45 research outputs found

    ShutUp: End-to-End Containment of Unwanted Traffic

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    While the majority of Denial-of-Service (DoS) defense proposals assume a purely infrastructure-based architecture, some recent proposals suggest that the attacking endhost may be enlisted as part of the solution, through tamper-proof software, network-imposed incentives, or user altruism. While intriguing, these proposals ultimately raise the deployment bar by requiring both the infrastructure and endhosts to cooperate. In this paper, we explore the design of a pure end-to-end architecture based on tamper-proof endhost software implemented for instance with trusted platforms and virtual machines. We present the design of a ?Shutup Service?, whereby the recipient of unwanted traffic can ask the sender to slowdown or stop. We show that this service is effective in stopping DoS attacks, and in significantly slowing down other types of unwanted traffic such as worms. The Shutup service is incrementally deployable with buy-in from OS or antivirus vendors, requiring only minimal changes to the endhost software stack and no changes to the protocol stack. We show through experimentation that the service is effective and has little impact on legitimate traffic

    On Utilization of Contributory Storage in Desktop Grids

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    The availability of desktop grids and shared computing platforms has popularized the use of contributory resources, such as desktops, as computing substrates for a variety of applications. However, addressing the exponentially growing storage demands of applications, especially in a contributory environment, remains a challenging research problem. In this report, we propose a transparent distributed storage system that harnesses the storage contributed by grid participants arranged in a peer-to-peer network to yield a scalable, robust, and self-organizing system. The novelty of our work lies in (i) design simplicity to facilitate actual use; (ii) support for easy integration with grid platforms; (iii) ingenious use of striping and error coding techniques to support very large data files; and (iv) the use of multicast techniques for data replication. Experimental results through simulations and an actual implementation show that our system can provide reliable and efficient storage with large file support for desktop grid applications

    Middleware-based Database Replication: The Gaps between Theory and Practice

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    The need for high availability and performance in data management systems has been fueling a long running interest in database replication from both academia and industry. However, academic groups often attack replication problems in isolation, overlooking the need for completeness in their solutions, while commercial teams take a holistic approach that often misses opportunities for fundamental innovation. This has created over time a gap between academic research and industrial practice. This paper aims to characterize the gap along three axes: performance, availability, and administration. We build on our own experience developing and deploying replication systems in commercial and academic settings, as well as on a large body of prior related work. We sift through representative examples from the last decade of open-source, academic, and commercial database replication systems and combine this material with case studies from real systems deployed at Fortune 500 customers. We propose two agendas, one for academic research and one for industrial R&D, which we believe can bridge the gap within 5-10 years. This way, we hope to both motivate and help researchers in making the theory and practice of middleware-based database replication more relevant to each other.Comment: 14 pages. Appears in Proc. ACM SIGMOD International Conference on Management of Data, Vancouver, Canada, June 200

    Distributed k-ary System: Algorithms for Distributed Hash Tables

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    This dissertation presents algorithms for data structures called distributed hash tables (DHT) or structured overlay networks, which are used to build scalable self-managing distributed systems. The provided algorithms guarantee lookup consistency in the presence of dynamism: they guarantee consistent lookup results in the presence of nodes joining and leaving. Similarly, the algorithms guarantee that routing never fails while nodes join and leave. Previous algorithms for lookup consistency either suffer from starvation, do not work in the presence of failures, or lack proof of correctness. Several group communication algorithms for structured overlay networks are presented. We provide an overlay broadcast algorithm, which unlike previous algorithms avoids redundant messages, reaching all nodes in O(log n) time, while using O(n) messages, where n is the number of nodes in the system. The broadcast algorithm is used to build overlay multicast. We introduce bulk operation, which enables a node to efficiently make multiple lookups or send a message to all nodes in a specified set of identifiers. The algorithm ensures that all specified nodes are reached in O(log n) time, sending maximum O(log n) messages per node, regardless of the input size of the bulk operation. Moreover, the algorithm avoids sending redundant messages. Previous approaches required multiple lookups, which consume more messages and can render the initiator a bottleneck. Our algorithms are used in DHT-based storage systems, where nodes can do thousands of lookups to fetch large files. We use the bulk operation algorithm to construct a pseudo-reliable broadcast algorithm. Bulk operations can also be used to implement efficient range queries. Finally, we describe a novel way to place replicas in a DHT, called symmetric replication, that enables parallel recursive lookups. Parallel lookups are known to reduce latencies. However, costly iterative lookups have previously been used to do parallel lookups. Moreover, joins or leaves only require exchanging O(1) messages, while other schemes require at least log(f) messages for a replication degree of f. The algorithms have been implemented in a middleware called the Distributed k-ary System (DKS), which is briefly described

