As discussed in Chapter 2, service fairness issue regarding higher bandwidth requirement demands is a serious problem in EONs. As confirmed in [7] and [72] higher rate demands tend to be blocked much more often than lower rate demands. The level of unfairness across the various demand sizes may not always be acceptable by network operators demanding certain QoS requirements. Still, works studying and/or proposing solutions for service unfairness are very uncommon in the literature. In fact, after a literature review we have only found two articles that regard the service fairness problem. Indeed authors in [7] comment on the fact that the RSA algorithm articles they reviewed do not address this issue.
Some fragmentation-aware algorithms available in the literature may indirectly reduce unfairness. These algorithms, however, are not as effective in increasing service fairness as algorithms that focus on this purpose as analyzed in [7].
Authors in [7] and [72] propose spectrum partitioning and reservation as a means to increase service fairness in EONs. The algorithm proposed in [72] is described in Section 3.2. Simulations performance results in [72] indicate that DP have promoted the better level of fairness and decreased bandwidth blocking probability when compared to CS. SP presented lower level of fairness than DP but lower BBP than DP.
In [7] the authors propose a mechanism to promote fairness in EONs. Their proposal is developed to work in two rate EONs. Similar to SP algorithm in [72], the algorithm called Two Rate Reservation (TRR) partitions the spectrum for both dedicated and shared use. One spectrum range is reserved for the lowest bandwidth requirement connections, a second partition is reserved to serve only the highest BW requirement connections and a third spectrum may accommodate any of the two possible BW requirement demands. Each partition must have a previously calculated number of dedicated FSs.
When the shared partition has 0 FSs the TRR algorithm is referred to as Fixed RSA algorithm, where each group of demands is reserved a dedicated spectrum
band as in DP proposed by [72]. Demands with distinct rates may not share the same partition. In both algorithms proposed, first fit is implemented as spectrum allocation policy, and connections with a given BW requirement are accommodated from the left of the left border of their respective partitions.
Simulation performance results indicated that Fixed RSA algorithm provided a highest fairness level in detriment of highest blocking probability results when compared to TRR. TRR, on the other hand, presented higher fairness level when compared to the benchmark algorithms selected by the authors. However, TRR presented higher BP results than the benchmark algorithms.
The advantage of the work in [72] over [7], is that in [72] authors explain the optimum partitions size calculation, which is based on statistical data about each demand BW requirement arrival frequency and probability. In [72], the authors propose a solution for a three rate network. Authors present performance results based on the bandwidth blocking probability and do not do so on demands blocking probability results.
In general, dedicated spectrum partition and reservation solutions tend to increase the blocking probability of demands in the network. Thereupon, both [7] and [72] propose a spectrum band to be shared by all types of connections. This intermediate strategy provides better blocking probability results when compared to dedicated partitioning strategies.
4
Previous contributions
Before developing the Priority Realloc mechanism for EONs, we have developed other studies and proposals for differentiated services on optical networks. We have previously focused on WDM networks and to this end we have studied current available priority of service strategy alternatives and developed a mechanism that promotes differentiation of resources distribution according to different classes of service. This differentiated resources allocation follows a constraint model that determines the maximum bandwidth a given CT value connection may be assigned and/or the amount of resources that would be reallocated to a higher priority demand. Part of this work has been published in a conference paper, while other remains unpublished.
Besides the contribution of this previous work to the research area of optical networks, this work have also inspired the creation and development of Priority Realloc. For these reasons, in this chapter, we present the study we have developed on priority of service on WDM networks and explain the differentiated service mechanism we have proposed for WDM networks.
The study and analysis on differentiated priority of service for WDM networks is presented in Section 4.1. We developed a differentiated resources distribution mechanism for WDM networks to be implemented in an offline scenario (explained in Section 4.2) and another version of the mechanism that operates in a dynamic scenario (explained in Section 4.3.1). Both versions of the mechanism rely on the RDM, previously cited in Chapter 2, as bandwidth constraint model. The adaptation of the original RDM into the proposed mechanism is explained in Section 4.2.
4.1
Priority of connection request processing
We have studied the available differentiated service in MPLS networks, with routing performed by the PCE [67], so we could propose a similar strategy for WDM networks. Since WDM networks may be controlled by Generalized
Table 4.1: BW requested and BW assigned following BC model Priority field
equals to Description
Setup The same value as the demand’s set-up priority Hold The same value as the demand’s holding priority
The same value as the average of the demand’s Average holding and setup priority values
The same value as the difference between Difference the demand’s holding and setup priority values
Multi-Protocol Label Switching (GMPLS) protocol suite [78] in tandem with the PCE, an adaptation of strategy is possible.
We have analyzed the priority field described in [66] for the PCE with different values. The PCE centralizes the route and resource assignment tasks in a network. In order for the PCE architecture to properly accommodate the differentiated service characteristics of MPLS [79] it must follow some requirements when computing a path.
In the PCE architecture, a path computation request (PCReq) message contains the requisites for the constrained based path computation [80]. The Request Parameters Object (RP) contains a Priority field (Pri field) with possible values which may be used by the PCE scheduler to determine in what order among many requests that specific request would be processed. Therefore the higher the Priority value of a demand more likely it will be processed before other requests.
The Label Switched Path Attributes (LSPA) Object contains required attributes for the establishment of a lightpath [80]. It contains, among other requirements, the setup and holding priority attributes of the requested path. This requirement is not necessarily considered by a PCE but, when it is considered, a connection request with higher setup priority may preempt a current connection with lower holding priority value to use its resources.
We extended the aforementioned concepts to a WDM network and tested the impact on network performance when Priority fields have different values relating to the setup and holding priority values.
4.1.1
Results and analysis
We implemented WDM network simulations as described in [65], where we tested different values for the Priority field as described in Table 4.1.
Network simulation results indicate that when the Priority field value equals the difference between the demand’s setup and holding priority values the network blocking probability results are lower than the results achieved when the Priority field has the other tested values. However this Priority field value also presented the highest number of repeated connection request messages. A repeated connection request message refers to a request from a connection that was previously preempted.
Results also indicate that respecting the Priority field values, when ordering connection requests, increases the volume of resources assigned to demands with higher setup priority values. In this case the actual value of the priority field has little impact on the amount of resources assigned, even though when the value is equal to the demand’s holding priority value more bandwidth were allocated to lower setup priority value connections in detriment of the highest setup priority value connections.
In general, it is possible to conclude that the combined use of preemption policies and the Priority field value equivalent to the difference between the demand’s setup and the holding priority values is the most beneficial set of values in terms of performance. Once a preemption policy is implemented the demands priority field has direct impact on the WDM network performance.