delayed and no-CSIT. Each state is associated with a fraction of time denoted by $λ_P, λ_D$ and $λ_N $, respectively. We provide new results for DoF of the two-user SISO X-channel when the available CSIT alternates between these three cases under a certain distribution $Λ(λ_P, λ_D, λ_N )$. Specifically, we show that the X-channel with alternating CSIT for $Λ(1/8, 3/8, 1/2)$ can achieve $5/4$ DoF. The interesting thing about $5/4$ is that it represents a position of compromise or a middle ground between the channel knowledge that transmitters need to steer interference and the degrees of freedom that the network can achieve. Moreover, $5/4$ is strictly greater than $6/5$ which is the upper bound for the X-channel with \textit{fixed} delayed CSIT.
SocialDTN: A DTN implementation for Digital and Social Inclusion
Venue: arXiv cs.NI 2014
Year: 2014

Despite of the importance of access to computers and to the Internet for the development of people and their inclusion in society, there are people that still suffer with digital divide and social exclusion. Delay/Disruption-Tolerant Networking (DTN) can help the digital/social inclusion of these people as it allows opportunistic and asynchronous communication, which does not depend upon networking infrastructure. We introduce SocialDTN, an implementation of the DTN architecture for Android devices that operates over Bluetooth, taking advantages of the social daily routines of users. As we want to exploit the social proximity and interactions existing among users, SocialDTN includes a social-aware opportunistic routing proposal, dLife, instead of the well-known (but social-oblivious) PROPHET. Simulations show the potential of dLife for our needs. Additionally, some preliminary results from field experimentations are presented.
Joint Network and Gelfand-Pinsker Coding for 3-Receiver Gaussian Broadcast Channels with Receiver Message Side Information
Venue: arXiv cs.IT 2014
Year: 2014

The problem of characterizing the capacity region for Gaussian broadcast channels with receiver message side information appears difficult and remains open for N >= 3 receivers. This paper proposes a joint network and Gelfand-Pinsker coding method for 3-receiver cases. Using the method, we establish a unified inner bound on the capacity region of 3-receiver Gaussian broadcast channels under general message side information configuration. The achievability proof of the inner bound uses an idea of joint interference cancelation, where interference is canceled by using both dirty-paper coding at the encoder and successive decoding at some of the decoders. We show that the inner bound is larger than that achieved by state of the art coding schemes. An outer bound is also established and shown to be tight in 46 out of all 64 possible cases.
Software for Computing the Spheroidal Wave Functions Using Arbitrary Precision Arithmetic
Venue: arXiv cs.MS 2014
Year: 2014

The spheroidal wave functions, which are the solutions to the Helmholtz equation in spheroidal coordinates, are notoriously difficult to compute. Because of this, practically no programming language comes equipped with the means to compute them. This makes problems that require their use hard to tackle. We have developed computational software for calculating these special functions. Our software is called spheroidal and includes several novel features, such as: using arbitrary precision arithmetic; adaptively choosing the number of expansion coefficients to compute and use; and using the Wronskian to choose from several different methods for computing the spheroidal radial functions to improve their accuracy. There are two types of spheroidal wave functions: the prolate kind when prolate spheroidal coordinates are used; and the oblate kind when oblate spheroidal coordinate are used. In this paper, we describe both, methods for computing them, and our software. We have made our software freely available on our webpage.
Randomized Memetic Artificial Bee Colony Algorithm
Venue: arXiv cs.NE 2014
Year: 2014

