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Stream processing applications have recently gained significant attention in the networking and database community. At the core of these applications is a stream processing engine that performs resource allocation and management to support continuous tracking of queries over collections of physically-distributed and rapidly-updating data streams. While numerous stream processing systems exist, there has been little work on understanding the performance characteristics of these applications in a distributed setup. In this paper, we examine the performance bottlenecks of streaming data applications, in particular the Linear Road stream data management benchmark, in achieving good performance in large-scale distributed environments, using the Stream Processing Core (SPC), a stream processing middleware we have developed.First, we present the design and implementation of the Linear Road benchmark on the SPC middleware. SPC has been designed to scale to tens of thousands of processing nodes, while supporting concurrent applications and multiple simultaneous queries. Second, we identify the main performance bottlenecks in the Linear Road application in achieving scalability and low query response latency. Our results show that data locality, buffer capacity, physical allocation of processing elements to infrastructure nodes, and packaging for transporting streamed data are important factors in achieving good application performance. Though we evaluate our system primarily for the Linear Road application, we believe it also provides useful insights into the overall system behavior for supporting other distributed and large-scale continuous streaming data applications. Finally, we examine how SPC can be used and tuned to enable a very efficient implementation of the Linear Road application in a distributed environment.

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The biology and fisheries of Tilapia mariae, the only tilapiine cichlid fish in the Iba Oku (Uyo, Nigeria) wetland stream was studied. There were more females than males in the population. The smallest sexually mature female fish was 11.0 cm total length (TL) while the size at 50% maturity was 17.1 cm TL. Absolute fecundity (F e ) ranged from 953 to 3200 eggs and was positively correlated with TL. The fish bred year-round with peaks in November, March-April and July-September. The seasonalized von Bertalanffy growth function (VBGF) was fitted to the 12 consecutive months length-frequency data (n ¼ 2439) to obtain a VBGF with the following parameters: L1 (asymptotic length) ¼ 30.4 cm TL, K (growth coefficient) ¼ 0.4 year )1 , C (amplitude of growth oscillation) ¼ 0.4, and WP (winter point) ¼ 0.9. The seasonalized lengthconverted catch curve method gave Z (instantaneous total mortality coefficient) as 1.75 year )1 , M (instantaneous natural mortality coefficient) was 0.99 year )1 while F (instantaneous fishing mortality coefficient) was 0.76 year )1 and E ( ¼ F/Z the current exploitation rate) was 0.43. Length at first capture (Lc) was 17.7 cm TL. The fish was recruited to the fishery yearround with two pulses. From the Beverton and Holt relative yield per recruit analysis via the selection ogive procedure, E max (predicted maximum exploitation rate) was 0.54. The stock was not overexploited, since E < E max . This study also showed that the fish is an r-selected species with a few K-selected traits.

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