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.
Similar content being viewed by others
References
Gaynor M, Moulton S (2004) Integrating wireless sensor networks with the grid [J]. IEEE Internet Comput 7:32–39
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
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
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
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
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
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
Öztürk P, Rossland K, Gundersen OE (2010) A multiagent framework for coordinated parallel problem solving. Appl Intell 33(2):132–143
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.
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
Pallikonda Rajasekaran M, Radhakrishnan S, Subbaraj P (2010) Sensor grid applications in patient monitoring. Future Gener Comput Syst 26(4):569–575
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
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.
Lim HB, Lee D (2007) An integrated and flexible scheduler for sensor grids. In: UIC 2007. LNCS, vol 4611. Springer, Berlin, pp 567–578
Murillo J, Muñoz V, Busquets D, López B (2011) Schedule coordination through egalitarian recurrent multi-unit combinatorial auctions. Appl Intell 34(1):47–63
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
Luh PB, Hoitomt DJ (1993) Scheduling of manufacturing systems using the Lagrangian relaxation technique. IEEE Trans Autom Control 38(7):1066–1079
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
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
Li C, Li L (2007) Joint QoS optimization for layered computational grid. Inf Sci 177(15):3038–3059
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
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
Fukuda M, Kashiwagi K, Kobayashi S (2006) AgentTeamwork: coordinating grid-computing jobs with mobile agents. Appl Intell 25(2):181–198
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
Corresponding author
Rights 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
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10489-012-0397-1