Admission Control and Scheduling for High-Performance WWW Servers

In this paper we examine a number of admission control and scheduling protocols for high-performance web servers based on a 2-phase policy for serving HTTP requests. The first "registration" phase involves establishing the TCP connection for the HTTP request and parsing/interpreting its arguments, whereas the second "service" phase involves the service/transmission of data in response to the HTTP request. By introducing a delay between these two phases, we show that the performance of a web server could be potentially improved through the adoption of a number of scheduling policies that optimize the utilization of various system components (e.g. memory cache and I/O). In addition, to its premise for improving the performance of a single web server, the delineation between the registration and service phases of an HTTP request may be useful for load balancing purposes on clusters of web servers. We are investigating the use of such a mechanism as part of the Commonwealth testbed being developed at Boston University.

Unicast Routing: Cost-Performance Tradeoffs

The objective of unicast routing is to find a path from a source to a destination. Conventional routing has been used mainly to provide connectivity. It lacks the ability to provide any kind of service guarantees and smart usage of network resources. Improving performance is possible by being aware of both traffic characteristics and current available resources. This paper surveys a range of routing solutions, which can be categorized depending on the degree of the awareness of the algorithm: (1) QoS/Constraint-based routing solutions are aware of traffic requirements of individual connection requests; (2) Traffic-aware routing solutions assume knowledge of the location of communicating ingress-egress pairs and possibly the traffic demands among them; (3) Routing solutions that are both QoS-aware as (1) and traffic-aware as (2); (4) Best-effort solutions are oblivious to both traffic and QoS requirements, but are adaptive only to current resource availability. The best performance can be achieved by having all possible knowledge so that while finding a path for an individual flow, one can make a smart choice among feasible paths to increase the chances of supporting future requests. However, this usually comes at the cost of increased complexity and decreased scalability. In this paper, we discuss such cost-performance tradeoffs by surveying proposed heuristic solutions and hybrid approaches.

Intersubject Regularity in the Intrinsic Shape of Human V1

Previous studies have reported considerable intersubject variability in the three-dimensional geometry of the human primary visual cortex (V1). Here we demonstrate that much of this variability is due to extrinsic geometric features of the cortical folds, and that the intrinsic shape of V1 is similar across individuals. V1 was imaged in ten ex vivo human hemispheres using high-resolution (200 μm) structural magnetic resonance imaging at high field strength (7 T). Manual tracings of the stria of Gennari were used to construct a surface representation, which was computationally flattened into the plane with minimal metric distortion. The instrinsic shape of V1 was determined from the boundary of the planar representation of the stria. An ellipse provided a simple parametric shape model that was a good approximation to the boundary of flattened V1. The aspect ration of the best-fitting ellipse was found to be consistent across subject, with a mean of 1.85 and standard deviation of 0.12. Optimal rigid alignment of size-normalized V1 produced greater overlap than that achieved by previous studies using different registration methods. A shape analysis of published macaque data indicated that the intrinsic shape of macaque V1 is also stereotyped, and similar to the human V1 shape. Previoud measurements of the functional boundary of V1 in human and macaque are in close agreement with these results.