Apresentação feita em 2005 no Annual Simulation Symposium.
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Apresentação feita em 2005 no Annual Simulation Symposium. Apresentação feita em 2005 no Annual Simulation Symposium. Presentation Transcript

  • Modeling and Simulation of a LFVC Scheduler Prof. Antonio M. Alberti INATEL: Instituto Nacional de Telecomunicações National Institute of Telecommunications Santa Rita do Sapucai Brazil
  • Modeling and Simulation of LFVC Scheduler Presentation Outline Introduction Leap Forward Virtual Clock Developed Model Interaction Between LFVC and ATM Network Models Model Validation Performance Evaluation Final Remarks
  • Modeling and Simulation of LFVC Scheduler Introduction One of the most important issues in integrated services networks is the choice of the service discipline to be used at each packet queuing point in order to select the appropriate packet service order. Why? 1. Service disciplines affect network performance not only in terms of delay and loss, but also in terms of throughput and fairness. 2. Service disciplines become a key to offer QoS isolation among connections/flows in the network.
  • Modeling and Simulation of LFVC Scheduler Introduction Amongst current service disciplines, the ones that approximate Generalized Processor Sharing (GPS) have had a lot of success satisfying such requirements. In 1993, Parekh and Gallanger demonstrated that employing GPS servers in network switches, end-to-end QoS guarantees can be provided for a connection. However, GPS is an idealized discipline that does not can be implemented in real world.
  • Modeling and Simulation of LFVC Scheduler Introduction So Parekh and Gallanger proposed a packet-based approximation to the GPS, which was called Packet-by- Packet Generalized Processor Sharing (PGPS). In 1996, Bennett and Zhang developed a new algorithm to approximate the GPS called Worst-case Fair Weighted Fair Queuing (WF2Q). Bennett and Zhang have demonstrated that WF2Q can work almost identical as GPS.
  • Modeling and Simulation of LFVC Scheduler Introduction Several other service disciplines have been developed since then. However, according to Suri et. al., just two disciplines can work almost identical as GPS: WF2Q and Leap Forward Virtual Clock (LFVC). In addition, there are two important differences among these algorithms: 1. LFVC is simpler to implement than WF2Q. 2. LFVC has a smaller computational overhead .
  • Modeling and Simulation of LFVC Scheduler Introduction These factors motivated us to implement LFVC algorithm in the context of an ATM network model previously developed to trustworthily evaluate QoS in ATM networks through simulation. The LFVC algorithm is fundamental in this network model, since very simple scheduling algorithms aren’t capable to capture service differences among connections. Our LFVC scheduler model interacts with the other models from this model set.
  • Modeling and Simulation of LFVC Scheduler Leap Forward Virtual Clock LFVC is a work-conserving fair-share scheduler. It will be never turned off if there are cells waiting for service. An ATM cell flow f which temporarily has used more bandwidth than allocated through a weight φf can be disciplined by placing the exceeding cells in a low priority queue L. However, well-behaved cell flows are stored in a high priority queue H.
  • Modeling and Simulation of LFVC Scheduler Leap Forward Virtual Clock Virtual clock service disciplines work allocating tags for each cell waiting for service. These tags represent the system clock value, when a cell will be served. Therefore, ATM cells are served in an increasing order of their tags. Just cells in the H queue are served. Cells in the L queue must be transferred to the H queue, in order to be served.
  • Modeling and Simulation of LFVC Scheduler Leap Forward Virtual Clock So, how long can the cells can be maintained in the L queue without the risk of an excessive delay? The maximum delay that cell c can suffer is: T (c ) − t s ≥ ∆ f T (c ) is the value of tag for cell c; t s is the current virtual clock value; ∆ f is the time required for cell c be served with the rate allocated to flow f.
  • Modeling and Simulation of LFVC Scheduler Leap Forward Virtual Clock It still remained another problem: what happens if all flows have been transferred for queue L and queue H becomes empty? The solution for this problem was to advance the server clock as far forward as possible, without violating the delay invariant of any flows in L. After the leap forward step, at least one active flow in L becomes eligible for transferring to H.
