OpenRaiser/Intern-Atlas huggingface dataset:
Language Oriented Modularity: From Theory to Practice
Venue: arXiv cs.SE 2017
Year: 2017

Language-oriented modularity (LOM) is a methodology that complements language-oriented programming (LOP) in providing on-demand language abstraction solutions during software development. It involves the implementation and immediate utilization of domain-specific languages (DSLs) that are also aspect-oriented (DSALs). However, while DSL development is affordable thanks to modern language workbenches, DSAL development lacks similar tool support. Consequently, LOM is often impractical and underutilized. The challenge we address is making the complexity of DSAL implementation comparable to that of DSLs and the effectiveness of programming with DSALs comparable to that of general-purpose aspect languages (GPALs). Today, despite being essentially both domain-specific and aspect-oriented, DSALs seem to be second-class. Aspect development tools (e.g., AJDT) do not work on DSAL code. DSL development tools like language workbenches (e.g., Spoofax) neither deal with the backend weaving nor handle the composition of DSALs. DSAL composition frameworks (e.g., Awesome) do not provide frontend development tools. DSAL code transformation approaches (e.g., XAspects) do not preserve the semantics of DSAL programs in the presence of other aspect languages. We extend AspectJ with a small set of annotations and interfaces that allows DSAL designers to define a semantic-preserving transformation to AspectJ and interface with AspectJ tools. Our transformation approach enables the use of standard language workbench to implement DSALs and use of standard aspect development tools to program with those DSALs. As a result, DSALs regain first-class status with respect to both DSLs and aspect languages. This, on the one hand, lowers the cost of developing DSALs to the level of DSLs and, on the other hand, raises the effectiveness of using a DSAL to the level of a GPAL. Consequently, LOM becomes cost-effective compared to the LOP baseline. We modified the ajc compiler to support our approach. Using two different language workbenches (Spoofax and Xtext) we then implemented several DSALs. AspectJ was supported out-of-the-box. We implemented Cool to demonstrate that the non-trivial composition of AspectJ and Cool can be accommodated using our approach. We applied LOM to crosscutting concerns in two open source projects (oVirt and muCommander), implementing in the process application-specific DSALs, thus providing a sense of the decrease in the cost of developing composable DSALs and the increase in the effectiveness of programming with them. Crosscutting concerns remain a problem in modern real-world projects (e.g., as observed in oVirt). DSALs are often the right tool for addressing these concerns. Our work makes LOM practical, thus facilitating use of DSAL solutions in the software development process.
Provisioning Low Latency, Resilient Mobile Edge Clouds for 5G
Venue: arXiv cs.NI 2017
Year: 2017

Network virtualization and SDN-based routing allow carriers to flexibly configure their networks in response to demand and unexpected network disruptions. However, cellular networks, by nature, pose some unique challenges because of user mobility and control/data plane partitioning, which calls for new architectures and provisioning paradigms. In this paper, we address the latter part by devising algorithms that can provision the data plane to create a distributed Mobile Edge Cloud (MEC), which provides opportunities for lower latencies and increased resilience (through placement of network functions at more distributed datacenter locations) and accounts for service disruption that could be incurred because of user mobility between the service areas of different datacenters. Through evaluations with topology and traffic data from a major carriers's network, we show that, compared to static, centralized networks, careful virtualized provisioning can yield significant savings in network costs while still minimizing service disruption due to mobility. We demonstrate that up to a 75% reduction in redundant datacenter capacity over the operator's current topology (while achieving the same level of resilience) is possible by distributing load over many mobile cloud datacenters.
Detection of malicious data in vehicular ad-hoc networks for traffic signal control applications
Venue: arXiv cs.NI 2017
Year: 2017

