OpenRaiser/Intern-Atlas huggingface dataset:
Application-layer Fault-Tolerance Protocols
Venue: arXiv cs.SE 2016
Year: 2016

The central topic of this book is application-level fault-tolerance, that is the methods, architectures, and tools that allow to express a fault-tolerant system in the application software of our computers. Application-level fault-tolerance is a sub-class of software fault-tolerance that focuses on the problems of expressing the problems and solutions of fault-tolerance in the top layer of the hierarchy of virtual machines that constitutes our computers. This book shows that application-level fault-tolerance is a key ingredient to craft truly dependable computer systems--other approaches, such as hardware fault-tolerance, operating system fault-tolerance, or fault-tolerant middleware, are also important ingredients to achieve resiliency, but they are not enough. Failing to address the application layer means leaving a backdoor open to problems such as design faults, interaction faults, or malicious attacks, whose consequences on the quality of service could be as unfortunate as, e.g., a physical fault affecting the system platform. In other words, in most cases it is simply not possible to achieve complete coverage against a given set of faults or erroneous conditions without embedding fault-tolerance provisions also in the application layer.
Nested algorithms for optimal reservoir operation and their embedding in a decision support platform
Venue: arXiv cs.DS 2016
Year: 2016

This is a PhD thesis of Blagoj Delipetrev explaining nested dynamic programming, nested stochastic dynamic programming and nested reinforcement learning algorithms that are applied in reservoir optimization problem. Additionally there are also multi-objective version of these algorithms.
Optimal Dynamic Point Selection for Power Minimization in Multiuser Downlink CoMP
Venue: arXiv cs.IT 2016
Year: 2016

This paper examines a CoMP system where multiple base-stations (BS) employ coordinated beamforming to serve multiple mobile-stations (MS). Under the dynamic point selection mode, each MS can be assigned to only one BS at any time. This work then presents a solution framework to optimize the BS associations and coordinated beamformers for all MSs. With target signal-to-interference-plus-noise ratios at the MSs, the design objective is to minimize either the weighted sum transmit power or the per-BS transmit power margin. Since the original optimization problems contain binary variables indicating the BS associations, finding their optimal solutions is a challenging task. To circumvent this difficulty, we first relax the original problems into new optimization problems by expanding their constraint sets. Based on the nonconvex quadratic constrained quadratic programming framework, we show that these relaxed problems can be solved optimally. Interestingly, with the first design objective, the obtained solution from the relaxed problem is also optimal to the original problem. With the second design objective, a suboptimal solution to the original problem is then proposed, based on the obtained solution from the relaxed problem. Simulation results show that the resulting jointly optimal BS association and beamforming design significantly outperforms fixed BS association schemes.
A Surrogate-based Generic Classifier for Chinese TV Series Reviews
Venue: arXiv cs.CL 2016
Year: 2016

With the emerging of various online video platforms like Youtube, Youku and LeTV, online TV series' reviews become more and more important both for viewers and producers. Customers rely heavily on these reviews before selecting TV series, while producers use them to improve the quality. As a result, automatically classifying reviews according to different requirements evolves as a popular research topic and is essential in our daily life. In this paper, we focused on reviews of hot TV series in China and successfully trained generic classifiers based on eight predefined categories. The experimental results showed promising performance and effectiveness of its generalization to different TV series.
The sub-$k$-domination number of a graph with applications to $k$-domination
Venue: arXiv cs.DM 2016
Year: 2016

In this paper we introduce and study a new graph invariant derived from the degree sequence of a graph $G$, called the sub-$k$-domination number and denoted $sub_k(G)$. We show that $sub_k(G)$ is a computationally efficient sharp lower bound on the $k$-domination number of $G$, and improves on several known lower bounds. We also characterize the sub-$k$-domination numbers of several families of graphs, provide structural results on sub-$k$-domination, and explore properties of graphs which are $sub_k(G)$-critical with respect to addition and deletion of vertices and edges.
Web 2.0 for Small and medium Sized Companies: A practical Case Study
Venue: arXiv cs.CY 2016
Year: 2016

