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Shuai-Zong Si

dblp:147/0491 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Internet of things and sensor networks · 100%
Theoretical computer science
1 paper
Graph algorithms and graph theory · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks
energy efficiency
0.212016
Toward Energy-Efficient and Robust Large-Scale WSNs: A Scale-Free Network Approach · IEEE J. Sel. Areas Commun. 2016
Internet of things and sensor networks
wireless sensor network
0.212016
Toward Energy-Efficient and Robust Large-Scale WSNs: A Scale-Free Network Approach · IEEE J. Sel. Areas Commun. 2016
Graph algorithms and graph theory › network analysis › complex networks
scale-free networks
0.112016
Toward Energy-Efficient and Robust Large-Scale WSNs: A Scale-Free Network Approach · IEEE J. Sel. Areas Commun. 2016

Methods — techniques the papers use, named apart from their topics

self-organizing schemes · 0.5common neighbor scheme · 0.5
YearPublicationVenuePosition
2016 Toward Energy-Efficient and Robust Large-Scale WSNs: A Scale-Free Network Approach
abstract
Due to the limited battery power of sensor nodes and harsh deployment environment, it is of fundamental importance and a great challenge to achieve high energy efficiency and strong robustness in large-scale wireless sensor networks (LS-WSNs). To this end, we propose two self-organizing schemes for LS-WSNs. The first scheme is the energy-aware common neighbor scheme, which considers the neighborhood overlap in link establishment. The second scheme is energy-aware low potential-degree common neighbor (ELDCN) scheme, which considers both neighborhood overlap in topology formation and the potential degrees of common neighbors. Both schemes generate clustering-based and scale-free-inspired LS-WSNs, which are energy-efficient and robust. However, the ELDCN scheme shows higher energy efficiency and stronger robustness to node failures, because it avoids establishing links to hub-nodes with high potential connectivity. Analytical and simulation results demonstrate that our proposed schemes outperform the existing scale-free evolution models in terms of energy efficiency and robustness.
Haixia Peng, Shuai-Zong Si, Mohamad Khattar Awad, Ning Zhang 0007, Hai Zhao 0002, Xuemin Shen
IEEE J. Sel. Areas Commun.2
2015 Energy-Efficient and Fault-Tolerant Evolution Models for Large-Scale Wireless Sensor Networks: A Complex Networks-Based Approach
abstract
In this paper, we present three network evolution models for generating fault-tolerant and energy- efficient large-scale peer-to-peer wireless sensor networks (WSNs) based on complex networks theory. Being scale-free is one of the intrinsic features of complex networks-based evolution models that generates fault- tolerant topologies. In this work, we argue that fault- tolerant topologies are not necessarily energy efficient. The three proposed energy-aware evolution models are energy-aware common neighbors (ECN), energy- aware large degree promoted (ELDP) and energy-aware large degree demoted (ELDD). ECN considers neighborhood overlap, whereas ELDP and ELDD consider topological overlap for node attachment. The ELDP model promotes the establishment of links to nodes with a large degree, whereas the ELDD model demotes this strategy. Performance evaluations demonstrate that the proposed models outperform a candidate clustering-based model, thereby providing greater energy savings and fault- tolerance. Among the proposed models, ECN is the winner in-terms of energy efficiency, ELDD performs best in- terms of fault-tolerance, and ELDP conveniently provides balance between the two.
Haixia Peng, Shuai-Zong Si, Mohamad Khattar Awad, Nan Cheng 0001, Xuemin Shen, Hai Zhao 0002
GLOBECOM2