Dragos Andrei

Integrated Provisioning of Sliding Scheduled Services Over WDM Optical Networks [Invited]

Many future Internet applications supported over optical networks may require large amounts of guaranteed bandwidth between two remote end hosts, but this bandwidth may not necessarily be needed immediately. To ensure a deterministic service, Internet customers may prefer to reserve network resources, e.g., lightpaths, in advance and may indicate an approximate time window in the future during which the bandwidth should be reserved for a certain period of time; however, the exact start time of the reservation is not specified, but can slide in the predefined time window. This type of user traffic is called ldquosliding scheduled traffic.rdquo Optical network design for provisioning sliding scheduled traffic is a highly complex task that has been dealt with in the literature by two-step approaches, which first schedule user demands in time and then perform their routing and wavelength assignment (RWA). We propose a scalable integrated design for the sliding scheduling provisioning problem (SSPP), based on the Lagrangean relaxation (LR) approach, which can jointly perform the scheduling and RWA of the demands. We first develop a new mathematical model for SSPP, to which it is suitable to apply the relaxation of some of the modelpsilas constraints. We use an integrated heuristic called IPSR (integrated provisioning of sliding requests), which is next enhanced with a cost assignment based on Lagrangean multiplier information, to serve as the primal algorithm for our LR approach (named IPSR-LR). We compare our approaches with an existing two-step heuristic algorithm for SSPP and show that both IPSR and IPSR-LR are able to outperform it. In addition, our numerical results show that IPSR-LR improves over IPSR under all typical experimental cases that we considered. Furthermore, we compare our approaches with the solutions provided by an integer linear program for the SSPP, which is, however, less scalable for large problem sizes compared with our algorithms.

Provisioning of deadline-driven requests with flexible transmission rates in WDM mesh networks

With the increasing diversity of applications supported over optical networks, new service guarantees must be offered to network customers. Among the emerging data-intensive applications are those which require their data to be transferred before a predefined deadline. We call these deadline-driven requests (DDRs). In such applications, data-transfer finish time (which must be accomplished before the deadline) is the key service guarantee that the customer wants. In fact, the amount of bandwidth allocated to transfer a request is not a concern for the customer as long as its service deadline is met. Hence, the service provider can choose the bandwidth (transmission rate) to provision the request. In this case, even though DDRs impose a deadline constraint, they provide scheduling flexibility for the service provider since it can choose the transmission rate while achieving two objectives: 1) satisfying the guaranteed deadline; and 2) optimizing the networks resource utilization. We investigate the problem of provisioning DDRs with flexible transmission rates in wavelength-division multiplexing (WDM) mesh networks, although this approach is generalizable to other networks also. We investigate several (fixed and adaptive to network state) bandwidth-allocation policies and study the benefit of allowing dynamic bandwidth adjustment, which is found to generally improve network performance. We show that the performance of the bandwidth-allocation algorithms depends on the DDR traffic distribution and on the node architecture and its parameters. In addition, we develop a mathematical formulation for our problem as a mixed integer linear program (MILP), which allows choosing flexible transmission rates and provides a lower bound for our provisioning algorithms.

Deadline-Driven Bandwidth Allocation with Flexible Transmission Rates in WDM Networks

We investigate dynamic bandwidth allocation with flexible transmission rates for deadline-driven requests (DDRs) in wavelength-division multiplexing (WDM) mesh networks. DDRs provide more scheduling flexibility to the network operator compared with typical requests with no deadline and requiring a fixed bandwidth. By choosing the bandwidth and adapting the transmission rate depending on network state, the networks performance can be improved. We investigate several bandwidth allocation policies and study their benefits on network performance. Our investigation shows that an adaptive policy generally performs the best. Further improvement can be achieved by using dynamic readjustment of the allocated bandwidth.

