Load balancing mechanisms in fog computing: A systematic review

Recently, fog computing has been introduced as a modern distributed paradigm and complement to cloud computing to provide services. Fog system extends storing and computing to the edge of the network, which can solve the problem about service computing of the delay-sensitive applications remarkably besides enabling the location awareness and mobility support. Load balancing is an important aspect of fog networks that avoids a situation with some under-loaded or overloaded fog nodes. Quality of Service (QoS) parameters such as resource utilization, throughput, cost, response time, performance, and energy consumption can be improved with load balancing. In recent years, some researches in load balancing techniques in fog networks have been carried out, but there is no systematic review to consolidate these studies. This article reviews the load-balancing mechanisms systematically in fog computing in four classifications, including approximate, exact, fundamental, and hybrid methods (published between 2013 and August 2020). Also, this article investigates load balancing metrics with all advantages and disadvantages related to chosen load balancing mechanisms in fog networks. The evaluation techniques and tools applied for each reviewed study are explored as well. Additionally, the essential open challenges and future trends of these mechanisms are discussed.

[1]  Gustavo Rau de Almeida Callou,et al.  An algorithm to optimise the load distribution of fog environments , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[2]  Gerhard J. Woeginger,et al.  Exact Algorithms for NP-Hard Problems: A Survey , 2001, Combinatorial Optimization.

[3]  Ganesh Neelakanta Iyer,et al.  Analytical Review and Study on Load Balancing in Edge Computing Platform , 2020, 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC).

[4]  Farzad Tashtarian,et al.  Load-Balancing Algorithm for Multiple Gateways in Fog-Based Internet of Things , 2020, IEEE Internet of Things Journal.

[5]  Rajkumar Buyya,et al.  A survey on load balancing algorithms for virtual machines placement in cloud computing , 2016, Concurr. Comput. Pract. Exp..

[6]  Roel Wieringa,et al.  Requirements engineering paper classification and evaluation criteria: a proposal and a discussion , 2005, Requirements Engineering.

[7]  Jason P. Jue,et al.  All One Needs to Know about Fog Computing and Related Edge Computing Paradigms , 2019 .

[8]  Rajkumar Buyya,et al.  Computational Intelligence Based QoS-Aware Web Service Composition: A Systematic Literature Review , 2017, IEEE Transactions on Services Computing.

[9]  Nadeem Javaid,et al.  Heuristic Min-conflicts Optimizing Technique for Load Balancing on Fog Computing , 2018, INCoS.

[10]  Amir Masoud Rahmani,et al.  Load-balancing algorithms in cloud computing: A survey , 2017, J. Netw. Comput. Appl..

[11]  Mehdi Hosseinzadeh,et al.  Load Balancing Mechanisms in the Software Defined Networks: A Systematic and Comprehensive Review of the Literature , 2018, IEEE Access.

[12]  Wanchun Dou,et al.  A Heuristic Virtual Machine Scheduling Method for Load Balancing in Fog-Cloud Computing , 2018, 2018 IEEE 4th International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing, (HPSC) and IEEE International Conference on Intelligent Data and Security (IDS).

[13]  Nadeem Javaid,et al.  Modified Shortest Job First for Load Balancing in Cloud-Fog Computing , 2018, BWCCA.

[14]  Jiafu Wan,et al.  Fog Computing for Energy-Aware Load Balancing and Scheduling in Smart Factory , 2018, IEEE Transactions on Industrial Informatics.

[15]  Harsh Kumar Singh,et al.  An efficient data replication and load balancing technique for fog computing environment , 2016, 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom).

[16]  Pearl Brereton,et al.  Lessons from applying the systematic literature review process within the software engineering domain , 2007, J. Syst. Softw..

[17]  Mostafa Haghi Kashani,et al.  Fog-based smart homes: A systematic review , 2020, J. Netw. Comput. Appl..

[18]  Fariborz Jolai,et al.  Lion Optimization Algorithm (LOA): A nature-inspired metaheuristic algorithm , 2016, J. Comput. Des. Eng..

