Paper Info
Title
Cost-Effective Processing in Fog-Integrated Internet of Things Ecosystems.
Abstract
The emerging Internet of Things (IoT) paradigm creates a growing need to analyze a significant amount of data produced by the interconnected IoT devices. Since IoT devices have limited computation capabilities, Fog Computing is a natural complement, to provide distributed, location-aware, and easy-to-access computation resources. In this work, we address the problem of application processing and data offloading in a Fog-integrated IoT ecosystem. By leveraging the Lyapunov optimization technique, we design an online and distributed system control policy called the Distributed Weighted Backpressure (DWB) policy that asymptotically minimizes the cost of IoT devices. A three-way tradeoff among queue backlogs, communication cost, and computation cost is then investigated. Finally, simulation study has been conducted to validate the correctness and usefulness of the proposed DWB policy.
Year
DOI
Venue
2017
10.1145/3127540.3127547
MSWiM '17: 20th ACM Int'l Conference on Modelling, Analysis and Simulation of Wireless and Mobile Systems Miami Florida USA November, 2017
Keywords
Field
DocType
Internet of Things, fog computing, data processing, stochastic optimization
Data processing,Stochastic optimization,Computer science,Internet of Things,Queue,Correctness,Computer network,Fog computing,Lyapunov optimization,Computation,Distributed computing
Conference
ISBN
Citations 
PageRank 
978-1-4503-5162-1
1
0.36
References 
Authors
17
7
Name
Order
Citations
PageRank
Wei Bao118414.70
Wei Li222725.46
Flávia Coimbra Delicato327232.77
Paulo F. Pires458762.83
Dong Yuan576848.06
Bing Bing Zhou663347.28
Albert Y. Zomaya75709454.84