49376
Pipelined van Emde Boas Tree: Algorithms, Analysis, and Applications
Priority queues are essential for various network processing applications, including per-flow queueing with quality-of-service (QoS) guarantees, management of large fast packet buffers, and management of statistics counters. In this paper, we propose a new data structure for implementing high-performance priority queues based on a pipelined version of the van Emde Boas tree. We show that we can achieve O(1) amortized time operations using our architecture, but we can achieve this algorithmic efficiency using only O (log log u) number of pipelined stages, where u is the size of the universe used to represent the priority keys.
4332805
Stable egress route selection for interdomain traffic engineering: model and analysis
We present a general model of interdomain route selection to study interdomain traffic engineering. In this model, the routing of multiple destinations can be coordinated. Thus the model can capture general traffic engineering behaviors such as load balancing and link capacity constraints. We first identify potential routing instability and inefficiency of interdomain traffic engineering. We then derive a sufficient condition to guarantee convergence. We also show that the constraints on local policies imposed by business considerations in the Internet can guarantee stability without global coordination. Using realistic Internet topology, we evaluate the extent to which routing instability of interdomain traffic engineering can happen when the constraints are violated
1344510
COPE: traffic engineering in dynamic networks
Traffic engineering plays a critical role in determining the performance and reliability of a network. A major challenge in traffic engineering is how to cope with dynamic and unpredictable changes in traffic demand. In this paper, we propose COPE, a class of traffic engineering algorithms that optimize for the expected scenarios while providing a worst-case guarantee for unexpected scenarios. Using extensive evaluations based on real topologies and traffic traces, we show that COPE can achieve efficient resource utilization and avoid network congestion in a wide variety of scenarios.
4379994
Interdomain Routing as Social Choice
Interdomain routing is essential to both the stability and efficiency of the global Internet. However, most previous studies focus only on stability, and only on a special class of routing protocols, namely BGP-type, path-vector protocols. In this paper, we conduct a systematic analysis of interdomain routing considering optimality and implementation in strategic settings. We adopt the novel perspective that an interdomain routing system is one which defines a social choice rule that aggregates individual preferences of all of the autonomous systems (ASes) in a network to select interdomain routes with a set of desirable properties. An interdomain routing protocol, then, is a mechanism to implement the identified interdomain routing social choice rule, when the ASes can adopt strategic actions. By pointing out the incompatibility among the desirable properties of an interdomain routing system and the requirements for strategic implementation in distributed settings, we reveal fundamental tradeoffs that must be made when extending BGP or designing the next-generation interdomain routing system. We also provide new insights into BGP, by "reverseengineering" its behaviors from the perspective of social choice and implementation theory.
4407504
Optimal ISP subscription for Internet multihoming: algorithm design and implication analysis
Multihoming is a popular method used by large enterprises and stub ISPs to connect to the Internet to reduce cost and improve performance. Recently researchers have studied the potential benefits of multihoming and proposed protocols and algorithms to realize these benefits. They focus on how to dynamically select which ISPs to use for forwarding and receiving packets, and assume that the set of subscribed ISPs is given a priori. In practice, a user often has the freedom to choose which subset of ISPs among all available ISPs to subscribe to. We call the problem of how to choose the optimal set of ISPs the ISP subscription problem. In this paper, We design a dynamic programming algorithm to solve the ISP subscription problem optimally. We also design a more efficient algorithm for a large class of common pricing functions. Using real traffic traces and realistic pricing data, we show that our algorithm reduces users' cost. Next we study how ISPs respond to users' optimal ISP subscription by adjusting their pricing strategies. We call this problem the ISP pricing problem. Using a realistic charging model, we formulate the problem as a non-cooperative game. We first prove that if cost is the only criterion used by a user to determine which subset of ISPs to subscribe to, at any equilibrium all ISPs receive zero revenue. We then study a more practical formulation in which different ISPs provide different levels of reliability and users choose ISPs to both improve reliability and reduce cost. We analyze this problem and show that at any equilibrium an ISP's revenue is positive and determined by its reliability.
7757393
Reliability as an interdomain service
Reliability is a critical requirement of the Internet. The availability and resilience of the Internet under failures can have significant global effects. However, in the current Internet routing architecture, achieving the high level of reliability demanded by many mission critical activities can be costly. In this paper, we first propose a novel solution framework called reliability as an interdomain service (REIN) that can be incrementally deployed in the Internet and may improve the redundancy of IP networks at low cost. We then present robust algorithms to efficiently utilize network redundancy to improve reliability. We use real IP network topologies and traffic traces to demonstrate the effectiveness of our framework and algorithms.
