Grid computing technologies are emerging as the latest generation of distributed computing, as they allow the aggregation of resources that are geographically distributed over different locations. Since researchers need to conduct repeatable and controlled experiments, it is easier to use simulation as a means of studying complex scenarios. In this area, the GridSim simulation toolkit is a widely accepted option. We have designed and implemented a simulator of systems that integrates sensors and a grid. In particular, an extension of GridSim has been created in order to enable the execution of simulations in a way the users can perform queries on sensor networks. In this paper, we present the features of the system to be simulated, the modeling proposed, and the high-level user interfaces of the simulator. We also describe an experiment that demonstrates how our proposal works, which may well be helpful for the research community.
BakerMBuyyaRLaforenzaD. Grids and grid technologies for wide-area distributed computing. Software Pract Ex2002; 32: 1437–1466.
2.
The Cloud Computing and Distributed Systems (CLOUDS) Laboratory. GridSim homepage, http://www.gridbus.org/gridsim/ (Accessed on 22September2010).
3.
AkyildizIF. A survey on sensor networks. IEEE Commun Mag2002; 40: 102–114.
4.
De RoureD. Improving flood warning times using pervasive and grid computing. Ingenia Mag2005; 1: 48–51.
5.
SanabriaJ. A sensor grid framework for acoustic surveillance applications. In: proceedings of the fifth international joint conference on INC, IMS and IDC, Seoul Korea, 2009, pp.31–38.
6.
RehmanAShaikhZAShaikhNA. An integrated framework to develop context-aware sensor grid for agriculture. Aust J Basic Appl Sci2010; 4: 922–931.
BramleyR. Instruments and sensors as network services: Making instruments first class members of the grid. Technical report, 588, Indiana University, Computer Science Department, 2003.
11.
HockBL. Sensor grid: Integration of wireless sensor networks and the grid. In: proceedings of the 30th IEEE conference on local computer networks (LCN’05), Sydney, Australia, 2005, pp.92–98.
12.
ChuX. Open sensor web architecture: core services. Minor Project Thesis of Master of Information Technology, University of Melbourne, 2005.
13.
BottsM. Sensor web enablement: Overview and high level architecture. Technical report OGC 07–165, Open Geospatial Consortium, 2007.
14.
KobialkaT. Sensor web: Integration of sensor networks with web and cyber infrastructure. In: Handbook of research on developments and trends in wireless sensor networks: From principle to practice. IGI Global, Hershey, PA, USA, 2010, Chapter 20.
AvilésEGarcíaJA. Providing service-oriented abstractions for the wireless sensor grid. In: proceedings of the 2nd international conference on advances in grid and pervasive computing (GPC’07) in LNCS 4459, Paris, France, 2007, pp.710–715.
18.
FoxG. A collaborative sensor grids framework. In: proceedings of the international symposium on collaborative technologies and systems (CTS’08), Irvine, USA, 2008, pp.29–38.
19.
StaschCWalkowskiACJirkaS. A geosensor network architecture for disaster management based on open standards. In: digital earth summit on geoinformatics 2008: tools for climate change research, Potsdam, Germany, 2008, pp.54–59.
20.
LiX. ASGrid: autonomic management of hybrid sensor grid systems and applications. Int J Sensor Networks2009; 6: 234–250.
21.
SuSThamCK. SensorGrid for real-time traffic management. In: proceedings of the 3rd international conference on intelligent sensors, sensor networks and information processing (ISSNIP’07), Melbourne, Australia, 2007, pp.443–448.
22.
KaoFC. The design of intelligent sensor network based on grid structure. In: proceedings of the IEEE Asia-Pacific services computing conference (APSCC’08), Yilan, Taiwan, 2008, pp.623–630.
23.
ThamCK. Sensor-grid computing and sensorgrid architecture for event detection, classification and decision-making. In: Sensor networks and configuration: fundamentals, standards, platforms, and applications. Springer, Heidelberg, Germany, 2007, Chapter 5.
24.
AhujaSPMyersJR. A survey on wireless grid computing. J Supercomput2006; 37: 3–21.
25.
GangL. A survey on wireless grids and clouds. In: proceedings of the eighth international conference on grid and cooperative computing, Lanzhou, China, 2009, pp.261–267.
26.
SulistioA. A toolkit for modelling and simulating data grids: An extension to GridSim. Concurrency Comput Pract Ex2008; 20: 1591–1609.
27.
SulistioABuyyaR. A grid simulation infrastructure supporting advance reservation. In: proceedings of the 16th international conference on parallel and distributed computing and systems (PDCS’04), Cambridge, USA, 2004, pp.1–7.
28.
SulistioAYeoCSBuyyaR. Visual modeler for grid modeling and simulation (GridSim) toolkit. In: proceedings of the 3rd international conference on computational science (ICCS’03) in LNCS 2659, Melbourne, Australia, 2003, pp.1123–1132.
29.
KurowskiK. Grid scheduling simulations with GSSIM. In: proceedings of the 13th international conference on parallel and distributed systems (ICPADS’07), Hsinchu, Taiwan, 2007, pp.1–8.
30.
Klusáč ekDMatyskaLRudováH. Alea - Grid scheduling simulation environment. In: proceedings of the 7th international conference on parallel processing and applied mathematics (PPAM’07), Gdan′sk, Poland, 2007, pp. 1029–1038.
31.
Klusáč ekDRudováH. Alea 2 - Job scheduling simulator. In: proceedings of the 3rd international conference on simulation tools and techniques (SIMUTools 2010), Málaga, Spain, 2010.
32.
CamineroA. Extending GridSim with an architecture for failure detection. In: proceedings of the 13th international conference on parallel and distributed systems (ICPADS’07), Hsinchu, Taiwan, 2007, pp.1–8.
33.
CamineroA. Simulation of buffer management policies in networks for grids. In: proceedings of the 41st annual simulation symposium (ANSS’08), Ottawa, Canada, 2008, pp.1–8.
34.
Dias de AssuncaoMBuyyaR. An evaluation of communication demand of auction protocols in grid environments. In: proceedings of the 3rd international workshop on grid economics and business (GECON’06), Singapore, 2006, pp.24–33.
35.
MessinaF. A QoS-aware architecture for multimedia content provisioning in a grid environment. In: proceedings of the 7th workshop from objects to agents (WOA’06), Catania, Italy, 2006, pp.60–65.
36.
SulistioA. On incorporating differentiated levels of network service into GridSim. Future Generat Comput Syst2007; 23: 606–615.
DijkstraEW. A note on two problems in connexion with graphs. Numer Math1959; 1: 269–271.
39.
BirkhoffG. The algebra of multivariate interpolation. In: Constructive approaches to mathematical models (proceedings of a conference in honor of R. J. Duffin), New York, 1979, pp.345–363.
40.
FasshauerG. Meshfree approximation methods with MATLAB. River Edge, NJ: World Scientific Publishing Co., Inc., 2007.
41.
CaliariMDe MarchiSVianelloM. Bivariate polynomial interpolation on the square at new nodal sets. Appl Math Comput2005; 165: 261–274.
42.
KalmanD. The generalized Vandermonde Matrix. Math Mag1984; 57: 15–24.
43.
GoodaleCLAberJDOllingeSV. Mapping monthly precipitation, temperature, and solar radiation for Ireland with polynomial regression and a digital elevation model. Clim Res1998; 10: 35–49.
44.
DepoorterW. Scalability of grid simulators: an evaluation. In: proceedings of the 14th international euro-par conference on parallel processing (Euro-Par’08), Las Palmas de Gran Canaria, Spain, 2008, pp.544–553. Springer.
