Energy Efficient Task Assignment in Virtualized Wireless Sensor Networks

TL;DR

This paper addresses energy-efficient task assignment in virtualized Wireless Sensor Networks by formulating the problem with ILP, demonstrating significant energy savings compared to traditional non-virtualized networks.

Contribution

It introduces an ILP-based approach for static task assignment in virtualized WSNs, considering energy constraints and virtualization overhead, and compares it to traditional WSNs.

Findings

Virtualization enables energy savings in WSNs.

Proper task assignment reduces overall energy consumption.

Virtualized WSNs outperform traditional ones in energy efficiency.

Abstract

Wireless Sensor Networks (WSNs) are being used extensively today in various domains. However, they are traditionally deployed with applications embedded in them which precludes their re-use for new applications. Nowadays, virtualization enables several applications on a same WSN by abstracting the physical resources (i.e. sensing capabilities) into logical ones. However, this comes at a cost, including an energy cost. It is therefore critical to ensure the efficient allocation of these resources. In this paper, we study the problem of assigning application sensing tasks to sensor devices, in virtualized WSNs. Our goal is to minimize the overall energy consumption resulting from the assignment. We focus on the static version of the problem and formulate it using Integer Linear Programming (ILP), while accounting for sensor nodes' available energy and virtualization overhead. We solve the problem over different scenarios and compare the obtained solution to the case of a traditional WSN, i.e. one with no support for virtualization. Our results show that significant energy can be saved when tasks are appropriately assigned in a WSN that supports virtualization.