An efficient placement of sinks and SDN controller nodes for optimizing the design cost of industrial IoT systems

Recently, a growing trend has emerged toward using Internet of Things (IoT) in the context of industrial systems, which is referred to as industrial IoT. To deal with the time‐critical requirements of industrial applications, it is necessary to consider reliability and timeliness during the design of an industrial IoT system. Through the separation of the control plane and the data plane, software‐defined networking provides control units (controllers) coexisting with sink nodes, efficiently coping with network dynamics during run‐time. It is of paramount importance to select a proper number of these devices (i.e., software‐defined networking controllers and sink nodes) and locate them wisely in a network to reduce deployment cost. In this paper, we optimize the type and location of sinks and controllers in the network, subject to reliability and timeliness as the prominent performance requirements in time‐critical IoT systems through ensuring that each sensor node is covered by a certain number of sinks and controllers. We propose PACSA‐MSCP, an algorithm hybridizing a parallel version of the max‐min ant system with simulated annealing for multiple‐sink/controller placement. We evaluate the proposed algorithm through extensive experiments. The performance is compared against several well‐known methods, and it is shown that our approach outperforms those methods by lowering the total deployment cost by up to 19%. Moreover, the deviation from the optimal solution achieved by CPLEX is shown to be less than 2.7%.

[1]  Gunjan Tank,et al.  Software-Defined Networking-The New Norm for Networks , 2012 .

[2]  Bang Wang,et al.  Coverage problems in sensor networks: A survey , 2011, CSUR.

[3]  Xuxun Liu,et al.  A Deployment Strategy for Multiple Types of Requirements in Wireless Sensor Networks , 2015, IEEE Transactions on Cybernetics.

[4]  Rolland Vida,et al.  Deploying Multiple Sinks in Multi-hop Wireless Sensor Networks , 2007, IEEE International Conference on Pervasive Services.

[5]  Xiangjian He,et al.  A Sybil attack detection scheme for a forest wildfire monitoring application , 2018, Future Gener. Comput. Syst..

[6]  Wint Yi Poe,et al.  Placing Multiple Sinks in Time-Sensitive Wireless Sensor Networks using a Genetic Algorithm , 2008, MMB.

[7]  Kate Ching-Ju Lin,et al.  Joint sink deployment and association for multi-sink wireless camera networks , 2016, Wirel. Commun. Mob. Comput..

[8]  Rob Sherwood,et al.  The controller placement problem , 2012, HotSDN '12.

[9]  Hong He,et al.  Task allocation for maximizing reliability of distributed computing systems using honeybee mating optimization , 2010, J. Syst. Softw..

[10]  Jiannong Cao,et al.  Deploying Wireless Sensor Networks with Fault Tolerance for Structural Health Monitoring , 2012, 2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems.

[11]  Thomas Nolte,et al.  A time-predictable fog-integrated cloud framework: One step forward in the deployment of a smart factory , 2018, 2018 Real-Time and Embedded Systems and Technologies (RTEST).

[12]  Prasanta K. Jana,et al.  PSO-Based Multiple-sink Placement Algorithm for Protracting the Lifetime of Wireless Sensor Networks , 2016 .

[13]  Chao Chen,et al.  Energy-aware scheduling of virtual machines in heterogeneous cloud computing systems , 2017, Future Gener. Comput. Syst..

[14]  Wassim El-Hajj,et al.  A robust topology control solution for the sink placement problem in WSNs , 2014, J. Netw. Comput. Appl..

[15]  Michel Gendreau,et al.  Handbook of Metaheuristics , 2010 .

[16]  Ciprian Dobre,et al.  Big Data and Internet of Things: A Roadmap for Smart Environments , 2014, Big Data and Internet of Things.

[17]  Arunabha Sen,et al.  Relay node placement in large scale wireless sensor networks , 2006, Comput. Commun..

[18]  Peng-Yeng Yin,et al.  Task allocation for maximizing reliability of a distributed system using hybrid particle swarm optimization , 2007, J. Syst. Softw..

[19]  Dina S. Deif,et al.  Classification of Wireless Sensor Networks Deployment Techniques , 2014, IEEE Communications Surveys & Tutorials.

[20]  Bingo Wing-Kuen Ling,et al.  Maximizing lifetime of a wireless sensor network via joint optimizing sink placement and sensor-to-sink routing , 2017 .

[21]  Thierry Turletti,et al.  A Survey of Software-Defined Networking: Past, Present, and Future of Programmable Networks , 2014, IEEE Communications Surveys & Tutorials.

[22]  Hwee Pink Tan,et al.  Sensor OpenFlow: Enabling Software-Defined Wireless Sensor Networks , 2012, IEEE Communications Letters.

[23]  El-Ghazali Talbi,et al.  Metaheuristics - From Design to Implementation , 2009 .

[24]  Mohamed Faten Zhani,et al.  Dynamic Controller Provisioning in Software Defined Networks , 2013, Proceedings of the 9th International Conference on Network and Service Management (CNSM 2013).

[25]  Hao Sun,et al.  Optimal sensor placement in structural health monitoring using discrete optimization , 2015 .

