Skip to main content
Log in

Agent based sensors resource allocation in sensor grid

  • Published:
Applied Intelligence Aims and scope Submit manuscript

Abstract

Sensor enabled grid may combine real time data about physical environment with vast computational resources derived from the grid architecture. One of the major challenges of designing a sensor enabled grid is how to efficiently schedule sensor resource to user jobs across the collection of sensor resources. The paper presents an agent based scheme for assigning sensor resources to appropriate sensor grid users on the basis of negotiation results among agents. The proposed model consists of two types of agents: the sensor resource agents that represent the economic interests of the underlying sensor resource providers of the sensor grid and the sensor user agents that represent the interests of grid user application using the grid to achieve goals. Interactions between the two agent types are mediated by means of market mechanisms. We model sensor allocation problems by introducing the sensor utility function. The goal is to find a sensor resource allocation that maximizes the total profit. This paper proposes a distributed optimal sensor resource allocation algorithm. The performance evaluation of proposed algorithm is evaluated and compared with other resource allocation algorithms for sensor grid. The paper also gives the application example of proposed approach.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Algorithm 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Gaynor M, Moulton S (2004) Integrating wireless sensor networks with the grid [J]. IEEE Internet Comput 7:32–39

    Article  Google Scholar 

  2. Humble J, Greenhalgh C, Hamsphire A, Muller HL, Rennick S (2005) Egglestone, a generic architecture for sensor data integration with the grid. In: SAG 2004. LNCS, vol 3458. Springer, Berlin, pp 99–107

    Google Scholar 

  3. Li X, Liu X, Zhao H, Jiang N, Parashar M (2008) Autonomic management of hybrid sensor grid systems and applications. In: Proceedings of 17th international conference on computer communications and networks, 3–7 Aug 2008, ICCCN’08, pp 1–6

    Google Scholar 

  4. Kanbayashi R, Sato M (2009) A distributed architecture of sensing web for sharing open sensor nodes. In: GPC 2009. LNCS, vol 5529. Springer, Berlin, pp 340–352

    Google Scholar 

  5. Iqbal M, Lim HB, Wang W, Yao Y (2008) A sensor grid infrastructure for large-scale ambient intelligence. In: Ninth international conference on parallel and distributed computing, applications and technologies, 2008, PDCAT 2008, 1–4 Dec 2008, pp 468–473

    Chapter  Google Scholar 

  6. Komisarczuk P, Welch I (2010) Internet sensor grid: experiences with passive and active instruments. In: IFIP advances in information and communication technology, pp 132–145

    Google Scholar 

  7. Lim HB, Iqbal M, Wang W, Yao Y (2010) The national weather sensor grid: a large-scale cyber-sensor infrastructure for environmental monitoring. Int J Sens Netw 7(1–2):19–36

    Article  Google Scholar 

  8. Öztürk P, Rossland K, Gundersen OE (2010) A multiagent framework for coordinated parallel problem solving. Appl Intell 33(2):132–143

    Article  Google Scholar 

  9. Rao I, Imran N, Khan S, Huh E-N, Chung T (2007) Adaptive and reconfigurable resource management for wireless sensors using grid technology. In: 2nd international conference on communication systems software and middleware, COMSWARE 2007, pp 1–5.

    Chapter  Google Scholar 

  10. Avilés-López E, García-Macías JA (2007) Providing service-oriented abstractions for the wireless sensor grid. In: GPC 2007. LNCS, vol 4459. Springer, Berlin, pp 710–715

    Google Scholar 

  11. Pallikonda Rajasekaran M, Radhakrishnan S, Subbaraj P (2010) Sensor grid applications in patient monitoring. Future Gener Comput Syst 26(4):569–575

    Article  Google Scholar 

  12. Johnson MP, Rowaihy H, Pizzocaro D, Bar-Noy A, Chalmers S, La Porta T, Preece A (2008) Frugal sensor assignment. In: DCOSS 2008. LNCS, vol 5067. Springer, Berlin, pp 219–236

    Google Scholar 

  13. Oh S-J, Lee C-W (2008) u-Healthcare SensorGrid gateway for connecting wireless sensor network and grid network, advanced communication technology. In: 10th international conference on ICACT 2008, vol 1, pp 827–831.

    Google Scholar 

  14. Lim HB, Lee D (2007) An integrated and flexible scheduler for sensor grids. In: UIC 2007. LNCS, vol 4611. Springer, Berlin, pp 567–578

    Google Scholar 

  15. Murillo J, Muñoz V, Busquets D, López B (2011) Schedule coordination through egalitarian recurrent multi-unit combinatorial auctions. Appl Intell 34(1):47–63

    Article  Google Scholar 

  16. Kelly F, Maulloo A, Tan D (1998) Rate control for communication networks: shadow prices, proportional fairness and stability. J Oper Res Soc 49(3):237–252

    MATH  Google Scholar 

  17. Luh PB, Hoitomt DJ (1993) Scheduling of manufacturing systems using the Lagrangian relaxation technique. IEEE Trans Autom Control 38(7):1066–1079

    Article  MathSciNet  Google Scholar 

  18. Both F, Hoogendoorn M, van der Mee A, Treur J, de Vos M (2012) An intelligent agent model with awareness of workflow progress. Appl Intell 36(2):498–510

    Article  Google Scholar 

  19. Isern D, Moreno A, Sánchez D, Hajnal Á, Pedone G, Varga LZ (2011) Agent-based execution of personalised home care treatments. Appl Intell 34(2):155–180

    Article  Google Scholar 

  20. Li C, Li L (2007) Joint QoS optimization for layered computational grid. Inf Sci 177(15):3038–3059

    Article  Google Scholar 

  21. Li C, Li L (2007) Utility based QoS optimisation strategy for multi-criteria scheduling on the grid. J Parallel Distrib Comput 67(2):142–153

    Article  MATH  Google Scholar 

  22. Ardaiz O, Artigas P, Eymann T, Freitag F, Navarro L, Reinicke M (2006) The catallaxy approach for decentralized economic-based allocation in grid resource and service markets. Appl Intell 25(2):131–145

    Article  Google Scholar 

  23. Fukuda M, Kashiwagi K, Kobayashi S (2006) AgentTeamwork: coordinating grid-computing jobs with mobile agents. Appl Intell 25(2):181–198

    Article  MATH  Google Scholar 

Download references

Acknowledgements

The work was partly supported by the National Natural Science Foundation of China (NSF) under grant (No. 61272116, No. 61171075), National Key Basic Research Program of China (973 Program) under Grant No.2011CB302601, Open Fund of the State Key Laboratory of Software Development Environment. Any opinions, findings, and conclusions are those of the authors and do not necessarily reflect the views of the above agencies.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chunlin Li.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Li, C., Li, L. & Luo, Y. Agent based sensors resource allocation in sensor grid. Appl Intell 39, 121–131 (2013). https://doi.org/10.1007/s10489-012-0397-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10489-012-0397-1

Keywords

Navigation