This project is a holistic analysis of web 2.0 and combines ideas from systems theory and organizational theory and goes on to attempt to bridge the gap between the ongoing theoretical discourse and its implications for the development process. The goal is to shift the discussion from a descriptive, highly philosophical one to a prescriptive framework that can directly be applied for the design, evaluation and deployment. Effectively this work posits that unless a practical framework can be synthesized from this rich debate the application and development of web 2.0 is at risk of proceeding haphazardly and this could potentially limit the benefits organizations reap from it. It then establishes the applicability of web 2.0 to the small organization and accordingly applies the framework to a practical case study.
Action Recognition Based on Joint Trajectory Maps Using Convolutional Neural Networks
Venue: arXiv cs.CV 2016
Year: 2016

Recently, Convolutional Neural Networks (ConvNets) have shown promising performances in many computer vision tasks, especially image-based recognition. How to effectively use ConvNets for video-based recognition is still an open problem. In this paper, we propose a compact, effective yet simple method to encode spatio-temporal information carried in $3D$ skeleton sequences into multiple $2D$ images, referred to as Joint Trajectory Maps (JTM), and ConvNets are adopted to exploit the discriminative features for real-time human action recognition. The proposed method has been evaluated on three public benchmarks, i.e., MSRC-12 Kinect gesture dataset (MSRC-12), G3D dataset and UTD multimodal human action dataset (UTD-MHAD) and achieved the state-of-the-art results.
Tailored Mutants Fit Bugs Better
Venue: arXiv cs.SE 2016
Year: 2016

Mutation analysis measures test suite adequacy, the degree to which a test suite detects seeded faults: one test suite is better than another if it detects more mutants. Mutation analysis effectiveness rests on the assumption that mutants are coupled with real faults i.e. mutant detection is strongly correlated with real fault detection. The work that validated this also showed that a large portion of defects remain out of reach. We introduce tailored mutation operators to reach and capture these defects. Tailored mutation operators are built from and apply to an existing codebase and its history. They can, for instance, identify and replay errors specific to the project for which they are tailored. As our point of departure, we define tailored mutation operators for identifiers, which mutation analysis has largely ignored, because there are too many ways to mutate them. Evaluated on the Defects4J dataset, our new mutation operators creates mutants coupled to 14% more faults, compared to traditional mutation operators. These new mutation operators, however, quadruple the number of mutants. To combat this problem, we propose a new approach to mutant selection focusing on the location at which to apply mutation operators and the unnaturalness of the mutated code. The results demonstrate that the location selection heuristics produce mutants more closely coupled to real faults for a given budget of mutation operator applications. In summary, this paper defines and explores tailored mutation operators, advancing the state of the art in mutation testing in two ways: 1) it suggests mutation operators that mutate identifiers and literals, extending mutation analysis to a new class of faults and 2) it demonstrates that selecting the location where a mutation operator is applied decreases the number of generated mutants without affecting the coupling of mutants and real faults.
Control Exchange Points: Providing QoS-enabled End-to-End Services via SDN-based Inter-domain Routing Orchestration
Venue: arXiv cs.NI 2016
Year: 2016

This paper presents the vision of the Control Exchange Point (CXP) architectural model. The model is motivated by the inflexibility and ossification of today's inter-domain routing system, which renders critical QoS-constrained end-to-end (e2e) network services difficult or simply impossible to provide. CXPs operate on slices of ISP networks and are built on basic Software Defined Networking (SDN) principles, such as the clean decoupling of the routing control plane from the data plane and the consequent logical centralization of control. The main goal of the architectural model is to provide e2e services with QoS constraints across domains. This is achieved through defining a new type of business relationship between ISPs, which advertise partial paths (so-called pathlets) with specific properties, and the orchestrating role of the CXPs, which dynamically stitch them together and provision e2e QoS. Revenue from value-added services flows from the clients of the CXP to the ISPs participating in the service. The novelty of the approach is the combination of SDN programmability and dynamic path stitching techniques for inter-domain routing, which extends the value proposition of SDN over multiple domains. We first describe the challenges related to e2e service provision with the current inter-domain routing and peering model, and then continue with the benefits of our approach. Subsequently, we describe the CXP model in detail and report on an initial feasibility analysis.
Estimating motion with principal component regression strategies
Venue: arXiv cs.CV 2016
Year: 2016

