With the advent of the Internet and Internet-connected devices, modern business applications can experience rapid increases as well as variability in transactional workloads. Database replication has been employed to scale performance and improve availability of relational databases but past approaches have suffered from various issues including limited scalability, performance versus consistency tradeoffs, and requirements for database or application modifications. This paper presents Hihooi, a replication-based middleware system that is able to achieve workload scalability, strong consistency guarantees, and elasticity for existing transactional databases at a low cost. A novel replication algorithm enables Hihooi to propagate database modifications asynchronously to all replicas at high speeds, while ensuring that all replicas are consistent. At the same time, a fine-grained routing algorithm is used to load balance incoming transactions to available replicas in a consistent way. Our thorough experimental evaluation with several well-established benchmarks shows how Hihooi is able to achieve almost linear workload scalability for transactional databases.

Database replication can be employed for scaling transactional workloads while maintaining strong consistency semantics. However, past approaches suffer from various issues such as limited scalability, performance versus consistency tradeoffs, and requirements for database or application modifications. Hihooi is a new replication-based master-slave middleware system that is able to overcome the aforementioned limitations. The novelty of Hihooi lies in its modern architecture as well as its replication and transaction routing algorithms. In particular, Hihooi replicates all write statements asynchronously and applies them in parallel at the replica nodes, while ensuring replica consistency. At the same time, a fine-grained transaction routing algorithm ensures that all read transactions are load balanced to the replicas consistently. This demonstration will showcase the key functionalities of Hihooi, including (i) practical management of system components and databases (e.g., add a new replica node), (ii) increased scalability compared to state-of-the-art approaches, and (iii) support for elasticity by suspending and resuming database replicas online without service interruption.

Estimating the rate, with which the buffers of the nodes in a Wireless Sensor Network (WSN) fill-up, can contribute to the efficient operation of congestion control algorithms. In this paper we attempt, using a macroscopic fluid dynamic model, to estimate the rate with which the buffers of nodes fill-up, when congestion occurs in the network. This estimation can become a useful tool for the development of particular mechanisms, for congestion or overload control algorithms, that can improve their performance.