Web computing is a variant of parallel computing where the idle times of PCs donated by worldwide distributed users are employed to execute parallel programs. In this thesis we consider a web computing variant with two important properties: First, we support the execution of coupled, massively parallel algorithms (rather than distributed data processing). And second, we organize the system in peer-to-peer fashion.We present the Paderborn University BSP-based Web Computing (PUB-Web) library, which supports the execution of parallel programs in the bulk-synchronous style (BSP) in such a web computing setting. In this thesis, we focus on important technical and algorithmic aspects, in particular: In order to schedule processes with respect to the currently available computing power, which continually changes in an unpredictable fashion, we need intelligent load balancing algorithms and as a basic precondition the technical ability to migrate threads at runtime.To achieve the latter, we present the PadMig thread migration and checkpointing library. In order to tackle the distributed load balancing problem, we present an algorithm based on Distributed Heterogeneous Hash-Tables. In order to judge the quality of the schedules produced, we perform extensive experiments. Beside the available computing power, we finally also consider the network bandwidth as a secondary criterion for load balancing.