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Large-scale optimization problems abound in data mining and machine learning applications, and the computational challenges they pose are often addressed through parallelization. We identify structural properties under which a convex optimization problem can be massively parallelized via map-reduce operations using the Frank-Wolfe (FW) algorithm. The class of problems that can be tackled this way...
In today's era of big data, robust least-squares regression becomes a more challenging problem when considering the adversarial corruption along with explosive growth of datasets. Traditional robust methods can handle the noise but suffer from several challenges when applied in huge dataset including 1) computational infeasibility of handling an entire dataset at once, 2) existence of heterogeneously...
We present a deterministic distributed algorithm that computes a (2δ-1)-edge-coloring, or even list-edge-coloring, in any n-node graph with maximum degree δ, in O(log^8 δ ⋅ log n) rounds. This answers one of the long-standing open questions of distributed graph algorithms} from the late 1980s, which asked for a polylogarithmic-time algorithm. See, e.g.,...
We study computing all-pairs shortest paths (APSP) on distributed networks (the CONGEST model). The goal is for every node in the (weighted) network to know the distance from every other node using communication. The problem admits (1+o(1))-approximation Õ(n)-time algorithms [2], [3], which are matched with \tilde Ω(n)-time lower bounds [4], [5],\footnote{\tilde \Theta, Õ...
Combinatorial multi-armed bandit (MAB) problem can be used to formulate sequential decision problems with exploration-exploitation tradeoff. Dynamic spectrum access (DSA) in cognitive radio (CR) networks is one of important applications. In this work, we briefly overview combinatorial MAB problems with its possible applications to CR networks. We first investigate the standard MAB problems where a...
In this paper, a continuous-time distributed optimization algorithm based on multi-agent system is proposed for solving the distributed least absolute deviation problems subject to hybrid constraints. In the multi-agent network, each of the L1-norm functions is realized using the projection operator. Meanwhile, each agent must be subject to the local hybrid constraints. Then all the agents constitute...
The Network Function Placement (NFP) problem involves placing Virtual Network Functions (VNFs) in a network in order to meet the Service Function Chain (SFC) requirements of the flows through the network. Simultaneously, the usage of network resources by the VNF instances must be optimized. Prior work primarily treated this as a constraint satisfaction problem, using linear programming to find optimal...
After the occurrence of a disaster one of the main needs for the rescue teams and volunteer helpers is a functional communication infrastructure even during the first hours. The disaster recovery system (DRS) originally presented by us in a previous work [1] is based on an IEEE 802.11s wireless mesh network which is set up by non damaged legacy, mesh capable and battery powered devices still available...
Recently, to overcome the long WAN latencies, the framework of mobile ad hoc cloud has been proposed, where the neighboring mobile devices are pooled together for resource sharing. In this paper, we consider the problem of resource allocation mechanism in the mobile ad hoc cloud, where the demanding users suffer from resource limitation and the supplying users are willing to share their idle resources...
In this paper, based on minimum-time consensus, a distributed algorithm is proposed to solve economic dispatch problem (EDP). Firstly, The EDP is transformed to the average consensus problem and the ratio consensus protocol is utilized to address the average consensus problem over unbalanced directed topology. The proposed algorithm is implemented in a fully distributed fashion without using any global...
Intersection computation of convex sets is a typical problem in distributed optimization. In this paper, a multi-agent network is considered for continuous-time dynamics with the fixed topology, in which each agent is associated with a convex set. The objective is for all the agents to achieve an agreement within the intersection of the associated convex sets. A distributed “projected consensus algorithm”...
Finding a dominating set in a Wireless Sensor Network can be used for the clustering or the routing. There is an abundant literature on methods, centralized or distributed, for detecting these sets. In this work, we propose a new distributed algorithm for the search of the nodes forming a dominating set in a wireless sensor network, which uses a new concept called Wait-Before-Starting that allows...
Pathfinder network scaling is a graph sparsification technique that has been popularly used due to its efficacy of extracting the “important” structure of a graph. However, existing algorithms to compute the pathfinder network (PFNET) of a graph have prohibitively expensive time complexity for large graphs: O(n3) for the general case and O(n2 log n) for a specific parameter setting, PFNET(r = ∞, q...
Although randomized algorithms have widely been used in distributed computing as a means to tackle impossibility results, it is currently unclear what type of randomization leads to the best performance in such algorithms. This paper proposes three automated techniques to find the probability distribution that achieves minimum average recovery time for an input randomized distributed self-stabilizing...
The performance of computer networks relies on how bandwidth is shared among different flows. Fair resource allocation is a challenging problem particularly when the flows evolve over time. To address this issue, bandwidth sharing techniques that quickly react to the traffic fluctuations are of interest, especially in large scale settings with hundreds of nodes and thousands of flows. In this context,...
Nowadays environmental science experiences tremendous growth of raster data: N-dimensional (N-d) arrays coming mainly from numeric simulation and Earth remote sensing. An array DBMS is a tool to streamline raster data processing. However, raster data are usually stored in files, not in databases. Moreover, numerous command line tools exist for processing raster files. This paper describes a distributed...
This paper considers the optimal energy generation problem for hierarchical system, which consists of multi-cluster power system. In particular, consensus-based distributed hierarchical coordination algorithm is proposed to meet the power generation/demand balance. By using Lagrangian-based approach, we show that the optimization problem for the hierarchical system can be separated into each layer's...
Online social networks offer a rich data source for analyzing diffusion processes including rumor and viral spreading in communities. While many models exist, a unified model which enables analytical computation of complex, nonlinear phenomena while considering multiple factors was only recently proposed. We design an optimized implementation of the unified model of influence for vertex centric graph...
There are numerous situations in which collaboration of two or more agents is required to accomplish a task. The accomplishment of such task by physical agents (i.e., robots) is possible only when all the agents are at the location where the task is to be carried out. Even though, if multiple agents are available in an environment but, unlikely spread at different locations, they will not able to...
Due to the explosion of data from various sources, data analytics is found to be difficult using the CPU alone. For huge networks, the most popular graph algorithms using a single processor failed to accomplish this task. Hence the need of algorithms that have higher processing capabilities became dominant. Graph analytics is gaining importance in the realm of data analysis due to the advantages over...
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