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Wolfgang Segmuller

dblp:24/4042 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none

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

Computer networks · 2Systems, architecture and hardware · 1

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 architecture, parallel and distributed computing, and storage systems
2 papers
Cloud and datacenter computing · 42% Parallel and multicore computing · 26% High-performance computing · 26%
Computer networks
1 paper
Internet architecture and protocols · 100%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Parallel and multicore computing
load balancing
0.222012
Design, Implementation, and Performance of a Load Balancer for SIP Server Clusters · IEEE/ACM Trans. Netw. 2012
Load Balancing for SIP Server Clusters · INFOCOM 2009
Cloud and datacenter computing › datacenter services › online service systems
request routing
0.222012
Design, Implementation, and Performance of a Load Balancer for SIP Server Clusters · IEEE/ACM Trans. Netw. 2012
Load Balancing for SIP Server Clusters · INFOCOM 2009
High-performance computing › cluster computing
server cluster
0.222012
Design, Implementation, and Performance of a Load Balancer for SIP Server Clusters · IEEE/ACM Trans. Netw. 2012
Load Balancing for SIP Server Clusters · INFOCOM 2009
Cloud and datacenter computing › cluster resource management and scheduling
cluster resource management
0.112012
Design, Implementation, and Performance of a Load Balancer for SIP Server Clusters · IEEE/ACM Trans. Netw. 2012
Internet architecture and protocols › signaling protocol
SIP
0.012009
Load Balancing for SIP Server Clusters · INFOCOM 2009

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

simulation · 0.2performance evaluation · 0.1load balancing algorithm · 0.1
YearPublicationVenuePosition
2012 Design, Implementation, and Performance of a Load Balancer for SIP Server Clusters
abstract
This paper introduces several novel load-balancing algorithms for distributing Session Initiation Protocol (SIP) requests to a cluster of SIP servers. Our load balancer improves both throughput and response time versus a single node while exposing a single interface to external clients. We present the design, implementation, and evaluation of our system using a cluster of Intel x86 machines running Linux. We compare our algorithms to several well-known approaches and present scalability results for up to 10 nodes. Our best algorithm, Transaction Least-Work-Left (TLWL), achieves its performance by integrating several features: knowledge of the SIP protocol, dynamic estimates of back-end server load, distinguishing transactions from calls, recognizing variability in call length, and exploiting differences in processing costs for different SIP transactions. By combining these features, our algorithm provides finer-grained load balancing than standard approaches, resulting in throughput improvements of up to 24% and response-time improvements of up to two orders of magnitude. We present a detailed analysis of occupancy to show how our algorithms significantly reduce response time.
Hongbo Jiang 0001, Arun Iyengar, Erich M. Nahum, Wolfgang Segmuller, Asser N. Tantawi, Charles P. Wright
IEEE/ACM Trans. Netw.4
2009 Load Balancing for SIP Server Clusters
abstract
This paper introduces several novel load balancing algorithms for distributing session initiation protocol (SIP) requests to a cluster of SIP servers. Our load balancer improves both throughput and response time versus a single node, while exposing a single interface to external clients. We present the design, implementation and evaluation of our system using a cluster of Intel x86 machines running Linux. We compare our algorithms with several well-known approaches and present scalability results for up to 10 nodes. Our best algorithm, transaction least-work-left (TLWL), achieves its performance by integrating several features: knowledge of the SIP protocol; dynamic estimates of back-end server load; distinguishing transactions from calls; recognizing variability in call length; and exploiting differences in processing costs for different SIP transactions. By combining these features, our algorithm provides finer-grained load balancing than standard approaches, resulting in throughput improvements of up to 24 percent and response time improvements of up to two orders of magnitude. We present a detailed analysis of occupancy to show how our algorithms significantly reduce response time.
Hongbo Jiang 0001, Arun Iyengar, Erich M. Nahum, Wolfgang Segmuller, Asser N. Tantawi, Charles P. Wright
INFOCOM4
2008 CPU demand for web serving: Measurement analysis and dynamic estimation
Giovanni Pacifici, Wolfgang Segmuller, Mike Spreitzer, Asser N. Tantawi
Perform. Evaluation2