Quality of Service Management in GMPLS-based Grid OBS Networks Rafael Esteves
Antonio Abelém
Michael Stanton
Universidade Federal do Pará Rua Augusto Corrêa, 01 Belém, Brazil
Universidade Federal do Pará Rua Augusto Corrêa, 01 Belém, Brazil
Universidade Federal Fluminense Rua Passo da Pátria, 156 Rio de Janeiro, Brazil
[email protected]
[email protected]
[email protected]
as an external component. Now, the tendency is to regard the network as a grid resource, just like the processors, memory and input/output devices, that provides new alternatives for service integration [2].
ABSTRACT This paper proposes an architecture for the establishment of routes with absolute QoS constraints for optical burst switched grid networks. This model uses traffic engineering provided by GMPLS to build LSPs that matches the required performance in response to a request made by the user/application of the grid. Results show that the proposal is capable of enforcing QoS by reducing the loss experienced by burst classes and allowing a better utilization of the computing resources.
Due to the large volume of data manipulated, a grid needs a robust communication infrastructure that is appropriate to the characteristics of this model. In particular, recent advances in optical communications have been made in order to make alloptical networks capable of supporting new network services, such as grid applications, which may have strict performance requirements.
Categories and Subject Descriptors C.2.3 [Computer-Communication Operations – network management
Networks]:
Network
In this context, the all-optical switching paradigm, which attempts to eliminate the existing limitations of electronic switching, and its different alternatives (lambda switching, packet switching and burst switching) appears as an alternative that turns these nextgeneration optical networks into the best candidates for grid computing. Specifically, optical burst switching (OBS) [3] presents some advantages compared to the other all-optical switching alternatives, like high link utilization and low processing and synchronization overhead, and is easily integrated with grid computing as jobs can be mapped to optical bursts [4].
General Terms Management, Design, Performance.
Keywords Optical Burst Switching, Quality of Service, Grid Networks, Traffic Engineering.
A recurrent discussion is about the control plane used for the functions of routing resource reservation and failure recovery, among others. There are centralized approaches for a control plane that are best suited for situations requiring a more precise and flexible resource reservation, because in these centralized planes we can have a complete view of all resources.
1. INTRODUCTION The grid is a model that proposes the use of computational resources from several machines situated in different locations to solve problems that demand great computational power [1]. In addition to computers, a grid is composed of data repositories, scientific instruments and visualization devices, amongst others, which offer great opportunities for collaboration.
A distributed control plane is adequate when there is a need to establish connections rapidly and with resource discovery capabilities [5]. The GMPLS (Generalized Multiprotocol Label Switching) architecture [6] is a great option to build a distributed control plane due to its suitability to optical networks, when the labels are used to represent the wavelengths in the fiber, and because of its support for traffic engineering. The current trend is to consider a hybrid alternative, with the coexistence of centralized and distributed functionalities, which would provide broader support for the demands of grid computing.
Computer networks are basic building blocks to for grid construction, and efforts are being directed to developing communication models more suited to the needs of grid computing. One important aspect is the change in the way computer networks are seen in the context of grid computing. Until now, the network infrastructure that supports grid computing has been considered an important component, although not one fully integrated with other grid resources, and seen more
The objective of this paper is to propose an architecture to provision network routes that satisfy the performance constraints of a grid job. This architecture is based on optical burst switching and on the utilization of a control plane that combines GMPLS signaling with a component that stores information about grid resources (both computing and network resources). This component, called the Grid OBS Connection Server, processes
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requests about the availability of resources to handle a job and calculates a possible route that satisfies the QoS constraints of the request. With this information, the GMPLS signaling is used to reserve all the resources along the path.
3. ARCHITECTURE FOR CONSTRAINTBASED LSP SELECTION IN GRID OBS NETWORKS 3.1 GOBS Connection Server
In addition to this introductory section, the paper is made up of five other sections. Section 2 presents some concepts related to optical burst switched networks in the context of grid computing, section 3 describes the architecture proposed for LSP (Label Switched Path) calculation in Grid OBS networks. The simulation results are shown in section 4. Finally, section 5 mentions related work and section 6 presents conclusions and some possibilities for future research.
