Today’s Internet carries an ever broadening range of application traffic with different requirements. This has stressed its original, one-class, best-effort model, and has been one of the main drivers behind the many efforts aimed at introducing QoS. Those efforts have, however, experienced only limited success because their added complexity often conflict with the scalability requirements of the ... [Show full abstract] Internet. This has motivated many proposals that try to offer service differentiation while keeping complexity low. This paper shares similar goals and proposes a simple scheme, BoundedRandomDrop (BRD), that supports multiple service classes. BRD focuses on loss differentiation, as although both losses and delay are important performance parameters, the steadily rising speed of Internet links is progressively limiting the impact of delay differentiation. BRD offers strong loss differentiation capabilities with minimal added cost. BRD does not require traffic profiles or admission controls. It guarantees each class losses that, when feasible, are no worse than a specified bound, and enforces differentiation only when required to meet those bounds. In addition, BRD is implemented using a single FIFO queue and a simple random dropping mechanism. The performance of BRD is investigated for a broad range of traffic mixes and shown to consistently achieve its design goals.