Effective applications of vehicular ad hoc networks in traffic signal control require new methods for detection of malicious data. Injection of malicious data can result in significantly decreased performance of such applications, increased vehicle delays, fuel consumption, congestion, or even safety threats. This paper introduces a method, which combines a model of expected driver behaviour with position verification in order to detect the malicious data injected by vehicle nodes that perform Sybil attacks. Effectiveness of this approach was demonstrated in simulation experiments for a decentralized self-organizing system that controls the traffic signals at multiple intersections in an urban road network. Experimental results show that the proposed method is useful for mitigating the negative impact of malicious data on the performance of traffic signal control.
Frames: A Corpus for Adding Memory to Goal-Oriented Dialogue Systems
Venue: arXiv cs.CL 2017
Year: 2017

This paper presents the Frames dataset (Frames is available at http://datasets.maluuba.com/Frames), a corpus of 1369 human-human dialogues with an average of 15 turns per dialogue. We developed this dataset to study the role of memory in goal-oriented dialogue systems. Based on Frames, we introduce a task called frame tracking, which extends state tracking to a setting where several states are tracked simultaneously. We propose a baseline model for this task. We show that Frames can also be used to study memory in dialogue management and information presentation through natural language generation.
Wireless Full-duplex Medium Access Control for Enhancing Energy Efficiency
Venue: arXiv cs.NI 2017
Year: 2017

Recent years have witnessed a proliferation of battery-powered mobile devices, e.g., smartphones, tablets, sensors, and laptops, which leads a significant demand for high capacity wireless communication with high energy efficiency. Among technologies to provide the efficiency is full-duplex wireless communication. Full-duplex wireless enhances capacity by simultaneously transmitting uplink and downlink data with limited frequency resources. Previous studies on full-duplex wireless mostly focuses on doubling the network capacity, whereas in this paper we discuss that full-duplex wireless can also provide higher energy efficiency. We propose low power communication by wireless full-duplexing (LPFD), focusing on the fact that the full-duplex communication duration becomes half of the halfduplex communication duration. In the LPFD, by using the sleep state in which the transceiver provided in the wireless communication terminal is turned off, power consumption of the wireless communication terminal is reduced and energy efficiency in wireless full duplex is improved. Simulation results show that the energy efficiency achieved by LPFD is up to approximately 17.3 times higher than the energy efficiency achieved by existing full-duplex medium access protocol. Further, it is up to approximately 27.5 times higher than the energy efficiency using power saving mode of half-duplex communication.
BlockChain: A distributed solution to automotive security and privacy
Venue: arXiv cs.CR 2017
Year: 2017

Interconnected smart vehicles offer a range of sophisticated services that benefit the vehicle owners, transport authorities, car manufacturers and other service providers. This potentially exposes smart vehicles to a range of security and privacy threats such as location tracking or remote hijacking of the vehicle. In this article, we argue that BlockChain (BC), a disruptive technology that has found many applications from cryptocurrencies to smart contracts, is a potential solution to these challenges. We propose a BC-based architecture to protect the privacy of the users and to increase the security of the vehicular ecosystem. Wireless remote software updates and other emerging services such as dynamic vehicle insurance fees, are used to illustrate the efficacy of the proposed security architecture. We also qualitatively argue the resilience of the architecture against common security attacks.
Algorithms for Routing of Unmanned Aerial Vehicles with Mobile Recharging Stations
Venue: arXiv cs.RO 2017
Year: 2017

We study the problem of planning a tour for an energy-limited Unmanned Aerial Vehicle (UAV) to visit a set of sites in the least amount of time. We envision scenarios where the UAV can be recharged along the way either by landing on stationary recharging stations or on Unmanned Ground Vehicles (UGVs) acting as mobile recharging stations. This leads to a new variant of the Traveling Salesperson Problem (TSP) with mobile recharging stations. We present an algorithm that finds not only the order in which to visit the sites but also when and where to land on the charging stations to recharge. Our algorithm plans tours for the UGVs as well as determines best locations to place stationary charging stations. While the problems we study are NP-Hard, we present a practical solution using Generalized TSP that finds the optimal solution. If the UGVs are slower, the algorithm also finds the minimum number of UGVs required to support the UAV mission such that the UAV is not required to wait for the UGV. Our simulation results show that the running time is acceptable for reasonably sized instances in practice.
Online Geographical Load Balancing for Mobile Edge Computing with Energy Harvesting
Venue: arXiv cs.IT 2017
Year: 2017

