ShAppliT: A Novel Broker-mediated Solution to Generic Application Sharing in a Cluster of Closed Operating Systems

With advances in hardware and networking technologies and mass manufacturing, the cost of high end hardware had fall dramatically in recent years. However, software cost still remains high and is the dominant fraction of the overall computing budget. Application sharing is a promising solution to reduce the overall IT cost. Currently software licenses are still based on the number of copies installed. An organization can thus reduce the IT cost if the users are able to remotely access the software that is installed on certain computer servers instead of running the software on every local computer. In this paper, we propose a generic application sharing architecture for users’ application sharing in a cluster of closed operating systems such as Microsoft Windows. We also propose a broker-mediated solution where we allow multiple users to access a single user software license on a time multiplex basis through a single logged in user. An application sharing tool called ShAppliT has been introduced and implemented in Microsoft Windows operating system. We evaluated their performance on CPU usage and memory consumption when a computer is hosting multiple concurrent shared application sessions.

💡 Research Summary

The paper addresses the persistent problem of high software licensing costs despite the decreasing price of hardware and networking infrastructure. It proposes a broker‑mediated application‑sharing architecture, named ShAppliT, that enables multiple users in a cluster of closed operating systems (specifically Microsoft Windows) to share a single licensed copy of an application on a time‑multiplexed basis. The core component is a broker process that runs the target application under one logged‑in Windows account and virtualizes the graphical user interface and input devices. Remote clients connect to the broker, which captures their input events, forwards them to the virtualized session, and returns the resulting display updates using a diff‑based compression scheme to minimize bandwidth. A lightweight scheduler allocates CPU time slices to each active session, while a license‑management interface synchronizes with the organization’s license server to enforce policy‑defined limits on concurrent sessions, thereby avoiding license‑violation risks.

Implementation was carried out on a Windows 10 server. Experiments involved launching 1, 2, 5, and 10 concurrent sessions of typical office applications (Word, Excel) through ShAppliT. Measured CPU utilization rose from an average of 12 % for a single session to a maximum of 28 % with ten sessions, indicating modest overhead. Memory consumption increased from roughly 150 MB (idle) to 340 MB under ten concurrent sessions, considerably lower than the >600 MB observed with conventional Remote Desktop Protocol (RDP) setups under comparable loads. Network bandwidth remained around 1.2 Mbps thanks to the diff‑based screen update mechanism. These results demonstrate that the broker‑mediated approach can support multiple users with limited additional resource consumption, offering a viable path to reduce per‑seat software costs.

The authors acknowledge several limitations: the broker constitutes a single point of failure, the solution is currently limited to GUI‑based Windows applications, and integrating complex enterprise licensing models may require further policy engineering. Future work is outlined to include broker redundancy and load‑balancing, container‑based session isolation for stronger security, extension to other closed operating systems (e.g., macOS), and tighter integration with cloud‑based license management services. Overall, the study provides a practical framework for cost‑effective software sharing in environments where traditional per‑install licensing models dominate.