In this paper, two simple principal component regression methods for estimating the optical flow between frames of video sequences according to a pel-recursive manner are introduced. These are easy alternatives to dealing with mixtures of motion vectors in addition to the lack of prior information on spatial-temporal statistics (although they are supposed to be normal in a local sense). The 2D motion vector estimation approaches take into consideration simple image properties and are used to harmonize regularized least square estimates. Their main advantage is that no knowledge of the noise distribution is necessary, although there is an underlying assumption of localized smoothness. Preliminary experiments indicate that this approach provides robust estimates of the optical flow.
Stitching Inter-Domain Paths over IXPs
Venue: arXiv cs.NI 2016
Year: 2016

Modern Internet applications, from HD video-conferencing to health monitoring and remote control of power-plants, pose stringent demands on network latency, bandwidth and availability. An approach to support such applications and provide inter-domain guarantees, enabling new avenues for innovation, is using centralized inter-domain routing brokers. These entities centralize routing control for mission-critical traffic across domains, working in parallel to BGP. In this work, we propose using IXPs as natural points for stitching inter-domain paths under the control of inter-domain routing brokers. To evaluate the potential of this approach, we first map the global substrate of inter-IXP pathlets that IXP members could offer, based on measurements for 229 IXPs worldwide. We show that using IXPs as stitching points has two useful properties. Up to 91 % of the total IPv4 address space can be served by such inter-domain routing brokers when working in concert with just a handful of large IXPs and their associated ISP members. Second, path diversity on the inter-IXP graph increases by up to 29 times, as compared to current BGP valley-free routing. To exploit the rich path diversity, we introduce algorithms that inter-domain routing brokers can use to embed paths, subject to bandwidth and latency constraints. We show that our algorithms scale to the sizes of the measured graphs and can serve diverse simulated path request mixes. Our work highlights a novel direction for SDN innovation across domains, based on logically centralized control and programmable IXP fabrics.
Spectral Statistics of Lattice Graph Percolation Models
Venue: arXiv cs.NA 2016
Year: 2016

In graph signal processing, the graph adjacency matrix or the graph Laplacian commonly define the shift operator. The spectral decomposition of the shift operator plays an important role in that the eigenvalues represent frequencies and the eigenvectors provide a spectral basis. This is useful, for example, in the design of filters. However, the graph or network may be uncertain due to stochastic influences in construction and maintenance, and, under such conditions, the eigenvalues of the shift matrix become random variables. This paper examines the spectral distribution of the eigenvalues of random networks formed by including each link of a D-dimensional lattice supergraph independently with identical probability, a percolation model. Using the stochastic canonical equation methods developed by Girko for symmetric matrices with independent upper triangular entries, a deterministic distribution is found that asymptotically approximates the empirical spectral distribution of the scaled adjacency matrix for a model with arbitrary parameters. The main results characterize the form of the solution to an important system of equations that leads to this deterministic distribution function and significantly reduce the number of equations that must be solved to find the solution for a given set of model parameters. Simulations comparing the expected empirical spectral distributions and the computed deterministic distributions are provided for sample parameters.
Fully-Dynamic Minimum Spanning Forest with Improved Worst-Case Update Time
Venue: arXiv cs.DS 2016
Year: 2016