Mobile Edge Computing (MEC) (a.k.a. fog computing) has recently emerged to enable low-latency and location-aware data processing at the edge of mobile networks. Since providing grid power supply in support of MEC can be costly and even infeasible in some scenarios, on-site renewable energy is mandated as a major or even sole power supply. Nonetheless, the high intermittency and unpredictability of energy harvesting creates many new challenges of performing effective MEC. In this paper, we develop an algorithm called GLOBE that performs joint geographical load balancing (GLB) and admission control for optimizing the system performance of a network of MEC-enabled and energy harvesting-powered base stations. By leveraging and extending the Lyapunov optimization with perturbation technique, GLOBE operates online without requiring future system information and addresses significant challenges caused by battery state dynamics and energy causality constraints. Moreover, GLOBE works in a distributed manner, which makes our algorithm scalable to large networks. We prove that GLOBE achieves a close-to-optimal system performance compared to the offline algorithm that knows full future information, and present a critical tradeoff between battery capacity and system performance. Simulation results validate our analysis and demonstrate the superior performance of GLOBE compared to benchmark algorithms.
Structured Parallel Programming for Monte Carlo Tree Search
Venue: arXiv cs.AI 2017
Year: 2017

In this paper, we present a new algorithm for parallel Monte Carlo tree search (MCTS). It is based on the pipeline pattern and allows flexible management of the control flow of the operations in parallel MCTS. The pipeline pattern provides for the first structured parallel programming approach to MCTS. Moreover, we propose a new lock-free tree data structure for parallel MCTS which removes synchronization overhead. The Pipeline Pattern for Parallel MCTS algorithm (called 3PMCTS), scales very well to higher numbers of cores when compared to the existing methods.
Dense Multi-view 3D-reconstruction Without Dense Correspondences
Venue: arXiv cs.CV 2017
Year: 2017

We introduce a variational method for multi-view shape-from-shading under natural illumination. The key idea is to couple PDE-based solutions for single-image based shape-from-shading problems across multiple images and multiple color channels by means of a variational formulation. Rather than alternatingly solving the individual SFS problems and optimizing the consistency across images and channels which is known to lead to suboptimal results, we propose an efficient solution of the coupled problem by means of an ADMM algorithm. In numerous experiments on both simulated and real imagery, we demonstrate that the proposed fusion of multiple-view reconstruction and shape-from-shading provides highly accurate dense reconstructions without the need to compute dense correspondences. With the proposed variational integration across multiple views shape-from-shading techniques become applicable to challenging real-world reconstruction problems, giving rise to highly detailed geometry even in areas of smooth brightness variation and lacking texture.
Exploring Choice Overload in Related-Article Recommendations in Digital Libraries
Venue: arXiv cs.IR 2017
Year: 2017

We investigate the problem of choice overload - the difficulty of making a decision when faced with many options - when displaying related-article recommendations in digital libraries. So far, research regarding to how many items should be displayed has mostly been done in the fields of media recommendations and search engines. We analyze the number of recommendations in current digital libraries. When browsing fullscreen with a laptop or desktop PC, all display a fixed number of recommendations. 72% display three, four, or five recommendations, none display more than ten. We provide results from an empirical evaluation conducted with GESIS' digital library Sowiport, with recommendations delivered by recommendations-as-a-service provider Mr. DLib. We use click-through rate as a measure of recommendation effectiveness based on 3.4 million delivered recommendations. Our results show lower click-through rates for higher numbers of recommendations and twice as many clicked recommendations when displaying ten instead of one related-articles. Our results indicate that users might quickly feel overloaded by choice.
A Survey of Distributed Message Broker Queues
Venue: arXiv cs.DC 2017
Year: 2017

