In peer-to-peer systems, attrition attacks include both traditional, network-level denial of service attacks as well as application-level attacks in which malign peers conspire to waste loyal peers' resources. We describe several defenses for LOCKSS, a peer-to-peer digital preservation system, that help ensure that application-level attacks even from powerful adversaries are less effective than simple network-level attacks, and that network-level attacks must be intense, wide-spread, and prolonged to impair the system.
Admission control has been used to improve the usability of overloaded services. For example, @cite_1 propose admission control strategies that help protect long-running Web service sessions (i.e., related sequences of requests) from abrupt termination. Preserving the responsiveness of Web services in the face of demand spikes is critical, whereas LOCKSS peers need only manage their resources to make progress at the necessary rate in the long term. They can treat demand spikes as hostile behavior. In a P2P context, @cite_14 use admission control (and rate limiting) to mitigate the effects of a query flood attack against superpeers in unstructured file-sharing peer-to-peer networks such as Gnutella.
@cite_14 @cite_1
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We consider a new, session-based workload for measuring web server performance. We define a session as a sequence of client's individual requests. Using a simulation model, we show that an overloaded web server can experience a severe loss of throughput measured as a number of completed sessions compared against the server throughput measured in requests per second. Moreover, statistical analysis of completed sessions reveals that the overloaded web server discriminates against longer sessions. For e-commerce retail sites, longer sessions are typically the ones that would result in purchases, so they are precisely the ones for which the companies want to guarantee completion. To improve Web QoS for commercial Web servers, we introduce a session-based admission control (SBAC) to prevent a web server from becoming overloaded and to ensure that longer sessions can be completed. We show that a Web server augmented with the admission control mechanism is able to provide a fair guarantee of completion, for any accepted session, independent of a session length. This provides a predictable and controllable platform for web applications and is a critical requirement for any e-business. Additionally, we propose two new adaptive admission control strategies, hybrid and predictive, aiming to optimize the performance of SBAC mechanism. These new adaptive strategies are based on a self-tunable admission control function, which adjusts itself accordingly to variations in traffic loads. An admission control algorithm must coordinate between flows to provide guarantees about how the medium is shared. In wired networks, nodes can monitor the medium to see how much bandwidth is being used. However, in ad hoc networks, communication from one node may consume the bandwidth of neighboring nodes. Therefore, the bandwidth consumption of flows and the available resources to a node are not local concepts, but related to the neighboring nodes in carrier-sensing range. Current solutions do not address how to perform admission control in such an environment so that the admitted flows in the network do not exceed network capacity. In this paper, we present a scalable and efficient admission control framework - contention-aware admission control protocol (CACP) - to support QoS in ad hoc networks. We present several options for the design of CACP and compare the performance of these options using both mathematical analysis and simulation results. We also demonstrate the effectiveness of CACP compared to existing approaches through extensive simulations. There is a growing adoption of cloud computing services, attracting users with different requirements and budgets to run their applications in cloud infrastructures. In order to match users' needs, cloud providers can offer multiple service classes with different pricing and Service Level Objective (SLO) guarantees. Admission control mechanisms can help providers to meet target SLOs by limiting the demand at peak periods. This paper proposes a prediction-based admission control model for IaaS clouds with multiple service classes, aiming to maximize request admission rates while fulfilling availability SLOs defined for each class. We evaluate our approach with trace-driven simulations fed with data from production systems. Our results show that admission control can reduce SLO violations significantly, specially in underprovisioned scenarios. Moreover, our predictive heuristics are less sensitive to different capacity planning and SLO decisions, as they fulfill availability SLOs for more than 91 of requests even in the worst case scenario, for which only 56 of SLOs are fulfilled by a simpler greedy heuristic and as little as 0.2 when admission control is not used. Networks that support multiple services through "link-sharing" must address the fundamental conflicting requirement between isolation among service classes to satisfy each class' quality of service requirements, and statistical sharing of resources for efficient network utilization. While a number of service disciplines have been devised which provide mechanisms to both isolate flows and fairly share excess capacity, admission control algorithms are needed which exploit the effects of inter-class resource sharing. In this paper, we develop a framework of using statistical service envelopes to study inter-class statistical resource sharing. We show how this service envelope enables a class to over-book resources beyond its deterministically guaranteed capacity by statistically characterizing the excess service available due to fluctuating demands of other service classes. We apply our techniques to several multi-class schedulers, including generalized processor sharing, and design new admission control algorithms for multi-class link-sharing environments. We quantify the utilization gains of our approach with a set of experiments using long traces of compressed video.