Decentralized Flow Control Research Articles

Packet‐based feedback control of electrical drive and its application to trajectory tracking of manipulator

SummaryIn systems disconnected from the external grid, such as mobile robots and vehicles, the effective use of renewables and energy harvesting techniques helps a longer operation with less weight and space for batteries. Power packet dispatching system is a promising measure to manage the complex power flow created by such distributed power sources of various profiles. In the system, power is transferred as a pulse, and information tag is attached to the pulse power in voltage waveforms. The physical integration of power and information realizes a smooth inclusion of sources and loads of different profiles and their decentralized operation. This paper discusses the application of the system to load control. We propose a decentralized packet‐based feedback control scheme. The successful operation of the proposed scheme is confirmed by an application to an electrical drive. In addition, the application to trajectory control of 2‐degree‐of‐freedom manipulator reveals the possibility of a peak‐power reduction based on a demand response operation of the proposed scheme. The results contribute to a realization of decentralized flow control of power packets based on the convenience of both the sources and the loads.

A Simple Parallel Algorithm with an $O(1/t)$ Convergence Rate for General Convex Programs

This paper considers convex programs with a general (possibly nondifferentiable) convex objective function and Lipschitz continuous convex inequality constraint functions. A simple algorithm is developed and achieves an $O(1/t)$ convergence rate. Similar to the classical dual subgradient algorithm and the alternating direction method of multipliers (ADMM) algorithm, the new algorithm has a parallel implementation when the objective and constraint functions are separable. However, the new algorithm has a faster $O(1/t)$ convergence rate compared with the best known $O(1/\sqrt{t})$ convergence rate for the dual subgradient algorithm with primal averaging. Further, it can solve convex programs with nonlinear constraints, which cannot be handled by the ADMM algorithm. The new algorithm is applied to a multipath network utility maximization problem and yields a decentralized flow control algorithm with the fast $O(1/t)$ convergence rate.

Diffusion-Type Autonomous Decentralized Flow Control for End-to-End Flow in High-Speed Networks

SUMMARY We have proposed diffusion-type flow control as a solution for the extremely time-sensitive flow control required for high-speed networks. In our method of flow control, we design in advance simple and appropriate rules for action at the nodes, and these automatically result in stable and efficient network-wide performance through local interactions between nodes. Specifically, we design the rules for the flow control action of each node that simulates the local interaction of a diffusion phenomenon, in order that the packet density is diffused throughout the network as soon as possible. However, in order to make a comparison with other flow control methods under the same conditions, the evaluations in our previous studies used a closed network model, in which the number of packets was unchanged. This paper investigates the performance of our flow control method for an end-to-end flow, in order to show that it is still effective in more realistic networks. We identify the key issues associated with our flow control method when applied to an open network model, and demonstrate a two-step solution. First, we consider the rule for flow control action at the boundary node, which is the ingress node in the network, and propose a rule to achieve smooth diffusion of the packet density. Secondly, we introduce a shaping mechanism, which keeps the number of packets in the

NEW CONGESTION CONTROL SCHEMES OVER WIRELESS NETWORKS: DELAY SENSITIVITY ANALYSIS AND SIMULATIONS

This paper proposes two new congestion control schemes for packet switched wireless networks. Starting from the seminal work of Kelly (Kelly et al., Dec 1999), we consider the decentralized flow control model for a TCP-like scheme and extend it to the wireless scenario. Motivated by the presence of channel errors, we introduce updates in the part of the model representing the number of connections the user establishes with the network; this assumption has important physical interpretation. Specifically, we propose two updates: the first is static, while the second evolves dynamically. The global stability of both schemes has been proved; also, a stochastic stability study and the rate of convergence of the two algorithms have been investigated. This paper focuses on the delay sensitivity of both schemes. A stability condition on the parameters of the system is introduced and proved. Moreover, some deeper insight on the structure of the oscillations of the system is attained. To support the theoretical results, simulations are provided.

Optimal decentralized flow control of Markovian queueing networks with multiple controllers

A Markovian queueing network model is used to derive decentralized flow control mechanisms in computer communication networks with multiple controllers. Under the network optimization criterion, finding the optimal decentralized flow control that maximizes the average network throughput under an average network delay bound becomes a team decision problem. It is shown that the network optimization problem depends on the parameters of the network only through the conditional estimates of the total arrival and departure rates. Using linear programming, the network optimal control is demonstrated to be a set of window-type mechanisms. Under the user optimization criterion, each individual user maximizes its average throughput subject to a constraint on its average time delay. Finding the optimal decentralized flow control under the individual user's performance results in a multiple objective optimization problem and leads to a game theoretic formulation. Structural results which simplify the problem are presented. It is shown that the user optimization problem depends on the parameters of the network and the action of the other users only through the conditional estimate of the user service rate. The Nash equilibrium solution under the game theoretic formulation is demonstrated to be a set of window-type mechanisms. Finally, the class of decentralized flow control problems with Nash equilibrium solutions is characterized.

Flow Control Power is Nondecentralizable

Flow control in store-and-forward computer networks is appropriate for execution. A formal description of a class of decentralized flow control is given. The feasibility of maximizing power with such algorithms is investigated. On the assumption that communication links behave like M/M/1 servers it is shown that no decentralized flow control algorithm can maximize network power. Power has been suggested in the literature as a network performance objective. It is also shown that no objective based only on the users' throughputs and average delay is decentralizable. Finally, a restricted class of algorithms cannot even approximate power.