We give a Las Vegas data structure which maintains a minimum spanning forest in an n-vertex edge-weighted dynamic graph undergoing updates consisting of any mixture of edge insertions and deletions. Each update is supported in O(n^{1/2 - c}) expected worst-case time for some constant c > 0 and this worst-case bound holds with probability at least 1 - n^{-d} where d is a constant that can be made arbitrarily large. This is the first data structure achieving an improvement over the O(n^{1/2}) deterministic worst-case update time of Eppstein et al., a bound that has been standing for nearly 25 years. In fact, it was previously not even known how to maintain a spanning forest of an unweighted graph in worst-case time polynomially faster than Theta(n^{1/2}). Our result is achieved by first giving a reduction from fully-dynamic to decremental minimum spanning forest preserving worst-case update time up to logarithmic factors. Then decremental minimum spanning forest is solved using several novel techniques, one of which involves keeping track of low-conductance cuts in a dynamic graph. An immediate corollary of our result is the first Las Vegas data structure for fully-dynamic connectivity where each update is handled in worst-case time polynomially faster than Theta(n^{1/2}) w.h.p.; this data structure has O(1) worst-case query time.
A Unified Maximum Likelihood Approach for Optimal Distribution Property Estimation
Venue: arXiv cs.IT 2016
Year: 2016

The advent of data science has spurred interest in estimating properties of distributions over large alphabets. Fundamental symmetric properties such as support size, support coverage, entropy, and proximity to uniformity, received most attention, with each property estimated using a different technique and often intricate analysis tools. We prove that for all these properties, a single, simple, plug-in estimator---profile maximum likelihood (PML)---performs as well as the best specialized techniques. This raises the possibility that PML may optimally estimate many other symmetric properties.
Exploring Vickrey-Clarke-Groves Mechanism for Electricity Markets
Venue: arXiv cs.GT 2016
Year: 2016

Control reserves are power generation or consumption entities that ensure balance of supply and demand of electricity in real-time. In many countries, they are operated through a market mechanism in which entities provide bids. The system operator determines the accepted bids based on an optimization algorithm. We develop the Vickrey-Clarke-Groves (VCG) mechanism for these electricity markets. We show that all advantages of the VCG mechanism including incentive compatibility of the equilibria and efficiency of the outcome can be guaranteed in these markets. Furthermore, we derive conditions to ensure collusion and shill bidding are not profitable. Our results are verified with numerical examples.
Throughput Analysis of Decentralized Coded Content Caching in Cellular Networks
Venue: arXiv cs.IT 2016
Year: 2016

Decentralized coded content caching for next generation cellular networks is studied. The contents are linearly combined and cached in under-utilized caches of User Terminals (UTs) and its throughput capacity is compared with decentralized uncoded content caching. In both scenarios, we consider multihop Device-to-Device (D2D) communications and the use of femtocaches in the network. It is shown that decentralized coded content caching can increase the network throughput capacity compared to decentralized uncoded caching by reducing the number of hops needed to deliver the desired content. Further, the throughput capacity for Zipfian content request distribution is computed and it is shown that the decentralized coded content cache placement can increase the throughput capacity of cellular networks by a factor of $(\log(n))^2$ where $n$ is the number of nodes served by a femtocache.
A Brief Survey of Non-Residue Based Computational Error Correction
Venue: arXiv cs.OH 2016
Year: 2016

The idea of computational error correction has been around for over half a century. The motivation has largely been to mitigate unreliable devices, manufacturing defects or harsh environments, primarily as a mandatory measure to preserve reliability, or more recently, as a means to lower energy by allowing soft errors to occasionally creep. While residue codes have shown great promise for this purpose, there have been several orthogonal non-residue based techniques. In this article, we provide a high level outline of some of these non-residual approaches.
On $\mathbb{Z}_{2}\mathbb{Z}_{2}[u]$-$(1+u)$-additive constacyclic
Venue: arXiv cs.IT 2016
Year: 2016