To allow the selection of a route that attends the requirements of a grid application, it is necessary that some resource information be made available to the control and management planes. We assume that this information is stored in components responsible for determining the best path that matches the application’s requirements. After that, GMPLS routing and signaling protocols make effective resource reservations for the application. The component that stores grid resource information and calculates deterministic paths for an application will be called a GOBS Connection Server. Through queries made by the grid user/application, the GOBS Connection Server verifies which possible routes are best suited to a specific request.
2. GRID OBS NETWORKS Communication networks need to be adapted to grid computing because they are fundamental to the viability of the services offered by the grid. Many research initiatives are being led to create new communication models for grid computing. At this point, next-generation optical networks based on all-optical switching and on the utilization of advanced control planes are seen as major drivers to achieve this.
There are basically two types of resources in the context of this study. A computing resource is a usually a grid node that process and/or stores grid jobs. A network resource is an optical switch. From now we use grid node to refer to computing resources and network node for network resources.
In the context of all-optical networks there are basically three switching approaches: lambda switching, packet switching and burst switching. Optical burst switching attempts to overcome the limitations of the other alternatives like low resource utilization and high implementation complexity [7] [8]. In OBS, single packets are assembled into units called bursts that are transmitted in the optical domain. In general, prior signaling is carried out to reserve network resources along a route, in order to build an alloptical path. After a short time interval, called the offset time, the burst is sent to the destination in the all-optical domain.
When a node is inserted in the grid it needs to be registered at a specific GOBS Connection Server, which will store the information related to that node. This information refers to the type of the node (grid or network), processing and storage capacity, current blocking and class of service. The structure suggested for the GOBS Connection Server is presented below and is exemplified in Table 1. Figure 1 illustrates the GOBS Connection Server in a typical context.
Optical burst switching has as its main advantage high network utilization, since resources are reserved only if there is traffic demand and they are released as soon as the burst has passed. Also, there is low signaling latency due to the lack of confirmation (in most signaling schemes) and a simpler implementation compared to optical packet switching, since the switching performance required for handling bursts is lower than for packets. Grid networks based on lambda switching present some disadvantages, as stated in [9]. A dedicated path to every request in a grid environment would lead to very high costs. Requests in a grid are very unpredictable due to the high number of users; therefore networks based on lambda switching are not suited for these cases. Also, there are situations where the duration of a path reservation is much smaller than the path setup time. Optical burst switching is been considered as a candidate for grid computing for many factors [4]: Application jobs can be mapped directly to optical bursts due to the variable granularity of the bursts which allow different traffic profiles. The separation between control data and application data allows an all-optical transmission of the data bursts without signal conversion from the optical to the electronic domain. Also, since the control packets (BCP – Burst Control Packet) in OBS networks are processed electronically, new features can be added for grid computing, like resource discovery.
•
Type of node (type): Defines if a node is a grid node or a network node.
•
Available processing capacity (processing): The current processing capacity of a node measured in billions of floating point operations per second (GFLOPs). Applicable to grid nodes only.
•
Available storage capacity (storage): The current storage capacity of a node (in megabytes). Applicable to grid nodes only.
•
Blocking Probability (blocking): Applicable to network nodes only. This parameter is obtained on-line based on the number of blocked requests divided by the total number of requests.
•
Class of service (qos_class): Needed for service differentiation. Applicable to network nodes only.
Table 1. Example of an entry in a GOBS Connection Server
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Node
Type
Processing
Storage
Blocking
QoS Class
0
grid
2
1024
-
-
1
network
-
-
0.001
0
2
grid
5
512
-
-
3
network
-
-
0.03
2
4. RESULTS 4.1 Simulation description We conducted several simulation studies in order to evaluate the impact of the proposed architecture in the overall performance of a Grid OBS network. The simulation tool used was ns-2 (version 2.32) [11]. The topology used in the simulations is illustrated in Figure 2. The nodes that generate grid jobs are numbered 0, 1 and 2. Nodes 20 to 27 are grid computing nodes. The remaining nodes (3 to 19) are network nodes (optical switches). The links have a capacity of 10 Gbps and a propagation delay of 1 millisecond. Each link has 8 wavelengths. The total traffic load is divided equally for the three classes.
Figure 1. GOBS Connection Server
We defined three service classes for this study. Class 0 has the highest priority and class 2 has the lowest. Table 2 shows the constraints associated with each class.
