When Sensor-Cloud Meets Mobile Edge Computing

Sensor-clouds are a combination of wireless sensor networks (WSNs) and cloud computing. The emergence of sensor-clouds has greatly enhanced the computing power and storage capacity of traditional WSNs via exploiting the advantages of cloud computing in resource utilization. However, there are still many problems to be solved in sensor-clouds, such as the limitations of WSNs in terms of communication and energy, the high latency, and the security and privacy issues due to applying a cloud platform as the data processing and control center. In recent years, mobile edge computing has received increasing attention from industry and academia. The core of mobile edge computing is to migrate some or all of the computing tasks of the original cloud computing center to the vicinity of the data source, which gives mobile edge computing great potential in solving the shortcomings of sensor-clouds. In this paper, the latest research status of sensor-clouds is briefly analyzed and the characteristics of the existing sensor-clouds are summarized. After that we discuss the issues of sensor-clouds and propose some applications, especially a trust evaluation mechanism and trustworthy data collection which use mobile edge computing to solve the problems in sensor-clouds. Finally, we discuss research challenges and future research directions in leveraging mobile edge computing for sensor-clouds.

[1]  Xiangxiang Zeng,et al.  MOEA/HD: A Multiobjective Evolutionary Algorithm Based on Hierarchical Decomposition , 2019, IEEE Transactions on Cybernetics.

[2]  Li Liu,et al.  Fast participant recruitment algorithm for large-scale Vehicle-based Mobile Crowd Sensing , 2017, Pervasive Mob. Comput..

[3]  Anfeng Liu,et al.  Bidirectional Prediction-Based Underwater Data Collection Protocol for End-Edge-Cloud Orchestrated System , 2020, IEEE Transactions on Industrial Informatics.

[4]  Ke Gu,et al.  A cost-efficient framework for finding prospective customers based on reverse skyline queries , 2018, Knowl. Based Syst..

[5]  Gaogang Xie,et al.  Low Cost and High Accuracy Data Gathering in WSNs with Matrix Completion , 2018, IEEE Transactions on Mobile Computing.

[6]  Song Guo,et al.  Secure Multimedia Big Data in Trust-Assisted Sensor-Cloud for Smart City , 2017, IEEE Communications Magazine.

[7]  Xi Wang,et al.  FOGPLAN: A Lightweight QoS-Aware Dynamic Fog Service Provisioning Framework , 2019, IEEE Internet of Things Journal.

[8]  Sudip Misra,et al.  QoS-aware sensor allocation for target tracking in sensor-cloud , 2015, Ad Hoc Networks.

[9]  Md Zakirul Alam Bhuiyan,et al.  Preserving Balance Between Privacy and Data Integrity in Edge-Assisted Internet of Things , 2020, IEEE Internet of Things Journal.

[10]  M. Shamim Hossain,et al.  A Survey on Sensor-Cloud: Architecture, Applications, and Approaches , 2013, Int. J. Distributed Sens. Networks.

[11]  Shiming He,et al.  An efficient privacy-preserving compressive data gathering scheme in WSNs , 2015, Inf. Sci..

[12]  Kaoru Ota,et al.  Adaptive data and verified message disjoint security routing for gathering big data in energy harvesting networks , 2020, J. Parallel Distributed Comput..

[13]  Arun Kumar Sangaiah,et al.  Energy-Efficient and Trustworthy Data Collection Protocol Based on Mobile Fog Computing in Internet of Things , 2020, IEEE Transactions on Industrial Informatics.

[14]  Xi Zheng,et al.  Crowdsourcing Mechanism for Trust Evaluation in CPCS Based on Intelligent Mobile Edge Computing , 2019, ACM Trans. Intell. Syst. Technol..

[15]  Mohammad Hossein Anisi,et al.  Data Collection in Smart Communities Using Sensor Cloud: Recent Advances, Taxonomy, and Future Research Directions , 2018, IEEE Communications Magazine.

