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IEEE Transactions on Signal and Information Processing over Networks

Issue 2 • June 2017

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Displaying Results 1 - 21 of 21
  • Table of Contents

    Publication Year: 2017, Page(s):C1 - C4
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  • IEEE Transactions on Signal and Information Processing over Networks publication information

    Publication Year: 2017, Page(s): C2
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  • Introduction to the Issue on Distributed Information Processing in Social Networks

    Publication Year: 2017, Page(s):219 - 221
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  • Social Learning Over Weakly Connected Graphs

    Publication Year: 2017, Page(s):222 - 238
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (874 KB) | HTML iconHTML

    In this paper, we study diffusion social learning over weakly connected graphs. We show that the asymmetric flow of information hinders the learning abilities of certain agents regardless of their local observations. Under some circumstances that we clarify in this paper, a scenario of total influence (or “mind-control”) arises where a set of influential agents ends up shaping the be... View full abstract»

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  • Information Cascades With Noise

    Publication Year: 2017, Page(s):239 - 251
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (769 KB) | HTML iconHTML

    Online networks enable agents to better observe the behavior of others and in doing so potentially learn from their actions. A key feature of models for such social learning is that information cascades can result, in which agents ignore their private information and blindly follow the actions of other agents. This paper considers the impact of noise in the form of observation errors in such a mod... View full abstract»

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  • Analyzing Resilience of Interest-Based Social Networks Against Node and Link Failures

    Publication Year: 2017, Page(s):252 - 267
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (858 KB) | HTML iconHTML

    In typical online social networks, users are linked by symmetric friend relations and can define circles of friends based on shared interests. In this paper, we look at social networks where users form links subject to both friendships and shared interests. Our goal is to understand resilience of these networks in terms of connectivity when both nodes and links are allowed to fail. We derive a zer... View full abstract»

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  • Data Trading With Multiple Owners, Collectors, and Users: An Iterative Auction Mechanism

    Publication Year: 2017, Page(s):268 - 281
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1108 KB) | HTML iconHTML

    In the big data era, it is vital to allocate the vast amount of data to heterogeneous users with different interests. To clinch this goal, various agents including data owners, collectors, and users should cooperate to trade data efficiently. However, the data agents (data owners, collectors, and users) are selfish and seek to maximize their own utilities instead of the overall system efficiency. ... View full abstract»

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  • Preserving Privacy Enables “Coexistence Equilibrium” of Competitive Diffusion in Social Networks

    Publication Year: 2017, Page(s):282 - 297
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1144 KB) | HTML iconHTML

    With the advent of social media, different companies often promote competing products simultaneously for word-of-mouth diffusion and adoption by users in social networks. For such scenarios of competitive diffusion, prior studies show that the weaker product will soon become extinct (i.e., “winner takes all”). It is intriguing to observe that in practice, however, competing products,... View full abstract»

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  • Tracking Infection Diffusion in Social Networks: Filtering Algorithms and Threshold Bounds

    Publication Year: 2017, Page(s):298 - 315
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1765 KB) | HTML iconHTML

    This paper deals with the statistical signal processing over graphs for tracking infection diffusion in social networks. Infection (or Information) diffusion is modeled using the susceptible-infected-susceptible (SIS) model. Mean field approximation is employed to approximate the discrete valued infection dynamics by a deterministic difference equation, thereby yielding a generative model for the ... View full abstract»

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  • Temporally Agnostic Rumor-Source Detection

    Publication Year: 2017, Page(s):316 - 329
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1600 KB) | HTML iconHTML

    We revisit the problem of inferring the source of a rumor on a network, given a snapshot of the extent of its spread. We differ from prior work in two aspects: We consider settings where additional relative information about the infection times of a fraction of node pairs is also available to the estimator and instead of only considering the most likely spreading pattern, we take a complementary a... View full abstract»

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  • Hidden Chinese Restaurant Game: Grand Information Extraction for Stochastic Network Learning

    Publication Year: 2017, Page(s):330 - 345
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (600 KB) | HTML iconHTML

    Agents in networks often encounter circumstances requiring them to make decisions. Nevertheless, the effectiveness of the decisions may be uncertain due to the unknown system state and the uncontrollable externality. The uncertainty can be eliminated through learning from information sources, such as user-generated contents or revealed actions. Nevertheless, the user-generated contents could be un... View full abstract»

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  • Detecting Changes in Dynamic Events Over Networks

