John G. Waclawsky

Unlocking the Advantages of Dynamic Service Selection and Pricing

AbstractBandwidth limitations, resource greedy applications verbose mark-up languages and an increasing number of voice and data users are straining the air interface of wireless networks. Hence, novel approaches and new algorithms to manage wireless bandwidth are needed. In addition, usage based pricing is becoming increasingly prevalent (pre-paid cell phones, calling cards, non-contract minutes, etc.). This paper unlocks the potential to improving the performance of overall system behavior by allowing users to change service level and/or service provider for a (small) price. The ability to dynamically re-negotiate service gives the user the power to control QoS while minimizing usage cost. On the other hand, the ability to change service level pricing dynamically allows the service providers to manage traffic better, improve resource usage and most importantly maximize their profit. This provides a surprising win-win situation for BOTH the service providers AND the users. In this paper we present easy to implement on-line algorithms to minimize the overall usage cost to individual mobile users. This on-line algorithm continuously receives pricing information and evaluates minimum QoS requirements. The algorithm then determines appropriate service level, chooses a service provider and sets a time for re-negotiation dynamically. Our algorithm can handle many practical issues such as capacity limitations, arbitrary price fluctuations and loss/gain of service providers due to mobility. Our results do not assume any specific technologies and can be applied to any environment that can employ dynamic pricing, including wired networks. In fact, dynamic pricing is becoming increasingly desirable since service provider and capacity changes are a growing by-product of mobility. Arriving and departing users at/from a cell tower (or wireless LAN) can effectively reduce or increase the available bandwidth in a cell (or LAN transmission area) and represents a natural opportunity for a pricing change.

Dynamics of token ring protocols

We present a new approach for analyzing token ring LANs. The token ring model presented supports the behavior obtained from actual ring measurements. Using this model, employing deterministic bounds analysis techniques, we prove several theorems which lead to some interesting conclusions that support observed ring performance. The results obtained give insight into practical behavior of a token ring environments.<<ETX>>