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We attack the sensor network deployment problem. We define the deployment problem as the problem of deciding how many sensor nodes should be deployed in the sensor field over how many phases during its lifetime. We target the optimal deployment strategy that meets user-defined availability requirement with minimum total cost taking into consideration node failures and changing field trip to sensor node cost ratio. We model WSN availability and total cost as functions of the deployment plan, then, we formalize the deployment problem as a 2D optimization problem. Our modeling enables us to explore cost-benefit tradeoffs, we believe, this is a solid step toward bringing cost as an explicit dimension in the design space of WSN protocols. We compare the performance of the optimized solution (denoted as pro-active) to more ad-hoc solutions: on-demand and at-front. The former strategy schedules future deployments only on demand. The latter strategy deploys all nodes at front with no later field trips. Using extensive simulations, we show that proactive outperforms at-front and on-demand in terms of total cost per availability unit in all application scenarios. For example, using pro-active costs $7 compared to $40 and $280 per total uptime in case of on-demand and at-front, respectively.