# A Framework to Model Bursty Electronic Data Interchange Messages for Queueing Systems +
## 1 Introduction
### Background and Previous Work
#### 1.1.3 EDI Deployments  
When looking at a supply chain organisation, we pay particular attention to B2B messages, also known as EDI messages. We note that EDI messages electronically support the trading of transactions between a customer and its trading partner. EDI messaging allows customers and trading partners to trade electronically using digital signatures. Some of the beneficial features of EDI include message integrity, confidentiality, interoperability, non-repudiation of a contract and traceability of a transaction [15]. Deploying EDI in B2B organisations can save up to 15 min per invoice transaction query between a supplier and its trading partner [16]. EDI was born in the UK, and its expected growth in 1991 was perceived to grow at a sigmoidal rate [17]. EDI is deployed in many organisations, with some examples shown in Table 1[17].  
Our research focuses on modelling EDI messages through queueing systems. EDI messages are bursty. One incoming message may result in many messages being sent to a queue at once. These bursty messages may cause bottlenecks in a queueing system, and so understanding them is useful for stress testing and simulating queue environments. When modelling these messages, it is important to identify what characteristics determine whether an EDI message will be bursty. For example, when a customer sends in 100 transactions, are you stress testing a queueing system for 100 individual transactions or a burst of those transactions? The system may need to be ready for a single transaction resulting in hundreds of messages ingested by a queue.  
We found that the Department of Defence developed and advanced system architecture to support EDI messages based on different modelling and simulation techniques. This was motivated by ever-growing transaction sizes and the inter-twining of many applications. They used modelling and simulation techniques to support the decision making of their advanced system architecture [15].  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Standard** & **Industry** \\ \hline ANA & Food, Retail, distribution \\ TF2 & Health Service \\ FLEETNET & Fleet Car Industry \\ EDISHIP & Shipping/Forwarding \\ PHARMEDI & Pharmaceutical \\ EDICON & Construction \\ EDICUG & Components \\ BEDIS & Book Publishing Libraries \\ PIPE & Paper/Printing \\ EDIA & Banking, Transport \\ ODETTE & Automotive \\ \hline \hline \end{tabular}
\end{table}
Table 1: Industries using EDI.  
EDI implementations have also been studied. For example, one study investigated if the adoption of EDI improves customer service [18]. The main factors that influence a companies decision to implement EDI were also considered [19]. Their findings indicate that companies will adopt EDI depending on whether their business partners are doing so. A study of EDI and the motor trade industry aimed to partly examine the extent to which EDI was used in the motor carrier industry and potential problems that might hinder the use of EDI for these motor carriers [20].  
We note that although EDI has been researched in different areas, none of these studies addresses EDI implementation regarding simulation and performance testing, specifically around queueing systems and modelling service and inter-arrival times. We note that these EDI messages suffer from burstiness. We found little evidence of research around the field of being able to identify using different elements of an EDI message of a bursty versus a non-bursty message. We believe this is a gap in the research that should be addressed.