[19]  Muhammad Ali Babar,et al.  Systematic reviews in software engineering: An empirical investigation , 2013, Inf. Softw. Technol..

[20]  James R. Larus,et al.  Join-Idle-Queue: A novel load balancing algorithm for dynamically scalable web services , 2011, Perform. Evaluation.

[21]  Giovanni Schembra,et al.  Battery Management in a Green Fog-Computing Node: a Reinforcement-Learning Approach , 2017, IEEE Access.

[22]  Di Chen,et al.  Adaptive Radio Unit Selection and Load Balancing in the Downlink of Fog Radio Access Network , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).

[23]  Caro Lucas,et al.  Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition , 2007, 2007 IEEE Congress on Evolutionary Computation.

[24]  Choong Seon Hong,et al.  Fog Load Balancing for Massive Machine Type Communications: A Game and Transport Theoretic Approach , 2019, IEEE Access.

[25]  Ganapati Panda,et al.  A survey on nature inspired metaheuristic algorithms for partitional clustering , 2014, Swarm Evol. Comput..

[26]  H. T. Mouftah,et al.  Queuing Model for EVs Energy Management: Load Balancing Algorithms Based on Decentralized Fog Architecture , 2018, 2018 IEEE International Conference on Communications (ICC).

[27]  Barbara Kitchenham,et al.  Procedures for Performing Systematic Reviews , 2004 .

[28]  John Thompson,et al.  Computational Load Balancing on the Edge in Absence of Cloud and Fog , 2019, IEEE Transactions on Mobile Computing.

[29]  Zhiyuan Ren,et al.  Research on Load Balancing for Software Defined Cloud-Fog Network in Real-Time Mobile Face Recognition , 2016, ChinaCom.

[30]  Niranjan Kumar Ray,et al.  A Review of Load Balancing in Fog Computing , 2019, 2019 International Conference on Information Technology (ICIT).

[31]  Sudip Misra,et al.  Theoretical modelling of fog computing: a green computing paradigm to support IoT applications , 2016, IET Networks.

[32]  Mohsen Jahanshahi,et al.  Using Simulated Annealing for Task Scheduling in Distributed Systems , 2009, 2009 International Conference on Computational Intelligence, Modelling and Simulation.

[33]  Raheleh Sarvizadeh,et al.  A swarm intelligence based memetic algorithm for task allocation in distributed systems , 2012, International Conference on Machine Vision.

[34]  Raul Muñoz,et al.  SDN/NFV orchestration of multi-technology and multi-domain networks in cloud/fog architectures for 5g services , 2016, 2016 21st OptoElectronics and Communications Conference (OECC) held jointly with 2016 International Conference on Photonics in Switching (PS).

[35]  Nadeem Javaid,et al.  State Based Load Balancing Algorithm for Smart Grid Energy Management in Fog Computing , 2018, INCoS.

[36]  Xuehai Zhou,et al.  SSLB: Self-Similarity-Based Load Balancing for Large-Scale Fog Computing , 2018 .

[37]  Li Peng,et al.  A secure-efficient data collection algorithm based on self-adaptive sensing model in mobile Internet of vehicles , 2016 .

[38]  Amir Masoud Rahmani,et al.  Internet of Things applications: A systematic review , 2019, Comput. Networks.

[39]  Xavier Masip-Bruin,et al.  Do we all really know what a fog node is? Current trends towards an open definition , 2017, Comput. Commun..

[40]  Sergio Barbarossa,et al.  The Fog Balancing: Load Distribution for Small Cell Cloud Computing , 2015, 2015 IEEE 81st Vehicular Technology Conference (VTC Spring).

[41]  Anju Sharma,et al.  Design and exploration of load balancers for fog computing using fuzzy logic , 2020, Simul. Model. Pract. Theory.

[42]  Albert Y. Zomaya,et al.  Secure and Sustainable Load Balancing of Edge Data Centers in Fog Computing , 2018, IEEE Communications Magazine.

[43]  Alfio Lombardo,et al.  An SDN/NFV Platform for Personal Cloud Services , 2017, IEEE Transactions on Network and Service Management.