[16]  G. Yen,et al.  A Consensus Community-Based Particle Swarm Optimization for Dynamic Community Detection , 2020, IEEE Transactions on Cybernetics.

[17]  Yang Li,et al.  A Comprehensive Trustworthy Data Collection Approach in Sensor-Cloud Systems , 2022, IEEE Transactions on Big Data.

[18]  Wenbing Wu,et al.  An Asynchronous Clustering and Mobile Data Gathering Schema Based on Timer Mechanism in Wireless Sensor Networks , 2019 .

[19]  Tong Liu,et al.  Online task dispatching and pricing for quality-of-service-aware sensing data collection for mobile edge clouds , 2018, CCF Trans. Netw..

[20]  Li-Hong Huang,et al.  A novel adaptive data hiding based on improved EMD and interpolation , 2017, Multimedia Tools and Applications.

[21]  Jingjing Yao,et al.  QoS-Aware Fog Resource Provisioning and Mobile Device Power Control in IoT Networks , 2019, IEEE Transactions on Network and Service Management.

[22]  Jinjun Chen,et al.  Weighted principal component analysis-based service selection method for multimedia services in cloud , 2014, Computing.

[23]  Weijia Jia,et al.  A novel trust mechanism based on Fog Computing in Sensor-Cloud System , 2020, Future Gener. Comput. Syst..

[24]  Ming Zhao,et al.  Adjusting forwarder nodes and duty cycle using packet aggregation routing for body sensor networks , 2020, Inf. Fusion.

[25]  Peng Liu,et al.  A Novel Linguistic Steganography Based on Synonym Run-Length Encoding , 2017, IEICE Trans. Inf. Syst..

[26]  Md Zakirul Alam Bhuiyan,et al.  Fog-Based Computing and Storage Offloading for Data Synchronization in IoT , 2019, IEEE Internet of Things Journal.

[27]  Shiming He,et al.  Interference-Aware Multisource Transmission in Multiradio and Multichannel Wireless Network , 2019, IEEE Systems Journal.

[28]  Anfeng Liu,et al.  A Survey of Fog Computing in Wireless Sensor Networks: Concepts, Frameworks, Applications and Issues , 2019, Ad Hoc Sens. Wirel. Networks.

[29]  Anfeng Liu,et al.  Pipeline slot based fast rerouting scheme for delay optimization in duty cycle based M2M communications , 2019, Peer-to-Peer Networking and Applications.

[30]  Guangjie Han,et al.  A Trust Cloud Model for Underwater Wireless Sensor Networks , 2017, IEEE Communications Magazine.

[31]  Wei Hao,et al.  Reversible Natural Language Watermarking Using Synonym Substitution and Arithmetic Coding , 2018 .

[32]  Shiming He,et al.  PPNC: Privacy Preserving Scheme for Random Linear Network Coding in Smart Grid , 2017, KSII Trans. Internet Inf. Syst..

[33]  Xuyun Zhang,et al.  A QoS-aware virtual machine scheduling method for energy conservation in cloud-based cyber-physical systems , 2019, World Wide Web.

[34]  Jianhua Liu,et al.  A dynamic multiple-keys game-based industrial wireless sensor-cloud authentication scheme , 2018, The Journal of Supercomputing.

[35]  Tong Wang,et al.  A novel WSN key pre-distribution scheme based on group-deployment , 2014, Int. J. Sens. Networks.

[36]  Jiannong Cao,et al.  Recover Corrupted Data in Sensor Networks: A Matrix Completion Solution , 2017, IEEE Transactions on Mobile Computing.

[37]  Xiangxiang Zeng,et al.  An Evolutionary Algorithm Based on Minkowski Distance for Many-Objective Optimization , 2019, IEEE Transactions on Cybernetics.

[38]  Yue Wang,et al.  An incentive-based protection and recovery strategy for secure big data in social networks , 2020, Inf. Sci..

[39]  Gang Liu,et al.  Energy Efficient Resource Allocation Algorithm in Energy Harvesting-Based D2D Heterogeneous Networks , 2019, IEEE Internet of Things Journal.

