SMER: a secure method of exchanging resources in heterogeneous internet of things

Abstract

The number of IoT (internet of things) connected devices increases rapidly. These devices have different operation systems and therefore cannot communicate with each other. As a result, the data they collected is limited within their own platform. Besides, IoT devices have very constrained resources like weak MCU (micro control unit) and limited storage. Therefore, they need direct communication method to cooperate with each other, or with the help of nearby devices with rich resources. In this paper, we propose a secure method to exchange resources (SMER) between heterogeneous IoT devices. In order to exchange resources among devices, SMER adopts a compensable mechanism for resource exchange and a series of security mechanisms to ensure the security of resource exchanges. Besides, SMER uses a smart contract based scheme to supervise resource exchange, which guarantees the safety and benefits of IoT devices. We also introduce a prototype system and make a comprehensive discussion.

Keywords

internet of things / P2P resource exchange / blockchain / smart contract

References

[1] Wörner D, Bomhard V T. When your sensor earns money: exchanging data for cash with bitcoin. In: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication. 2014, 295–298

[2] Shiraz M, Gani A, Khokhar R H, Buyya R. A review on distributed application processing frameworks in smart mobile devices for mobile cloud computing. IEEE Communications Surveys & Tutorials, 2013, 15(3): 1294–1313

[3] Ma X, Cui Y, Wang L, Stojmenovic I. Energy optimizations for mobile terminals via computation offloading. In: Proceedings of the 2nd IEEE International Conference on Parallel Distributed and Grid Computing. 2012, 236–241

[4] Cuervo E, Balasubramanian A, Cho D K, Wolman A, Saroiu S, Chandra R, Bahl P. Maui: making smartphones last longer with code offload. In: Proceedings of the 8th International Conference on Mobile systems, Applications, and Services. 2010, 49–62

[5] Chun B G, Ihm S, Maniatis P, Naik M, Patti A. Clonecloud: elastic execution between mobile device and cloud. In: Proceedings of the 6th Conference on Computer Systems. 2011, 301–314

[6] Hasan R, Hossain M M, Khan R. Aura: an IoT based cloud infrastructure for localized mobile computation outsourcing. In: Proceedings of the 3rd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud). 2015, 183–188

[7] Al Noor S, Hasan R, Haque M M. Cellcloud: a novel cost effective formation of mobile cloud based on bidding incentives. In: Proceedings of the 7th IEEE International Conference on Cloud Computing. 2014, 200–207

[8] Ferrer E C. The blockchain: a new framework for robotic swarm systems. In: Proceedings of the Future Technologies Conference. 2018, 1037–1058

[9] Sikorski J J, Haughton J, Kraft M. Blockchain technology in the chemical industry: machine-to-machine electricity market. Applied Energy, 2017, 195: 234–246

[10] Christidis K, Devetsikiotis M. Blockchains and smart contracts for the internet of things. IEEE Access, 2016, 4: 2292–2303

[11] Lowe D G. Object recognition from local scale-invariant features. In: Proceedings of the 7th IEEE International Conference on Computer Vision. 1999, 1150–1157

[12] Muja M, Lowe D G. Fast approximate nearest neighbors with automatic algorithm configuration. In: Proceedings of UISAPP International Conference on Computer Vision Theory and Application. 2009, 331–340

RIGHTS & PERMISSIONS

Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature