Resource allocation and congestion control in task-oriented distributed sensor networks

Abstract

Resource allocation and congestion control are two interrelated critical issues that arise in a task-oriented distributed sensor network. An effective resource management policy must account for these and their impact on the overall objectives of the network. In this paper, the viability of a virtual per-flow framework for addressing both resource allocation and congestion control in an integrated environment is demonstrated. In this framework, the resources being allocated to a physical buffer at a decision node are established by allocating and maintaining certain virtual resources to each incoming data flow. The virtual per-flow framework allows the design of controllers for each link independently of the others thus enabling a decoupled analysis and allowing one to incorporate different delay models and nonlinearities for each input data link. The effectiveness of the per-flow strategy is demonstrated via the design of a robust H(infinity )-norm based feedback controller that ensures extremely good tracking of a dynamically changing set-point of a decision node buffer of a distributed sensor network. The design is robust against the time-varying and uncertain nature of network-induced delays.