In this paper, we initiate the study of the problem of ordering objects from their pairwise comparison results when allowed to discard up to a certain number of objects as outliers. More specifically, we seek to find ...
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ISBN:
(纸本)9783030461508;9783030461492
In this paper, we initiate the study of the problem of ordering objects from their pairwise comparison results when allowed to discard up to a certain number of objects as outliers. More specifically, we seek to find an ordering under the popular Kendall tau distance measure, i.e., minimizing the number of pairwise comparison results that are inconsistent with the ordering, with some outliers removed. The presence of outliers challenges the assumption that a global consistent ordering exists and obscures the measure. This problem does not admit a polynomial time algorithm unless NP. BPP, and therefore, we develop approximation algorithms with provable guarantees for all inputs. Our algorithms have running time and memory usage that are almost linear in the input size. Further, they are readily adaptable to run on massively parallel platforms such as MapReduce or Spark.
Knapsack problems (KPs) are common in industry, but solving KPs is known to be NP-hard and has been tractable only at a relatively small scale. This paper examines KPs in a slightly generalized form and shows that the...
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ISBN:
(纸本)9781450370233
Knapsack problems (KPs) are common in industry, but solving KPs is known to be NP-hard and has been tractable only at a relatively small scale. This paper examines KPs in a slightly generalized form and shows that they can be solved nearly optimally at scale via distributed algorithms. The proposed approach can be implemented fairly easily with off-the-shelf distributed computing frameworks (e.g. MPI, Hadoop, Spark). As an example, our implementation leads to one of the most efficient KP solvers known to date - capable to solve KPs at an unprecedented scale (e.g., KPs with 1 billion decision variables and 1 billion constraints can be solved within 1 hour). The system has been deployed to production and called on a daily basis, yielding significant business impacts at Ant Financial.
In 5G and beyond network architectures, operators and content providers base their content distribution strategies on Heterogeneous Networks, where macro and small(er) cells are combined to offer better Quality of Ser...
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ISBN:
(纸本)9781728150895
In 5G and beyond network architectures, operators and content providers base their content distribution strategies on Heterogeneous Networks, where macro and small(er) cells are combined to offer better Quality of Service (QoS) to wireless users. On top of such networks, edge caching and Coordinated Multi-Point (CoMP) transmissions are used to further improve performance. The problem of optimally utilizing the cache space in dense and heterogeneous cell networks has been extensively studied under the name of "FemtoCaching." However, related literature usually assumes relatively simple physical layer (PHY) setups and known or stationary content popularity. In this paper, we address these issues by proposing a class of fully distributed and dynamic caching algorithms that take advantage of CoMP capabilities towards minimizing PHY-aware metrics, such as end-to-end (E2E) delay. Our policies outperform existing dynamic solutions that are PHY-unaware, under both synthetic and real (non-stationary) request processes, and converge to efficient centralized solutions, in static setups.
Securing a wireless sensor network against the various attacks with minimal energy consumption is a challenging task because the nodes usually have limited energy source, are distributed in harsh environments and comm...
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ISBN:
(纸本)9781728172064
Securing a wireless sensor network against the various attacks with minimal energy consumption is a challenging task because the nodes usually have limited energy source, are distributed in harsh environments and communicate over standard radio channels. Adding malicious nodes to an existing wireless sensor network is one of the common types of attacks. The malicious nodes can reduce the reliability of a network by flooding heavy traffic, sending fake data or counterfeiting the paths. This study proposes a new localized algorithm for identifying the malicious nodes in WSNs where the existing verified nodes detect the malicious nodes using neighborhood information and signature of messages. The testbed experiments and simulation results show that the proposed algorithm is a feasible and efficient approach for detecting the malicious nodes.
Wireless power transfer technologies lead the way towards new paradigms for pervasive networking and have already penetrated the mobile and portable user device research and market. Their use is not only limited to ch...
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ISBN:
(纸本)9781728143514
Wireless power transfer technologies lead the way towards new paradigms for pervasive networking and have already penetrated the mobile and portable user device research and market. Their use is not only limited to charging devices like smartphones wirelessly by using a central wireless charger, but it is also extended to peer-to-peer (P2P) wireless crowd charging, when a user device shares energy directly with another user device. This paper surveys the literature over the period 2014-2020 on both P2P and central wireless crowd charging from the point of view of algorithmic applications as it applies to ubiquitously networked user devices and identifies some open research challenges for the future.
Calibration and localisation of a camera sensor network is an essential requirement for higher-level computer vision tasks, such as mapping or tracking. Additionally, distributed algorithms are being increasingly used...
