Minimizing the Net Present Cost of Deploying and Operating Wireless Sensor Networks

TL;DR

This paper introduces a net present cost model for wireless sensor networks that optimizes deployment and operational expenses considering interest rates, enabling cost-effective planning for network lifetime.

Contribution

It develops a convex optimization framework for minimizing NPC in WSNs by modeling expenditure timing and size, accounting for interest rates and operational constraints.

Findings

Convex optimization can find global NPC minimum under certain conditions.

Even expenditure spacing yields near-optimal costs when recurring costs are low.

Numerical examples demonstrate significant cost savings with the proposed model.

Abstract

Minimizing the cost of deploying and operating a Wireless Sensor Network (WSN) involves deciding how to partition a budget between competing expenses such as node hardware, energy, and labor. Most commercial network operators account for interest rates in their budgeting exercises, providing a financial incentive to defer some costs until a later time. In this paper, we propose a net present cost (NPC) model for WSN capital and operating expenses that accounts for interest rates. Our model optimizes the number, size, and spacing between expenditures in order to minimize the NPC required for the network to achieve a desired operational lifetime. In general this optimization problem is non-convex, but if the spacing between expenditures is linearly proportional to the size of the expenditures, and the number of maintenance cycles is known in advance, the problem becomes convex and can be solved to global optimality. If non-deferrable recurring costs are low, then evenly spacing the expenditures can provide near-optimal results. With the provided models and methods, network operators can now derive a payment schedule to minimize NPC while accounting for various operational parameters. The numerical examples show substantial cost benefits under practical assumptions.