We have investigated the effects of the built-in electric field in GaN/Al 0.15 Ga 0.85 N quantum wells by photoluminescence spectroscopy. The fundamental electron heavy-hole transition redshifts well below the GaN bulk gap for well widths larger than 3 nm for the specific quantum wells investigated and exhibits a concomitant reduction of the intensity with increasing well thickness. The experimental data are quantitatively explained by means of a self-consistent tight-binding model that includes screening ͑either dielectric or by free-carriers͒, piezoelectric field and spontaneous polarization field. The impact of the built-in field on the exciton stability is discussed in detail. We demonstrate that the exciton binding energy is substantially reduced by the built-in field, well below the values expected from the quantum size effect in the flat band condition.

Client request rates for Internet services tend to be bursty and thus it is important to maintain efficient resource utilization under a wide range of load conditions. Network service clients typically seek services interactively and maintaining reasonable response time is often imperative for such services. In addition, providing differentiated service qualities and resource allocation to multiple service classes can also be desirable at times. This paper presents an integrated resource management framework (part of Neptune system) that provides flexible service quality specification, efficient resource utilization, and service differentiation for cluster-based services. This framework introduces the metric of quality-aware service yield to combine the overall system efficiency and individual service response time in one flexible model. Resources are managed through a two-level request distribution and scheduling scheme. At the cluster level, a fully decentralized request distribution architecture is employed to achieve high scalability and availability. Inside each service node, an adaptive scheduling policy maintains efficient resource utilization under a wide range of load conditions. Our trace-driven evaluations demonstrate the performance, scalability, and service differentiation achieved by the proposed techniques.

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Component additions and failures are common for large-scale storage clusters in production environments. To improve availability and manageability, we investigate and compare data location schemes for a large self-organizing storage cluster that can quickly adapt to the additions or departures of storage nodes. We further present an efficient location scheme that differentiates between small and large file blocks for reduced management overhead compared to uniform strategies. In our protocol, small blocks, which are typically in large quantities, are placed through consistent hashing. Large blocks, much fewer in practice, are placed through a usage-based policy, and their locations are tracked by Bloom filters. The proposed scheme results in improved storage utilization even with non-uniform cluster nodes. To achieve high scalability and fault resilience, this protocol is fully distributed, relies only on soft states, and supports data replication. We demonstrate the effectiveness and efficiency of this protocol through trace-driven simulation.