Joint buffer management and scheduling for input queued switches

Input queued (IQ) switches are highly scalable and they have been the focus of many studies from academia and industry. Many scheduling algorithms have been proposed for IQ switches. However, they do not consider the buffer space requirement inside an IQ switch that may render the scheduling algorithms inefficient in practical applications. In this dissertation, the Queue Length Proportional (QLP) algorithm is proposed for IQ switches. QLP considers both the buffer management and the scheduling mechanism to obtain the optimal allocation region for both bandwidth and buffer space according to real traffic load. In addition, this dissertation introduces the Queue Proportional Fairness (QPF) criterion, which employs the cell loss ratio as the fairness metric. The research in this dissertation will show that the utilization of network resources will be improved significantly with QPF. Furthermore, to support diverse Quality of Service (QoS) requirements of heterogeneous and bursty traffic, the Weighted Minmax algorithm (WMinmax) is proposed to efficiently and dynamically allocate network resources. Lastly, to support traffic with multiple priorities and also to handle the decouple problem in practice, this dissertation introduces the multiple dimension scheduling algorithm which aims to find the optimal scheduling region in the multiple Euclidean space

Scheduling algorithms for high-speed switches

The virtual output queued (VOQ) switching architecture was adopted for high speed switch implementation owing to its scalability and high throughput. An ideal VOQ algorithm should provide Quality of Service (QoS) with low complexity. However, none of the existing algorithms can meet these requirements. Several algorithms for VOQ switches are introduced in this dissertation in order to improve upon existing algorithms in terms of implementation or QoS features. Initially, the earliest due date first matching (EDDFM) algorithm, which is stable for both uniform and non-uniform traffic patterns, is proposed. EDDFM has lower probability of cell overdue than other existing maximum weight matching algorithms. Then, the shadow departure time algorithm (SDTA) and iterative SDTA (ISDTA) are introduced. The QoS features of SDTA and ISDTA are better than other existing algorithms with the same computational complexity. Simulations show that the performance of a VOQ switch using ISDTA with a speedup of 1.5 is similar to that of an output queued (OQ) switch in terms of cell delay and throughput. Later, the enhanced Birkhoff-von Neumann decomposition (EBVND) algorithm based on the Birkhoff-von Neumann decomposition (BVND) algorithm, which can provide rate and cell delay guarantees, is introduced. Theoretical analysis shows that the performance of EBVND is better than BVND in terms of throughput and cell delay. Finally, the maximum credit first (MCF), the Enhanced MCF (EMCF), and the iterative MCF (IMCF) algorithms are presented. These new algorithms have the similar performance as BNVD, yet are easier to implement in practice

On scheduling input queued cell switches

Output-queued switching, though is able to offer high throughput, guaranteed delay and fairness, lacks scalability owing to the speed up problem. Input-queued switching, on the other hand, is scalable, and is thus becoming an attractive alternative. This dissertation presents three approaches toward resolving the major problem encountered in input-queued switching that has prohibited the provision of quality of service guarantees. First, we proposed a maximum size matching based algorithm, referred to as min-max fair input queueing (MFIQ), which minimizes the additional delay caused by back pressure, and at the same time provides fair service among competing sessions. Like any maximum size matching algorithm, MFIQ performs well for uniform traffic, in which the destinations of the incoming cells are uniformly distributed over all the outputs, but is not stable for non-uniform traffic. Subse-quently, we proposed two maximum weight matching based algorithms, longest normalized queue first (LNQF) and earliest due date first matching (EDDFM), which are stable for both uniform and non-uniform traffic. LNQF provides fairer service than longest queue first (LQF) and better traffic shaping than oldest cell first (OCF), and EDDEM has lower probability of delay overdue than LQF, LNQF, and OCF. Our third approach, referred to as store-sort-and-forward (SSF), is a frame based scheduling algorithm. SSF is proved to be able to achieve strict sense 100% throughput, and provide bounded delay and delay jitter for input-queued switches if the traffic conforms to the (r, T) model

Scheduling Architectures for DiffServ Networks with Input Queuing Switches

ue to its simplicity and scalability, the differentiated services (DiffServ) model is expected to be widely deployed across wired and wireless networks. Though supporting DiffServ scheduling algorithms for output-queuing (OQ) switches have been widely studied, there are few DiffServ scheduling algorithms for input-queuing (IQ) switches in the literaure. In this paper, we propose two algorithms for scheduling DiffServ DiffServ networks with IQ switches: the dynamic DiffServ scheduling (DDS) algorithm and the hierarchical DiffServ scheduling (HDS) algorithm. The basic idea of DDS and HDS is to schedule EF and AF traffic According to Their minimum service rates with the reserved bandwidth and schedule AF and BE traffic fairly with the excess bandwidth. Both DDS and HDS find a maximal weight matching but in different ways. DDS employs a Centralized scheduling scheme. HDS features a hierarchical scheduling scheme That Consists of two levels of schedulers: the central scheduler and port schedulers. Using such a hierarchical scheme, the Implementation complexity and the amount of information needs to be Transmitted between input ports and the central scheduler for HDS are dramatically reduced Compared with DDS. Through simulations, we show That both DDS and HDS popup Guarantees a minimum bandwidth for EF and AF traffic, as well as fair bandwidth allocation for BE traffic. The delay and jitter performance of the DDS is close to That of PQWRR, an existing DiffServ supporting scheduling algorithm for OQ switches. The tradeoff of the simpler Implementation scheme of HDS is its slightly worse delay performance Compared with DDS

On Asymptotic Optimality of Dual Scheduling Algorithm In A Generalized Switch

Generalized switch is a model of a queueing system where parallel servers are interdependent and have time-varying service capabilities. This paper considers the dual scheduling algorithm that uses rate control and queue-length based scheduling to allocate resources for a generalized switch. We consider a saturated system in which each user has infinite amount of data to be served. We prove the asymptotic optimality of the dual scheduling algorithm for such a system, which says that the vector of average service rates of the scheduling algorithm maximizes some aggregate concave utility functions. As the fairness objectives can be achieved by appropriately choosing utility functions, the asymptotic optimality establishes the fairness properties of the dual scheduling algorithm. The dual scheduling algorithm motivates a new architecture for scheduling, in which an additional queue is introduced to interface the user data queue and the time-varying server and to modulate the scheduling process, so as to achieve different performance objectives. Further research would include scheduling with Quality of Service guarantees with the dual scheduler, and its application and implementation in various versions of the generalized switch model