    Publication Year: 2017, Page(s):346 - 359
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1276 KB) | HTML iconHTML Multimedia Media

    Large volumes of networked streaming event data are becoming increasingly available in a wide variety of applications such as social network analysis, Internet traffic monitoring, and health care analytics. Streaming event data are discrete observations occurring in continuous time, and the precise time interval between two events carries substantial information about the dynamics of the underlyin... View full abstract»

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  • Stochastic Multidimensional Scaling

    Publication Year: 2017, Page(s):360 - 375
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1241 KB) | HTML iconHTML

    Multidimensional scaling (MDS) is a popular dimensionality reduction technique that has been widely used for network visualization and cooperative localization. However, the traditional stress minimization formulation of MDS necessitates the use of batch optimization algorithms that are not scalable to large-sized problems. This paper considers an alternative stochastic stress minimization framewo... View full abstract»

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  • Posting Behavior Dynamics and Active Filtering for Content Diversity in Social Networks

    Publication Year: 2017, Page(s):376 - 387
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (497 KB) | HTML iconHTML

    In this paper, we have two objectives: First, we model the posting behavior of publishers in Social Networks which have externalities, and the second objective is to propose content active filtering in order to increase content diversity from different publishers. By externalities, we mean that when the quantity of posted contents from a specific publisher impacts the popularity of other posted co... View full abstract»

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  • Multireceiver Predicate Encryption for Online Social Networks

    Publication Year: 2017, Page(s):388 - 403
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1184 KB) | HTML iconHTML

    Among the applications of the internet and cloud computing, online social network (OSN) is a very popular service. Since a lot of personal information is stored on the OSN platform, privacy protection on such an application has become a critical issue. Apart from this, OSN platforms need advertisement revenue to enable continued operations. However, if the users encrypt their messages, then OSN pr... View full abstract»

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  • Compressed Sensing in Wireless Sensor Networks Without Explicit Position Information

    Publication Year: 2017, Page(s):404 - 415
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (621 KB) | HTML iconHTML

    Reconstruction in compressed sensing relies on knowledge of a sparsifying transform. In a setting where a sink reconstructs a field based on measurements from a wireless sensor network, this transform is tied to the locations of the individual sensors, which may not be available to the sink during reconstruction. In contrast to previous works, we do not assume that the sink knows the position of e... View full abstract»

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  • A Coalitional Game Theoretic Outlook on Distributed Adaptive Parameter Estimation

    Publication Year: 2017, Page(s):416 - 429
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (905 KB) | HTML iconHTML

    In this paper, the parameter estimation problem based on diffusion least-mean-squares strategies is analyzed from a coalitional game theoretical perspective. Specifically, while selfishly minimizing only their own mean-square costs, the nodes in a network form coalitions that benefit them. Due to its nature, the problem is modeled as a nontransferable game and two scenarios are studied, one where ... View full abstract»

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  • Consensus-Based Algorithms for Distributed Network-State Estimation and Localization

    Publication Year: 2017, Page(s):430 - 444
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    Recent advances of hardware design and radio technologies have opened the way for an emerging category of network-enabled smart physical devices as a result of convergence in computing and wireless communication capabilities. Inspired by biological interactions, distributed processing of data collected by individual devices is now becoming crucial to let the nodes self-learn relevant network-state... View full abstract»

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  • IEEE Transactions on Signal and Information Processing over Networks Edics

    Publication Year: 2017, Page(s): 445
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  • IEEE Transactions on Multimedia information for authors

    Publication Year: 2017, Page(s):446 - 447
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  • IEEE Transactions on Signal and Information Processing over Networks

    Publication Year: 2017, Page(s): C3
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Aims & Scope

The IEEE Transactions on Signal and Information Processing over Networks publishes high-quality papers that extend the classical notions of processing of signals defined over vector spaces (e.g. time and space) to processing of signals and information (data) defined over networks, potentially dynamically varying. In signal processing over networks, the topology of the network may define structural relationships in the data, or may constrain processing of the data. Topics include distributed algorithms for filtering, detection, estimation, adaptation and learning, model selection, data fusion, and diffusion or evolution of information over such networks, and applications of distributed signal processing.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Petar Djuric
Stony Brook University, Electrical & Computer Engineering
Light Engineering, Room 245
Stony Brook, NY
11794-2350
USA
+1 631-632-8423
Fax: +1 631-632-8494
petar.djuric@stonybrook.edu