Abstract
The increased traffic load, proliferation of network nodes and, in particular, wireless user devices, and the boom in user services and exponential growth of information stored in content distribution networks (CDNs) have brought new challenges for current networks. One major challenge has and continues to be efficient load balancing and information access. The topics have been well studied for wired networks for, for example, process load balancing in distributed computer networks with migration. However, the wireless networks and ubiquitous computing environments create new limitations and additional requirements to perform service or process migration. In this paper, we present a simulation case and proof-of-concept implementation for service mobility as a part of the BIONETS service evolution process with the aim of optimizing service penetration in a pervasive computing environment and balancing the load in the system caused by the high service utilization rate.
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References
Chlamtac, I., Miorandi, D., Steglich, S., Radusch, I., Linner, D., Huusko, J., Lahti, J.: BIONETS: Bio-Inspired Principles for Service Provisioning in Pervasive Computing Environments. In: Di Nitto, E., Sassen, A.M., Traverso, P., Zwegers, A. (eds.) At your service: service engineering in the Information Society Technologies Program. MIT Press, Cambridge (2008)
Miorandi, D., Huusko, J., De Pellegrini, F., Pfeffer, H., Linner, D., Moiso, C., Schreckling, D.: D1.1.3/3.1.3 Serworks architecture v1.0. BIONETS Deliverable, D1.1.3/3.1.3 (2008)
Nakano, T., Suda, T.: Adaptive and Evolvable Network Services. In: Deb, K., et al. (eds.) GECCO 2004. LNCS, vol. 3102, pp. 151–162. Springer, Heidelberg (2004)
Nakano, T., Suda, T.: Self-organizing network services with evolutionary adaptation. IEEE Trans. on Neural Networks (2005)
Suzuki, J., Suda, T.: A middleware platform for a biologically inspired network architecture supporting autonomous and adaptive applications. IEEE Journal on Selected Areas in Communications 23(2), 249–260 (2005)
Milojičić, D.S., Douglis, F., Paindaveine, Y., Wheeler, R., Zhou, S.: Process migration. ACM Computing Surveys (CSUR) 32(3), 241–299 (2000)
Luke, S., Cioffi-Revilla, C., Panait, L., Sullivan, K.: MASON: A New Multi-Agent Simulation Toolkit. In: Proceedings of the 2004 SwarmFest Workshop (2004)
Yoon, J., Liu, M., Noble, B.: Sound mobility models. In: Proc. of ACM MobiCom, San Diego, CA (2003)
SIGAR API, http://www.hyperic.com/products/sigar.html
GlassFish, https://glassfish.dev.java.net
Appserver Management Extensions, https://glassfish.dev.java.net/javaee5/amx
Mäkelä, J., Pentikousis, K., Majanen, M., Huusko, J.: Trigger management and mobile node cooperation. In: Katz, M., Fitzek, F.H.P. (eds.) Cognitive Wireless Networks: Concepts, Methodologies and Visions – Inspiring the Age of Enlightenment of Wireless Communications, pp. 199–211. Springer, Heidelberg (2007)
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© 2010 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Lahti, J., Rivas, H., Huusko, J., Könönen, V. (2010). Simulation and Implementation of the Autonomic Service Mobility Framework. In: Altman, E., Carrera, I., El-Azouzi, R., Hart, E., Hayel, Y. (eds) Bioinspired Models of Network, Information, and Computing Systems. BIONETICS 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 39. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12808-0_6
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DOI: https://doi.org/10.1007/978-3-642-12808-0_6
Publisher Name: Springer, Berlin, Heidelberg
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