Artificial Bee Colony (ABC) optimization algorithm is one of the recent population based probabilistic approach developed for global optimization. ABC is simple and has been showed significant improvement over other Nature Inspired Algorithms (NIAs) when tested over some standard benchmark functions and for some complex real world optimization problems. Memetic Algorithms also become one of the key methodologies to solve the very large and complex real-world optimization problems. The solution search equation of Memetic ABC is based on Golden Section Search and an arbitrary value which tries to balance exploration and exploitation of search space. But still there are some chances to skip the exact solution due to its step size. In order to balance between diversification and intensification capability of the Memetic ABC, it is randomized the step size in Memetic ABC. The proposed algorithm is named as Randomized Memetic ABC (RMABC). In RMABC, new solutions are generated nearby the best so far solution and it helps to increase the exploitation capability of Memetic ABC. The experiments on some test problems of different complexities and one well known engineering optimization application show that the proposed algorithm outperforms over Memetic ABC (MeABC) and some other variant of ABC algorithm(like Gbest guided ABC (GABC),Hooke Jeeves ABC (HJABC), Best-So-Far ABC (BSFABC) and Modified ABC (MABC) in case of almost all the problems.
Impact of Human Behavior on Social Opportunistic Forwarding
Venue: arXiv cs.NI 2014
Year: 2014

The current Internet design is not capable to support communications in environments characterized by very long delays and frequent network partitions. To allow devices to communicate in such environments, delay-tolerant networking solutions have been proposed by exploiting opportunistic message forwarding, with limited expectations of end-to-end connectivity and node resources. Such solutions envision non-traditional communication scenarios, such as disaster areas and development regions. Several forwarding algorithms have been investigated, aiming to offer the best trade-off between cost (number of message replicas) and rate of successful message delivery. Among such proposals, there has been an effort to employ social similarity inferred from user mobility patterns in opportunistic routing solutions to improve forwarding. However, these research effort presents two major limitations: first, it is focused on distribution of the intercontact time over the complete network structure, ignoring the impact that human behavior has on the dynamics of the network; and second, most of the proposed solutions look at challenging networking environments where networks have low density, ignoring the potential use of delay-tolerant networking to support low cost communications in networks with higher density, such as urban scenarios. This paper presents a study of the impact that human behavior has on opportunistic forwarding. Our goal is twofold: i) to show that performance in low and high density networks can be improved by taking the dynamics of the network into account; and ii) to show that the delay-tolerant networking can be used to reduce communication costs in networks with higher density by taking the behavior of the user into account.
A Real-Time Spatial Index for In-Vehicle Units
Venue: arXiv cs.DS 2014
Year: 2014

We construct a spatial indexing solution for the highly constrained environment of an in-vehicle unit in a distributed vehicle tolling scheme based on satellite navigation (GNSS). We show that an immutable, purely functional implementation of a high-fanout quadtree is a simple, practical solution that satisfies all the requirements of such a system.
New data, new possibilities: Exploring the insides of Altmetric.com
Venue: arXiv cs.DL 2014
Year: 2014

This paper analyzes Altmetric.com, one of the most important altmetric data providers currently used. We have analyzed a set of publications with DOI number indexed in the Web of Science during the period 2011-2013 and collected their data with the Altmetric API. 19% of the original set of papers was retrieved from Altmetric.com including some altmetric data. We identified 16 different social media sources from which Altmetric.com retrieves data. However five of them cover 95.5% of the total set. Twitter (87.1%) and Mendeley (64.8%) have the highest coverage. We conclude that Altmetric.com is a transparent, rich and accurate tool for altmetric data. Nevertheless, there are still potential limitations on its exhaustiveness as well as on the selection of social media sources that need further research.
Variational Depth from Focus Reconstruction
Venue: arXiv cs.CV 2014
Year: 2014

This paper deals with the problem of reconstructing a depth map from a sequence of differently focused images, also known as depth from focus or shape from focus. We propose to state the depth from focus problem as a variational problem including a smooth but nonconvex data fidelity term, and a convex nonsmooth regularization, which makes the method robust to noise and leads to more realistic depth maps. Additionally, we propose to solve the nonconvex minimization problem with a linearized alternating directions method of multipliers (ADMM), allowing to minimize the energy very efficiently. A numerical comparison to classical methods on simulated as well as on real data is presented.
Beamforming for Secure Communication via Untrusted Relay Nodes Using Artificial Noise
Venue: arXiv cs.IT 2014
Year: 2014