[40]  Hui Tian,et al.  Data collection from WSNs to the cloud based on mobile Fog elements , 2017, Future Gener. Comput. Syst..

[41]  Jie Gao,et al.  Partial Offloading Scheduling and Power Allocation for Mobile Edge Computing Systems , 2019, IEEE Internet of Things Journal.

[42]  Jiguo Yu,et al.  Privacy-Preserving and Scalable Service Recommendation Based on SimHash in a Distributed Cloud Environment , 2017, Complex..

[43]  Yang Xu,et al.  A Blockchain-Based Nonrepudiation Network Computing Service Scheme for Industrial IoT , 2019, IEEE Transactions on Industrial Informatics.

[44]  Guojun Wang,et al.  Detection of hidden data attacks combined fog computing and trust evaluation method in sensor‐cloud system , 2018, Concurr. Comput. Pract. Exp..

[45]  Jianhua Liu,et al.  Energy-Efficient Two-Layer Cooperative Defense Scheme to Secure Sensor-Clouds , 2018, IEEE Transactions on Information Forensics and Security.

[46]  Weijia Jia,et al.  Coupling resource management based on fog computing in smart city systems , 2019, J. Netw. Comput. Appl..

[47]  Anfeng Liu,et al.  Quick Convex Hull-Based Rendezvous Planning for Delay-Harsh Mobile Data Gathering in Disjoint Sensor Networks , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[48]  Xuyun Zhang,et al.  An Exception Handling Approach for Privacy-Preserving Service Recommendation Failure in a Cloud Environment , 2018, Sensors.

[49]  Anfeng Liu,et al.  UAVs joint vehicles as data mules for fast codes dissemination for edge networking in Smart City , 2019, Peer-to-Peer Networking and Applications.

[50]  Arun Kumar Sangaiah,et al.  Big Data Cleaning Based on Mobile Edge Computing in Industrial Sensor-Cloud , 2020, IEEE Transactions on Industrial Informatics.

[51]  Xuyun Zhang,et al.  A Distributed Locality-Sensitive Hashing-Based Approach for Cloud Service Recommendation From Multi-Source Data , 2017, IEEE Journal on Selected Areas in Communications.

[52]  Narendra Singh Raghuwanshi,et al.  DVSP: Dynamic Virtual Sensor Provisioning in Sensor–Cloud-Based Internet of Things , 2019, IEEE Internet of Things Journal.

[53]  Haiyan Liu,et al.  An improved linear kernel for complementary maximal strip recovery: Simpler and smaller , 2019, Theor. Comput. Sci..

[54]  Cheng Zhang,et al.  Blockchain Empowered Arbitrable Data Auditing Scheme for Network Storage as a Service , 2020, IEEE Transactions on Services Computing.

[55]  Anfeng Liu,et al.  A Unified Trustworthy Environment Establishment Based on Edge Computing in Industrial IoT , 2020, IEEE Transactions on Industrial Informatics.

[56]  Abdul Hanan Abdullah,et al.  A Secure Trust Model Based on Fuzzy Logic in Vehicular Ad Hoc Networks With Fog Computing , 2017, IEEE Access.

[57]  Nicola Marchetti,et al.  Virtual MIMO Wireless Sensor Networks: Propagation Measurements and Fusion Performance , 2019, IEEE Transactions on Antennas and Propagation.

[58]  Tie Qiu,et al.  Security and Privacy Preservation Scheme of Face Identification and Resolution Framework Using Fog Computing in Internet of Things , 2017, IEEE Internet of Things Journal.

[59]  Hao Luo,et al.  MTES: An Intelligent Trust Evaluation Scheme in Sensor-Cloud-Enabled Industrial Internet of Things , 2020, IEEE Transactions on Industrial Informatics.

[60]  Ying Cui,et al.  A novel protocol of energy-constrained sensor network for emergency monitoring , 2014, Int. J. Sens. Networks.

