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Optical wide area networks using spring framework togenerate code 128a in asp.net web,windows application barcode pdf417 Assembly Queue Length Time threshold T Burst length threshold B P 1 P2 heavy load light load Time Figure 9.4 Burst length and time thresholds for burst assembly algorithms. After Yu et al.

(2004).. 2004 IEEE. B can be either xed or adju sted dynamically. Based on these thresholds, burst assembly algorithms can be classi ed into the following four categories (Yu et al., 2004):.

r Time-Based Assembly Algorithms: The rst category contains time-based burst assembly algorithms where a xed time threshold T is used as the criterion to send out a burst (i.e., the burst is transmitted after T time units).

r Burst Length Based Assembly Algorithms: The second category contains burst length based burst assembly algorithms where a burst length threshold B is used as the criterion to send out a burst (i.e., the burst is transmitted as soon as the aggregated burst reaches or exceeds B).

Each of the two aforementioned types of burst assembly algorithms suffer from some shortcomings at low and high traf c loads due to the fact that they consider only a single criterion (either time or burst length). To see this, consider Fig. 9.

4 which illustrates the impact of burst length threshold B and time threshold T on the transmission of a burst under heavy and light loads. Under light load, a burst length based assembly algorithm does not provide any constraints on the queueing delay of packets that wait for being aggregated into a burst of size B. As a result, burst length based assembly algorithms are unable to guarantee any bound on the maximum or average queueing delay.

As shown in Fig. 9.4, a time-based assembly algorithm could solve this problem since it will send out the burst after time T at point P2 in the gure, no matter how many packets the burst contains.

On the other hand, time-based assembly algorithms lead to longer average queueing delays than burst length assembly algorithms under heavy traf c. Unlike time-based assembly algorithms, under heavy traf c loads a burst length algorithm sends out the burst at point P1 in Fig. 9.

4 as soon as the burst length threshold B is crossed well before the. Optical burst switching Table 9.1. Forward resource reservation (FRR) parameters Parameter Tb Th Td a o De nition Time when a new burst starts to be assembled Time when corresponding control packet is sent Time when burst is sent Duration of burst assembly Offset between control packet and burst.

time threshold T is reached. swing barcode 128 Clearly, it is desirable to have a burst assembly algorithm that performs well under all traf c load conditions (i.e.

, a burst is sent out at P1 under heavy load and at P2 under light load), which gives rise to the third category of burst assembly algorithms. r Mixed Time/Burst Length Based Assembly Algorithms: The third category of burst assembly algorithms uses both a time threshold T and a burst length threshold B as criteria to send out a burst. Depending on the traf c loads and the values of parameters T and B, generally either threshold T or threshold B is crossed rst and the burst is transmitted.

In general, threshold T will be crossed before threshold B at light traf c loads and vice versa at heavy traf c loads. r Dynamic Assembly Algorithms: The fourth category of burst assembly algorithms makes use of dynamic thresholds, where either the time threshold T or the burst length threshold B or both are set dynamically according to network traf c conditions. Dynamic burst assembly algorithms are adaptive and therefore achieve an improved performance at the expense of an increased computational complexity compared to the rst three categories of burst assembly algorithms which use xed (static) thresholds.

It is important to note that burst assembly algorithms executed by OBS users at the edge of OBS networks help smooth the input IP packet process and reduce the degree of self-similarity of IP traf c (Yu et al., 2004; Ge et al., 2000).

This traf c smoothing effect of burst assembly algorithms simpli es traf c engineering (TE) and capacity planning of OBS networks. An advanced burst assembly algorithm, called forward resource reservation (FRR), was studied in Liu et al. (2003).

FRR deploys the following two performance-enhancing techniques: (1) prediction of the packet traf c arriving at edge OBS users, and (2) pretransmission of control packets in order to reduce the burst assembly delay incurred at the edge of OBS networks. FRR makes use of several parameters which are listed and explained in Table 9.1.

FRR comprises three steps and works as follows: 1. Prediction: As soon as the previous burst is assembled, a new burst starts to be assembled at time Tb by a given OBS user. Based on a linear prediction method, the OBS user predicts the length of the new burst.

2. Pretransmission: Instead of waiting for the new burst to be assembled completely, the OBS user constructs a control packet upon completion of the prediction of the.
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