A two-phase beamforming solution for secure communication using untrusted relay nodes is presented. To thwart eavesdropping attempts of relay nodes, we deliberately introduce artificial noise in the source message. After pointing out the incongruity in evaluating secrecy rate in our model for certain scenarios, we provide an SNR based frame work for secure communication. We intend to bring down the SNR at each of the untrusted relay nodes below a certain predefined threshold, whereas, using beamforming we want to boost the SNR at the destination. With this motive optimal scaling vector is evaluated for beamforming phase which not only nullifies the artificial noise transmitted initially, but also maximizes the SNR at the destination. We discuss both the total and individual power constraint scenarios and provide analytical solution for both of them.
Adaptive Wavelet Based Identification and Extraction of PQRST Combination in Randomly Stretching ECG Sequence
Venue: arXiv cs.CV 2014
Year: 2014

Cardiovascular system study using ECG signals have evolved tremendously in the domain of electronics and signal processing. However, there are certain floating challenges unresolved in the analysis and detection of abnormal performances of cardiovascular system. As the medical field is moving towards more automated and intelligent systems, wrong detection or wrong interpretations of ECG waveform of abnormal conditions can be quite fatal. Since the PQRST signals vary their positions randomly, the process of locating, identifying and classifying each feature can be cumbersome and it is prone to errors. Here we present an automated scheme using adaptive wavelet to detect prominent R-peak with extreme accuracy and algorithmically tag and mark the coexisting peaks P, Q, S, and T with almost same accuracy. The adaptive wavelet approach used in this scheme is capable of detecting R-peak in ECG with 99.99% accuracy along with the rest of the waveforms.
Precision of Pulse-Coupled Oscillator Synchronization on FPGA-Based Radios
Venue: arXiv cs.OH 2014
Year: 2014

The precision of synchronization algorithms based on the theory of pulse-coupled oscillators is evaluated on FPGA-based radios for the first time. Measurements show that such algorithms can reach precision in the low microsecond range when being implemented in the physical layer. Furthermore, we propose an algorithm extension accounting for phase rate deviations of the hardware and show that an improved precision below one microsecond is possible with this extension in the given setup. The resulting algorithm can thus be applied in ad hoc wireless systems for fully distributed synchronization of transmission slots or sleep cycles, in particular, if centralized synchronization is impossible.
A Pattern Recognition System for Detecting Use of Mobile Phones While Driving
Venue: arXiv cs.CV 2014
Year: 2014

It is estimated that 80% of crashes and 65% of near collisions involved drivers inattentive to traffic for three seconds before the event. This paper develops an algorithm for extracting characteristics allowing the cell phones identification used during driving a vehicle. Experiments were performed on sets of images with 100 positive images (with phone) and the other 100 negative images (no phone), containing frontal images of the driver. Support Vector Machine (SVM) with Polynomial kernel is the most advantageous classification system to the features provided by the algorithm, obtaining a success rate of 91.57% for the vision system. Tests done on videos show that it is possible to use the image datasets for training classifiers in real situations. Periods of 3 seconds were correctly classified at 87.43% of cases.
Pre-Reduction Graph Products: Hardnesses of Properly Learning DFAs and Approximating EDP on DAGs
Venue: arXiv cs.CC 2014
Year: 2014