12042823
bSpace: A Data Cleaning Approach for RFID Data Streams Based on Virtual Spatial Granularity
RFID holds the promise of real-time identifying, locating, tracking and monitoring physical objects without line of sight, and can be used for a wide range of pervasive computing applications. To achieve these goals, RFID data have to be collected, filtered, and transformed into semantic application data. RFID data, however, contain false readings and duplicates. Such data cannot be used directly by applications unless they are filtered and cleaned. To compensate for the inherent unreliability of RFID data streams, most RFID middleware systems employ a “smoothing filtering”. In this paper, a new “smoothing filtering” approach named bSpace is proposed, which is based on the concept of virtual spatial granularity. For providing accurate RFID data to applications, bSpace uses a Bayesian estimation algorithm to fill up false negatives, and uses the rules which we define to solve false positives.
3839837
Creating Vulnerability Signatures Using Weakest Preconditions
Signature-based tools such as network intrusion detection systems are widely used to protect critical systems. Automatic signature generation techniques are needed to enable these tools due to the speed at which new vulnerabilities are discovered. In particular, we need automatic techniques which generate sound signatures - signatures which will not mistakenly block legitimate traffic or raise false alarms. In addition, we need signatures to have few false negatives and will catch many different exploit variants. We investigate new techniques for automatically generating sound vulnerability signatures with fewer false negatives than previous research using program binary analysis. The key problem to reducing false negatives is to consider as many as possible different program paths an exploit may take. Previous work considered each possible program path an exploit may take separately, thus generating signatures that are exponential in the size of the number of branches considered. In the exact same scenario, we show how to reduce the overall signature size and the generation time from exponential to polynomial. We do this without requiring any additional assumptions, or relaxing any properties. This efficiency gain allows us to consider many more program paths, which results in reducing the false negatives of generated signatures. We achieve these results by creating algorithms for generating vulnerability signatures that are based on computing weakest preconditions (WP). The weakest precondition for a program path to a vulnerability is a function which matches all exploits that may exploit the vulnerability along that path. We have implemented our techniques and generated signatures for several binary programs. Our results demonstrate that our WP-based algorithm generates more succinct signatures than previous approaches which were based on forward symbolic execution.
38679232
Short Definitions of the Ordinals
In this paper, a simple inductive characterization of the ordinal numbers is stated and developed. The characterization forms the basis for a set of axioms for ordinal theory and also for several short explicit definitions of the ordinals. The axioms are shown to be sufficient for ordinal theory, and, subject to suitable existence assumptions, each of the definitions is shown to imply the axioms. The present results apply to the familiar von Neumann version of the ordinals, but the methods used are easily adapted to other versions. ? 1. Axioms for ordinal theory. According to the usual interpretation, each ordinal is the set of all lesser ordinals. Thus zero is the empty set A, a successor ordinal x' is x U {x} for some ordinal x, and a limit ordinal is a set w of ordinals that is equal to its own sum set Zw. In fact, the class On of all ordinals might be characterized informally as the smallest class Z such that (1) AEZ, (2) (y) (yEZ D y'EZ), and (3) (w) (1w = w c Z D wEZ). More simply, On can be characterized as the smallest Z such that
15799228
Security policy reconciliation in distributed computing environments
A major hurdle in sharing resources between organizations is heterogeneity. Therefore, in order for two organizations to collaborate their policies have to be resolved. The process of resolving different policies is known as policy reconciliation, which in general is an intractable problem. This paper addresses policy reconciliation in the context of security. We present a formal framework and hierarchical representation for security policies. Our hierarchical representation exposes the structure of the policies and leads to an efficient reconciliation algorithm. We also demonstrate that agent preferences for security mechanisms can be readily incorporated into our framework. We have implemented our reconciliation algorithm in a library called the policy reconciliation engine or PRE. In order to test the implementation and measure the overhead of our reconciliation algorithm, we have integrated PRE into a distributed high-throughput system called Condor.
5067889
Facial Expression Synthesis and Recognition with Intensity Alignment
A method of cooling section steel, particularly sectional steel girders, from rolling heat, wherein, prior to a final air cooling, a water cooling process is carried out in such a way that section steel portions with material concentrations are cooled at outwardly projecting portions of the steel sections over a width of application and a duration of application which are variable and subject to a predetermined cooling strategy supported by a process computer to a value which is at least still slightly above the transformation temperature Ar1.