Use of Salesforce Platform for Building Real-Time Service Systems in Cloud

Author(s):  
Aneta Poniszewska-Maranda ◽  
Radoslaw Matusiak ◽  
Natalia Kryvinska
GPS Solutions ◽  
2021 ◽  
Vol 25 (2) ◽  
Author(s):  
Meifang Wu ◽  
Baoqi Sun ◽  
Yuanxin Wang ◽  
Zhe Zhang ◽  
Hang Su ◽  
...  

2008 ◽  
Author(s):  
Tan Miaoqing ◽  
Andres Arjona ◽  
Antti Ylä-Jääski

Author(s):  
Randall E. Duran ◽  
Anh Duc Do

System architectures that deliver real-time services to customers must be flexible, scalable, and support a wide range of communication channels. This chapter presents an architecture that was designed to support multiple delivery channels and was successfully used to implement mobile banking services. The considerations behind the design and the approach used to deliver SMS-based mobile services using service-oriented architecture principles are reviewed and some of the practical challenges that were encountered with the implementation are explored. The ability for this solution architecture to support other real-time service channels is also examined.


Author(s):  
Jacqueline Stewart ◽  
Thomas McCabe ◽  
Robert Stewart ◽  
Sean Kennedy

Wireless Sensor Networks and the smart applications designed to operate upon them have enjoyed a rapid increase in popularity over the last decade. The main challenge currently is the provision of real-time service delivery for wireless sensor networks to cater for new applications with guaranteed Quality of Service (QoS) requirements. However each application has a different service requirement. In order to deliver real-time services the dimensioning of such networks is important to service providers in order to meet these service requirements. If packets cannot be stored due to insufficient memory they are lost. Lost packets result in the resending of the packets and hence an increase in delay in delivery of the application traffic. It is this memory provisioning of these wireless sensor networks that is the focus of the work presented in this paper. More specifically the relationship between the application design, implementation and memory resources required to run the service are explored using a stack analysis tool. This stack analysis tool enables the stack footprint to be measured. Results of memory usage for two different WSN applications are presented. Recommendations based on this study for efficient memory provisioning and ultimately real-time service delivery are given.


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