Evaluating new network protocols, applications, and architectures uses many kinds of experimentation environments: simulators, emulators, testbeds, and sometimes, combinations of these. As the functionality and complexity of these tools increases, mastering and efficiently using each of them is becoming increasingly difficult. In this paper, we consider how to make it easier to use multiple tools separately and together to improve the productivity of network researchers. We show how a single object model which encompasses every aspect of a typical experimentation workflow can be used to completely describe experiments to be run within very different experimentation environments. Although NEPI is still in early design and prototyping stage, we expect that its ability to describe and automate easily complex mixed experiments will enable further experimentation with heterogenous networks. 1

Middleware for Web service compositions, such as BPEL engines, provides the execution environment for services as well as additional functionalities, such as monitoring and self-tuning. Given its role in service provisioning, it is very important to assess the performance of middleware in the context of a Serviceoriented Architecture (SOA). This paper presents SOABench, a framework for the automatic generation and execution of testbeds for benchmarking middleware for composite Web services and for assessing the performance of existing SOA infrastructures. SOABench defines a testbed model characterized by the composite services to execute, the workload to generate, the deployment configuration to use, the performance metrics to gather, the data analyses to perform on them, and the reports to produce. We have validated SOABench by benchmarking the performance of different BPEL engines. 1

Distributed systems often employ replication to solve two different kinds of availability problems. First, to prevent the loss of data through the permanent destruction or disconnection of a distributed node, and second, to allow prompt retrieval of data when some distributed nodes respond slowly. For simplicity, many systems further handle crash-restart failures and timeouts by treating them as a permanent disconnection followed by the birth of a new node, relying on peer replication rather than persistent storage to preserve data. We posit that for applications deployed in modern managed infrastructures, delays are typically transient and failed processes and machines are likely to be restarted promptly, so it is often desirable to resume crashed processes from persistent checkpoints. In this paper we present MaceKen, a synthesis of complementary techniques including Ken, a lightweight and decentralized rollback-recovery protocol that transparently masks crash-restart failures by careful handling of messages and state checkpoints; and Mace, a programming toolkit supporting development of distributed applications and application-specific availability via replication. MaceKen requires near-zero additional developer effort—systems implemented in Mace can immediately benefit from the Ken protocol by virtue of following the Mace execution model. Moreover, Ken allows multiple, independently developed application components to be seamlessly composed, preserving strong global reliability guarantees. Our implementation is available as open source software. 1