This paper surveys the message brokers that are in vogue today for distributed communication. Their primary goal is to facilitate the construction of decentralized topologies without single points of failure, enabling fault tolerance and high availability. These characteristics make them optimal for usage within distributed architectures. However, there are multiple protocols built to achieve this, and it would be beneficial to have a empirical comparison between their features and performance to determine their real-world applicability. This paper focuses on two popular protocols (Kafka and AMQP) and explores the divergence in their features as well as their performance under varied testing workloads.
CRLB Calculations for Joint AoA, AoD and Multipath Gain Estimation in Millimeter Wave Wireless Networks
Venue: arXiv cs.IT 2017
Year: 2017

In this report we present an analysis of the non-random and the Bayesian Cramer-Rao lower bound (CRLB) for the joint estimation of angle-of-arrival (AoA), angle-of-departure (AoD), and the multipath amplitudes, for the millimeter-wave (mmWave) wireless networks. Our analysis is applicable to multipath channels with Gaussian noise and independent path parameters. Numerical results based on uniform AoA and AoD in $[0,π)$, and Rician fading path amplitudes, reveal that the Bayesian CRLB decreases monotonically with an increase in the Rice factor. Further, the CRLB obtained by using beamforming and combining code books generated by quantizing directly the domain of AoA and AoD was found to be lower than those obtained with other types of beamforming and combining code books.
Power Control in Massive MIMO with Dynamic User Population
Venue: arXiv cs.NI 2017
Year: 2017

This paper considers the problem of power control in Massive MIMO systems taking into account the pilot contamination issue and the arrivals and departures of users in the network. Contrary to most of existing work in MIMO systems that focuses on the physical layer with fixed number of users, we consider in this work that the users arrive dynamically and leave the network once they are served. We provide a power control strategy, having a polynomial complexity, and prove that this policy stabilizes the network whenever possible. We then provide a distributed implementation of the power control policy requiring low information exchange between the BSs and show that it achieves the same stability region as the centralized policy.
3D Object Reconstruction from Hand-Object Interactions
Venue: arXiv cs.CV 2017
Year: 2017

Recent advances have enabled 3d object reconstruction approaches using a single off-the-shelf RGB-D camera. Although these approaches are successful for a wide range of object classes, they rely on stable and distinctive geometric or texture features. Many objects like mechanical parts, toys, household or decorative articles, however, are textureless and characterized by minimalistic shapes that are simple and symmetric. Existing in-hand scanning systems and 3d reconstruction techniques fail for such symmetric objects in the absence of highly distinctive features. In this work, we show that extracting 3d hand motion for in-hand scanning effectively facilitates the reconstruction of even featureless and highly symmetric objects and we present an approach that fuses the rich additional information of hands into a 3d reconstruction pipeline, significantly contributing to the state-of-the-art of in-hand scanning.
Dynamic Planar Embeddings of Dynamic Graphs
Venue: arXiv cs.DS 2017
Year: 2017

We present an algorithm to support the dynamic embedding in the plane of a dynamic graph. An edge can be inserted across a face between two vertices on the face boundary (we call such a vertex pair linkable), and edges can be deleted. The planar embedding can also be changed locally by flipping components that are connected to the rest of the graph by at most two vertices. Given vertices $u,v$, linkable$(u,v)$ decides whether $u$ and $v$ are linkable in the current embedding, and if so, returns a list of suggestions for the placement of $(u,v)$ in the embedding. For non-linkable vertices $u,v$, we define a new query, one-flip-linkable$(u,v)$ providing a suggestion for a flip that will make them linkable if one exists. We support all updates and queries in O(log$^2 n$) time. Our time bounds match those of Italiano et al. for a static (flipless) embedding of a dynamic graph. Our new algorithm is simpler, exploiting that the complement of a spanning tree of a connected plane graph is a spanning tree of the dual graph. The primal and dual trees are interpreted as having the same Euler tour, and a main idea of the new algorithm is an elegant interaction between top trees over the two trees via their common Euler tour.
A parametric level-set method for partially discrete tomography
Venue: arXiv cs.CE 2017
Year: 2017