3.2 Route Selection Route selection in this context is actually a multi-objective search problem, that is, starting from a space composed by grid nodes, which are connected to other nodes, a search for a path is performed based on all application constraints. This selection must consider parameters like the blocking probability currently experienced by bursts in the nodes and the processing and storage capacities available at a grid node. Since in a grid there is no determination of which node is going to be responsible for handling the task, we consider an anycast approach [10] for resource reservation. The destination is fixed at the moment a path is calculated in response to a request to the GOBS Connection Server. After this, GMPLS explicit signaling reserves all the resources along the path. A search algorithm to allow route selection for an application will now be described. The objective of this algorithm is to return an explicit route to the OBS edge node that requested the path. This response contains a route that matches the task demands and will be used as input information for GMPLS signaling protocols.
Figure 2. Topology used in simulations Next, there is a high-level description of the search algorithm. Table 2. Constraints associated with each QoS class Route selection: 1: Determine the source node, mark source node as checked. 2: Starting from the source, check the next reachable nodes. Include the source in the explicit route vector. Analyze the first reachable node. 3: Check the type of the node. 4: If it is a grid node and it has not been checked: 5: Check if there is available processing/storage capacity and mark as checked. In the case that the request can be matched include this node in the explicit route vector. 6: If it is a network node and it has not been checked: 7: Check if the service levels (blocking) are within the defined specifications and mark as checked. In the case that the request can be matched include the downstream node of the link in the explicit route vector. 8: Continue with the breadth-first search (repeat from step 3) until it reaches a grid edge node capable of handling the request (step 5). 9: If no path can be found then use a random destination.
QoS Class
Maximum Blocking
0
0.01
1
0.05
2
0.1
The sizes of the jobs are exponentially distributed with a mean of 1.5 megabytes [12], the processing demand is defined as a percentage of the total processing capacity also exponentially distributed, with a mean of 20%. The grid nodes (20 to 27) have total storage and processing capacities of 1 gigabyte and 15 GFLOPS, respectively. The inter-arrival time of jobs follows a Poisson process. The offset time is 3 milliseconds. We use an admission control mechanism similar to the dynamic wavelength grouping proposed in [13] where a maximum number of wavelengths are associated with each service class, but there is no imposition of which wavelength is associated with a particular
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class. We defined class 0 to have 5 wavelengths, class 1 to have 3 and class 2 to have only 1 wavelength.
4.2 Result analysis Figure 3 shows the blocking probability for all service classes using the proposed route discovery scheme compared to default routing.
Figure 5. Mean storage utilization at grid nodes For storage the load is better balanced between the nodes, due to the high traffic load offered to the network, and the route calculation has little influence in the results, except for nodes 21 and 27 which have an higher increase in their storage utilization. The mean end-to-end delay of a burst is illustrated in Figure 6.
Figure 3. Blocking probability vs. Class of service It should be observed that the GOBS Connection Server allows for the reduction of the blocking probability in a general way for all service classes. This is due to the rerouting of bursts to other destinations, which allows for a reduction in the traffic load sent to a node and, in consequence, results in a smaller loss rate. It is important to point out that all the blocking values are within the constraints defined for each service class. We also conducted an analysis of the utilization of the grid nodes by evaluating the utilization of processing capacity of a grid node (20 to 27). Figures 4 and 5 illustrate the mean processor and storage utilization for the grid nodes.
Figure 6. End-to-end delay The best delay result is for default routing. The increase in the delay is a consequence of several queries to the GOBS Connection Server, but, as can be seen, the difference is not too high. Figure 7 shows the proportion of requests that could not be guaranteed as a result of a query to the GOBS Connection Server which was not successful in finding an adequate path for the burst.
Figure 4. Mean processor utilization at grid nodes It is possible to observe that our proposal can reduce the processing load at node 23, since it distributes these jobs to several grid nodes, illustrating the anycast routing feature of the architecture. Figure 7. Proportion of unsuccessful requests
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Results show that, in default routing, for traffic loads above 25 erlangs, the majority of requests cannot be served adequately by the GOBS Connection Server. However, using the proposed LSP calculation scheme, the number of unsuccessful requests is below 30% of the total for loads above 40 erlangs.
8. REFERENCES [1] Foster, I. Grid: A New Infrastructure For 21st Century Science, Physics Today, 2002. [2] Travostino, Franco; Mambretti, Joe.; Kamous-Edwards, Gigi. Grid Networks: Enabling Grids with Advanced Communication Technology. John Wiley and Sons, 2006.
