OpenRaiser/Intern-Atlas huggingface dataset:
SAM: Support Vector Machine Based Active Queue Management
Venue: arXiv cs.NI 2016
Year: 2016

Recent years have seen an increasing interest in the design of AQM (Active Queue Management) controllers. The purpose of these controllers is to manage the network congestion under varying loads, link delays and bandwidth. In this paper, a new AQM controller is proposed which is trained by using the SVM (Support Vector Machine) with the RBF (Radial Basis Function) kernal. The proposed controller is called the support vector based AQM (SAM) controller. The performance of the proposed controller has been compared with three conventional AQM controllers, namely the Random Early Detection, Blue and Proportional Plus Integral Controller. The preliminary simulation studies show that the performance of the proposed controller is comparable to the conventional controllers. However, the proposed controller is more efficient in controlling the queue size than the conventional controllers.
An Empirical Study of Irregular AG Block Turbo Codes over Fading Channels
Venue: arXiv cs.IT 2016
Year: 2016

This study will present the design, construction and implementation of Algebraic Geometric Irregular Block Turbo Codes (AGIBTCs). Furthermore, we will evaluate its performance over fast fading channels using different modulation schemes (BPSK, QPSK, 16QAM and 64QAM). The idea behind the design of AGIBTC is to overcome the high system complexity of Algebraic Geometric Block Turbo Codes (AGBTCs) while maintaining a high Bit-Error Rate (BER) performance. This design is inspired by the idea of unequal protection of information symbols which is the core of IBTCs. Our experiments conducted over the worst case of fading channels which is the fast fading channels; and this is done in order to show the magnitude of gain in BER or the reduction in system complexity that can be achieved by this design. Our experiments shows that despite a very slight negative gain over BPSK and QPSK modulation schemes the system complexity is significantly reduced. However, when applying higher modulation schemes a gain in both BER and system complexity are achieved.
A Statistical Block Fading Channel Model for Multiuser Massive MIMO System
Venue: arXiv cs.IT 2016
Year: 2016

This paper presents a statistical block fading channel model for multiuser massive MIMO system. The proposed channel model is evolved from correlation based stochastic channel model (CBSCM) but in addition to the properties of CBSCM, it has capability of capturing channel variations along time or frequency and along space simultaneously. It has a simplified analytical expression, still being able to simulate underlying physical phenomena which otherwise need a complex geometry based stochastic channel model (GBSCM). The channel model is verified with reported measurement data of channel for massive MIMO. Spatial determinism in channel, the basic cause of unfavorable propagation, is modeled into controlling parameters of channel model. Channel model uses only three controlling parameters; one parameter describes variation in channel along resource block (along time or frequency) and remaining two parameters describe spatial variation in channel. Modeling of simultaneous variation along time and space belongs to a very common scenario where mobility of mobile terminal and angular power distribution at base station receiver, are key parameters. Additionally, simulation results reveal the hidden advantages of spatial determinism in channel for multiuser massive MIMO.
Throughput-Optimal Broadcast in Wireless Networks with Dynamic Topology
Venue: arXiv cs.IT 2016
Year: 2016

We consider the problem of throughput-optimal broadcast- ing in time-varying wireless networks, whose underlying topology is restricted to Directed Acyclic Graphs (DAG). Previous broadcast algorithms route packets along spanning trees. In large networks with time-varying connectivities, these trees are difficult to compute and maintain. In this paper we propose a new online throughput-optimal broadcast algorithm which makes packet-by-packet scheduling and routing decisions, obviating the need for maintaining any global topological structures, such as spanning-trees. Our algorithm relies on system-state information for making transmission decisions and hence, may be thought of as a generalization of the well-known back-pressure algorithm which makes point-to-point unicast transmission decisions based on queue-length information, without requiring knowledge of end-to-end paths. Technically, the back-pressure algorithm is derived by stochastically stabilizing the network-queues. However, because of packet-duplications associated with broadcast, the work-conservation principle is violated and queuing processes are difficult to define in the broadcast problem. To address this fundamental issue, we identify certain state-variables which behave like virtual queues in the broadcast setting. By stochastically stabilizing these virtual queues, we devise a throughput-optimal broadcast policy. We also derive new characterizations of the broadcast-capacity of time-varying wireless DAGs and derive an efficient algorithm to compute the capacity exactly under certain assumptions of interference model, and a poly-time approximation algorithm for computing the capacity under less restrictive assumptions.
Elevated Multiplexing and Signal Space Partitioning in the 2 User MIMO IC with Partial CSIT
Venue: arXiv cs.IT 2016
Year: 2016

