Performance Evaluation of Service Orchestration with Dynarric Latency Simulation

Dynamic latency over the Intemet is an Important parameter for evaluating the performance of Web service orchestration. In this paper, we propose a performance analyzing and correctness checking method for service orchestration with dynamic latency simulated in Colored PetriNets （CPNs）. First, we extend the CPN to Web Service Composition Orchestration Network System （WS-CONS） for the description of dynamic latency in service orchestration. Secondly, with simulated dynamic latency, a buffer-limited policy and admittance-control policy are designed in WS- CONS and implemented on CPN Tools. In the buffer-limited policy, the passing messages would be discarded if the node capacity is not adequate. In the admittance-control policy, the ability of a message entering the system depends on the number of messages concurrently flowing in the system. This helps to enhance the success rate of message passing. Finally, the system performance is evaluated through running models in CPN Tools. Simulated results show that the dynamic latency plays an important role in the system throughput and response latency. This simulation helps system designers to quickly make proper compromises at low cost.

Service Function Chain Orchestration across Multiple Clouds

Network function virtualization is a new network concept that moves network functions from dedicated hardware to software-defined applications running on standard high volume severs. In order to accomplish network services, traffic flows are usually processed by a list of network functions in sequence which is defined by service function chain. By incorporating network function virtualization in inter-data center(DC) network, we can use the network resources intelligently and deploy network services faster. However, orchestrating service function chains across multiple data centers will incur high deployment cost, including the inter-data center bandwidth cost, virtual network function cost and the intra-data center bandwidth cost. In this paper, we orchestrate SFCs across multiple data centers, with a goal to minimize the overall cost. An integer linear programming(ILP) model is formulated and we provide a meta-heuristic algorithm named GBAO which contains three modules to solve it. We implemented our algorithm in Python and performed side-by-side comparison with prior algorithms. Simulation results show that our proposed algorithm reduces the overall cost by at least 21.4% over the existing algorithms for accommodating the same service function chain requests.

Event-driven process execution model for process virtual machine

Current orchestration and choreography process engines only serve with dedicate process languages.To solve these problems,an Event-driven Process Execution Model(EPEM) was developed.Formalization and mapping principles of the model were presented to guarantee the correctness and efficiency for process transformation.As a case study,the EPEM descriptions of Web Services Business Process Execution Language(WS-BPEL) were represented and a Process Virtual Machine(PVM)-OncePVM was implemented in compliance with the EPEM.

Toward Interoperable Multi‑hazard Modeling: A Disaster Management System for Disaster Model Service Chain

A natural hazard-related disaster event often causes a series of secondary disasters, forming a disaster chain. Modeling the evolution of disaster chains in multihazard scenarios is crucial for risk governance and urban resilience. However, existing multi-hazard models are limited by complex model design and fixed disaster types, making it impossible to ensure flexible reactions to complex and diverse scenarios. This study presents a disaster management system for disaster model service chain(DMSC) to implement interoperable multi-hazard modeling. To achieve efficient model interaction in the DMSC, a management module is designed to normalize heterogeneous single-hazard models based on disaster system theory and the Open Geospatial Consortium standards, enabling them to be accessible,reusable, and interoperable. The normalized models are then adaptively orchestrated through an orchestration module to establish optimal executable DMSCs for different multihazard scenarios. Taking an earthquake disaster chain as a case study, we demonstrate that the disaster management system shows stable and flexible performance for multihazard modeling.