    Protection Models for Web Applications

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    Early web applications were a set of static web pages connected to one another. In contrast, modern applications are full-featured programs that are nearly equivalent to desktop applications in functionality. However, web servers and web browsers, which were initially designed for static web pages, have not updated their protection models to deal with the security consequences of these full-featured programs. This mismatch has been the source of several security problems in web applications. This dissertation proposes new protection models for web applications. The design and implementation of prototypes of these protection models in a web server and a web browser are also described. Experiments are used to demonstrate the improvements in security and performance from using these protection models. Finally, this dissertation also describes systematic design methods to support the security of web applications

    Performance Improvement of Multithreaded Java Applications Execution on Multiprocessor Systems

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    El disseny del llenguatge Java, que inclou aspectes importants com són la seva portabilitat i neutralitat envers l'arquitectura, les seves capacitats multithreading, la seva familiaritat (degut a la seva semblança amb C/C++), la seva robustesa, les seves capacitats en seguretat i la seva naturalesa distribuïda, fan que sigui un llenguatge potencialment interessant per ser utilitzat en entorns paral·lels com són els entorns de computació d'altes prestacions (HPC), on les aplicacions poden treure profit del suport que ofereix Java a l'execució multithreaded per realitzar càlculs en paral·lel, o en entorns e-business, on els servidors Java multithreaded (que segueixen l'especificació J2EE) poden treure profit de les capacitats multithreading de Java per atendre de manera concurrent un gran nombre de peticions.No obstant, l'ús de Java per la programació paral·lela ha d'enfrontar-se a una sèrie de problemes que fàcilment poden neutralitzar el guany obtingut amb l'execució en paral·lel. El primer problema és el gran overhead provocat pel suport de threads de la JVM quan s'utilitzen threads per executar feina de gra fi, quan es crea un gran nombre de threads per suportar l'execució d'una aplicació o quan els threads interaccionen estretament mitjançant mecanismes de sincronització. El segon problema és la degradació en el rendiment produïda quan aquestes aplicacions multithreaded s'executen en sistemes paral·lels multiprogramats. La principal causa d'aquest problemes és la manca de comunicació entre l'entorn d'execució i les aplicacions, la qual pot induir a les aplicacions a fer un ús descoordinat dels recursos disponibles.Aquesta tesi contribueix amb la definició d'un entorn per analitzar i comprendre el comportament de les aplicacions Java multithreaded. La contribució principal d'aquest entorn és que la informació de tots els nivells involucrats en l'execució (aplicació, servidor d'aplicacions, JVM i sistema operatiu) està correlada. Aquest fet és molt important per entendre com aquest tipus d'aplicacions es comporten quan s'executen en entorns que inclouen servidors i màquines virtuals, donat que l'origen dels problemes de rendiment es pot trobar en qualsevol d'aquests nivells o en la seva interacció.Addicionalment, i basat en el coneixement adquirit mitjançant l'entorn d'anàlisis proposat, aquesta tesi contribueix amb mecanismes i polítiques de planificació orientats cap a l'execució eficient d'aplicacions Java multithreaded en sistemes multiprocessador considerant les interaccions i la coordinació dels mecanismes i les polítiques de planificació en els diferents nivells involucrats en l'execució. La idea bàsica consisteix en permetre la cooperació entre les aplicacions i l'entorn d'execució en la gestió de recursos establint una comunicació bi-direccional entre les aplicacions i el sistema. Per una banda, les aplicacions demanen a l'entorn d'execució la quantitat de recursos que necessiten. Per altra banda, l'entorn d'execució pot ser inquirit en qualsevol moment per les aplicacions ser informades sobre la seva assignació de recursos. Aquesta tesi proposa que les aplicacions utilitzin la informació proporcionada per l'entorn d'execució per adaptar el seu comportament a la quantitat de recursos que tenen assignats (aplicacions auto-adaptables). Aquesta adaptació s'assoleix en aquesta tesi per entorns HPC per mitjà de la mal·leabilitat de les aplicacions, i per entorns e-business amb una proposta de control de congestió que fa control d'admissió basat en la diferenciació de connexions SSL per prevenir la degradació del rendiment i mantenir la Qualitat de Servei (QoS).Els resultats de l'avaluació demostren que subministrar recursos de manera dinàmica a les aplicacions auto-adaptables en funció de la seva demanda millora el rendiment de les aplicacions Java multithreaded tant en entorns HPC com en entorns e-business. Mentre disposar d'aplicacions auto-adaptables evita la degradació del rendiment, el subministrament dinàmic de recursos permet satisfer els requeriments de les aplicacions en funció de la seva demanda i adaptar-se a la variabilitat de les seves necessitats de recursos. D'aquesta manera s'aconsegueix una millor utilització dels recursos donat que els recursos que no utilitza una aplicació determinada poden ser distribuïts entre les altres aplicacions.The design of the Java language, which includes important aspects such as its portability and architecture neutrality, its multithreading facilities, its familiarity (due to its resemblance with C/C++), its robustness, its security capabilities and its distributed nature, makes it a potentially interesting language to be used in parallel environments such as high performance computing (HPC) environments, where applications can benefit from the Java multithreading support for performing parallel calculations, or e-business environments, where multithreaded Java application servers (i.e. following the J2EE specification) can take profit of Java multithreading facilities to handle concurrently a large number of requests.However, the use of Java for parallel programming has to face a number of problems that can easily offset the gain due to parallel execution. The first problem is the large overhead incurred by the threading support available in the JVM when threads are used to execute fine-grained work, when a large number of threads are created to support the execution of the application or when threads closely interact through synchronization mechanisms. The second problem is the performance degradation occurred when these multithreaded applications are executed in multiprogrammed parallel systems. The main issue that causes these problems is the lack of communication between the execution environment and the applications, which can cause these applications to make an uncoordinated use of the available resources.This thesis contributes with the definition of an environment to analyze and understand the behavior of multithreaded Java applications. The main contribution of this environment is that all levels in the execution (application, application server, JVM and operating system) are correlated. This is very important to understand how this kind of applications behaves when executed on environments that include servers and virtual machines, because the origin of performance problems can reside in any of these levels or in their interaction.In addition, and based on the understanding gathered using the proposed analysis environment, this thesis contributes with scheduling mechanisms and policies oriented towards the efficient execution of multithreaded Java applications on multiprocessor systems considering the interactions and coordination between scheduling mechanisms and policies at the different levels involved in the execution. The basis idea consists of allowing the cooperation between the applications and the execution environment in the resource management by establishing a bi-directional communication path between the applications and the underlying system. On one side, the applications request to the execution environment the amount of resources they need. On the other side, the execution environment can be requested at any time by the applications to inform them about their resource assignments. This thesis proposes that applications use the information provided by the execution environment to adapt their behavior to the amount of resources allocated to them (self-adaptive applications). This adaptation is accomplished in this thesis for HPC environments through the malleability of the applications, and for e-business environments with an overload control approach that performs admission control based on SSL connections differentiation for preventing throughput degradation and maintaining Quality of Service (QoS).The evaluation results demonstrate that providing resources dynamically to self-adaptive applications on demand improves the performance of multithreaded Java applications as in HPC environments as in e-business environments. While having self-adaptive applications avoids performance degradation, dynamic provision of resources allows meeting the requirements of the applications on demand and adapting to their changing resource needs. In this way, better resource utilization is achieved because the resources not used by some application may be distributed among other applications