  • Modeling and Simulation of LFVC Scheduler Developed Model To implement the H and L queues, a priority queue data structure was used. Besides priority queues H and L, the original algorithm uses a FIFO queue for each flow f. This queue is called Qf. In fact, it is the queue Qf that stores the cells, while the H and L priority queues just handle the service order and which flow is oversubscribed or not. In our implementation, this per-flow queue already exists in another model of the ATM models set: Per-VC Queuing model.
  • Modeling and Simulation of LFVC Scheduler Developed Model The developed model has two main algorithms: ReceiveCell: To receive a new cell in the LFVC scheduler. It has one subroutine: • ProcessHead: to process the head of the Qf queue. TransmitCell: To transmit a cell to outside the scheduler. This algorithm has two subroutines: • TransferCells: to transfer cells from the L queue to the H queue. • ServiceCell: to serve a cell whose token waits in the H queue.
  • Modeling and Simulation of LFVC Scheduler Developed Model ReceiveCell ReceiveCell (t m) Looks for the occupation of the queue Q f . Q f = 1? Yes Call ProcessHead Q f No End
  • t m - Arrival time of a cell from flow f. t f - Current tag of a flow f. Modeling and Simulation of LFVC Scheduler Developed Model t fprev - Previous tag of a flow f. φ f - Flow f weight. ProcessHead Subroutine Q f - FIFO queue for flow f. ProcessHead Q . f ∆ f - Time period required for the (t m) transmission of a flow f cell in the rate allocated for this flow. t fprev = t f t s - Current scheduler timer. Looks for the pointer of the τ - Transmission frames period. cell in the head of the ρ - Rounding parameter. queue Q f . 1 SC - Scheduler capacity in cells/second. τ= SC tl - Service time. prev Recover t f and φ f . Schedule cell in the H t f ≤ ts + ∆ f + τ + ρ ? Yes priority queue with the tag field set up to t f . 1 ∆f = φ f .SC No Schedule cell in the L priority queue with the tag A t f = max (t s , t fprev ) + ∆ f field set up to t f − ∆ f .
  • Modeling and Simulation of LFVC Scheduler Developed Model Scheduler is ProcessHead Subroutine A “turned on”? No Schedule cell transmission of the H queue to the time t m - Arrival time of a cell from flow f. instant equal to the Turn on scheduler. t f - Current tag of a flow f. beginning of the next frame period. t fprev - Previous tag of a flow f. Yes φ f - Flow f weight. Q f - FIFO queue for flow f. ∆ f - Time period required for the There are cells in Turn off scheduler. No transmission of a flow f cell in the H or L queues? the rate allocated for this flow. t s - Current scheduler timer. Yes τ - Transmission frames period. ρ - Rounding parameter. Schedule cell transmission SC - Scheduler capacity in cells/second. of the H queue to the time instant t m + τ . tl - Service time. Return
  • Modeling and Simulation of LFVC Scheduler Developed Model TransmitCell TransmitCell ( tl ) Call TransferCells H queue is No Call ServiceCell empty? Yes Turn off the scheduler. End
  • Modeling and Simulation of LFVC Scheduler Developed Model TransferCells Subroutine TransferCells While there are cells in L If empty Return No queue. If H queue is k min ≤ t s + τ + ρ Yes t s = max (t s , (k min − ρ )) empty? No Yes Transfer cell to H queue. Loop end
  • Modeling and Simulation of LFVC Scheduler Developed Model ServiceCell Subroutine ServiceCell Schedule an event to carry the served cell to the next model at the instant t end . Remove cell from head of H queue. ts = ts +τ Schedule an event to the Per-VC Queuing informing that the cell must be removed from the Schedule processing of queue Q f . the Q f queue head to the instant tl . Calculate end of service time t end = tl + τ . Return
  • Modeling and Simulation of LFVC Scheduler Interaction Between LFVC and ATM Network Models LFVC model was implemented as a Scheduler (S) model in the ATM Network Model. LFVC is used to define the service order of the cells stored in Queuing Structure (QS) models, such as Per-VC Queuing. The weight (φf) of each flow f is calculated by a Connection Admission Control (CAC) model when a new connection is being established.