In this paper, we study $\mathbb{Z}_{2}\mathbb{Z}_{2}[u]$-$(1+u)$-additive constacyclic code of arbitrary length. Firstly, we study the algebraic structure of this family of codes and a set of generator polynomials for this family as a $(\mathbb{Z}_{2}+u\mathbb{Z}_{2})[x]$-submodule of the ring $R_{α,β}$. Secondly, we give the minimal generating sets of this family codes, and we determine the relationship of generators between the $\mathbb{Z}_{2}\mathbb{Z}_{2}[u]$-$(1+u)$-additive constacyclic codes and its dual and give the parameters in terms of the degrees of the generator polynomials of the code. Lastly, we also study $\mathbb{Z}_{2}\mathbb{Z}_{2}[u]$-$(1+u)$-additive constacyclic code in terms of the Gray images.
5G Multimedia Massive MIMO Communications Systems
Venue: arXiv cs.IT 2016
Year: 2016

In the Fifth generation (5G) wireless communication systems, a majority of the traffic demands is contributed by various multimedia applications. To support the future 5G multimedia communication systems, the massive multiple-input multiple-output (MIMO) technique is recognized as a key enabler due to its high spectral efficiency. The massive antennas and radio frequency (RF) chains not only improve the implementation cost of 5G wireless communication systems but also result in an intense mutual coupling effect among antennas because of the limited space for deploying antennas. To reduce the cost, an optimal equivalent precoding matrix with the minimum number of RF chains is proposed for 5G multimedia massive MIMO communication systems considering the mutual coupling effect. Moreover, an upper bound of the effective capacity is derived for 5G multimedia massive MIMO communication systems. Two antenna receive diversity gain models are built and analyzed. The impacts of the antenna spacing, the number of antennas, the quality of service (QoS) statistical exponent, and the number of independent incident directions on the effective capacity of 5G multimedia massive MIMO communication systems are analyzed. Comparing with the conventional zero-forcing precoding matrix, simulation results demonstrate that the proposed optimal equivalent precoding matrix can achieve a higher achievable rate for 5G multimedia massive MIMO communication systems.
Fast Adaptation of Activity Sensing Policies in Mobile Devices
Venue: arXiv cs.HC 2016
Year: 2016

With the proliferation of sensors, such as accelerometers, in mobile devices, activity and motion tracking has become a viable technology to understand and create an engaging user experience. This paper proposes a fast adaptation and learning scheme of activity tracking policies when user statistics are unknown a priori, varying with time, and inconsistent for different users. In our stochastic optimization, user activities are required to be synchronized with a backend under a cellular data limit to avoid overcharges from cellular operators. The mobile device is charged intermittently using wireless or wired charging for receiving the required energy for transmission and sensing operations. Firstly, we propose an activity tracking policy by formulating a stochastic optimization as a constrained Markov decision process (CMDP). Secondly, we prove that the optimal policy of the CMDP has a threshold structure using a Lagrangian relaxation approach and the submodularity concept. We accordingly present a fast Q-learning algorithm by considering the policy structure to improve the convergence speed over that of conventional Q-learning. Finally, simulation examples are presented to support the theoretical findings of this paper.
Reduce positive and negative falses from attacks collected from the deployment of distributed honeypot network
Venue: arXiv cs.CR 2016
Year: 2016

Current tools and systems of detecting vulnerabilities simply alert the administrator of attempted attacks against his network or system. However, generally, the huge number of alerts to analyze and the amount time required to update security rules after analyzing alerts provides time and opportunity for the attacker to inflict damages. Moreover, most of these tools generate positive and negative falses, which may be important to the attacked network. Otherwise, many solutions exist such as IPS, but it shows a great defect due, fundamentally, to false positives. Indeed, attackers often make IPS block a legitimate traffic when they detect its presence in the attacked network. In this paper we describe an automated algorithm that gives the ability to detect attacks before they occurrence, then reduce positive and negative falses rates. Moreover, we use a set of data related to malicious traffic captured using a network of honeypots to recognize potential threats sources.