[61]  Sukanya C.M Integration of Wireless Sensor Networks and Mobile Cloud- a Survey , 2014 .

[62]  Weijia Jia,et al.  Identity-Based Multi-Proxy Signature Scheme in the Standard Model , 2017, Fundam. Informaticae.

[63]  Jing Zhang,et al.  An Efficient Message-Authentication Scheme Based on Edge Computing for Vehicular Ad Hoc Networks , 2019, IEEE Transactions on Intelligent Transportation Systems.

[64]  György Dán,et al.  Decentralized Algorithm for Randomized Task Allocation in Fog Computing Systems , 2019, IEEE/ACM Transactions on Networking.

[65]  Xiangrong Liu,et al.  On solutions and representations of spiking neural P systems with rules on synapses , 2019, Inf. Sci..

[66]  Victor C. M. Leung,et al.  Social Sensor Cloud: Framework, Greenness, Issues, and Outlook , 2018, IEEE Network.

[67]  Wanlei Zhou,et al.  E-AUA: An Efficient Anonymous User Authentication Protocol for Mobile IoT , 2019, IEEE Internet of Things Journal.

[68]  Mohammad S. Obaidat,et al.  On Theoretical Modeling of Sensor Cloud: A Paradigm Shift From Wireless Sensor Network , 2017, IEEE Systems Journal.

[69]  Anfeng Liu,et al.  Fog-based storage technology to fight with cyber threat , 2018, Future Gener. Comput. Syst..

[70]  Jian Shen,et al.  Lightweight authentication and matrix-based key agreement scheme for healthcare in fog computing , 2018, Peer-to-Peer Netw. Appl..

[71]  Sinan Q. Salih,et al.  TrustData: Trustworthy and Secured Data Collection for Event Detection in Industrial Cyber-Physical System , 2020, IEEE Transactions on Industrial Informatics.

[72]  Qiang He,et al.  Time-aware distributed service recommendation with privacy-preservation , 2019, Inf. Sci..

[73]  Xiangliang Zhang,et al.  An up-to-date comparison of state-of-the-art classification algorithms , 2017, Expert Syst. Appl..

[74]  Anfeng Liu,et al.  A risk defense method based on microscopic state prediction with partial information observations in social networks , 2019, J. Parallel Distributed Comput..

[75]  Guojun Wang,et al.  Edge-based differential privacy computing for sensor-cloud systems , 2020, J. Parallel Distributed Comput..

[76]  Hai Jin,et al.  Lightweight Searchable Public-Key Encryption for Cloud-Assisted Wireless Sensor Networks , 2018, IEEE Transactions on Industrial Informatics.

[77]  Victor C. M. Leung,et al.  Multi-Method Data Delivery for Green Sensor-Cloud , 2017, IEEE Communications Magazine.

[78]  Jinjun Chen,et al.  A two-stage locality-sensitive hashing based approach for privacy-preserving mobile service recommendation in cross-platform edge environment , 2018, Future Gener. Comput. Syst..

[79]  Huiyong Wang,et al.  Privacy-Preserving Cloud-Based Road Condition Monitoring With Source Authentication in VANETs , 2019, IEEE Transactions on Information Forensics and Security.

[80]  Lianyong Qi,et al.  Privacy-Aware Multidimensional Mobile Service Quality Prediction and Recommendation in Distributed Fog Environment , 2018, Wirel. Commun. Mob. Comput..

[81]  Xiaoli Chu,et al.  Computation Offloading and Resource Allocation in Mixed Fog/Cloud Computing Systems With Min-Max Fairness Guarantee , 2018, IEEE Transactions on Communications.

[82]  Md Zakirul Alam Bhuiyan,et al.  A Secure IoT Service Architecture With an Efficient Balance Dynamics Based on Cloud and Edge Computing , 2019, IEEE Internet of Things Journal.

[83]  Yuansheng Luo,et al.  A Decision Function Based Smart Charging and Discharging Strategy for Electric Vehicle in Smart Grid , 2018, Mobile Networks and Applications.