9589474
DotSlash: A Self-Configuring and Scalable Rescue System for Handling Web Hotspots Effectively
DotSlash allows different web sites to form a mutual-aid community, and use spare capacity in the community to relieve web hotspots experienced by any individual site. As a rescue system, DotSlash intervenes when a web site becomes heavily loaded, and is phased out once the workload returns to normal. It aims to complement the existing web server infrastructure to handle short-term load spikes effectively. DotSlash is self-configuring, scalable, cost-effective, easy to use, and transparent to clients. It targets small web sites, although large web sites can also benefit from it. We have implemented a prototype of DotSlash on top of Apache. Experiments show that using DotSlash a web server can increase the request rate it supported and the data rate it delivered to clients by an order of magnitude, even if only HTTP redirect is used. Parts of this work may be applicable to other services such as Grid computational services.
30153007
Selective anti-entropy
Anti-entropy [1] is an important mechanism to achieve eventual consistency among a set of replicas. We refer to traditional antientropy [2, 3] as complete anti-entropy, where two replicas reconcile all inconsistent states between them in a two-way session or two one-way sessions. Complete anti-entropy works well in full replications, but may cause a summary problem (a replica cannot summarize its received updates using a summary vector) in partial replications (where the state set is divided into subsets referred to as scopes). To avoid the summary problem, we propose to use selective anti-entropy, which is to selectively reconcile inconsistent states between two replicas in a session, i.e., a replica specifies the subsets of updates it solicits, and thus controls what it receives from another replica. In selective anti-entropy, all updates that are initially received by the same replica R= belong to the same s u b s e t / ~ . The subset of a state is determined by the last update applied to it. A selective anti-entropy session where R¢ requests new updates in -P~i, Rx2, .... R~ k from R~ is denoted as O(R~, {/:/=~, Rx2, ..., R=k }, R~). We distinguish four types of selective anti-entropy sessions (listed in Figure 1) based on the number of subsets requested and whether the session is direct or indirect. We assume that a replica R¢ does not request updates in ~ from other replicas. A session is direct if it only requests updates in R--~ from R= (e.g., O___(R~, { ~ } , R~)), otherwise the session is indirect (e.g., O(R=, {1-~u}, R~)) or mixed (e.g., O(_R=, {R~, R~}, R~)). A select-multiple or select-all session can be viewed as comprising k (k >_ 2) select-one sessions, in which at most one is select-one-direct session, and the rest are select-one-indirect sessions. A select-all session is equivalent to a complete anti-entropy session. An anti-entropy session is safe if it will not cause the summary problem. A replica can always choose safe sessions by using selective anti-entropy. Any select-one-direct anti-entropy session, such as O(R=, {R~}, R~), is safe. A select-one-indirect anti-entropy session O(R=, {R-~y}, R~) is safe if S(R=) A S(Ru) C_ S(R~), where S(R=), S(Ru) and S(Rz) denote the scopes of Re, Rv and R~, respectively. In other words, if S(R=) n S(Ru) D S(R=), O(R=, {R-~}, Rz) may cause the summary problem. In Figure 2, for example, O(Ra, {R1}, R6) is safe because S(Ra) N S(R1) = {$1, $2} = S(R6) , but O(R3, {R6}, R2) may not be safe since
2999153
Distributed policy processing in virtual private operation environment for large scale networks
VPOE (virtual private operation environment) is an infrastructure to provide customized services for applications in large-scale heterogeneous networks. In this infrastructure, the programmable network devices - called "middleware boxes" can be deployed at some functional locations in the network and provide services effectively corresponding to the service requirements. The basic functionality of middleware box is to execute customized policies. With the number of applications increasing and new services becoming popular, the policy matching and processing have been becoming a bottleneck for the middleware box performance. We focus on designing a scalable policy processing architecture, aiming to deal with this issue. Particularly, our technologies include: (1) a distributed policy processing architecture for the middleware box; (2) two policy partitioning algorithms to achieve conflict-free policies for the distributed policy processing architecture and guarantee the correctness of the policy execution. We conduct extensive performance evaluations on different architectures and algorithms. The evaluation results show that the distributed architecture can achieve over 70 percent increase of performance/price ratio with proper assignment of the policy distribution degree. The experimental results also demonstrate that to make the policy both partition capable and conflict free, more new policies have to be generated, which can be effectively reduced by using the policy compression schemes.
14582686
Distributed policy processing in active-service based infrastructures
More and more applications in the Internet are requiring an intelligent service infrastructure to provide customized services. In this paper, we present an infrastructure, which can transparently and effectively provide customized active-services to end users and dynamically adapt to changing customized policies in large distributed heterogeneous environments. The infrastructure consists of two components: the policy agent and middleware box. Particularly, our technologies include: (1) Generic active-service based infrastructure, where the policy agent can integrate policies requested by applications, and middleware boxes can transparently execute services and (2) Distributed policy processing in the middleware box. We study two policy partitioning schemes to achieve conflict-free policies for distributed policy processing and guarantee the correctness of the policy execution. We conduct extensive performance evaluations on different schemes proposed. Our experimental results demonstrate that our policy partitioning schemes can effectively generate partition-capable and conflict-free policy sets. The evaluation results also show that distributed policy processing can achieve over 70% increase in performance/price ratio with proper assignment of the policy distribution degree compared to a purely centralized approach. Copyright © 2005 John Wiley & Sons, Ltd.
9581771
Scalable QoS guaranteed communication services for real-time applications
We propose an approach to flow-unaware admission control which is a combination with an aggregate packet forwarding scheme, improving scalability of networks while guaranteeing end-to-end deadlines for real-time applications. We achieve this by using an off-line delay computation and verification step, which allows to reduce the overhead at admission control while keeping admission probability and resource utilization high. Our evaluation data show that our system's admission probabilities are very close to those of significantly more expensive flow-aware approaches. At the same time, the admission control overhead during flow establishment is very low. Our results therefore support the claim from the DS architecture literature that scalability can be achieved through flow aggregation without sacrificing resource utilization and with significant reduction in run time overhead.
15389203
Analyzing and enhancing the resilience of structured peer-to-peer systems
In this paper, we propose an approach to analyze the resilience of structured peer-to-peer (P2P) systems under failures. The approach is Markov-chain based, and can be applied to systems with relatively stable size and uniform distribution of nodes. We apply our approach to several well-known structured P2P systems. We find that different system features (types of neighbors of nodes) in P2P systems have different impacts on their resilience against failures. Following this observation, we propose to add some extra neighbor(s) to CAN using small-world model principles to form a so-called CAN-SW system. We then apply the proposed approach to analyze its resilience. We find that the performance is improved significantly, particularly, in terms of the average path length.
17537617
Self-adaptive Worms and Countermeasures
In this paper, we address issues related to defending against widespreading worms on the Internet. We study a new class of worms called the selfadaptive worms. These worms dynamically adapt their propagation patterns to defensive countermeasures, in order to avoid or postpone detection, and to eventually infect more computers. We show that existing worm detection schemes cannot effectively defend against these self-adaptive worms. To counteract these worms, we introduce a game-theoretic formulation to model the interaction between worm propagator and defender. We show that the effective integration of multiple defensive schemes (e.g., worm detection, forensics analysis) is critical for defending against self-adaptive worms. We propose different combinations of defensive schemes for different kinds of self-adaptive worms, and evaluate the performance of defensive schemes based on real-world traffic traces.