  • Modeling and Simulation of LFVC Scheduler Interaction Between LFVC and ATM Network Models Legend: General Application Traffic Managers Delete Connection Connection DC Layers Requesting Ending and Conclude and Deleting Activate NC DC Traffic Switch and NC Source Cell Flow Traffic Traffic Receiver Source CAC Switch Fabric Packet Flow To an To an BM TP Queuing ATM ATM QS Structure client network SD Broadband Terminal Equipment model model S S Scheduler QS ATM Adaptation Layer S Connection CAC Admission BTE ATM Layer Switch ATM Layer Control To other Buffer ATM BM Input Physical Output Physical Input Physical Output Physical Management network Layer Layer Layer Layer model Selective SD Discard QS QS QS QS Traffic TP S S S S Policing CAC CAC CAC CAC BM BM BM BM SD SD SD SD TP TP TP TP To another ATM network model
  • Modeling and Simulation of LFVC Scheduler Model Validation Model validation was done through service order analysis. There are 10 applications (1-10) transmitting exactly 1 cell at time 0. For these applications, we configured a weight 0.05. One more application (11) transmits 10 cells starting at time 0, with a cell interval equals to 1 second. This application has a weight 0.5.
  • Modeling and Simulation of LFVC Scheduler Model Validation Evolution of the LFVC variables when cells are processed by ProcessHead subroutine at the time instant tm.
  • Modeling and Simulation of LFVC Scheduler Model Validation Occupation of the FIFO queue for flow f (Qf) in the Per-VC Queuing model. LFVC model produced the same service order shown by Suri et. al.
  • Modeling and Simulation of LFVC Scheduler Performance Evaluation Network Topology
  • Modeling and Simulation of LFVC Scheduler Performance Evaluation ATM Client Technologies Models Set Up App_0 up to App_2: They established connections to the App_5 using nrt-VBR service category. They transmitted a MPEG-4 Simple Program Transport Stream previously adapted to be carried over ATM networks. The ATM traffic contract elements are configured according with:
  • Modeling and Simulation of LFVC Scheduler Performance Evaluation ATM Technology Models Set Up BTE_0, Switch_0 and BTE_1: They used the following models: • Per-VC Queuing Structures • LFVC Schedulers • Effective Bandwidth Allocation Algorithms • Dynamic Partitioning Algorithms • CLR Selective Discard Algorithms
  • Modeling and Simulation of LFVC Scheduler Performance Evaluation Simulations Set Up Three applications scenarios have been considered in simulations: I. Just App_0 transmits. II. Applications App_0 and App_1 transmit. III. App_0, App_1 and App_2 transmit. For each scenario we run 8 simulations. In each of them, BTE_0, BTE_1 and Switch_0 QSs capacity were set to 16000, 8000, 4000, 2000, 1000, 500, 100 and 50 cells, respectively.
  • Modeling and Simulation of LFVC Scheduler Performance Evaluation Numerical Results Weight φi allocated by CAC algorithm for connections 0, 1 and 2 considering queuing structure capacities ranging from 16000 cells (left) to 50 cells (right).
  • Modeling and Simulation of LFVC Scheduler Performance Evaluation Numerical Results Mean per-VC queuing occupation in the output queuing structure of BTE_0.
  • Modeling and Simulation of LFVC Scheduler Performance Evaluation Numerical Results Mean cell delay in the output queuing structure of BTE_0.
  • Modeling and Simulation of LFVC Scheduler Performance Evaluation Numerical Results Mean cell loss ratio in the output physical layer of BTE_0.
  • Modeling and Simulation of LFVC Scheduler Final Remarks The LFVC model interacts with other models of the ATM model set, improving its quality. Numerical results validated our model, since it produced the same service order than the original algorithm. Results briefly demonstrated how our model can be used to analyze QoS in ATM networks. Results showed that LFVC scheduler is capable of isolating traffic effects among ATM connections. Future works include a performance comparison between LFVC scheduler and WF2Q scheduler.
  • Thank You! alberti@inatel.br