The $2$ user MIMO interference channel with arbitrary antenna configurations is studied under arbitrary levels of partial CSIT for each of the channels, to find the degrees of freedom (DoF) achievable by either user while the other user achieves his full interference-free DoF. The goal is to gain new insights due to the inclusion of MIMO (multiple antennas at both transmitters and receivers) into the signal space partitioning schemes associated with partial CSIT. An interesting idea that emerges from this study is "elevated multiplexing" where the signals are split into streams and transmitted from separate antennas at elevated power levels, which allows these signals to be jointly decoded at one receiver which has fewer spatial dimensions with lower interference floors, while another receiver is simultaneously able to separately decode these signals with a higher interference floor but across a greater number of spatial dimensions. Remarkably, we find that there is a DoF benefit from increasing the number of antennas at a transmitter even if that transmitter already has more antennas than its desired receiver and has no CSIT.
Statistical QoS Analysis of Full Duplex and Half Duplex Heterogeneous Cellular Networks
Venue: arXiv cs.IT 2016
Year: 2016

In this paper, statistical Quality of Service provisioning in next generation heterogeneous mobile cellular networks is investigated. To this aim, any active entity of the cellular network is regarded as a queuing system, whose statistical QoS requirements depend on the specific application. In this context, by quantifying the performance in terms of effective capacity, we introduce a lower bound for the system performance that facilitates an efficient analysis. We exploit this analytical framework to give insights about the possible improvement of the statistical QoS experienced by the users if the current heterogeneous cellular network architecture migrates from a Half Duplex to a Full Duplex mode of operation. Numerical results and analysis are provided, where the network is modeled as a Matérn point processes with a hard core distance. The results demonstrate the accuracy and computational efficiency of the proposed scheme, especially in large scale wireless systems.
Convex Computation of the Basin of Stability to Measure the Likelihood of Falling: A Case Study on the Sit-to-Stand Task
Venue: arXiv cs.SY 2016
Year: 2016

Locomotion in the real world involves unexpected perturbations, and therefore requires strategies to maintain stability to successfully execute desired behaviours. Ensuring the safety of locomoting systems therefore necessitates a quantitative metric for stability. Due to the difficulty of determining the set of perturbations that induce failure, researchers have used a variety of features as a proxy to describe stability. This paper utilises recent advances in dynamical systems theory to develop a personalised, automated framework to compute the set of perturbations from which a system can avoid failure, which is known as the basin of stability. The approach tracks human motion to synthesise a control input that is analysed to measure the basin of stability. The utility of this analysis is verified on a Sit-to-Stand task performed by 15 individuals. The experiment illustrates that the computed basin of stability for each individual can successfully differentiate between less and more stable Sit-to-Stand strategies.
Optimizing the Diffusion System Based on Continuous-Time Consensus Algorithm
Venue: arXiv cs.SY 2016
Year: 2016

Traditionally, systems governed by linear Partial Differential Equations (PDEs) are spatially discretized to exploit their algebraic structure and reduce the computational effort for controlling them. Due to beneficial insights of the PDEs, recently, the reverse of this approach is implemented where a spatially-discrete system is approximated by a spatially-continuous one, governed by linear PDEs forming diffusion equations. In the case of distributed consensus algorithms, this approach is adapted to enhance its convergence rate to the equilibrium. In previous studies within this context, constant diffusion parameter is considered for obtaining the diffusion equations. This is equivalent to assigning a constant weight to all edges of the underlying graph in the consensus algorithm. Here, by relaxing this restricting assumption, a spatially-variable diffusion parameter is considered and by optimizing the obtained system, it is shown that significant improvements are achievable in terms of the convergence rate of the obtained spatially-continuous system. As a result of approximation, the system is divided into two sections, namely, the spatially-continuous path branches and the lattice core which connects these branches at one end. The optimized weights and diffusion parameter for each of these sections are optimal individually but considering the whole system, they are suboptimal. It is shown that the symmetric star topology is an exception and the obtained results for this topology are globally optimal. Furthermore, through variational method, the results obtained for the symmetric star topology are validated and it is shown that the variable diffusion parameter improves the robustness of the system too.
On the Delay Performance of Interference Channels
Venue: arXiv cs.NI 2016
Year: 2016

A deep understanding of the queuing performance of wireless networks is essential for the advancement of future wireless communications. The stochastic nature of wireless channels in general gives rise to a time varying transmission rate. In such an environment, interference is increasingly becoming a key constraint. Obtaining an expressive model for offered service of such channels has major implications in the design and optimization of future networks. However, interference channels are not well-understood with respect to their higher layer performance. The particular difficulty for handling interference channels arises from the superposition of random fading processes for the signals of the transmitters involved (i.e., for the signal of interest and for the signals of the interferers). Starting from the distribution of the signal-to-interference-plus-noise ratio (SINR), we derive a statistical characterization of the underlying service process in terms of its Mellin transform. Then, we adapt a recent stochastic network calculus approach for fading channels to derive measures of the queuing performance of single- and multi-hop wireless interference networks. Special cases of our solution include noise-limited and interference-limited systems. A key finding of our analysis is that for a given average signal and average sum interference power, the performance of interfered systems not only depends on the relative strength of the sum interference with respect to the signal-of-interest power, but also on the interference structure (i.e., the number of interferers) as well as the absolute levels.
Rate-distortion Balanced Data Compression for Wireless Sensor Networks
Venue: arXiv cs.NI 2016
Year: 2016