5. RELATED WORK
[3] Chen, Y. Qiao C. e Yu, X. Optical burst switching: a new area in optical networking research, IEEE Network, vol.18, pp.16-23, May 2004.
Some anycast algorithms for OBS grid networks are presented in [10]. These algorithms differ in the way they perform burst destination assignment and burst deflection. A number of heuristics is proposed to deal with these issues. Our proposal attempts to extend this anycast concept to the core nodes in addition to destination nodes since it takes in consideration network resource information to make the path calculation.
[4] Simeonidou, D.; Nejabati, R.; Ciulli, N. (Editors). Grid Optical Burst Switched Networks (GOBS): Informational Track: draft-ggf-ghpn-GOBS-1. Jan, 2006. [5] Habib, I.W.; Qiang Song; Zhaoming Li; Rao, N.S.V. Deployment of the GMPLS control plane for grid applications in experimental high-performance networks Communications Magazine, IEEE, Vol.44, Iss.3, March 2006, Pages: 65- 73.
In [14] the authors propose an architecture based on the existence of active elements called active OBS routers and on a two-stage signaling scheme. In the first phase there is an active burst responsible for inform the constraints of the job to the active core nodes and for resource discovery. Next, in the second phase, the normal burst in sent towards the selected destination. Our proposal has similar aspects since it has a two-stage signaling, where the first phase is the query to the GOBS Connection Server and the second phase is the explicit signaling in response to this query. The main difference is that we use a centralized approach for route discovery, but not for signaling. In this way, we try to take advantage of a complete view of resources and a rapid signaling architecture.
[6] Mannie E. (Editor). Generalized Multi-Protocol Label Switching (GMPLS) Architecture. RFC 3945. Outubro, 2004. [7] Chen, Y. Qiao C.; Yu, X. Optical Burst Switching: a New Area in Optical Networking Research. IEEE Network, vol.18, p.16-23, Maio, 2004. [8] Vokkarane, V. M.; Jue, J. P. Optical Burst Switched Networks. Springer, 2005. [9] De Leenheer, M. et al. An OBS-based Grid Architecture. In: Workshop on High-Performance Global Grid Networks (Globecom, 2004). Proceedings of the IEEE Global Communications Conference, Dallas, TX, USA, Nov. 2004.
6. CONCLUSIONS This paper presented a model for the establishment of constraintbased connections for Grid OBS networks based on GMPLS. Our proposal has the advantages of combining both centralized and distributed features to establish paths with precision and with low latency, as well as using existing traffic engineering protocols to enable the anycast feature of the proposal.
[10] De Leenheer, M. et al, Anycast Algorithms Supporting Optical Burst Switched Grid Networks. Proc. International Conference on Networking and Services (ICNS), Silicon Valley, USA, July 2006.
The anycast feature of the proposed architecture is extended to deal with network resources in addition to grid nodes making route selection more precise, and is very important if there is a need to offer performance guarantees to certain applications.
[11] NS-2. The Network Simulator. URL: http://www.isi.edu/nsnam/ns/. Acessed in: January, 2008. [12] Chen, Y.; Tang, W.; Verma, P. K. Latency in Grid over Optical Burst Switching with Heterogeneous Traffic. In: Proceedings of High Performance Computing and Communications (HPCC 2007): 334-345.
One limitation of this proposal may be the reliance on the existence of sufficient resources to handle all the requests. Traffic engineering attempts to overcome this limitation by forwarding bursts to nodes (grid and network) that may not be in use at that moment.
[13] Zhang, Q.; Vokkarane, V. M.; Jue, J. P. e Chen, B. (2004). Absolute QoS Differentiation in Optical Burst-Switched Networks. IEEE Journal on Selected Areas in Communications (JSAC), 22(9):2062-2071.
Future work will be focused on a distributed alternative for the GOBS Connection Server, which will be important for interdomain routing, and in the evaluation of other resource discovery schemes that carry out reservation together with discovery.
[14] Nejabati, R et.al, Programmable Optical Burst Switched Network: A Novel Infrastructure for Grid, 5th IEEE/ACM International Symposium on Cluster Computing and the Grid, CCGrid 2005, Cardiff, UK, 9 - 12 May 2005.
We are also interested in addressing the scalability issues of the model and in including more metrics in the job’s constraints definition.
7. ACKNOWLEDGMENTS The authors would like to thank CAPES (Brazil) for financial support.
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