Performance Evaluation of Two-Shadow Speculative Concurrency Control

Speculative Concurrency Control (SCC) [Best92a] is a new concurrency control approach especially suited for real-time database applications. It relies on the use of redundancy to ensure that serializable schedules are discovered and adopted as early as possible, thus increasing the likelihood of the timely commitment of transactions with strict timing constraints. In [Best92b], SCC-nS, a generic algorithm that characterizes a family of SCC-based algorithms was described, and its correctness established by showing that it only admits serializable histories. In this paper, we evaluate the performance of the Two-Shadow SCC algorithm (SCC-2S), a member of the SCC-nS family, which is notable for its minimal use of redundancy. In particular, we show that SCC-2S (as a representative of SCC-based algorithms) provides significant performance gains over the widely used Optimistic Concurrency Control with Broadcast Commit (OCC-BC), under a variety of operating conditions and workloads.

Generating Representative Web Workloads for Network and Server Performance Evaluation

One role for workload generation is as a means for understanding how servers and networks respond to variation in load. This enables management and capacity planning based on current and projected usage. This paper applies a number of observations of Web server usage to create a realistic Web workload generation tool which mimics a set of real users accessing a server. The tool, called Surge (Scalable URL Reference Generator) generates references matching empirical measurements of 1) server file size distribution; 2) request size distribution; 3) relative file popularity; 4) embedded file references; 5) temporal locality of reference; and 6) idle periods of individual users. This paper reviews the essential elements required in the generation of a representative Web workload. It also addresses the technical challenges to satisfying this large set of simultaneous constraints on the properties of the reference stream, the solutions we adopted, and their associated accuracy. Finally, we present evidence that Surge exercises servers in a manner significantly different from other Web server benchmarks.

A Performance Evaluation of Hyper Text Transfer Protocols

Version 1.1 of the Hyper Text Transfer Protocol (HTTP) was principally developed as a means for reducing both document transfer latency and network traffic. The rationale for the performance enhancements in HTTP/1.1 is based on the assumption that the network is the bottleneck in Web transactions. In practice, however, the Web server can be the primary source of document transfer latency. In this paper, we characterize and compare the performance of HTTP/1.0 and HTTP/1.1 in terms of throughput at the server and transfer latency at the client. Our approach is based on considering a broader set of bottlenecks in an HTTP transfer; we examine how bottlenecks in the network, CPU, and in the disk system affect the relative performance of HTTP/1.0 versus HTTP/1.1. We show that the network demands under HTTP/1.1 are somewhat lower than HTTP/1.0, and we quantify those differences in terms of packets transferred, server congestion window size and data bytes per packet. We show that when the CPU is the bottleneck, there is relatively little difference in performance between HTTP/1.0 and HTTP/1.1. Surprisingly, we show that when the disk system is the bottleneck, performance using HTTP/1.1 can be much worse than with HTTP/1.0. Based on these observations, we suggest a connection management policy for HTTP/1.1 that can improve throughput, decrease latency, and keep network traffic low when the disk system is the bottleneck.

Load Profiling in Distributed Real-Time Systems

Load balancing is often used to ensure that nodes in a distributed systems are equally loaded. In this paper, we show that for real-time systems, load balancing is not desirable. In particular, we propose a new load-profiling strategy that allows the nodes of a distributed system to be unequally loaded. Using load profiling, the system attempts to distribute the load amongst its nodes so as to maximize the chances of finding a node that would satisfy the computational needs of incoming real-time tasks. To that end, we describe and evaluate a distributed load-profiling protocol for dynamically scheduling time-constrained tasks in a loosely-coupled distributed environment. When a task is submitted to a node, the scheduling software tries to schedule the task locally so as to meet its deadline. If that is not feasible, it tries to locate another node where this could be done with a high probability of success, while attempting to maintain an overall load profile for the system. Nodes in the system inform each other about their state using a combination of multicasting and gossiping. The performance of the proposed protocol is evaluated via simulation, and is contrasted to other dynamic scheduling protocols for real-time distributed systems. Based on our findings, we argue that keeping a diverse availability profile and using passive bidding (through gossiping) are both advantageous to distributed scheduling for real-time systems.

Evaluation of a Load Profiling Approach to Routing Guaranteed Bandwidth Flows

To support the diverse Quality of Service (QoS) requirements of real-time (e.g. audio/video) applications in integrated services networks, several routing algorithms that allow for the reservation of the needed bandwidth over a Virtual Circuit (VC) established on one of several candidate routes have been proposed. Traditionally, such routing is done using the least-loaded concept, and thus results in balancing the load across the set of candidate routes. In a recent study, we have established the inadequacy of this load balancing practice and proposed the use of load profiling as an alternative. Load profiling techniques allow the distribution of "available" bandwidth across a set of candidate routes to match the characteristics of incoming VC QoS requests. In this paper we thoroughly characterize the performance of VC routing using load profiling and contrast it to routing using load balancing and load packing. We do so both analytically and via extensive simulations of multi-class traffic routing in Virtual Path (VP) based networks. Our findings confirm that for routing guaranteed bandwidth flows in VP networks, load balancing is not desirable as it results in VP bandwidth fragmentation, which adversely affects the likelihood of accepting new VC requests. This fragmentation is more pronounced when the granularity of VC requests is large. Typically, this occurs when a common VC is established to carry the aggregate traffic flow of many high-bandwidth real-time sources. For VP-based networks, our simulation results show that our load-profiling VC routing scheme performs better or as well as the traditional load-balancing VC routing in terms of revenue under both skewed and uniform workloads. Furthermore, load-profiling routing improves routing fairness by proactively increasing the chances of admitting high-bandwidth connections.