A Framework for Efficient and Scalable Service Offloading in the Mist

Mist computing puts computing on the very edge of the network. With mist computing, the computation is performed in users’ devices (smartphones, laptops, etc.) sensors or wearables (something fairly common in the context of the Internet of Things). Devices which are near may be part of a mist where each of these devices contributes to computation tasks. Each of them has computation capabilities which can be used in order to run tasks from other devices. However, devices in the network must be aware of available features in order to execute tasks within a device with the necessary hardware requirements. There is a compatibility problem between tasks and devices: not all devices satisfy all tasks needs. This article proposes a mist computing framework in order to tackle this compatibility problem.

[1]  Erdogan Dogdu,et al.  Development of a smart home ontology and the implementation of a semantic sensor network simulator: An Internet of Things approach , 2015, 2015 International Conference on Collaboration Technologies and Systems (CTS).

[2]  Ji Yang,et al.  A Hitchhiker's Guide to Computation Offloading: Opinions from Practitioners , 2017, IEEE Communications Magazine.

[3]  Amit P. Sheth,et al.  The SSN ontology of the W3C semantic sensor network incubator group , 2012, J. Web Semant..

[4]  Henri E. Bal,et al.  Cuckoo: A Computation Offloading Framework for Smartphones , 2010, MobiCASE.

[5]  Ying Zhang,et al.  Refactoring android Java code for on-demand computation offloading , 2012, OOPSLA '12.

[6]  Mohsen Guizani,et al.  Internet of Things Architecture: Recent Advances, Taxonomy, Requirements, and Open Challenges , 2017, IEEE Wireless Communications.

[7]  Ellen W. Zegura,et al.  Serendipity: enabling remote computing among intermittently connected mobile devices , 2012, MobiHoc '12.

[8]  Haibin Yu,et al.  An ontology based scheme for sensor description in context awareness system , 2015, 2015 IEEE International Conference on Information and Automation.

[9]  Winfried Lamersdorf,et al.  Computing at the Mobile Edge: Designing Elastic Android Applications for Computation Offloading , 2015, 2015 8th IFIP Wireless and Mobile Networking Conference (WMNC).

[10]  Axel Jantsch,et al.  The Benefits of Self-Awareness and Attention in Fog and Mist Computing , 2015, Computer.

[11]  Xin Liu,et al.  Learning-Based Task Offloading for Vehicular Cloud Computing Systems , 2018, 2018 IEEE International Conference on Communications (ICC).

[12]  Cartik R. Kothari,et al.  Building a Sensor Ontology: A Practical Approach Leveraging ISO and OGC Models , 2005, IC-AI.

[13]  Dimitrios Gunopulos,et al.  Misco: a MapReduce framework for mobile systems , 2010, PETRA '10.

[14]  Kenneth P. Fishkin,et al.  A taxonomy for and analysis of tangible interfaces , 2004, Personal and Ubiquitous Computing.

[15]  John Garrity,et al.  Harnessing the Internet of Things for Global Development , 2015 .

[16]  Andrés Marín López,et al.  Seamless human-device interaction in the internet of things , 2017, IEEE Transactions on Consumer Electronics.

[17]  Bernhard Mitschang,et al.  Dynamic Ontology-Based Sensor Binding , 2016, ADBIS.

[18]  John K. Ousterhout,et al.  In Search of an Understandable Consensus Algorithm , 2014, USENIX ATC.

[19]  Song Guo,et al.  Just-in-Time Code Offloading for Wearable Computing , 2015, IEEE Transactions on Emerging Topics in Computing.

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

[21]  J. Wenny Rahayu,et al.  Honeybee: A Programming Framework for Mobile Crowd Computing , 2012, MobiQuitous.

[22]  Myung Hwan Yun,et al.  A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives , 2017, PloS one.

[23]  Arvind Krishnamurthy,et al.  Customizable and Extensible Deployment for Mobile/Cloud Applications , 2014, OSDI.

[24]  Moisés Lima Dutra,et al.  An Application Domain-Based Taxonomy for IoT Sensors , 2016, ISPE TE.

[25]  Karolj Skala,et al.  Scalable Distributed Computing Hierarchy: Cloud, Fog and Dew Computing , 2015, Open J. Cloud Comput..

[26]  Sumi Helal,et al.  A device-centric approach to a safer internet of things , 2011, NoME-IoT '11.

[27]  Rajkumar Buyya,et al.  A survey on vehicular cloud computing , 2014, J. Netw. Comput. Appl..

[28]  Schahram Dustdar,et al.  DIANE - Dynamic IoT Application Deployment , 2015, 2015 IEEE International Conference on Mobile Services.

[29]  Sateesh Kumar Peddoju,et al.  Handoff Strategy for Improving Energy Efficiency and Cloud Service Availability for Mobile Devices , 2015, Wirel. Pers. Commun..