[44]  Deep Medhi,et al.  A Novel Strategy to Achieve Bandwidth Cost Reduction and Load Balancing in a Cooperative Three-Layer Fog-Cloud Computing Environment , 2020, IEEE Access.

[45]  Hesham A. Ali,et al.  Effective Load Balancing Strategy (ELBS) for Real-Time Fog Computing Environment Using Fuzzy and Probabilistic Neural Networks , 2019, Journal of Network and Systems Management.

[46]  Mahdi Jameii,et al.  A new distributed systems scheduling algorithm: a swarm intelligence approach , 2011, Other Conferences.

[47]  Tie Qiu,et al.  Survey on fog computing: architecture, key technologies, applications and open issues , 2017, J. Netw. Comput. Appl..

[48]  Houman Zarrabi,et al.  A new metaheuristic approach to task assignment problem in distributed systems , 2017, 2017 IEEE 4th International Conference on Knowledge-Based Engineering and Innovation (KBEI).

[49]  M. H. Kashani,et al.  A New Method Based on Memetic Algorithm for Task Scheduling in Distributed Systems , 2010 .

[50]  Nima Jafari Navimipour,et al.  Quality of service‐aware approaches in fog computing , 2020, Int. J. Commun. Syst..

[51]  Roch H. Glitho,et al.  A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges , 2017, IEEE Communications Surveys & Tutorials.

[52]  Eiji Kamioka,et al.  CFC-ITS: Context-Aware Fog Computing for Intelligent Transportation Systems , 2018, IT Professional.

[53]  Hong Wang,et al.  Bacterial Colony Optimization , 2012 .

[54]  Raja Lavanya,et al.  Fog Computing and Its Role in the Internet of Things , 2019, Advances in Computer and Electrical Engineering.

[55]  Debasish Ghose,et al.  Glowworm swarm optimisation: a new method for optimising multi-modal functions , 2009, Int. J. Comput. Intell. Stud..

[56]  Nirwan Ansari,et al.  Towards Workload Balancing in Fog Computing Empowered IoT , 2020, IEEE Transactions on Network Science and Engineering.

[57]  Pearl Brereton,et al.  Systematic literature reviews in software engineering - A systematic literature review , 2009, Inf. Softw. Technol..

[58]  Zhiyuan Ren,et al.  A novel load balancing strategy of software-defined cloud/fog networking in the Internet of Vehicles , 2016, China Communications.

[59]  Ebrahim Mahdipour,et al.  Big data analytics meets social media: A systematic review of techniques, open issues, and future directions , 2020, Telematics and Informatics.

[60]  Eero Silfverberg.  Fog computing based interoperability in IoT systems , 2018 .

[61]  Lei Guo,et al.  Transmission and Latency-Aware Load Balancing for Fog Radio Access Networks , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[62]  Nadeem Javaid,et al.  Priority Based Load Balancing in Cloud and Fog Based Systems , 2018, BWCCA.

[63]  Jonathan Timmis,et al.  Artificial Immune Systems: A New Computational Intelligence Approach , 2003 .

[64]  Hesham A. Ali,et al.  A load balancing and optimization strategy (LBOS) using reinforcement learning in fog computing environment , 2020, Journal of Ambient Intelligence and Humanized Computing.

[65]  Munam Ali Shah,et al.  Load balancing algorithms in cloud computing: A survey of modern techniques , 2015, 2015 National Software Engineering Conference (NSEC).

[66]  Xin-She Yang,et al.  Firefly algorithm, stochastic test functions and design optimisation , 2010, Int. J. Bio Inspired Comput..

[67]  Nadeem Javaid,et al.  Metaheuristic Optimization Technique for Load Balancing in Cloud-Fog Environment Integrated with Smart Grid , 2018, NBiS.

[68]  Claus Pahl,et al.  Cloud Migration Research: A Systematic Review , 2013, IEEE Transactions on Cloud Computing.

[69]  Jiong Jin,et al.  Context-Aware Privacy Preservation in a Hierarchical Fog Computing System , 2019, ICC 2019 - 2019 IEEE International Conference on Communications (ICC).

