Optimized IoT service placement in the fog

Aazam M, Huh EN (2015) Dynamic resource provisioning through fog micro datacenter. In: 12th IEEE international workshop on managing ubiquitous communications and services. St. Louis, Missouri, USA, pp 105–110

Armbrust M, Fox A, Griffith R, Joseph AD, Katz R, Konwinski A, Lee G, Patterson D, Rabkin A, Stoica I, Zaharia M (2010) A view of cloud computing. Commun ACM 53:50–58

Atzori L, Iera A, Morabito G (2010) The internet of things: a survey. Comput Netw 54:2787–2805

Bonomi F, Milito R, Natarajan P, Zhu J (2014) Fog computing: a platform for internet of things and analytics. In: Big data and internet of things: a roadmap for smart environments. Studies in computational intelligence 546: 169–186. Springer

Botta A, de Donato W, Persico V, Pescape A (2016) Integration of cloud computing and internet of things: a survey. Fut Gener Comput Syst 56:684–700

Brent RP (1989) Efficient implementation of the first-fit strategy for dynamic storage allocation. ACM Trans Prog Lang Syst 11(3):388–403

Cardellini V, Grassi V, Lo Presti F, Nardelli M (2016) Optimal operator placement for distributed stream processing applications. In: 10th ACM international conference on distributed and event-based Systems (DEBS’16), pp 69–80. ACM, Irvine, California, USA

Chen M, Mao S, Liu Y (2014) Big data: a survey. Mobile Netw Appl 19(2):171–209

Dabek F, Cox R, Kaashoek F, Morris R (2004) Vivaldi: a decentralized network coordinate system. ACM SIGCOMM Comput Commun Rev 13(4):15–26

Dastjerdi AV, Gupta H, Calheiros RN, Ghosh SK, Buyya R (2016) Fog computing: principles, architectures, and applications. In: Internet of things: principles and paradigms, chap. 4, Morgan Kaufmann

De S, Barnaghi P, Bauer M, Meissner S (2011) Service modelling for the internet of things. In: Federated conference on computer science and information systems, 2011. IEEE, Szczecin, Poland, pp 949–955

Dinh HT, Lee C, Niyato D, Wang P (2013) A survey of mobile cloud computing: architecture, applications, and approaches. Wirel Commun Mob Comput 13:1587–1611

Elmroth E, Leitner P, Schulte S, Venugopal S (2017) Connecting fog and cloud computing. IEEE Cloud Comput 4(2):22–25

Fernando N, Loke SW, Rahayu W (2013) Mobile cloud computing: a survey. Fut Gener Comput Syst 29:84–106

Georgakopoulos D, Jayaraman PP, Fazia M, Villari M, Ranjan R (2016) Internet of things and edge cloud computing roadmap for manufacturing. IEEE Cloud Comput 3(4):66–73

Giang NK, Blackstock M, Lea R, Leung VC (2015) Developing IoT Applications in the fog: a distributed dataflow approach. In: 5th International conference on the internet of things (IoT). IEEE, Seoul, Korea. pp 155–162

Gupta H, Dastjerdi AV, Ghosh SK, Buyya R (2017) iFogSim: a toolkit for modeling and simulation of resource management techniques in the internet of things, edge and fog computing environments. Softw Pract Exp 47:1275–1296

Han B, Gopalakrishnan V, Ji L, Lee S (2015) Network function virtualization: challenges and opportunities for innovations. IEEE Commun Mag 53(2):90–97

Hochreiner C, Vögler M, Waibel P, Dustdar S (2016) VISP: an ecosystem for elastic data stream processing for the internet of things. In: IEEE 20th International enterprise distributed object computing conference (EDOC), 2016. IEEE, pp 1–11

Hong K, Lillethun D, Ramachandran U, Ottenwlder B, Koldehofe B (2013) Mobile fog: a programming model for largescale applications on the internet of things. In: 1st ACM SIGCOMM workshop on mobile cloud computing. Hong Kong, China, pp 15–20

