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Emily M. Craparo

dblp:92/7142 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2011
—ORCID · unresolved

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

Computer networks · 1 · 1 first-author

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
Wireless networking · 46% Network optimization and economics · 23% Cellular and mobile networks · 23%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wireless networking › mobile ad hoc networks
mobile backbone networks
0.112011
Throughput Optimization in Mobile Backbone Networks · IEEE Trans. Mob. Comput. 2011
Cellular and mobile networks › radio resource management
node association
0.112011
Throughput Optimization in Mobile Backbone Networks · IEEE Trans. Mob. Comput. 2011
Network optimization and economics
resource allocation
0.112011
Throughput Optimization in Mobile Backbone Networks · IEEE Trans. Mob. Comput. 2011
Wireless networking › wireless network optimization
throughput optimization
0.112011
Throughput Optimization in Mobile Backbone Networks · IEEE Trans. Mob. Comput. 2011

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

mixed integer linear programming · 0.1approximation algorithm · 0.1
YearPublicationVenuePosition
2011 Throughput Optimization in Mobile Backbone Networks
abstract
This paper describes new algorithms for throughput optimization in a mobile backbone network. This hierarchical communication framework combines mobile backbone nodes, which have superior mobility and communication capability, with regular nodes, which are constrained in mobility and communication capability. An important quantity of interest in mobile backbone networks is the number of regular nodes that can be successfully assigned to mobile backbone nodes at a given throughput level. This paper develops a novel technique for maximizing this quantity in networks of fixed regular nodes using mixed-integer linear programming (MILP). The MILP-based algorithm provides a significant reduction in computation time compared to existing methods and is computationally tractable for problems of moderate size. An approximation algorithm is also developed that is appropriate for large-scale problems. This paper presents a theoretical performance guarantee for the approximation algorithm and also demonstrates its empirical performance. Finally, the mobile backbone network problem is extended to include mobile regular nodes, and exact and approximate solution algorithms are presented for this extension.
Emily M. Craparo, Jonathan P. How, Eytan H. Modiano
IEEE Trans. Mob. Comput.1