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Calibration and localisation of a camera sensor network is an essential requirement for higher-level computer vision tasks, such as mapping or tracking. Additionally, distributed algorithms are being increasingly used to create scalable networks robust to node failure. We propose a distributed calibration and localisation algorithm based on multi-view one-dimensional calibration, alternating direction method of multipliers, and Gaussian belief propagation. Our algorithm builds upon an existing calibration algorithm by improving the numerical conditioning and non-linear refinement. We adapt this to a distributed network, bringing local estimates at each camera node to global consensus. Simulation and experimental results show that our algorithm performs with high accuracy compared to other calibration techniques, in centralised and distributed networks, and is well suited for practical applications. (C) 2019 Elsevier Ltd. All rights reserved.
This paper addresses consensus problems in the presence of adversaries that can move within the network and induce faulty behaviors in the attacked agents. By employing mobile adversary models from the computer scienc...
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This paper addresses consensus problems in the presence of adversaries that can move within the network and induce faulty behaviors in the attacked agents. By employing mobile adversary models from the computer science literature, we develop three protocols which can mitigate the influence of malicious agents. The algorithms follow the class of mean subsequence reduced (MSR) algorithms, under which agents ignore the suspicious values received from neighbors during their state updates. Different from the static model, even after the adversaries move away, the infected agents may remain faulty in their values for a short while, which must be taken into account. We develop conditions on the network structures for both the complete and non-complete graph cases, under which the proposed algorithms are guaranteed to attain resilient consensus. An illustrative example is provided to verify the effectiveness of our approach. Copyright (C) 2020 The Authors.
Flooding is among the simplest and most fundamental of all graph/network algorithms. Consider a (distributed network in the form of a) finite undirected graph G with a distinguished node v that begins flooding by send...
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ISBN:
(纸本)9783959771405
Flooding is among the simplest and most fundamental of all graph/network algorithms. Consider a (distributed network in the form of a) finite undirected graph G with a distinguished node v that begins flooding by sending copies of the same message to all its neighbours and the neighbours, in the next round, forward the message to all and only the neighbours they did not receive the message from in that round and so on. We assume that nodes do not keep a record of the flooding event, thus, raising the possibility that messages may circulate infinitely even on a finite graph. We call this history-less process amnesiac flooding (to distinguish from a classic distributed implementation of flooding that maintains a history of received messages to ensure a node never sends the same message again). Flooding will terminate when no node in G sends a message in a round, and, thus, subsequent rounds. As far as we know, the question of termination for amnesiac flooding has not been settled - rather, non-termination is implicitly assumed. In this paper, we show that surprisingly synchronous amnesiac flooding always terminates on any arbitrary finite graph and derive exact termination times which differ sharply in bipartite and non-bipartite graphs. In particular, synchronous flooding terminates in e rounds, where e is the eccentricity of the source node, if and only if G is bipartite, and, otherwise, in j rounds where e < j <= e+ d+ 1 and d is the diameter of G. Since e is bounded above by d, this implies termination times of at most d and of at most 2d + 1 for bipartite and non-bipartite graphs respectively. This suggests that if communication/broadcast to all nodes is the motivation, the history-less amnesiac flooding is asymptotically time optimal and obviates the need for construction and maintenance of spanning structures like spanning trees. Moreover, the clear separation in the termination times of bipartite and non-bipartite graphs may suggest possible mechanisms for dis
This article presents a randomized (Las Vegas) distributed algorithm that constructs a minimum spanning tree (MST) in weighted networks with optimal (up to polylogarithmic factors) time and message complexity. This al...
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This article presents a randomized (Las Vegas) distributed algorithm that constructs a minimum spanning tree (MST) in weighted networks with optimal (up to polylogarithmic factors) time and message complexity. This algorithm runs in (O) over tilde (D + root N) time and exchanges (O) over tilde (m) messages (both with high probability), where n is the number of nodes of the network, D is the hop-diameter, and m is the number of edges. This is the first distributed MST algorithm that matches simultaneously the time lower bound of (Omega) over tilde (D + root n)[10] and the message lower bound of Omega(m) [31], which both apply to randomized Monte Carlo algorithms. The prior time and message lower bounds are derived using two completely different graph constructions;the existing lower-bound construction that shows one lower bound does not work for the other. To complement our algorithm, we present a new lower-bound graph construction for which any distributed MST algorithm requires both (Omega) over tilde (D + root n) rounds and Omega(m) messages.
In this paper, we study the problem of finding the least square solutions of over-determined linear algebraic equations over networks in a distributed manner. Each node has access to one of the linear equations and ho...
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In this paper, we study the problem of finding the least square solutions of over-determined linear algebraic equations over networks in a distributed manner. Each node has access to one of the linear equations and holds a dynamic state. We first propose a distributed least square solver over connected undirected interaction graphs and establish a necessary and sufficient on the step-size under which the algorithm exponentially converges to the least square solution. Next, we develop a distributed least square solver over strongly connected directed graphs and show that the proposed algorithm exponentially converges to the least square solution provided the step-size is sufficiently small. Moreover, we develop a finite-time least square solver by equipping the proposed algorithms with a finite-time decentralized computation mechanism. The theoretical findings are validated and illustrated by numerical simulation examples. (C) 2019 Elsevier Ltd. All rights reserved.
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