This paper presents a data compression algorithm with error bound guarantee for wireless sensor networks (WSNs) using compressing neural networks. The proposed algorithm minimizes data congestion and reduces energy consumption by exploring spatio-temporal correlations among data samples. The adaptive rate-distortion feature balances the compressed data size (data rate) with the required error bound guarantee (distortion level). This compression relieves the strain on energy and bandwidth resources while collecting WSN data within tolerable error margins, thereby increasing the scale of WSNs. The algorithm is evaluated using real-world datasets and compared with conventional methods for temporal and spatial data compression. The experimental validation reveals that the proposed algorithm outperforms several existing WSN data compression methods in terms of compression efficiency and signal reconstruction. Moreover, an energy analysis shows that compressing the data can reduce the energy expenditure, and hence expand the service lifespan by several folds.
Characterizations of the Connected Forcing Number of a Graph
Venue: arXiv cs.DM 2016
Year: 2016

Zero forcing is a dynamic graph coloring process whereby a colored vertex with a single uncolored neighbor forces that neighbor to be colored. This forcing process has been used to approximate certain linear algebraic parameters, as well as to model the spread of diseases and information in social networks. In this paper, we introduce and study the connected forcing process -- a restriction of zero forcing in which the initially colored set of vertices induces a connected subgraph. We show that the connected forcing number -- the cardinality of the smallest initially colored vertex set which forces the entire graph to be colored -- is a sharp upper bound to the maximum nullity, path cover number, and leaf number of the graph. We also give closed formulas and bounds for the connected forcing numbers of several families of graphs including trees, hypercubes, and flower snarks, and characterize graphs with extremal connected forcing numbers.
An Information Theoretic Study for Noisy Compressed Sensing With Joint Sparsity Model-2
Venue: arXiv cs.IT 2016
Year: 2016

In this paper, we study a support set reconstruction problem in which the signals of interest are jointly sparse with a common support set, and sampled by joint sparsity model-2 (JSM-2) in the presence of noise. Using mathematical tools, we develop upper and lower bounds on the failure probability of support set reconstruction in terms of the sparsity, the ambient dimension, the minimum signal to noise ratio, the number of measurement vectors and the number of measurements. These bounds can be used to provide a guideline to determine the system parameters in various applications of compressed sensing with noisy JSM-2. Based on the bounds, we develop necessary and sufficient conditions for reliable support set reconstruction. We interpret these conditions to give theoretical explanations about the benefits enabled by joint sparsity structure in noisy JSM-2. We compare our sufficient condition with the existing result of noisy multiple measurement vectors model (MMV). As a result, we show that noisy JSM-2 may require less number of measurements than noisy MMV for reliable support set reconstruction.
Evaluation of the use of web technology by government of Sri Lanka to ensure food security for its citizens
Venue: arXiv cs.CY 2016
Year: 2016

Web technology is one of the key areas in information and communication technology to be used as a powerful tool in ensuring food security which is one of the main issues in Sri Lanka. Web technology involves in communicating and sharing resources in network of computers all over the world. Main focus of food security is to ensure that all people have fair access to sufficient and quality food without endangering the future supply of the same food. In this context, web sites play a vital and major role in achieving food security in Sri Lanka. In this case study, websites pertaining to Sri Lankan government and link with food security were analyzed to find out their impact in achieving the goals of food security using web technologies and how they are being involved in ensuring food security in Sri Lanka. The other objective of this study is to make the Sri Lankan government aware of present situation of those websites in addressing food security related issues and how modern web technologies could be effectively and efficiently used to address those issues. So, the relevant websites were checked against several criteria and scores were used to assess their capabilities to address the concerns of food security. It was found that the amount of emphasis given by these websites to address the issues of food security is not satisfactory. Further, it showed that if these web sites could be improved further, they would generate a powerful impact on ensuring food security in Sri Lanka.
Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers
Venue: arXiv cs.CV 2016
Year: 2016

Layer-wise relevance propagation is a framework which allows to decompose the prediction of a deep neural network computed over a sample, e.g. an image, down to relevance scores for the single input dimensions of the sample such as subpixels of an image. While this approach can be applied directly to generalized linear mappings, product type non-linearities are not covered. This paper proposes an approach to extend layer-wise relevance propagation to neural networks with local renormalization layers, which is a very common product-type non-linearity in convolutional neural networks. We evaluate the proposed method for local renormalization layers on the CIFAR-10, Imagenet and MIT Places datasets.
Classifying Developers into Core and Peripheral: An Empirical Study on Count and Network Metrics
Venue: arXiv cs.SE 2016
Year: 2016

