P. Butz, „Implementation, Deployment and Evaluation of UDS,“ G. Habiger (Betreuung), F. J. Hauck (Prüfer), Inst. of Distr. Sys., Ulm Univ., 2017 –
Abgeschlossen.
The increasing world wide spread of computers and mobile devices combined with better international network set high demands on service providers. A huge number of parallel access to services offered in the Internet requires huge throughput. At the same time, the availability of services is key, especially in areas like financial and cloud services. Data centers provide these requirements by replicating critical services and data among numerous computers. However, this distribution means that hardware failures are not the exception but become the rule. The State Machine Replication (SMR) approach is an attempt to allow the recovery of crashed servers. Additionally, manipulations of servers and software failures are still a problem of such systems. Byzantine fault tolerant systems build up on state machine replication and face this issue by allowing clients to validate the correctness of service responses. However, SMR requires the client requests to arrive in the same order on every server, so that this has to be decided by a consensus. Furthermore, SMR requires deterministic processing, so that the states among all machines are equal, which is usually ensured by sequential request processing. This seems inefficient, especially considering multi core and multi CPU hardware of today's server systems. Enabling parallel request processing while fulfilling the demands of SMR requires a deterministic scheduler. These are complex and more resource-intensive than general schedulers. The aim of this thesis is the implementation of such a scheduler and the evaluation of the performance to gain knowledge about the efficiency of those schedulers to compare the overhead in scheduling with the gained parallelization. As a result, the overhead in deterministic scheduling is a huge factor, which only allows a performance improvement up to a certain point based on the cost of computations within critical sections.