State-machine replication (SMR) is a popular fault-tolerance technique for building highly-available services. Usually, consensus protocols are used to enforce a deterministic service-request ordering among replicas, in order to prevent their state from diverging. Over the last decades, a multitude of consensus protocols have been developed which come with different characteristics but also with different communication and programming models. Our Consensus-Agnostic Replication Toolkit (CART) is a wrapper for consensus protocols that relieves clients from most consensus configuration and support. Besides, it implements a generic client and application interface to support different consensus protocols and configurations, e.g. in cloud deployments. CART has built-in authentication of services based on BLS threshold signatures. It can further prove malicious behaviour of replicas, thus speeding up recovery in case of Byzantine faults. We evaluate the performance overhead of our approach in a real-world WAN deployment for two different consensus protocol implementations using the YCSB benchmark. Our results show that CART is able to reach up to 90% of the throughput achieved by the native consensus protocol with an additional latency overhead of only 10%.

Modern mobile devices are mainstream and ubiquitous devices. The widespread adoption of mobile devices has resulted in surge of mobile applications (apps) hosted on marketplaces (app stores) of several mobile platforms. Besides other benefits, these apps are also applied in healthcare-related and medical use, for instance, in case of tinnitus, where tinnitus disorder is associated with the perception of ringing sound without external sound source. In particular, for tinnitus, these apps allow provision of tinnitus-related relief, self-help, and general management. The collective aim of this chapter is to foster and report on Mobile Health (mHealth) solutions, in particular mobile apps within the tinnitus context. First, this chapter provides an up-to-date overview of existing mHealth apps available for major mobile platforms. Second, this chapter provides deep insights into quality and effectiveness of said mobile apps for tinnitus treatment and management. Finally, this chapter provides discussions in relation to the tinnitus-related mHealth apps.