Knowledge about the roles developers play in a software project is crucial to understanding the project's collaborative dynamics. Developers are often classified according to the dichotomy of core and peripheral roles. Typically, operationalizations based on simple counts of developer activities (e.g., number of commits) are used for this purpose, but there is concern regarding their validity and ability to elicit meaningful insights. To shed light on this issue, we investigate whether commonly used operationalizations of core--peripheral roles produce consistent results, and we validate them with respect to developers' perceptions by surveying 166 developers. Improving over the state of the art, we propose a relational perspective on developer roles, using developer networks to model the organizational structure, and by examining core--peripheral roles in terms of developers' positions and stability within the organizational structure. In a study of 10 substantial open-source projects, we found that the existing and our proposed core--peripheral operationalizations are largely consistent and valid. Furthermore, we demonstrate that a relational perspective can reveal further meaningful insights, such as that core developers exhibit high positional stability, upper positions in the hierarchy, and high levels of coordination with other core developers.
A Modified CSMA/CA Protocol for OFDM Underwater Networks: Cross Layer Design
Venue: arXiv cs.IT 2016
Year: 2016

The underwater acoustic channel continues to present significant challenges to efficient throughput performance of underwater acoustic sensor networks (UASNs) in varying scenarios. As a result, cross-layer approaches that explore joint PHY/MAC strategies are worthy of further exploration. We consider a recent high-speed OFDM modem and propose a new cross-layer solution based on modified CSMA/CA, for a canonical star network topology with few nodes (the most common scenario in UASNs). Some innovations to an adaptive OFDM PHY link are developed to jointly select the modulation, convolutional coding and frequency diversity order (different transmission modes) for matching varying channel conditions. Additionally, receiver logic that disambiguates the cause of packet loss between a) that caused by channel vs. b) that due to collisions is used to modify the ARQ/backoff logic for retransmissions with CSMA/CA random access. Simulation results reveal that the cross-layer design can effectively increase network throughput.
Maximizing the Weighted Number of Spanning Trees: Near-$t$-Optimal Graphs
Venue: arXiv cs.DS 2016
Year: 2016

Designing well-connected graphs is a fundamental problem that frequently arises in various contexts across science and engineering. The weighted number of spanning trees, as a connectivity measure, emerges in numerous problems and plays a key role in, e.g., network reliability under random edge failure, estimation over networks and D-optimal experimental designs. This paper tackles the open problem of designing graphs with the maximum weighted number of spanning trees under various constraints. We reveal several new structures, such as the log-submodularity of the weighted number of spanning trees in connected graphs. We then exploit these structures and design a pair of efficient approximation algorithms with performance guarantees and near-optimality certificates. Our results can be readily applied to a wide verity of applications involving graph synthesis and graph sparsification scenarios.
A Particle-Filtering Based Approach for Distributed Fault Diagnosis of Large-Scale Interconnected Nonlinear Systems
Venue: arXiv cs.SY 2016
Year: 2016

This paper deals with the problem of designing a distributed fault detection and isolation algorithm for nonlinear large-scale systems that are subjected to multiple fault modes. To solve this problem, a network of communicating detection nodes is deployed to monitor the monolithic process. Each node consists of an estimator with partial observation of the system's state. The local estimator executes a distributed variation of the particle filtering algorithm using the partial sensor measurements and the fault progression model of the process. During the implementation of the algorithm, each node communicates with its neighbors by sharing pre-processed information. The communication topology is defined using graph theoretic tools. The information fusion between the neighboring nodes is performed by means of a distributed average consensus algorithm to ensure the agreement over the value of the local likelihood functions. The proposed method enables online hypothesis testing without the need of a bank of estimators. Numerical simulations demonstrate the efficiency of the proposed approach.
On the complexity of computing prime tables on a Turing machine
Venue: arXiv cs.DS 2016
Year: 2016

We prove that the complexity of computing the table of primes between $1$ and $n$ on a multitape Turing machine is $O(n \log n)$.
Directed Containers as Categories
Venue: arXiv cs.LO 2016
Year: 2016

Directed containers make explicit the additional structure of those containers whose set functor interpretation carries a comonad structure. The data and laws of a directed container resemble those of a monoid, while the data and laws of a directed container morphism those of a monoid morphism in the reverse direction. With some reorganization, a directed container is the same as a small category, but a directed container morphism is opcleavage-like. We draw some conclusions for comonads from this observation, considering in particular basic constructions and concepts like the opposite category and a groupoid.