The demand for real-time database services has been increasing recently. Examples include sensor data fusion, decision support, web information services, and online trading. In these applications, it is desirable to execute transactions within their deadlines using temporally consistent data. Due to the high service demand, real-time databases can be overloaded. As a result, many transactions may miss their deadlines, or data temporal consistency constraints can be violated. To address these problems, we present a QoS management scheme to support guarantees on deadline miss ratio and data freshness (temporal consistency) even in the presence of unpredictable workloads and data access patterns. Using our approach, admitted user transactions can be processed in time using fresh data. A simulation study shows that our QoS-sensitive approach can achieve a significant performance improvement, in terms of deadline miss ratio and data freshness, compared to several baseline approaches. Furthermore, our approach shows a comparable performance to the theoretical oracle that is privileged by a complete future knowledge of data accesses. 1

this paper, we argue that for interactive Internet applications, a decrease in MTTR is sometimes more valuable than the corresponding increase in MTTF to improve Availability by the same amount, and we make a case for adopting MTTR as the primary metric for reasoning about system availability and focusing designs on fast recovery

... attacks is becoming ever more challenging with the vast resources and techniques increasingly available to attackers. In this paper, we consider sophisticated attacks that are protocol-compliant, non-intrusive, and utilize legitimate application-layer requests to overwhelm system resources. We characterize applicationlayer resource attacks as either request flooding, asymmetric, or repeated one-shot, on the basis of the application workload parameters that they exploit. To protect servers from these attacks, we propose a counter-mechanism that consists of a suspicion assignment mechanism and a DDoS-resilient scheduler, DDoS Shield. In contrast to prior work, our suspicion mechanism assigns a continuous value as opposed to a binary measure to each client session, and the scheduler utilizes these values to determine if and when to schedule a session’s requests. Using testbed experiments on a web application, we demonstrate the potency of these resource attacks and evaluate the efficacy of our countermechanism. For instance, we mount an asymmetric attack which overwhelms the server resources, increasing the response time of legitimate clients from 0.1 seconds to 40 seconds. Under the same attack scenario, DDoS Shield improves the victims’ performance to 1.5 seconds.

In this paper, we propose SFD algorithm to reduce the user-perceived web response time (i.e. web latency) . This algorithm gives short flows preferential treatment and penalizes long flows. We implement SFD algorithm as a simple differentiated services policy and evaluate its performance in simulation. We find that the transmission latency of short flows and the response time to retrieve representative web pages are both reduced by about 30%. Using web traces we demonstrate that 99% web pages would be transferred faster. SFD also bounds the penalty to long flows. We further evaluate how different schemes trade-off the performance between short and long flows.

Response time is a key differentiation among electronic commerce (e-commerce) applica- tions. For many e-commerce applications, Web pages are created dynamically based on the current state of a business stored in database systems. Recently, the topic of Web acceleration for database-driven Web applica- tions has drawn a lot of attention in both the research community and commercial arena.

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Interactive TCP applications, such as Telnet and the Web, are particularly sensitive to network congestion. Indeed, congestion-induced queuing and packet loss can be a significant cause of large delays and variability, thereby decreasing user-perceived quality. We consider addressing these effects using service differentiation, by giving priority to interactive applications' traffic in the network. We study different packet marking schemes and handling mechanisms (packet dropping and scheduling) in the network. For marking packets, two approaches are considered. First, we look into application-based marking, and show how the protection of Telnet traffic against loss can eliminate large echo delays caused by retransmit timeouts, and how, by limiting packet loss for Web page downloads, their delays can be significantly reduced, resulting in enhanced interactivity. Second, we consider differentiation based on TCP state, where we present a marking algorithm that prioritizes packets at the source, based on each connection's window size. In addition, we describe the shaping mechanisms required for conformance to agreements with the network. We show how this marking results in good response times for short transfers, which are characteristic of interactive applications, without significantly affecting longer ones.

Abstract — The scale, reliability, and cost requirements of enterprise data centers require automation of center management. Examples include provisioning, scheduling, capacity planning, logging and auditing. A key component of such automation functions is online monitoring. In contrast to monitoring systems designed for human users, a particular concern for online enterprise monitoring is Quality of Service (QoS). Since breaking service level agreements (SLAs) has direct financial and legal implications, enterprise monitoring must be conducted so as to maintain SLAs. This includes the ability to differentiate the QoS of monitoring itself for different classes of users or more generally, for software components subject to different SLAs. Thus, without embedding notions of QoS into the monitoring systems used in next generation data centers, it will not be possible to accomplish the desired automation of their operation. This paper both demonstrates the importance of QoS in monitoring, and it presents a QoS-capable monitoring system, termed QMON. QMON supports utility-aware monitoring while also able to differentiate between different classes of monitoring, corresponding to classes of SLAs. The implementation of QMON offers high levels of predictability for service delivery (i.e., predictable performance), and it is dynamically configurable to deal with changes in enterprise needs or variations in services and applications. We demonstrate the importance of QoS in monitoring and the QoS capabilities of QMON in a series of case studies and experiments, using a multi-tier web service benchmark. I.

Abstract. Traditionally, user traffic profiling is performed by analyzing traffic traces collected on behalf of the user at aggregation points located in the middle of the network. However, the modern enterprise network has a highly mobile population that frequently moves in and out of its physical perimeter. Thus an in-the-network monitor is unlikely to capture full user activity traces when users move outside the enterprise perimeter. The distinct environments, such as the cubicle and the coffee shop (among others), that users visit, may each pose different constraints and lead to varied behavioral modes. It is thus important to ask: is the profile of a user constructed in one environment representative of the same user in another environment? In this paper, we answer in the negative for the mobile population of an enterprise. Using real corporate traces collected at nearly 400 endhosts for approximately 5 weeks, we study how end-host usage differs across three environments: inside the enterprise, outside the enterprise but using a VPN, and entirely outside the enterprise network. Within these environments, we examine three types of features: (i) environment lifetimes, (ii) relative usage statistics of network services, and (iii) outlier detection thresholds as used for anomaly detection. We find significant diversity in end-host behavior across environments for many features, thus indicating that profiles computed for a user in one environment yield inaccurate representations of the same user in a different environment. 1

SILK stands for Scout In the Linux Kernel, and is a port of the Scout operating system to run as a Linux kernel module. SILK forms a replacement networking subsystem for standard Linux 2.4 kernels. Linux applications create and use Scout paths via the Linux socket interface with virtually no modifications to the applications themselves. SILK provides Linux applications with the benefits of Scout paths, including early packet demultiplexing, per-flow accounting of resources, and explicit scheduling of network processing. SILK also introduces the concept of an extended path to provide a framework for application QoS. We demonstrate the utility of SILK by showing how it can provide QoS for the Apache Web server.