Phase I: Comparison of Grid Systems and IaaS Clouds

In Phase I of the IAI process, we analyze the interoperability of grid systems and IaaS clouds. We identify the prerequisites of interoperability as well as describe the survey about interoperability solutions. This task is performed manually by the interoperability analyst.

6.1.1 Common and Complementary Functionalities

Based on the direct comparison of the grid and cloud models, which is depicted in Fig-ure 6.1, we identify common as well as complementary functionalities. Both systems are based on physical hardware. Within grid systems, the local resources are directly deployed on physical hardware. In contrast, IaaS clouds offer a resource management interface to

6 Interoperability of Grid and IaaS Cloud Systems 66

S i M d l f Cl d C t l M d l f G id Service Model of Clouds

Grid Scheduler Conceptual Model of Grids SaaS

Grid

L l R PaaS

Grid

Local Resources

IaaS

Physical Hardware Physical Hardware

Figure 6.1: Comparing the layers of cloud with grid

install operating systems and applications dynamically within virtual machines and virtual infrastructures that are deployed on the underlying hardware. The installation of operating systems and applications is already done in our grid model, since the local resources on the bottom layer deploy a pre-configured software stack directly on the physical hardware.

Therefore, a layer with similar functionalities as provided by IaaS clouds does not exist in our grid model. All grid functionalities including local resource functionalities are on the same level of abstraction as PaaS and SaaS clouds. However, the deployment of grid resources on IaaS clouds offers a valuable opportunity for interoperation.

The needs for grid-cloud interoperability are manifold. A combined usage of grid and IaaS clouds fosters an efficient resource use and resources on demand. IaaS clouds can be used for data replication and to decrease costs by choosing the best suited solution. In addition, a grid-cloud interoperability solution would allow the preservation of previous in-vestment in grid application and system development. For example, it would be possible to migrate a well engineered grid application and grid environment into an IaaS cloud without any changes.

6.1.2 Survey Interoperability Solutions

To our best knowledge, standardization institutes do not consider the development of a grid-cloud interoperability standard. This is mainly caused by the heterogeneity of both systems.

Additionally, there is only low commercial interest in grid systems that are mainly deployed and applied for academic research. However, some researchers worked on the integration of grid and cloud systems. In contrast to our work, these approaches usually do not distinguish between the different cloud layers in relation to the grid model. We describe the related work in Section 6.4.

In the grid and cloud domains, interoperability approaches exist mainly for interoper-ability between systems of the same domain. These approaches lay the foundation for

67 6.1 Phase I: Comparison of Grid Systems and IaaS Clouds

Standard Unicore 6 GT 4 GLite GOS v3.2 Fura

Security X.509

Security Assertion Markup Language (SAML) extensible Access Control Markup Language (XACML) Virtual Organization Membership Service (VOMS) WS-Security (Transport Level Security (TLS)) Execution Job Submission Description Language (JSDL)

OGSA-BES (Basic Execution Service)

Distributed Resource Management Application API (DRMAA)

Data OGSA-ByteIO

GridFTP (defacto)

Information Web Service Resource Framework (WSRF) OGSA RUS (Resource Usage Service) OGSA-RUS (Resource Usage Service) OGSA-UR (Usage Record)

Table 6.1: Comparison of implemented standards in grid systems

grid-cloud interoperability. For interoperability between clouds, interoperability gateways and standards have been proposed. Many interoperability gateways are implemented within Cloud APIs. For example, Deltacloud [4] or Libcloud [5], define connectors for several cloud systems. In addition to interoperability gateways, several cloud standards emerged, e.g., Open Cloud Computing Interface (OCCI) [102] developed by the OGF and Cloud Data Management Interface(CDMI) [135] published by theStorage Network Industry As-sociation(SNIA) [129]. However, cloud standards are still in their infancy and need to be improved further before global cloud stakeholders adapt them. Standardization effort by different organizations for cloud systems is described in [96].

In the grid domain, the interoperability gateway approach is implemented, e.g., in the HiLA for grid applications as well as in theJava Grid Application Toolkit(JavaGAT) [70]

that allow to access grid core services of different grid middleware implementations. Ta-ble 6.1 illustrates the standards that are in use in popular grid software packages: GT4, UNICORE 6,lightweight middleware for grid computing(gLite) [62, 86],Grid Operation System (GOS) 3.2 [155], and Fura [131]. These are dominated by OGF standards asso-ciated with OGSA and WSRF. Furthermore, thePublic-Key-Infrastructure (PKI) X.509 certificate system has found wide-spread adoption in all grid domains. The table also shows that the OGSA-BES, OGSA-RUS, andOGSA-Usage Records(OGSA-UR) standards have the broadest adoption amongst the middleware under consideration.

One aspect that is not captured by this table are grid systems that utilize very few stan-dards. In the United States of America (USA), TeraGrid [139] and Open Science Grid (OSG) [107] are both dominated by custom-made software, or packages distributed through theVirtual Data Toolkit(VDT) [141]. In these cases, the only visible standards are GridFTP and the X.509 identity system. Even authorization by X.509 certificates is handled differ-ently in different grids. In actuality, no operational grid systems rely exclusively (or even predominantly) on grid standards, but instead use a patchwork of custom-made and third-party software packages, expecting sites to be running the same version of the software to be interoperable.

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It is also essential to note that higher level grid applications often rely on underlying grid middleware services in a way that inhibits interoperability, even when two implemen-tations support the same underlying set of standards. The reason for this are incomplete implementations or patchwork standards environments.