As VLSI technology advances, the interconnection network represents a larger percentage of the total system cost and power consumption. In fact, a current trend in network design is to reduce the number of components. However, this leads to systems working closer to saturation point, and therefore an efficient congestion management technique is required. In that sense, RECN has been recently proposed for advanced switching (AS). RECN detects the formation of congestion trees and dynamically allocates queues for storing congested packets, thus, eliminating the HOL blocking introduced by congestion trees. These queues are deallocated when congestion vanishes. We have identified two shortcomings that may affect RECN scalability and implementation. Firstly, although RECN allocates queues in an efficient way, resource deallocation is performed in-order, thus losing efficiency and wasting resources. This leads to an excessive requirement of memory at switch ports. Secondly, both allocation and deallocation mechanisms involve the use of specific control packets not supported by the AS standard, thus preventing RECN implementation. In this sense we provide a detailed description of the current RECN deallocation mechanism. In this paper we present an enhanced RECN version (RECN-DD) where these problems have been eliminated. Specifically, we propose a new distributed queue deallocation mechanism that reduces the number of required resources and does not require the use of control packets. Moreover, we propose a new congestion notification mechanism that does not require non-standard AS packets. Instead, flow control packets are used to notify congestion, thus simplifying the implementation of RECN-DD in AS

In this paper, we propose a new congestion management strategy for lossless multistage interconnection networks that scales as network size and/or link bandwidth increase. Instead of eliminating congestion, our strategy avoids performance degradation beyond the saturation point by eliminating the HOL blocking produced by congestion trees. This is achieved in a scalable manner by using separate queues for congested flows. These are dynamically allocated only when congestion arises, and deallocated when congestion subsides. Performance evaluation results show that our strategy responds to congestion immediately and completely eliminates the performance degradation produced by HOL blocking while using only a small number of additional queues.