NDLI: Analyzing the Performance of Greedy Maximal Scheduling via Local Pooling and Graph Theory

Content Provider	IEEE Xplore Digital Library
Author	Birand, B. Chudnovsky, M. Ries, B. Seymour, P. Zussman, G. Zwols, Y.
Copyright Year	1993
Abstract	Efficient operation of wireless networks and switches requires using simple (and in some cases distributed) scheduling algorithms. In general, simple greedy algorithms (known as Greedy Maximal Scheduling, or GMS) are guaranteed to achieve only a fraction of the maximum possible throughput (e.g., 50% throughput in switches). However, it was recently shown that in networks in which the Local Pooling conditions are satisfied, GMS achieves 100% throughput. Moreover, in networks in which the σ-Local Pooling conditions hold, GMS achieves σ% throughput. In this paper, we focus on identifying the specific network topologies that satisfy these conditions. In particular, we provide the first characterization of all the network graphs in which Local Pooling holds under primary interference constraints (in these networks, GMS achieves 100% throughput). This leads to a linear-time algorithm for identifying Local-Pooling-satisfying graphs. Moreover, by using similar graph-theoretical methods, we show that in all bipartite graphs (i.e., input-queued switches) of size up to 7 × n, GMS is guaranteed to achieve 66% throughput, thereby improving upon the previously known 50% lower bound. Finally, we study the performance of GMS in interference graphs and show that in certain specific topologies, its performance could be very bad. Overall, the paper demonstrates that using graph-theoretical techniques can significantly contribute to our understanding of greedy scheduling algorithms.
Sponsorship	IEEE Computer Society IEEE Communications Society Association for Computing Machinery (ACM)
Starting Page	163
Ending Page	176
Page Count	14
File Size	4516841
File Format	PDF
ISSN	10636692
Volume Number	20
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-02-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Throughput Interference constraints Bipartite graph Scheduling Scheduling algorithm Stability analysis wireless networks Graph theory Local Pooling (LoP) scheduling switches throughput maximization
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Electrical and Electronic Engineering Computer Science Applications Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Analyzing the performance of greedy maximal scheduling via local pooling and graph theory

Analyzing the Performance of Greedy Maximal Scheduling via Local Pooling and Graph Theory

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