Network Utility Maximization Under Maximum Delay Constraints and Throughput Requirements

We consider a multi-path routing problem of maximizing the aggregate user utility over a multi-hop network, subject to link capacity constraints, maximum end-to-end delay constraints, and user throughput requirements. A user's utility is a concave function of the achieved throughput or the expe...

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Veröffentlicht in:	IEEE/ACM transactions on networking Jg. 28; H. 5; S. 2132 - 2145
Hauptverfasser:	Liu, Qingyu, Zeng, Haibo, Chen, Minghua
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.10.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Aggregates Algorithms Approximation algorithms Data centers Delay delay-aware multi-path routing Delay-sensitive multiple-unicast network flow Delays Maximization Multimedia Network management systems network utility maximization Optimization Polynomials Routing Throughput Unicast Utilities Utility theory Videoconferencing
ISSN:	1063-6692, 1558-2566
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Abstract	We consider a multi-path routing problem of maximizing the aggregate user utility over a multi-hop network, subject to link capacity constraints, maximum end-to-end delay constraints, and user throughput requirements. A user's utility is a concave function of the achieved throughput or the experienced maximum delay. The problem is important for supporting real-time multimedia traffic and is uniquely challenging due to the need of simultaneously considering maximum delay constraints and throughput requirements. In this paper, we first show that it is NP-complete either (i) to construct a feasible solution strictly meeting all constraints, or (ii) to obtain an optimal solution after relaxing either the maximum delay constraints or the throughput requirements. We then develop a polynomial-time approximation algorithm named PASS . The design of PASS leverages a novel understanding between non-convex maximum-delay-aware problems and their convex average-delay-aware counterparts, which can be of independent interest and suggests a new avenue for solving maximum-delay-aware network optimization problems. We prove that PASS always obtains approximate solutions (i.e., with theoretical performance guarantees), at the cost of violating both the maximum delay constraints and the throughput requirements by up to constant ratios. We also develop two variants of PASS , named PASS-M and PASS-T , to generate approximate solutions at the cost of violating either the maximum delay constraints or the throughput requirements by up to problem-dependent ratios. We evaluate our solutions using extensive simulations on Amazon EC2 datacenters supporting video-conferencing traffic. Compared to the existing algorithms and a conceivable baseline, our solutions obtain up to 100% improvement of utilities, by meeting the throughput requirements but relaxing the maximum delay constraints to the extent acceptable for practical video conferencing applications.
AbstractList	We consider a multi-path routing problem of maximizing the aggregate user utility over a multi-hop network, subject to link capacity constraints, maximum end-to-end delay constraints, and user throughput requirements. A user's utility is a concave function of the achieved throughput or the experienced maximum delay. The problem is important for supporting real-time multimedia traffic and is uniquely challenging due to the need of simultaneously considering maximum delay constraints and throughput requirements. In this paper, we first show that it is NP-complete either (i) to construct a feasible solution strictly meeting all constraints, or (ii) to obtain an optimal solution after relaxing either the maximum delay constraints or the throughput requirements. We then develop a polynomial-time approximation algorithm named PASS . The design of PASS leverages a novel understanding between non-convex maximum-delay-aware problems and their convex average-delay-aware counterparts, which can be of independent interest and suggests a new avenue for solving maximum-delay-aware network optimization problems. We prove that PASS always obtains approximate solutions (i.e., with theoretical performance guarantees), at the cost of violating both the maximum delay constraints and the throughput requirements by up to constant ratios. We also develop two variants of PASS , named PASS-M and PASS-T , to generate approximate solutions at the cost of violating either the maximum delay constraints or the throughput requirements by up to problem-dependent ratios. We evaluate our solutions using extensive simulations on Amazon EC2 datacenters supporting video-conferencing traffic. Compared to the existing algorithms and a conceivable baseline, our solutions obtain up to 100% improvement of utilities, by meeting the throughput requirements but relaxing the maximum delay constraints to the extent acceptable for practical video conferencing applications.
Author	Liu, Qingyu Zeng, Haibo Chen, Minghua
Author_xml	– sequence: 1 givenname: Qingyu orcidid: 0000-0003-1487-7682 surname: Liu fullname: Liu, Qingyu email: qyliu14@vt.edu organization: Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, USA – sequence: 2 givenname: Haibo orcidid: 0000-0003-1162-759X surname: Zeng fullname: Zeng, Haibo email: hbzeng@vt.edu organization: Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, USA – sequence: 3 givenname: Minghua orcidid: 0000-0003-4763-0037 surname: Chen fullname: Chen, Minghua email: minghua.chen@cityu.edu.hk organization: School of Data Science, City University of Hong Kong, Hong Kong
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References	ref13 ref35 ref12 ref15 ref37 ref14 ref31 ref11 ref33 ref10 ref2 ref1 Grtschel (ref36) 2012 ref16 ref38 (ref18) 2017 Weinstein (ref34) 2008 ref24 ref23 ref26 ref25 ref20 ref21 ref28 ref27 (ref19) 2003 ref29 ref8 ref7 ref9 ref4 (ref17) 2017 ref3 ref6 ref5 (ref22) 2017 Singh (ref30) 2017 (ref32) 2017
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SubjectTerms	Aggregates Algorithms Approximation algorithms Data centers Delay delay-aware multi-path routing Delay-sensitive multiple-unicast network flow Delays Maximization Multimedia Network management systems network utility maximization Optimization Polynomials Routing Throughput Unicast Utilities Utility theory Videoconferencing
Title	Network Utility Maximization Under Maximum Delay Constraints and Throughput Requirements
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