[70]  Zhan Qiang,et al.  Fog computing dynamic load balancing mechanism based on graph repartitioning , 2016, China Communications.

[71]  Arthur H. M. ter Hofstede,et al.  What's in a service? Towards accurate description of non-functional service properties , 2002 .

[72]  Nadeem Javaid,et al.  Hill Climbing Load Balancing Algorithm on Fog Computing , 2018, 3PGCIC.

[73]  Nadeem Javaid,et al.  Fog-Cloud Based Platform for Utilization of Resources Using Load Balancing Technique , 2018, NBiS.

[74]  Stephen P. Crago,et al.  Load Balancing for Minimizing Deadline Misses and Total Runtime for Connected Car Systems in Fog Computing , 2017, 2017 IEEE International Symposium on Parallel and Distributed Processing with Applications and 2017 IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC).

[75]  Nadeem Javaid,et al.  Load Stabilizing in Fog Computing Environment Using Load Balancing Algorithm , 2018, BWCCA.

[76]  Leïla Merghem,et al.  Efficient green solution for a balanced energy consumption and delay in the IoT-Fog-Cloud computing , 2017, 2017 IEEE 16th International Symposium on Network Computing and Applications (NCA).

[77]  Nima Jafari Navimipour,et al.  Load balancing mechanisms and techniques in the cloud environments: Systematic literature review and future trends , 2016, J. Netw. Comput. Appl..

[78]  Roberto Beraldi,et al.  Sequential Randomization load balancing for Fog Computing , 2018, 2018 26th International Conference on Software, Telecommunications and Computer Networks (SoftCOM).

[79]  Mianxiong Dong,et al.  FCSS: Fog-Computing-based Content-Aware Filtering for Security Services in Information-Centric Social Networks , 2019, IEEE Transactions on Emerging Topics in Computing.

[80]  Joongheon Kim,et al.  Adaptive Resource Balancing for Serviceability Maximization in Fog Radio Access Networks , 2017, IEEE Access.

[81]  D. Baburao,et al.  Survey on Service Migration, load optimization and Load Balancing in Fog Computing Environment , 2019, 2019 IEEE 5th International Conference for Convergence in Technology (I2CT).

[82]  Hyunseung Choo,et al.  An SDN-enhanced load-balancing technique in the cloud system , 2018, The Journal of Supercomputing.

[83]  Jin Yang,et al.  Low-latency cloud-fog network architecture and its load balancing strategy for medical big data , 2020 .

[84]  Xin-She Yang.  Harmony Search as a Metaheuristic Algorithm , 2009 .

[85]  Zhu Zeng,et al.  Fourth International Conference on Machine Vision (ICMV 2011) Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies , 2017 .

[86]  Nima Jafari Navimipour,et al.  Comprehensive and systematic review of the service composition mechanisms in the cloud environments , 2017, J. Netw. Comput. Appl..

[87]  WuCai Lin,et al.  The Load Balancing Research of SDN based on Ant Colony Algorithm with Job Classification , 2016 .

[88]  Nadeem Javaid,et al.  Integration of Cloud-Fog Based Platform for Load Balancing Using Hybrid Genetic Algorithm Using Bin Packing Technique , 2018, 3PGCIC.

[89]  Gustavo B. Figueiredo,et al.  Load Balancing in the Fog of Things Platforms Through Software-Defined Networking , 2018, 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData).

[90]  Andrew Lewis,et al.  Grey Wolf Optimizer , 2014, Adv. Eng. Softw..

[91]  P. Dhavachelvan,et al.  Appraisal and analysis on various web service composition approaches based on QoS factors , 2014, J. King Saud Univ. Comput. Inf. Sci..

[92]  Akramul Azim,et al.  Improving the Schedulability of Real-Time Tasks Using Fog Computing , 2019, IEEE Transactions on Services Computing.

[93]  Bruno Tardiole Kuehne,et al.  A Fog Model for Dynamic Load Flow Analysis in Smart Grids , 2018, 2018 IEEE Symposium on Computers and Communications (ISCC).