    On I/O Performance and Cost Efficiency of Cloud Storage: A Client\u27s Perspective

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    Cloud storage has gained increasing popularity in the past few years. In cloud storage, data are stored in the service provider’s data centers; users access data via the network and pay the fees based on the service usage. For such a new storage model, our prior wisdom and optimization schemes on conventional storage may not remain valid nor applicable to the emerging cloud storage. In this dissertation, we focus on understanding and optimizing the I/O performance and cost efficiency of cloud storage from a client’s perspective. We first conduct a comprehensive study to gain insight into the I/O performance behaviors of cloud storage from the client side. Through extensive experiments, we have obtained several critical findings and useful implications for system optimization. We then design a client cache framework, called Pacaca, to further improve end-to-end performance of cloud storage. Pacaca seamlessly integrates parallelized prefetching and cost-aware caching by utilizing the parallelism potential and object correlations of cloud storage. In addition to improving system performance, we have also made efforts to reduce the monetary cost of using cloud storage services by proposing a latency- and cost-aware client caching scheme, called GDS-LC, which can achieve two optimization goals for using cloud storage services: low access latency and low monetary cost. Our experimental results show that our proposed client-side solutions significantly outperform traditional methods. Our study contributes to inspiring the community to reconsider system optimization methods in the cloud environment, especially for the purpose of integrating cloud storage into the current storage stack as a primary storage layer

    ENHANCING CLOUD SYSTEM RUNTIME TO ADDRESS COMPLEX FAILURES

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    As the reliance on cloud systems intensifies in our progressively digital world, understanding and reinforcing their reliability becomes more crucial than ever. Despite impressive advancements in augmenting the resilience of cloud systems, the growing incidence of complex failures now poses a substantial challenge to the availability of these systems. With cloud systems continuing to scale and increase in complexity, failures not only become more elusive to detect but can also lead to more catastrophic consequences. Such failures question the foundational premises of conventional fault-tolerance designs, necessitating the creation of novel system designs to counteract them. This dissertation aims to enhance distributed systems’ capabilities to detect, localize, and react to complex failures at runtime. To this end, this dissertation makes contributions to address three emerging categories of failures in cloud systems. The first part delves into the investigation of partial failures, introducing OmegaGen, a tool adept at generating tailored checkers for detecting and localizing such failures. The second part grapples with silent semantic failures prevalent in cloud systems, showcasing our study findings, and introducing Oathkeeper, a tool that leverages past failures to infer rules and expose these silent issues. The third part explores solutions to slow failures via RESIN, a framework specifically designed to detect, diagnose, and mitigate memory leaks in cloud-scale infrastructures, developed in collaboration with Microsoft Azure. The dissertation concludes by offering insights into future directions for the construction of reliable cloud systems
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