On-Demand Provisioning of Data-Aggregation Sessions Over WDM Optical Networks

We consider efficient network provisioning algorithms for applications that aggregate large data files from multiple remote sites to a central facility (where the aggregated data is further processed). Many important bandwidth-hungry scientific applications use such data aggregation, and it is important to efficiently use network resources to meet their requirements. We term an entire large-scale data-aggregation session as a data-aggregation request (DAR). In this paper, we investigate the problem of on-demand provisioning of DARs over a wavelength-division multiplexing (WDM) backbone network infrastructure. Our DAR provisioning problem is challenging, as for each DAR we need to jointly identify lightpaths (route, assign wavelengths, and groom) for each of the to-be-transferred files, and schedule DARs file transfers in time. We first model our DAR provisioning problem mathematically as a mixed integer linear program (MILP); to solve our problem in practice, we propose a DAR provisioning algorithm (named DARP). From our numerical results, we find DARP to be efficient when compared with other benchmark algorithms. We study DARPs performance for a varying number of aggregating sites deployed in the network (i.e., sites with supercomputer facilities) and perform a detailed sensitivity analysis on several parameters of our problem. We also investigate the effect of partitioning the data to be transferred into pieces and conclude that, if the partitioning method is carefully designed, slight improvement over the approach that transfers the whole file (DARP) is possible.

Provisioning Subwavelength Multicast Sessions With Flexible Scheduling Over WDM Networks

The distribution of large data sets from a centralized node to several destination sites is frequently required by many data-intensive networking applications; this distribution can be efficiently achieved by the means of multicasting. Multicasting has been typically considered for on-demand applications and services, e.g., video-on-demand, IPTV, etc., which usually require start of data transmission immediately. We consider that multicast sessions can be provisioned starting with flexible times and that the multicast client can specify a maximum allowed time by which all data needs to be delivered to destinations. This is true for e-Science and high-performance applications, in which data distribution is not necessarily immediate. In this paper, we study the problem of provisioning dynamic multicast data-distribution requests (MDDRs) with flexible scheduling over optical WDM networks. We consider the practical case of fractional-capacity multicast sessions that require less than the entire wavelength capacity (nodes are equipped with multicast-capable opaque switches). We devise provisioning methods based on the multicast tree (or light-tree) distribution model. In our first approach (named Rand), we generate multiple randomized alternate trees on which we try to provision the multicast session and then assign wavelengths and schedule the session. In our second approach (named AllSlots), we dynamically generate light-trees depending on the network state. In our next approach (named Break), when provisioning an entire tree fails, we try to “break” the tree into time-independent subtrees. We also study the impact of allowing data to be buffered at intermediary nodes and then transmitted toward destinations (method named Buffer) and consider an approach that partitions the data sets. Finally, we study the impact of the switch architecture on our provisioning by restricting our approaches to full-wavelength MDDRs.

On-Demand Provisioning of Data-Aggregation Requests over WDM Mesh Networks

Many large-scale scientific applications need to aggregate large amounts of data from multiple distributed sites to a centralized facility. We call such a request as a data-aggregation request (DAR). In this study, we investigate the novel problem of on-demand DAR provisioning over a wavelength-division multiplexing (WDM) backbone network. We provide a mathematical formulation for our problem as a mixed integer linear program (MILP). To solve large versions of our problem, we propose a DAR provisioning heuristic (called DARP). We use the MILP with various objectives as a benchmark for studying the performance of DARP.

Provisioning of Deadline-Driven Requests with Flexible Transmission Rates in Different WDM Network Architectures

We investigate the problem of provisioning deadline-driven requests with flexible transmission rates in WDM mesh networks. We analyze the networks performance and cost for different node architectures and for different traffic distributions.

A novel approach to provision differentiated services in survivable IP-over-WDM networks

IP-over-WDM networks are starting to replace legacy telecommunications infrastructure and they form a promising solution for next-generation networks (NGNs). Survivability of an IP-over-WDM network is gaining increasing interest from both the Internet research community and service providers (SPs). We consider a novel static bandwidth-provisioning algorithm to support differentiated services in a survivable IP-over-WDM network. We propose and investigate the characteristics of both integer linear program (ILP) and heuristic approaches to solve this problem. In the heuristic method, we propose backup reprovisioning to ensure network resilience against single-node or multiple-link failures. Illustrative examples compare and evaluate the performance of the two methods in terms of capacity-usage efficiency and computation time.