Huang X, Ganapathy S, Wolf T (2009) Evaluating algorithms for composable service placement in computer networks. In: IEEE International conference on communications. IEEE, Dresden, Germany. pp 2276–2281

Kubler S, Holmström J, Främling K, Turkama P (2016) Technological theory of cloud manufacturing. Stud Comput Intell 640:267–276 Springer

Leitner P, Hummer W, Satzger B, Inzinger C, Dustdar S (2012) Cost-efficient and application SLA-aware client side request scheduling in an infrastructure-as-a-service cloud. In: 5th International Conference on Cloud Computing. IEEE, Honolulu, HI, USA, pp 213–220

Papageorgiou A, Cheng B, Kovacs E (2015) Real-time data reduction at the network edge of internet-of-things systems. In: 11th International Conference on Network and Service Management. Barcelona, Spain, pp 284–291

Qu T, Lei SP, Wang ZZ, Nie DX, Chen X, Huang GQ (2016) IoT-based real-time production logistics synchronization system under smart cloud manufacturing. Int J Adv Manuf Technol 84(1):147–164

Rohjans S, Dnekas C, Uslar M (2012) Requirements for Smart Grid ICT-architectures. In: 3rd IEEE PES international conference and exhibition on innovative smart grid technologies. Berlin, Germany, pp 1–8

Schulte S, Hoenisch P, Hochreiner C, Dustdar S, Klusch M, Schuller D (2014) Towards process support for cloud manufacturing. In: 18th IEEE International enterprise distributed object computing conference. IEEE, Ulm, Germany, pp 142–149

Skarlat O, Borkowski M, Schulte S (2016) Towards a methodology and instrumentation toolset for cloud manufacturing. In: 1st International workshop on cyber-physical production systems, CPS week 2016. IEEE, Vienna, Austria, pp 1–4

Skarlat O, Nardelli M, Schulte S, Dustdar S (2017) Towards QoS-aware fog service placement. In: 1st IEEE international conference on fog and edge computing (ICFEC), 2017. IEEE, Madrid, Spain, pp 89–96

Skarlat O, Schulte S, Borkowski M, Leitner P (2016) Resource provisioning for IoT services in the fog. In: 9th IEEE international conference on service oriented computing and applications (SOCA), 2016. IEEE, Hong Kong, China, pp 32–39

Vaquero LM, Rodero-Merino L (2014) Finding your way in the fog: towards a comprehensive definition of fog computing. ACM SIGCOMM Comput Commun Rev 44(5):27–32

Vögler M, Schleicher J, Inzinger C, Dustdar S (2016) Optimizing elastic IoT application deployments. Trans Serv Comput PP:1–14

Whitley D (1994) A genetic algorithm tutorial. Stat Comput 4:65–85

Wu D, Greer MJ, Rose DW, Schaefer D (2013) Cloud manufacturing: strategic vision and state-of-the-art. J Manuf Syst 32:564–579

Xu M, Tian W, Buyya R (2017) A survey on load balancing algorithms for virtual machines placement in cloud computing. Concurr Comput e4123:1–16

Xu X (2012) From cloud computing to cloud manufacturing. Robot Comput Integr Manuf 28(1):75–86

Ye Z, Zhou X, Bouguettaya A (2011) Genetic algorithm based QoS-aware service compositions in cloud computing. In: 16th International conference on database systems for advanced applications (DASFAA) part II. Springer, Berlin, Heidelberg, Hong Kong, China, pp 321–334

Yoo M (2009) Real-time task scheduling by multiobjective genetic algorithm. J Syst Softw 82(4):619–628

Yu J, Buyya R, Ramamohanarao K (2009) Workflow scheduling algorithms for grid computing. Stud Comput Intell 146:173–214

Zhan ZH, Liu XF, Gong YJ, Zhang J, Chung HSH, Li Y (2015) Cloud computing resource scheduling and a survey of its evolutionary approaches. ACM Comput Surv 47(4):63