The study of graph products is a major research topic and typically concerns the term $f(G*H)$, e.g., to show that $f(G*H)=f(G)f(H)$. In this paper, we study graph products in a non-standard form $f(R[G*H]$ where $R$ is a "reduction", a transformation of any graph into an instance of an intended optimization problem. We resolve some open problems as applications. (1) A tight $n^{1-ε}$-approximation hardness for the minimum consistent deterministic finite automaton (DFA) problem, where $n$ is the sample size. Due to Board and Pitt [Theoretical Computer Science 1992], this implies the hardness of properly learning DFAs assuming $NP\neq RP$ (the weakest possible assumption). (2) A tight $n^{1/2-ε}$ hardness for the edge-disjoint paths (EDP) problem on directed acyclic graphs (DAGs), where $n$ denotes the number of vertices. (3) A tight hardness of packing vertex-disjoint $k$-cycles for large $k$. (4) An alternative (and perhaps simpler) proof for the hardness of properly learning DNF, CNF and intersection of halfspaces [Alekhnovich et al., FOCS 2004 and J. Comput.Syst.Sci. 2008].
Predicting missing links and their weights via reliable-route-based method
Venue: arXiv cs.SI 2014
Year: 2014

Link prediction aims to uncover missing links or predict the emergence of future relationships according to the current networks structure. Plenty of algorithms have been developed for link prediction in unweighted networks, with only a very few of them having been extended to weighted networks. Thus far, how to predict weights of links is important but rarely studied. In this Letter, we present a reliable-route-based method to extend unweighted local similarity indices to weighted indices and propose a method to predict both the link existence and link weights accordingly. Experiments on different real networks suggest that the weighted resource allocation index has the best performance to predict the existence of links, while the reliable-route-based weighted resource allocation index performs noticeably better on weight prediction. Further analysis shows a strong correlation for both link prediction and weight prediction: the larger the clustering coefficient, the higher the prediction accuracy.
Semi-Analytical Computation of Acoustic Scattering by Spheroids and Disks
Venue: arXiv cs.MS 2014
Year: 2014

Analytical solutions to acoustic scattering problems involving nonspherical shapes, such as spheroids and disks, have long been known and have many applications. However, these solutions require special functions that are not easily computable. For this reason, their asymptotic forms are typically used since they are more readily available. We explore these solutions and provide computational software for calculating their nonasymptotic forms, which are accurate over a wide range of frequencies and distances. This software, which runs in MATLAB, computes the solutions to acoustic scattering problems involving spheroids and disks by semi-analytical means, and is freely available from our webpage.
A Framework to Synergize Partial Order Reduction with State Interpolation
Venue: arXiv cs.LO 2014
Year: 2014

We address the problem of reasoning about interleavings in safety verification of concurrent programs. In the literature, there are two prominent techniques for pruning the search space. First, there are well-investigated trace-based methods, collectively known as "Partial Order Reduction (POR)", which operate by weakening the concept of a trace by abstracting the total order of its transitions into a partial order. Second, there is state-based interpolation where a collection of formulas can be generalized by taking into account the property to be verified. Our main contribution is a framework that synergistically combines POR with state interpolation so that the sum is more than its parts.
Distributed Markov Chains
Venue: arXiv cs.DC 2014
Year: 2014

The formal verification of large probabilistic models is important and challenging. Exploiting the concurrency that is often present is one way to address this problem. Here we study a restricted class of asynchronous distributed probabilistic systems in which the synchronizations determine the probability distribution for the next moves of the participating agents. The key restriction we impose is that the synchronizations are deterministic, in the sense that any two simultaneously enabled synchronizations must involve disjoint sets of agents. As a result, this network of agents can be viewed as a succinct and distributed presentation of a large global Markov chain. A rich class of Markov chains can be represented this way. We define an interleaved semantics for our model in terms of the local synchronization actions. The network structure induces an independence relation on these actions, which, in turn, induces an equivalence relation over the interleaved runs in the usual way. We construct a natural probability measure over these equivalence classes of runs by exploiting Mazurkiewicz trace theory and the probability measure space of the associated global Markov chain. It turns out that verification of our model, called DMCs (distributed Markov chains), can often be efficiently carried out by exploiting the partial order nature of the interleaved semantics. To demonstrate this, we develop a statistical model checking (SMC) procedure and use it to verify two large distributed probabilistic networks.