Abstract
Grid Computing is a concept, a network, a work in progress, part hype and part reality, and it is increasingly capturing the attention of the computing community. The advancements in wireless technologies and increased number of wireless device users supported the evolution of wireless grids. Grid information server (GIS) has to maintain the most up-to-date resource status information of all devices, so that, application can be scheduled to devices that meet its resource requirements.
Each wireless device is resource constrained, and its resource status keeps on varying dynamically depending upon number of applications it is executing, amount of data it is communicating, battery level, and mobility. In order to keep up-to-date resource status, a continuous monitoring is needed. The increase in number of status delivery of such monitored observations will consume lot much of bandwidth, making the database size of grid information server to grow continuously over a period of time.
To solve this problem, we consider moderate number of communications of status updates that balances both bandwidth consumption and resource status accuracy. Also, we propose three methods to represent these update messages so that bandwidth requirement and latency of communication with GIS is reduced. Normal representation, Variable bit length representation, and Relative difference representation methods are proposed and analyzed. Relative difference method is analyzed in best case as well as in worst case, and is found to be more efficient compared to other two methods in terms of memory requirements.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Foster, I., Kesselman, C.: The Grid: Blueprint for a New Computing Infrastructure. Elsevier publishers, Amsterdam (2009)
Foster, I., Kesselman, C.: The Globus Project: a Status Report. In: Proc. of IPPS/SPDP 1998, Workshop on Heterogeneous Computing, pp. 4–18 (1998)
Phan, T., Huang, L., Dulan, C.: Challenge: Integrating Mobile Wireless Devices into the Computational Grid. In: Proc. of the 8th International Conference on Mobile Computing and Networking, Atlanta, GA (2002)
Kurkovsky, S., Bhagyavati, Ray, A.: A Collaborative Problem-Solving Framework for Mobile Devices. In: ACMSE 2004, Huntsville, Alabama, USA, April 2-3 (2004)
Kurkovsky, S., Bhagyavati: Modeling a Computational Grid of Mobile Devices as a Multi-Agent System. In: Proc. of 2003 International Conference on Artificial Intelligence, Las Vegas, NV (2003)
Mudali, P., Adigun, M.O., Emuoyibofarhe, J.O.: Minimizing the Negative Effects of Device Mobility in Cell-based Ad-hoc Wireless Computational Grids. In: SATNAC, Stellenbosch, South Africa, vol. 1, p. 10 (2006)
Krauter, K., Buyya, R., Maheswaran, M.: A taxonomy and survey of grid resource management systems for distributed computing. Intl. journal of Software Practice and Experience, John Wiley 32, 135–164 (2002)
Chung, W.-C., Chang, R.-S.: A new mechanism for resource monitoring in Grid computing. Intl. journal of Future Generation Computer Systems 25, 1–7 (2009)
Zanikolas, S., Sakellariou, R.: A taxonomy of grid monitoring systems. Future Generation Computer Systems 21(1), 163–188 (2005)
Monitoring and discovery system, http://www.globus.org/toolkit/mds/
Andreozzi, S., De Bortoli, N., Fantinel, S., Ghiselli, A., Rubini, G.L., Tortone, G., Vistoli, M.C.: GridICE: A monitoring service for Grid systems. Future Generation Computer Systems 21(4), 559–571 (2005)
Sundaresanz, R., Kurcy, T., Lauriaz, M., Parthasarathyz, S., Saltz, J.: A slacker coherence protocol for pull-based monitoring of on-line data sources. In: Proc. of the 3rd IEEE/ACM International Symposium on Cluster Computing and the Grid, pp. 250–254 (2003)
Sundaresanz, R., Kurcy, T., Lauriaz, M., Parthasarathyz, S., Saltz, J.: Adaptive polling of grid resource monitors using a slacker coherence model. In: Proc. of the 12th IEEE International Symposium on High Performance Distributed Computing, pp. 260–269 (2003)
Huang, L., Garofalakis, M., Hellerstein, J., Joseph, A., Taft, N.: Toward Sophisticated Detection With Distributed Triggers. In: SIGCOMM 2006 Workshops, Pisa, Italy, September 11-15 (2006)
Huang, L., Garofalakis, M., Joseph, A., Taft, N.: Communication-efficient tracking of distributed triggers. Technical report (2006)
Keralapura, R., Cormode, G., Ramamirtham, J.: Communication-efficient distributed monitoring of thresholded counts. In: ACM SIGMOD (2006)
Manvi, S.S., Birje, M.N.: Device Resource Status Monitoring System in Wireless Grids. In: ACEEE Intl. conference on Advances in Computing, Control, and Telecommunication Technologies (ACT 2009), Trivandrum, Kerala, India, December 28-29 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Birje, M.N., Manvi, S.S. (2010). Monitoring and Status Representation of Devices in Wireless Grids. In: Bellavista, P., Chang, RS., Chao, HC., Lin, SF., Sloot, P.M.A. (eds) Advances in Grid and Pervasive Computing. GPC 2010. Lecture Notes in Computer Science, vol 6104. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13067-0_37
Download citation
DOI: https://doi.org/10.1007/978-3-642-13067-0_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13066-3
Online ISBN: 978-3-642-13067-0
eBook Packages: Computer ScienceComputer Science (R0)