Multicast Communication for Increased Data Exchange in Data- Intensive Distributed Systems

Sammanfattning: Modern applications are required to handle and communicate an increasing amount of data. Meanwhile, distributed systems containing multiple computationally weak components becomes more common, resulting in a problematic situation. Choosing among communication strategies, used for delivering message between entities, therefore becomes crucial in order to efficiently utilize available resources. Systems where identical data is delivered to many recipients are common nowadays, but may apply an underlying communication strategy based on direct interaction between sender and receiver which is insufficient. Multicasting refers to a technique for group communication where messages can be distributed to participating nodes in a single transmission. This technique is developed to circumvent the problem of high workload on sender side and redundant traffic in the network, and constitutes the focus for this thesis. Within the area of Electronic Warfare and self-protection systems, time constitutes a critical aspect in order to provide relevant information for decision making. Self-protection systems developed by Saab, used in military aircrafts, must provide situational awareness to guarantee that correct decisions can be made at the right time. With more advanced systems, where the amount of data needed to be transmitted increases, the need of fast communication is essential to achieve quality of service. This thesis investigates how the deployment of multicast, in a distributed data-intensive system, could prepare a system for increased data exchange. The result is a communication design which allows for the system to distribute messages to a group of receivers with less effort from the sender and with reduced redundant traffic transferred over the same link. Comparative measurements are conducted between the new implementation and the old system. The result of the evaluation shows that the multicast solution both can decrease the time for message handling as well as the workload on endpoints significantly.