This paper introduces a parametric level-set method for tomographic reconstruction of partially discrete images. Such images consist of a continuously varying background and an anomaly with a constant (known) grey-value. We represent the geometry of the anomaly using a level-set function, which we represent using radial basis functions. We pose the reconstruction problem as a bi-level optimization problem in terms of the background and coefficients for the level-set function. To constrain the background reconstruction we impose smoothness through Tikhonov regularization. The bi-level optimization problem is solved in an alternating fashion; in each iteration we first reconstruct the background and consequently update the level-set function. We test our method on numerical phantoms and show that we can successfully reconstruct the geometry of the anomaly, even from limited data. On these phantoms, our method outperforms Total Variation reconstruction, DART and P-DART.
Towards a property graph generator for benchmarking
Venue: arXiv cs.DB 2017
Year: 2017

The use of synthetic graph generators is a common practice among graph-oriented benchmark designers, as it allows obtaining graphs with the required scale and characteristics. However, finding a graph generator that accurately fits the needs of a given benchmark is very difficult, thus practitioners end up creating ad-hoc ones. Such a task is usually time-consuming, and often leads to reinventing the wheel. In this paper, we introduce the conceptual design of DataSynth, a framework for property graphs generation with customizable schemas and characteristics. The goal of DataSynth is to assist benchmark designers in generating graphs efficiently and at scale, saving from implementing their own generators. Additionally, DataSynth introduces novel features barely explored so far, such as modeling the correlation between properties and the structure of the graph. This is achieved by a novel property-to-node matching algorithm for which we present preliminary promising results.
Channel Feedback Based on AoD-Adaptive Subspace Codebook in FDD Massive MIMO Systems
Venue: arXiv cs.IT 2017
Year: 2017

Channel feedback is essential in frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems. Unfortunately, previous work on multiuser MIMO has shown that the codebook size for channel feedback should scale exponentially with the number of base station (BS) antennas, which is greatly increased in massive MIMO systems. To reduce the codebook size and feedback overhead, we propose an angle-of-departure (AoD)-adaptive subspace codebook for channel feedback in FDD massive MIMO systems. Our key insight is to leverage the observation that path AoDs vary more slowly than the path gains. Within the angle coherence time, by utilizing the constant AoD information, the proposed AoD-adaptive subspace codebook is able to quantize the channel vector in a more accurate way. We also provide performance analysis of the proposed codebook in the large-dimensional regime, where we prove that to limit the capacity degradation within an acceptable level, the required number of feedback bits only scales linearly with the number of resolvable (path) AoDs, which is much smaller than the number of BS antennas. Moreover, we compare quantized channel feedback using the proposed AoD-adaptive subspace codebook with analog channel feedback. Extensive simulations that verify the analytical results are provided.
Index Coding: Rank-Invariant Extensions
Venue: arXiv cs.IT 2017
Year: 2017

An index coding (IC) problem consisting of a server and multiple receivers with different side-information and demand sets can be equivalently represented using a fitting matrix. A scalar linear index code to a given IC problem is a matrix representing the transmitted linear combinations of the message symbols. The length of an index code is then the number of transmissions (or equivalently, the number of rows in the index code). An IC problem ${\cal I}_{ext}$ is called an extension of another IC problem ${\cal I}$ if the fitting matrix of ${\cal I}$ is a submatrix of the fitting matrix of ${\cal I}_{ext}$. We first present a straightforward $m$\textit{-order} extension ${\cal I}_{ext}$ of an IC problem ${\cal I}$ for which an index code is obtained by concatenating $m$ copies of an index code of ${\cal I}$. The length of the codes is the same for both ${\cal I}$ and ${\cal I}_{ext}$, and if the index code for ${\cal I}$ has optimal length then so does the extended code for ${\cal I}_{ext}$. More generally, an extended IC problem of ${\cal I}$ having the same optimal length as ${\cal I}$ is said to be a \textit{rank-invariant} extension of ${\cal I}$. We then focus on $2$-order rank-invariant extensions of ${\cal I}$, and present constructions of such extensions based on involutory permutation matrices.