Latency-aware cost optimization of the service infrastructure placement in 5G networks

Abstract Under 5G use case scenarios latency is a main challenge that must be addressed, since mission critical environments are mostly delay sensitive. To achieve this goal, the service infrastructure placement optimization is needed in the interest of minimizing the delays in the service access layer. To solve this problem, this paper mathematically models the placement problem in a Fog Computing/NFV environment as a Mixed-Integer Linear Programming problem and proposes a heuristic-based solution considering 5G mobile network requirements. As a practical result, an application was developed to achieve usability and flexibility while ensuring operational applicability of the proposed methods.

[1]  Mohsen Guizani,et al.  Network function virtualization in 5G , 2016, IEEE Communications Magazine.

[2]  Antonio Brogi,et al.  QoS-Aware Deployment of IoT Applications Through the Fog , 2017, IEEE Internet of Things Journal.

[3]  Jin Qin,et al.  A Simulated Annealing Methodology to Multiproduct Capacitated Facility Location with Stochastic Demand , 2015, TheScientificWorldJournal.

[4]  Honggang Zhang,et al.  On the Spatial Distribution of Base Stations and Its Relation to the Traffic Density in Cellular Networks , 2015, IEEE Access.

[5]  Mark Goh,et al.  Covering problems in facility location: A review , 2012, Comput. Ind. Eng..

[6]  David L. Woodruff,et al.  Pyomo: modeling and solving mathematical programs in Python , 2011, Math. Program. Comput..

[7]  Tao Yu,et al.  Infrastructure Deployment and Optimization for Cloud-Radio Access Networks , 2015, WASA.

[8]  Jordi Pérez-Romero,et al.  Technology pillars in the architecture of future 5G mobile networks: NFV, MEC and SDN , 2017, Comput. Stand. Interfaces.

[9]  Ran Wolff,et al.  A Local Facility Location Algorithm for Sensor Networks , 2005, DCOSS.

[10]  Ju-Liang Zhang,et al.  Capacitated facility location problem with general setup cost , 2006, Comput. Oper. Res..

[11]  Shaowei Wang,et al.  Rethinking cellular network planning and optimization , 2016, IEEE Wireless Communications.

[12]  Soumya Kanti Datta,et al.  Comparison of edge computing implementations: Fog computing, cloudlet and mobile edge computing , 2017, 2017 Global Internet of Things Summit (GIoTS).

[13]  Wolfgang Kellerer,et al.  Towards a Cost Optimal Design for a 5G Mobile Core Network Based on SDN and NFV , 2017, IEEE Transactions on Network and Service Management.

[14]  Charles C. Byers,et al.  Architectural Imperatives for Fog Computing: Use Cases, Requirements, and Architectural Techniques for Fog-Enabled IoT Networks , 2017, IEEE Communications Magazine.

[15]  Hiroyuki Koga,et al.  Analysis of fog model considering computing and communication latency in 5G cellular networks , 2016, 2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops).

[16]  Xuemin Shen,et al.  5G Mobile Communications , 2016 .

[17]  Reza Zanjirani Farahani,et al.  Facility location dynamics: An overview of classifications and applications , 2012, Comput. Ind. Eng..

[18]  Maria Barbati Models and Algorithms for Facility Location Problems with Equity Considerations , 2013 .

[19]  Christian Artigues,et al.  Linearization of Euclidean norm dependent inequalities applied to multibeam satellites design , 2019, Comput. Optim. Appl..

[20]  Jin Qin,et al.  Combined Simulated Annealing Algorithm for the Discrete Facility Location Problem , 2012, TheScientificWorldJournal.

[21]  F. Silva,et al.  A capacitated facility location problem with constrained backlogging probabilities , 2007 .

[22]  Francesco Musumeci,et al.  Optimal BBU Placement for 5G C-RAN Deployment Over WDM Aggregation Networks , 2016, Journal of Lightwave Technology.

[23]  Jordi Torres,et al.  Intelligent Placement of Datacenters for Internet Services , 2011, 2011 31st International Conference on Distributed Computing Systems.

[24]  Erik Carlsson,et al.  Shadow Prices in Territory Division , 2016 .

[25]  T. R. Kumar The spatial distribution , 2000 .

[26]  Chonggang Wang,et al.  Budgeted Cell Planning for Cellular Networks With Small Cells , 2015, IEEE Transactions on Vehicular Technology.

[27]  Wenjun Zhang,et al.  Infrastructure deployment and optimization of fog network based on MicroDC and LRPON integration , 2017, Peer-to-Peer Netw. Appl..

[28]  Pablo Chacin,et al.  A New Era for Cities with Fog Computing , 2017, IEEE Internet Computing.

[29]  Feng Chu,et al.  The Capacitated Plant Location Problem with Customers and Suppliers Matching , 2010 .

[30]  Chien-Sheng Wu,et al.  Application of Simulated Annealing Algorithm to Optimization Deployment of Mobile Wireless Base Stations , 2012 .

[31]  Thrasyvoulos Spyropoulos,et al.  Impact of Packetization and Scheduling on C-RAN Fronthaul Performance , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).

[32]  Emmanouel A. Varvarigos,et al.  Efficient Gateways Placement for Internet of Things with QoS Constraints , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).

[33]  Z. Ulukan,et al.  A Survey of Discrete Facility Location Problems , 2015 .

[34]  Shubhranshu Singh,et al.  5G service requirements and operational use cases: Analysis and METIS II vision , 2016, 2016 European Conference on Networks and Communications (EuCNC).

[35]  Nasrin Asgari,et al.  Multiple criteria facility location problems: A survey , 2010 .

[36]  F. Glover,et al.  Handbook of Metaheuristics , 2019, International Series in Operations Research & Management Science.

[37]  Basheer M. Khumawala,et al.  An empirical comparison of tabu search, simulated annealing, and genetic algorithms for facilities location problems , 1997 .