Advances　in　Edge　&　Fog　Computing　Research　and　Application　边缘计算和雾计算研究与应用

PART Ⅰ: Resource Management in Edge & Fog Computing

　　1  Steiner
Tree based Optimal Resource Caching Scheme in Fog Computing······················ 1

      
1.1  Introduction································································································· 1

      
1.2  Related work································································································ 3

       1.3 
Problem formulation······················································································ 4

      
1.4  Algorithm design··························································································· 5

      
1.5  Running illustration······················································································· 6

      
1.6  Numerical simulation····················································································· 8

      
1.7  Conclusion··································································································· 9

      
References········································································································ 10

　　2  Hypergraph
Based Radio Resource Management in 5G Fog Cell································ 12

      
2.1  Introduction······························································································· 12

      
2.2  Related work······························································································ 14

      
2.3  Network architecture of fog
computing in 5G···················································· 14

      
2.4  Radio resource management of
hypergraph partitioning in 5G Fog Cell················· 17

      
2.4.1  Task model······························································································ 17

      
2.4.2  Hypergraph model of 5G Fog
Cell resource pool············································· 18

      
2.4.3  Hypergraph cluster and
resource allocation···················································· 19

      
2.5  Numerical simulation··················································································· 21

      
2.6  Conclusion································································································· 22

      
References········································································································ 23

　　………

　　　　18.1 
Introduction························································································· 274

　　　　18.2 
Background materials············································································ 275

　　　　18.2.1  Fruit
fly optimization algorithm (FOA)···················································· 275

　　　　18.2.2 
Support vector machine (SVM)····························································· 278

　　　　18.3  The
proposed methodology····································································· 279

　　　　18.3.1 
Process of image restoration processing··················································· 279

　　　　18.3.2 
Optimization algorithm of TFOA based on LSSVR···································· 280

　　　　18.4 
Experiment and application···································································· 281

　　　　18.4.1 
Parameter optimization analysis of TFOA··············································· 281

　　　　18.4.2  Image
restoration analysis of LSSVM- TFOA··········································· 292

　　　　18.5 
Conclusion··························································································· 294

　　　　References···································································································· 295

In the big
data era, enormous amount of data is produced, which cannot be absolutely
processed by the cloud computing. Edge & Fog Computing paradigm is proposed
to deal with the data at network edge, which brings lots of advantages
comparing with cloud computing, e. g., serving time delay saving, core bandwidth
consumption saving, mobility supporting.

The main goal
of this book is sharing the recent achievements of Edge & Fog Computing in
our lab. It contains three parts. In the first part, we focus on the resource
management in Edge & Fog Computing including Resource Caching Scheme in Fog
Computing, Radio Resource Management in 5G
Fog Cell, Transmission of Malware in Fog Computing, Incentive to Contribute
Resource-based Crowd funding in Fog Computing, Resource Scheduling Scheme in
Fog Computing, Resource sharing Model in Fog Computing, and Fair Resource
Allocation in IDS for Edge Computing. In the second part, we introduce the
security management in Edge & Fog Computing including Security Model in Fog
Computing, Node State Monitoring Scheme in Fog Computing, IDS Model in Fog
Computing, Key Management Scheme in Fog Computing, Intrusion Response Strategy
in Fog Computing, Intrusion Detection in Fog Computing, and Security Mechanism
in Fog Computing. In the third part, we propose some applications of Edge &
Fog Computing. They are Real-time Fast Bi-dimensional Empirical Mode
Decomposition, Resource Management Scheme in Vehicular Social Edge Computing,
and Real-time Image Restoration in Edge Computing.

We wish that
this book can shed some light on the investigation of Edge & Fog Computing
theory.

Fuhong
Lin

2018-08-08