Application-Oriented Flow Control for Wireless Sensor Networks

Abstract

This paper addresses flow control and resource allocation problem for heterogeneous wireless sensor networks which consist of diverse sensor types and applications. The performance of these applications, either elastic data collecting or real-time monitoring, is modelled as a utility function of the sensor source rate. The traditional optimal flow control approach, which requires the utility function to be strictly concave, is no longer applicable because of realtime applications involved. Therefore, we propose a new utility-based flow control framework that is able to allocate the resources (wireless channel usage and sensor node energy) efficiently and guarantee the application performance in a utility proportional or max-min fair manner. Furthermore, the optimization and convergence of the algorithm is examined in the paper as well.

Market-based resource allocation for distributed data processing in wireless sensor networks

“…This algorithm is shown to ensure optimal and fair transmission rate allocation amongst a set of multiple data-related objectives ("missions"). Similarly, Jin et al [2007] employed utility-based concepts to develop an application-oriented flow control framework for heterogeneous WSNs. In this framework, wireless channel usage and sensor node energy are allocated efficiently such that total application performance is maximized.…”

Rate Allocation for SVC transmission in Energy-Constrained Wireless Sensor Networks

“…We use the power dissipation model proposed in [14] to consider energy consumption of sensor nodes. Since sensor nodes encounter much tighter energy constrains than sinks, we focus our power dissipation model on sensor nodes side and assume enough energy on sink side.…”

A hierarchical transport architecture for wireless sensor networks

“…When diverse sensor nodes with their own characteristics are involved, the objective of WSNs is no longer to simply maximize the sum of data rates from all the nodes, subject to certain constraints. The research community is in general agreement that there exists a severe bias in the rate allocation among sensor nodes of different types [2], [3] -in particular, a node with low demand is usually allocated a high bandwidth. To solve this problem, a flow control or resource allocation algorithm should be devised to cater for a variety of performance metrics depending on the type of the sensors.…”