On-Demand Computation Offloading Architecture in Fog Networks

With the advent of the Internet-of-Things (IoT), end-devices have been served as sensors, gateways, or local storage equipment. Due to their scarce resource capability, cloud-based computing is currently a necessary companion. However, raw data collected at devices should be uploaded to a cloud server, taking a significantly large amount of network bandwidth. In this paper, we propose an on-demand computation offloading architecture in fog networks, by soliciting available resources from nearby edge devices and distributing a suitable amount of computation tasks to them. The proposed architecture aims to finish a necessary computation job within a distinct deadline with a reduced network overhead. Our work consists of three elements: (1) resource provider network formation by classifying nodes into stem or leaf depending on network stability, (2) task allocation based on each node’s resource availability and soliciting status, and (3) task redistribution in preparation for possible network and computation losses. Simulation-driven validation in the iFogSim simulator demonstrates that our work achieves a high task completion rate within a designated deadline, while drastically reducing unnecessary network overhead, by selecting only some effective edge devices as computation delegates via locally networked computation.

[1]  Symeon Papavassiliou,et al.  Combined power and rate allocation in self-optimized multi-service two-tier femtocell networks , 2015, Comput. Commun..

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

[3]  Apostolos Malatras,et al.  State-of-the-art survey on P2P overlay networks in pervasive computing environments , 2015, J. Netw. Comput. Appl..

[4]  Sam Jabbehdari,et al.  A Novel Distributed Clustering Algorithm for Mobile Ad-hoc Networks , 2008 .

[5]  Barbara M. Masini,et al.  A Survey on the Roadmap to Mandate on Board Connectivity and Enable V2V-Based Vehicular Sensor Networks , 2018, Sensors.

[6]  Tarik Taleb,et al.  On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration , 2017, IEEE Communications Surveys & Tutorials.

[7]  Gade Krishna,et al.  A scalable peer-to-peer lookup protocol for Internet applications , 2012 .

[8]  Mohsen Guizani,et al.  Replisom: Disciplined Tiny Memory Replication for Massive IoT Devices in LTE Edge Cloud , 2016, IEEE Internet of Things Journal.

[9]  Rajkumar Buyya,et al.  iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments , 2016, Softw. Pract. Exp..

[10]  Sajal K. Das,et al.  WCA: A Weighted Clustering Algorithm for Mobile Ad Hoc Networks , 2002, Cluster Computing.

[11]  Khaled Ben Letaief,et al.  Dynamic Computation Offloading for Mobile-Edge Computing With Energy Harvesting Devices , 2016, IEEE Journal on Selected Areas in Communications.

[12]  Guoqiang Mao,et al.  New Multi-Hop Clustering Algorithm for Vehicular Ad Hoc Networks , 2019, IEEE Transactions on Intelligent Transportation Systems.

[13]  Vaduvur Bharghavan,et al.  Spine routing in ad hoc networks , 1998, Cluster Computing.

[14]  Symeon Papavassiliou,et al.  Game-theoretic Learning-based QoS Satisfaction in Autonomous Mobile Edge Computing , 2018, 2018 Global Information Infrastructure and Networking Symposium (GIIS).

[15]  John K. Zao,et al.  Augmented Brain Computer Interaction Based on Fog Computing and Linked Data , 2014, 2014 International Conference on Intelligent Environments.

[16]  Wenzhong Li,et al.  Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing , 2015, IEEE/ACM Transactions on Networking.

[17]  Min Chen,et al.  Task Offloading for Mobile Edge Computing in Software Defined Ultra-Dense Network , 2018, IEEE Journal on Selected Areas in Communications.

[18]  Srinivasan Parthasarathy,et al.  Minimizing broadcast latency and redundancy in ad hoc networks , 2008, TNET.

[19]  Enzo Baccarelli,et al.  Fog of Everything: Energy-Efficient Networked Computing Architectures, Research Challenges, and a Case Study , 2017, IEEE Access.

[20]  Narottam Chand,et al.  A Distributed Weighted Cluster Based Routing Protocol for MANETs , 2011, Wirel. Sens. Netw..

[21]  Ben Y. Zhao,et al.  Tapestry: a resilient global-scale overlay for service deployment , 2004, IEEE Journal on Selected Areas in Communications.

[22]  Antonio Pescapè,et al.  Integration of Cloud computing and Internet of Things: A survey , 2016, Future Gener. Comput. Syst..

[23]  Keqin Li,et al.  Multi-User Multi-Task Computation Offloading in Green Mobile Edge Cloud Computing , 2019, IEEE Transactions on Services Computing.