[26]  Donghyun Kim,et al.  Minimum Data-Latency-Bound $k$-Sink Placement Problem in Wireless Sensor Networks , 2011, IEEE/ACM Transactions on Networking.

[27]  Mohamed F. Younis,et al.  Strategies and techniques for node placement in wireless sensor networks: A survey , 2008, Ad Hoc Networks.

[28]  Kenneth N. Brown,et al.  Multiple Sink and Relay Placement in Wireless Sensor Networks , 2012 .

[29]  Jiang Zhu,et al.  Fog Computing: A Platform for Internet of Things and Analytics , 2014, Big Data and Internet of Things.

[30]  Jiajun Zhu,et al.  On the Deployment of a Connected Sensor Network for Confident Information Coverage , 2015, Sensors.

[31]  Kenneth N. Brown,et al.  Planning the deployment of multiple sinks and relays in wireless sensor networks , 2015, J. Heuristics.

[32]  Ivan Stojmenovic,et al.  The Fog computing paradigm: Scenarios and security issues , 2014, 2014 Federated Conference on Computer Science and Information Systems.

[33]  Sartaj Sahni,et al.  Approximation Algorithms for Sensor Deployment , 2007, IEEE Transactions on Computers.

[34]  I. K. Altinel,et al.  Binary integer programming formulation and heuristics for differentiated coverage in heterogeneous sensor networks , 2008, Comput. Networks.

[35]  Yon Dohn Chung,et al.  Parallel data processing with MapReduce: a survey , 2012, SGMD.

[36]  Parag C. Pendharkar An ant colony optimization heuristic for constrained task allocation problem , 2015, J. Comput. Sci..

[37]  Thomas Nolte,et al.  A Cost Efficient Design of a Multi-sink Multi-controller WSN in a Smart Factory , 2017, 2017 IEEE 19th International Conference on High Performance Computing and Communications; IEEE 15th International Conference on Smart City; IEEE 3rd International Conference on Data Science and Systems (HPCC/SmartCity/DSS).

[38]  Horacio Hideki Yanasse,et al.  Search intensity versus search diversity: a false trade off? , 2010, Applied Intelligence.

[39]  Hamid Reza Faragardi,et al.  Optimizing Timing-Critical Cloud Resources in a Smart Factory , 2018 .

[40]  C.D. Vournas,et al.  Unit Commitment by an Enhanced Simulated Annealing Algorithm , 2006, 2006 IEEE PES Power Systems Conference and Exposition.

[41]  Wassim El-Hajj,et al.  Particle Swarm Optimization based approach to solve the multiple sink placement problem in WSNs , 2012, 2012 IEEE International Conference on Communications (ICC).

[42]  Leila Ben Saad,et al.  Towards an Optimal Positioning of Multiple Mobile Sinks in WSNs for Buildings , 2009 .

[43]  Sanjay Ghemawat,et al.  MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.

[44]  Nasser Yazdani,et al.  Reliability-Aware Task Allocation in Distributed Computing Systems using Hybrid Simulated Annealing and Tabu Search , 2012, 2012 IEEE 14th International Conference on High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems.

[45]  Ning Zhong,et al.  Efficient point coverage in wireless sensor networks , 2006, J. Comb. Optim..

[46]  Mirza Mansoor Baig,et al.  Smart Health Monitoring Systems: An Overview of Design and Modeling , 2013, Journal of Medical Systems.

[47]  S. Sitharama Iyengar,et al.  Grid Coverage for Surveillance and Target Location in Distributed Sensor Networks , 2002, IEEE Trans. Computers.

[48]  Chih-Yung Chang,et al.  Energy-aware node placement, topology control and MAC scheduling for wireless sensor networks , 2008, Comput. Networks.

[49]  Yu Gu,et al.  Towards an Optimal Sink Placement in Wireless Sensor Networks , 2010, 2010 IEEE International Conference on Communications.

[50]  Thomas Nolte,et al.  A resource efficient framework to run automotive embedded software on multi-core ECUs , 2018, J. Syst. Softw..

[51]  Thomas Nolte,et al.  Towards Energy-Aware Placement of Real-Time Virtual Machines in a Cloud Data Center , 2015, 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security, and 2015 IEEE 12th International Conference on Embedded Software and Systems.

[52]  Francisco J. Ros,et al.  Synchronisation cost of multi-controller deployments in software-defined networks , 2016, Int. J. High Perform. Comput. Netw..

[53]  Thomas Stützle,et al.  MAX-MIN Ant System , 2000, Future Gener. Comput. Syst..

[54]  Mats Björkman,et al.  Communication and Security in Health Monitoring Systems -- A Review , 2016, 2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC).

[55]  Joseph S. B. Mitchell,et al.  Approximation algorithms for two optimal location problems in sensor networks , 2005, 2nd International Conference on Broadband Networks, 2005..

[56]  Phuoc Tran-Gia,et al.  POCO-framework for Pareto-optimal resilient controller placement in SDN-based core networks , 2014, 2014 IEEE Network Operations and Management Symposium (NOMS).