A mathematical framework for measuring network flexibility

Abstract In the field of networking research, increased flexibility of new system architecture proposals, protocols, or algorithms is often stated to be a competitive advantage over its existing counterparts. However, this advantage is usually claimed only on an argumentative level and neither formally supported nor thoroughly investigated due to the lack of a unified flexibility framework. As we will show in this paper, the flexibility achieved by a system implementation can be measured, which consequently can be used to make different networking solutions quantitatively comparable with each other. The idea behind our mathematical model is to relate network flexibility to the achievable subset of the set of all possible demand changes, and to use measure theory to quantify it. As increased flexibility might come with additional system complexity and cost, our framework provides a cost model which measures how expensive it is to operate a flexible system. The introduced flexibility framework contains different normalization strategies to provide intuitive meaning to the network flexibility value as well, and also provides guidelines for generating demand changes with (non-)uniform demand utilities. Finally, our network flexibility framework is applied on two different use-cases, and the benefits of a quantitative flexibility analysis compared to pure intuitive arguments are demonstrated.

[1]  Saifallah Benjaafar,et al.  Modeling and Analysis of Flexibility in Manufacturing Systems , 1992 .

[2]  Lajos Rónyai,et al.  Diversity Coding in Two-Connected Networks , 2017, IEEE/ACM Transactions on Networking.

[3]  Wolfgang Kellerer,et al.  How to Measure Network Flexibility? A Proposal for Evaluating Softwarized Networks , 2018, IEEE Communications Magazine.

[4]  Oscar A. Saenz,et al.  Analysis of the structural measures of flexibility and agility using a measurement theoretical framework , 2003 .

[5]  Suresh P. Sethi,et al.  Flexibility in manufacturing: A survey , 1990 .

[6]  Tom Mens,et al.  Measuring software flexibility , 2006, IEE Proc. Softw..

[7]  Chen-Hua Chung,et al.  An examination of flexibility measurements and performance of flexible manufacturing systems , 1996 .

[8]  Terrence Tao,et al.  An Introduction To Measure Theory , 2011 .

[9]  Ross D. Shachter,et al.  A Measure of Decision Flexibility , 1996, UAI.

[10]  Saifallah Benjaafar,et al.  The strategic value of flexibility in sequential decision making , 1995 .

[11]  Philip Powell,et al.  Towards a definition of flexibility: in search of the Holy Grail? , 2000 .

[12]  A D Wissner-Gross,et al.  Causal entropic forces. , 2013, Physical review letters.

[13]  Sanchoy K. Das,et al.  The measurement of flexibility in manufacturing systems , 1996 .

[14]  Jean B. Lasserre,et al.  Measuring decision flexibility in production planning , 1985 .

[15]  Thanasis Korakis,et al.  Network Store: Exploring Slicing in Future 5G Networks , 2015, MobiArch.

[16]  Ankit Singla,et al.  Fat-FREE Topologies , 2016, HotNets.

[17]  Wolfgang Kellerer,et al.  Flexibility in Softwarized Networks: Classifications and Research Challenges , 2019, IEEE Communications Surveys & Tutorials.

[18]  Nick McKeown,et al.  OpenFlow: enabling innovation in campus networks , 2008, CCRV.

[19]  Wolfgang Kellerer,et al.  Toward a Flexible Design of SDN Dynamic Control Plane: An Online Optimization Approach , 2019, IEEE Transactions on Network and Service Management.

[20]  Walter Willinger,et al.  On unbiased sampling for unstructured peer-to-peer networks , 2009, TNET.

[21]  Seungjoon Lee,et al.  Network function virtualization: Challenges and opportunities for innovations , 2015, IEEE Communications Magazine.

[22]  Koushik Kar,et al.  Minimum interference routing of bandwidth guaranteed tunnels with MPLS traffic engineering applications , 2000, IEEE Journal on Selected Areas in Communications.

[23]  R. Nelson,et al.  FLEXIBILITY, UNCERTAINTY, AND ECONOMIC THEORY , 1962 .

[24]  Yuefeng Ji,et al.  Baseband unit cloud interconnection enabled by flexible grid optical networks with software defined elasticity , 2015, IEEE Communications Magazine.

[25]  John A. Buzacott,et al.  Flexibility and decision making , 1990 .

[26]  Gal Shahaf,et al.  Beyond fat-trees without antennae, mirrors, and disco-balls , 2017, SIGCOMM.

[27]  G. Andersson,et al.  On operational flexibility in power systems , 2012, 2012 IEEE Power and Energy Society General Meeting.

[28]  Percy H. Brill,et al.  On measures of flexibility in manufacturing systems , 1989 .