Sharif Digital Repository

Averaging consensus on the values of nodes in a network is a principal problem in distributed computation. In the presence of erasure channels, conventional averaging consensus algorithms may not converge to the average value if packets are erased in arbitrary order. In this paper, we propose a 'Pseudo-Synchronous Averaging Consensus' (PSAC) algorithm to guarantee averaging consensus over erasure channels by employing tagged packets. We show that the PSAC algorithm has a simple structure and it can work with just two tags '0' and '1'. In asynchronous networks, the PSAC algorithm is a synchronizer in the sense that it keeps the updates of various nodes in step with each other. By exploiting... 

In the binary majority voting problem, each node initially chooses between two alternative choices. The goal is to design a distributed algorithm that informs nodes which choice is in majority. In this study, the authors formulate this problem as a hypothesis testing problem and propose fixed-size and sequential solutions using classical and Bayesian approaches. In the sequential version, the proposed mechanism enables nodes to test which choice is in majority, successively in time. Hence, termination of the algorithm is embedded within it, contrary to the existing approaches which require a monitoring algorithm to indicate the termination. This property makes the algorithm more efficient in... 

In distributed function computation, each node has an initial value and the goal is to compute a function of these values in a distributed manner. In this paper, we propose a novel token-based approach to compute a wide class of target functions to which we refer as "token-based function computation with memory" (TCM) algorithm. In this approach, node values are attached to tokens and travel across the network. Each pair of travelling tokens would coalesce when they meet, forming a token with a new value as a function of the original token values. In contrast to the coalescing random walk (CRW) algorithm, where token movement is governed by random walk, meeting of tokens in our scheme is... 

We consider the problem of recovering channel code parameters over a candidate set by merely analyzing the received encoded signals. We propose a deep learning-based solution that I) is capable of identifying the channel code parameters for several coding scheme (such as LDPC, Convolutional, Turbo, and Polar codes), II) is robust against channel impairments like multi-path fading, III) does not require any previous knowledge or estimation of channel state or signal-to-noise ratio (SNR), and IV) outperforms related works in terms of probability of detecting the correct code parameters. © 2012 IEEE  

We consider distributed statistical optimization in one-shot setting, where there are m machines each observing n i.i.d. samples. Based on its observed samples, each machine sends a B-bit-long message to a server. The server then collects messages from all machines, and estimates a parameter that minimizes an expected convex loss function. We investigate the impact of communication constraint, B, on the expected error and derive a tight lower bound on the error achievable by any algorithm. We then propose an estimator, which we call Multi-Resolution Estimator (MRE), whose expected error (when B ≥ d log mn where d is the dimension of parameter) meets the aforementioned lower bound up to a... 

One of the most challenging problems in Opportunistic Spectrum Access (OSA) is to design channel sensing-based protocol in multi secondary users (SUs) network. Quality of Service (QoS) requirements for SUs have significant implications on this protocol design. In this paper, we propose a new method to find joint policies for SUs which not only tries to guarantee QoS requirements but also maximize network throughput. We use Decentralized Partially Observable Markov Decision Process (Dec-POMDP) to formulate interactions between SUs. Meanwhile, a tractable approach for Dec-POMDP is utilized to extract sub-optimum joint policies for large horizons. Among these policies, the QoS-aware joint... 

In this paper, we consider a cognitive radio network in which multiple Secondary Users (SUs) contend to access primary network's channels with a random access scheme. Our goal is to analyze SUs' queuing delay performance in terms of mean queue lengths and find a minimum buffer space for which the overflow probability is less than a desired threshold. In general, the considered network can be modeled as a multidimensional Markov chain. However, the enormous state space makes the numerical analysis intractable. Nevertheless, the state space can be reduced to a two-dimensional Markov chain in the symmetric channel condition. By this approach, the optimal contention probability that minimizes... 

We study myopic sensing policy for an opportunistic communication system in which the states of channels evolve as independent Markov chains. A Secondary User (SU) takes one channel to sense and access in each time slot by myopic sensing policy. In the myopic policy, SU ignores the impact of the current action on the future decisions and tries to maximize the expected immediate reward. We propose an upper bound on the throughput achieved by the myopic sensing policy for general case in which channels have different Markov models. In particular, the proposed bound is compared with the Zhao et. al's upper bound (UZhao) for the channels with identical models. We prove that there are conditions... 

The main goal in many fields in the empirical sciences is to discover causal relationships among a set of variables from observational data. PC algorithm is one of the promising solutions to learn underlying causal structure by performing a number of conditional independence tests. In this paper, we propose a novel GPU-based parallel algorithm, called cuPC, to execute an order-independent version of PC. The proposed solution has two variants, cuPC-E and cuPC-S, which parallelize PC in two different ways for multivariate normal distribution. Experimental results show the scalability of the proposed algorithms with respect to the number of variables, the number of samples, and different graph... 

An important issue in designing multichannel MAC protocols for Opportunistic Spectrum Access (OSA) is the synchronization between Secondary Users (SUs). Synchronization can be performed in two phases: the initial handshaking, and then the synchronous hopping across available channels. In this paper, we address the problem of initial handshaking through the approach called "blind rendezvous". We first introduce a role-based solution by constructing two channel hopping sequences. The secondary transmitter and receiver jump across channels according to these two sequences. The proposed algorithm guarantees rendezvous in at most (C+1)2 time slots (where C is the number of channels) and two SUs... 

We consider the problem of learning causal models from observational data generated by linear non-Gaussian acyclic causal models with latent variables. Without considering the effect of latent variables, the inferred causal relationships among the observed variables are often wrong. Under faithfulness assumption, we propose a method to check whether there exists a causal path between any two observed variables. From this information, we can obtain the causal order among the observed variables. The next question is whether the causal effects can be uniquely identified as well. We show that causal effects among observed variables cannot be identified uniquely under mere assumptions of... 

Learning a foreign language encompasses a process of trial and error that can lead to the progression of the learner's interlanguage, meaning that the learners make use of their language knowledge that receives feedback and brings about progress through diagnosis of the problems and being corrected by the teacher. Therefore, there exists a need to analyze the underlying reasons causing the students to remain taciturn with a low willingness to communicate (WTC) during a language class. There has been much work done investigating the role of the learner's stable personal characteristics (traits) along with their situational changes at a specific time (states) that influence the student's... 

Accurate system identification (SI) is essential for flight controller design of unmanned aerial vehicles and microaerial vehicles (MAVs). SI can be performed either in frequency or time domain using flight test data. As flight testing is often costly and may even lead to catastrophic events before some flight stability analysis is at hand, a low-cost 5 degree-of-freedom free motion platform (FMP) is designed and used for initial identification of MAVs via wind tunnel testing. A typical MAV is constructed as a test case and equipped with inertial sensors for testing and validation purposes. The proposed FMP allows for both rotational as well as translational motions that in turn provide for... 

Using 3-D scanned data to analyze and extract pore network plays a vital role in investigation of porous media's characteristics. In this paper, a new simple method is developed to detect pores and throats for analyzing the connectivity and permeability of the network. This automated method utilizes some of the common and well-known image processing functions which are widely accessible by researchers and this has led to an easy algorithm implementation. In this method, after polishing and quality control of images, using city-block distance function and watershed segmentation algorithm, pores and throats are detected and 3-D network is produced. This method can also be applied on 2-D images...