A Scalable Multi-Tenant Architecture for Business Process Executions

Pathirage, Milinda; Perera, Srinath; Kumara, Indika; Weerasiri, Denis; Weerawarana, Sanjiva

doi:10.4018/jwsr.2012040102

Cited by 12 publications

(11 citation statements)

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“…The messages and their interpretations (ie, events and recorded states) carry the flow information (eg, the identifiers of the relevant entities). This flow information allows the enactment engine to isolate the executions of a given composite application by the end users of different tenants (similar to the use of the tenant‐context in the work of Pathirage et al for tenant execution isolation).…”

Section: The Sdsn@rt Middleware Environmentmentioning

confidence: 99%

“…In the first stage, when the routing REP of the user role receives an instantiation Web service request, the routing REP locates the regulation rules for the VSN via the regulation table. The Web service request contains the identifier of the VSN encoded in a message header or the part of the Web service endpoint reference of the user role (similar to the use of the tenant identifier in the work of Pathirage et al). The VSN identifier is the key to the regulation table.…”

Section: The Sdsn@rt Middleware Environmentmentioning

confidence: 99%

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SDSN@RT: A middleware environment for single‐instance multitenant cloud applications

et al. 2019

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With the single-instance multitenancy (SIMT) model for composite Software-as-a-Service (SaaS) applications, a single composite application instance can host multiple tenants, yielding the benefits of better service and resource utilization and reduced operational cost for the SaaS provider. An SIMT application needs to share services and their aggregation (the application) among its tenants while supporting variations in the functional and performance requirements of the tenants. The SaaS provider requires a middleware environment that can deploy, enact, and manage a designed SIMT application, to achieve the varied requirements of the different tenants in a controlled manner. This paper presents the SDSN@RT (software-defined service networks at runtime) middleware environment that can meet the aforementioned requirements. SDSN@RT represents an SIMT composite cloud application as a multitenant service network, where the same service network simultaneously hosts a set of virtual service networks, one for each tenant. A service network connects a set of services and coordinates the interactions between them. A virtual service network realizes the requirements for a specific tenant and can be deployed, configured, and logically isolated in the service network at runtime.SDSN@RT also supports the monitoring and runtime changes of the deployed multitenant service networks. We show the feasibility of SDSN@RT with a prototype implementation and demonstrate its capabilities to host SIMT applications and support their changes with a case study. The performance study of the prototype implementation shows that the runtime capabilities of our middleware incur little overhead.

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Section: The Sdsn@rt Middleware Environmentmentioning

confidence: 99%

Section: The Sdsn@rt Middleware Environmentmentioning

confidence: 99%

SDSN@RT: A middleware environment for single‐instance multitenant cloud applications

et al. 2019

Self Cite

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“…It can be obtained from the execution engine of the SOS by calculating the time difference between the arrival of user requests and the delivery of corresponding outcomes. This is feasible because the execution engine that invokes the distributed services is centrally managed by the SOS provider [38]. Each request will traverse one execution scenario, depending on the runtime decisions made in the branch structures of the SOS.…”

Section: Similarity Coefficientmentioning

confidence: 99%

Localizing Runtime Anomalies in Service-Oriented Systems

Xie

Wang

et al. 2017

IEEE Trans. Serv. Comput.

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In a distributed, dynamic and volatile operating environment, runtime anomalies occurring in service-oriented systems (SOSs) must be located and fixed in a timely manner in order to guarantee successful delivery of outcomes in response to user requests. Monitoring all component services constantly and inspecting the entire SOS upon a runtime anomaly are impractical due to excessive resource and time consumption required, especially in large-scale scenarios. We present a spectrum-based approach that goes through a five-phase process to quickly localize runtime anomalies occurring in SOSs based on end-to-end system delays. Upon runtime anomalies, our approach calculates the similarity coefficient for each basic component (BC) of the SOS to evaluate their suspiciousness of being faulty. Our approach also calculates the delay coefficients to evaluate each BC's contribution to the severity of the end-to-end system delays. Finally, the BCs are ranked by their similarity coefficient scores and delay coefficient scores to determine the order of them being inspected. Extensive experiments are conducted to evaluate the effectiveness and efficiency of the proposed approach. The results indicate that our approach significantly outperforms random inspection and the popular Ochiai-based inspection in localizing single and multiple runtime anomalies effectively. Thus, our approach can help save time and effort for localizing runtime anomalies occuring in SOSs.

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“…In the past decade, many approaches for quality-aware service selection have been proposed to compose single tenant SOSs [1]- [3], [37] and multi-tenant SOSs [6], [20], [25], [28], including ours [32], [18]. However, none of the existing approaches has systematically considered three critical issues that challenge their success rates of finding a solution: 1) multi-tenancy, i.e., the ability for an SOS to serve multiple tenants simultaneously based on a single application instance; 2) provider competition, the competition between service providers has not been fully explored in the open and competitive cloud environment; and 3) service complementarity, i.e., the complementarity between the quality of multiple services.…”

Section: Introductionmentioning

confidence: 99%

Quality-Aware Service Selection for Multi-Tenant Service Oriented Systems Based on Combinatorial Auction

Zhong

et al. 2019

IEEE Access

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Multi-tenant service-oriented systems (SOSs) have become a major software engineering paradigm in the cloud environment. Instead of serving a single end-user, a multi-tenant SOS provides multiple tenants with similar and yet customized functionalities and potentially different quality-of-service (QoS) values. Multiple tenants' differentiated multi-dimensional quality constraints for the SOS further complicates the NP-hard problem of quality-aware service selection. Existing quality aware service selection approaches suffer from poor success rates of finding a solution, especially in scenarios where tenants' quality constraints are stringent, due to the lack of systematic consideration of three critical issues: 1) the need to fulfil multiple tenants' differentiated quality constraints; 2) the competition among service providers; and 3) the complementarity between services. This paper proposes a novel approach called combinatorial auctionbased service selection for multi-tenant SOSs (CASSMT) to support effective quality-aware service selection for multi-tenant SOSs. CASSMT allows service providers to bid for the services of an SOS expressively. Based on received bids (i.e., QoS offers), CASSMT attempts to find a solution that achieves the system developer's optimization goal while fulfilling all tenants' quality constraints for the SOS. When no solution can be found based on the current bids, service providers can improve their bids to increase their chances of winning, which in the meantime, increases the chances of finding a solution. The experimental results show that CASSMT outperforms representative approaches in the success rate of finding a solution and system optimality. Meanwhile, its efficiency, measured by the number of auction rounds and computation time, is demonstrated to be satisfactory in scenarios on different scales.

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A Scalable Multi-Tenant Architecture for Business Process Executions

Cited by 12 publications

References 13 publications

SDSN@RT: A middleware environment for single‐instance multitenant cloud applications

SDSN@RT: A middleware environment for single‐instance multitenant cloud applications

Localizing Runtime Anomalies in Service-Oriented Systems

Quality-Aware Service Selection for Multi-Tenant Service Oriented Systems Based on Combinatorial Auction

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