Design and analysis of a replicated server architecture for supporting IP-host mobility

  • Authors:
  • Jason P. Jue;Dipak Ghosal

  • Affiliations:
  • Department of Electrical and Computer Engineering, University of California, Davis, CA 95616, USA;Department of Computer Science, University of California, Davis, CA 95616, USA

  • Venue:
  • Cluster Computing
  • Year:
  • 1998

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Abstract

Mobility support in IP networks requires servers to forward packets to mobile hosts and to maintain information pertaining to a mobile host’s location in the network. In the mobile Internet Protocol (mobile-IP), location and packet forwarding functions are provided by servers referred to as home agents. These home agents may become the bottleneck when there are a large number of mobile hosts in the network. In this paper, we consider the design and analysis of a replicated server architecture in which multiple home agents are used to provide mobility support. In order to minimize the delay across the home agents, one of the key aspects is the design of load balancing schemes in which a home agent may transfer the control of a mobile host to another home agent in the same network. The methods for triggering the transfer and the policy for selecting the next home agent define various load balancing schemes which have different performance characteristics. In this paper, we design a protocol that forms the building block for implementing such load balancing schemes, and we then study the performance characteristics of three selection schemes, namely, random, round-robin, and join the shortest queue (JSQ), and three transfers policies, namely, timer-, counter- and threshold-based. The key results of this study are as follows: (1) The results show that both random and round-robin selection policies can yield modest load balancing gains, and that these gains increase when the traffic is more bursty (burstiness is defined as the ratio of the peak arrival rate to the mean arrival rate) as well as when there are more home agents. (2) The threshold-based transfer policy performs better than timer-based and counter-based policies, since in threshold-based policies transfers are made only when the queue is overloaded, unlike counter- and timer-based policies in which transfers can be made from an unloaded home agent to an overloaded home agent.