The Community for Technology Leaders
RSS Icon
Issue No.12 - December (2009 vol.20)
pp: 1830-1843
Kenneth Hopkinson , Air Force Institute of Technology, Wright-Patterson AFB, OH
Kate Jenkins , Akamai Technologies, Cambridge
Kenneth Birman , Cornell University, Ithaca
James Thorp , Virginia Polytechnic Institute, Blacksburg
Gregory Toussaint , Air Force Institute of Technology, Wright-Patterson AFB, OH
Manu Parashar , Electric Power Group, Pasadena
Gossip-based communication protocols are attractive in cases where absolute delivery guarantees are not required due to their scalability, low overhead, and probabilistically high reliability. In earlier work, a gossip-based protocol known as gravitational gossip was created that allows the selection of quality ratings within subgroups based on workload and information update frequency. This paper presents an improved protocol that adds an adaptive component that matches the actual subgroup communication rates with desired rates coping with network variations by modifying underlying gossip weights. The protocol is designed for use in environments where many information streams are being generated and interest levels vary between nodes in the system. The gossip-based protocol is able to allow subscribers to reduce their expected workload in return for a reduced information rate. The protocol is a good fit for applications such as military information systems, sensor networks, and rescue operations. Experiments were conducted in order to compare the merits of different adaptation mechanisms. Experimental results show promise for this approach.
Adaptive communication, epidemic protocols, publish/subscribe systems.
Kenneth Hopkinson, Kate Jenkins, Kenneth Birman, James Thorp, Gregory Toussaint, Manu Parashar, "Adaptive Gravitational Gossip: A Gossip-Based Communication Protocol with User-Selectable Rates", IEEE Transactions on Parallel & Distributed Systems, vol.20, no. 12, pp. 1830-1843, December 2009, doi:10.1109/TPDS.2009.23
[1] K. Jenkins, K.M. Hopkinson, and K.P. Birman, “Reliable Group Communication with Subgroups,” Proc. Int'l Workshop Applied Reliable Group Comm. (WARGC), pp. 25-30, 2001.
[2] L. Rodrigues, S. Handurukande, J. Pereira, R. Guerraoui, and A.-M. Kermarrec, “Adaptive Gossip-Based Broadcast,” Proc. Int'l Conf. Dependable Systems and Networks, pp. 47-56, 2003.
[3] B. Garbinato, F. Pedone, and R. Schmidt, “An Adaptive Algorithm for Efficient Message Diffusion in Unreliable Environments,” Proc. Int'l Conf. Dependable Systems and Networks, pp. 507-516, 2004.
[4] J.V. Director for Strategic Plans and Policy, America's Military: Preparing for Tomorrow, DoD, ed. US Government Printing Office, June 2000.
[5] M. Gettle, “Air Force Releases New Mission Statement,” Air Force Print News, Dec. 2005.
[6] M.W. Wynn and T.M. Mosely, SECAF/CSAF Letter to Airmen: Mission Statement. US Air Force, Dec. 2005.
[7] US Air Force Scientific Advisory Board, Report on Information Management to Support the Warrior. HW USAF, Dec. 2000.
[8] S. Busenberg and C. Castillo-Chavez, “A General Solution to the Problem of Mixing of Sub-Populations, and Its Applications to Risk and Age-Structured Epidemic Models for the Spread of AIDS,” IMA J. Math. Applied in Medicine and Biology, vol. 8, pp. 1-29, 1991.
[9] A.J. Demers, D.H. Greene, C. Hauser, W. Irish, and J. Larson, “Epidemic Algorithms for Replicated Database Maintenance,” Proc. Symp. Principles of Distributed Computing, pp. 1-12, 1987.
[10] W.E. Boyce and R.C. DiPrima, Calculus. John Wiley and Sons, 1988.
[11] S.-C.J. Yam and M.-H. Wong, “Performance of Semantic-Dependent Two-Tier Gossip Mechanisms,” Proc. IEEE Sensors Applications Symp. (SAS), pp. 1-6, 2007.
[12] D.C. Erdil and M.J. Lewis, “Grid Resource Scheduling with Gossip Protocols,” Proc. IEEE Conf. Peer-to-Peer Computing, pp. 193-200, 2007.
[13] A.D.G. Dimakis, A.D. Sarwate, and M.J. Wainwright, “Geographic Gossip: Efficient Averaging for Sensor Networks,” IEEE Trans. Signal Processing, vol. 56, no. 3, pp. 1205-1216, Mar. 2008.
[14] W. Jia, D. Lu, G. Wang, and L. Zhang, “Local Retransmission-Based Gossip Protocol in Mobile Ad Hoc Networks,” Proc. IEEE Wireless Comm. and Networking Conf. (WCNC), pp. 4247-4252, 2007.
[15] The Mathworks, Inc., Optimization Toolbox User's Guide Version 3.0, fifth ed. The Mathworks, Inc., 2004.
[16] M.T. Heath, Scientific Computing. WCB/McGraw-Hill, 1997.
[17] K. Ogata, Modern Control Engineering, third ed. Prentice Hall, 1997.
[18] K. Ogata, Discrete-Time Control Systems. Prentice Hall, 1994.
[19] L. Breslau, D. Estrin, K. Fall, S. Floyd, J. Heidermann, A. Helmy, P. Huang, S. McCanne, K. Varadhan, Y. Xu, and H. Yu, “Advances in Network Simulation,” Computer, vol. 33, no. 5, pp. 59-67, May 2000.
[20] K.M. Hopkinson, “Overcoming Communications, Distributed Systems, and Simulation Challenges: A Case Study Involving the Protection and Control of the Electric Power Grid Using a Utility Intranet Based on Internet Technology,” PhD dissertation, Cornell Univ., p. 245, 2004.
[21] F. Lu, L.-T. Chia, and K.L. Tay, “NBGossip—Neighborhood Gossip with Network Coding Based Message Aggregation,” Proc. IEEE Mobile Adhoc and Sensor Systems (MASS), pp. 1-12, 2007.
28 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool