IEEE Transactions on Network Science and Engineering

IEEE Transactions on Network Science and Engineering (TNSE) publishes peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. Read the full scope of TNSE.

From the October-December 2018 issue

Cascading Edge Failures: A Dynamic Network Process

By June Zhang and Jose M.F. Moura

Featured article

This paper studies a network process that can be used to model cascading failures in networks. The Dynamic Bond Percolation (DBP) process models, through stochastic local rules, the failure or recovery of an edge/link (i,j) n a network. The probability that a working link fails or a failed link recovers may be independent of the state of other links or may be dependent locally on the state of neighboring links as described by a cascade function f. In applications, this means that failures or recovery of links may have a regional preference, or, alternatively, relationships between neighbors in the network can lead to changes in the links between neighbors of neighbors. This paper shows that the dynamic evolution of P(A, t), the probability that the network is in some state A, describing the collective states of all the links at time t, converges to a stationary distribution. We use this distribution to study the emergence of global behaviors like consensus (i.e., catastrophic failure or full recovery of all the edges) or mixed (i.e., some failed and some working substructures). In particular, we show that, depending on the local dynamical rule, different network substructures, such as hub or triangle subgraphs, are more prone to failure.

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Editorials and Announcements

Announcements

TNSE is now accepting nominations for the Best Paper Award by 10 Dec. 2018. Learn more.
TNSE is pleased to participate in a free trial offering of the new IEEE DataPort data repository, which supports authors in hosting and referring to their datasets during the article submission process. Learn more about this exciting opportunity.
TNSE is now indexed in the Clarivate Analytics Emerging Sources Citation Index (ESCI), a new edition of the Web of Science.
We are pleased to announce that Dapeng Oliver Wu, a professor in the Department of Electrical & Computer Engineering at the University of Florida, has been named the new 2017-2018 EIC for the IEEE Transactions on Network Science and Engineering.

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Call for Papers

Special Issue on Edge computing for Internet of Things

Submission deadline: 1 Apr. 2019. View PDF.

The Internet of Things (IoT) are expected to improve the quality of human lives through billions of Internet-based devices. To satisfy the computation and storage requirements of IoT, cloud computing has served as the most important computing infrastructure. However, with the explosion of the number of devices in IoT (expected to reach 50 billion by 2020), a large volume of raw data will be continuously generated by IoT devices, consequently making cloud computing inadequate to efficiently and securely handle the data. In particular, cloud computing will be highly limited in terms of network bandwidth and privacy protection in IoT. To solve this problem, many researchers have attempted to move data computation and service provisioning from the cloud to the edge, which results in the area of edge computing and the related fog computing. Early-stage research has indicated that edge computing could potentially enable IoT applications to meet their latency/delay requirements, improve the scalability and energy efficiency of IoT systems, and facilitate contextual information processing. Nevertheless, a series of challenging problems need to be addressed in order to fully utilize edge computing for IoT. For instance, most of the computation resources in edge computing are heterogeneous mobile devices that are highly energy-hungry, which means that edge computing tends to be unreliable. Moreover, how to efficiently distribute computation/data storage and how to combine edge computing with cloud computing in order to provide scalable services need to be further studied. In addition, how to support services without compromising privacy and security is a challenging problem in edge computing. This special issue aims to provide a prime venue for researchers from both academia and industry to discuss the key problems and present the innovative solutions in the area of edge computing for IoT.