3391053
Wealth-Based Evolution Model for the Internet AS-Level Topology
In this paper, we seek to understand the intrinsic reasons for the well-known phenomenon of heavy-tailed degree in the Internet AS graph and argue that in contrast to traditional models based on preferential attachment and centralized opti- mization, the Pareto degree of the Internet can be explained by the evolution of wealth associated with each ISP. The proposed topology model utilizes a simple multiplicative stochastic process that determines each ISP's wealth at different points in time and several "maintenance" rules that keep the degree of each node proportional to its wealth. Actual link formation is determined in a decentralized fashion based on random walks, where each ISP individually decides when and how to increase its degree. Simulations show that the proposed model, which we call Wealth-based Internet Topology (WIT), produces scale-free random graphs with tunable exponent α and high clustering coefficients (between 0.35 and 0.5) that stay invariant as the size of the graph increases. This evolution closely mimics that of the Internet observed since 1997.
1958263
On zone-balancing of peer-to-peer networks: analysis of random node join
Balancing peer-to-peer graphs, including zone-size distributions, has recently become an important topic of peer-to-peer (P2P) research [1], [2], [6], [19], [31], [36]. To bring analytical understanding into the various peer-join mechanisms, we study how zone-balancing decisions made during the initial sampling of the peer space affect the resulting zone sizes and derive several asymptotic results for the maximum and minimum zone sizes that hold with high probability.
322407
IRLbot: Scaling to 6 billion pages and beyond
This article shares our experience in designing a Web crawler that can download billions of pages using a single-server implementation and models its performance. We first show that current crawling algorithms cannot effectively cope with the sheer volume of URLs generated in large crawls, highly branching spam, legitimate multimillion-page blog sites, and infinite loops created by server-side scripts. We then offer a set of techniques for dealing with these issues and test their performance in an implementation we call IRLbot. In our recent experiment that lasted 41 days, IRLbot running on a single server successfully crawled 6.3 billion valid HTML pages (7.6 billion connection requests) and sustained an average download rate of 319 mb/s (1,789 pages/s). Unlike our prior experiments with algorithms proposed in related work, this version of IRLbot did not experience any bottlenecks and successfully handled content from over 117 million hosts, parsed out 394 billion links, and discovered a subset of the Web graph with 41 billion unique nodes.
1669034
Modeling Heterogeneous User Churn and Local Resilience of Unstructured P2P Networks
Previous analytical results on the resilience of unstructured P2P systems have not explicitly modeled heterogeneity of user churn (i.e., difference in online behavior) or the impact of in-degree on system resilience. To overcome these limitations, we introduce a generic model of heterogeneous user churn, derive the distribution of the various metrics observed in prior experimental studies (e.g., lifetime distribution of joining users, joint distribution of session time of alive peers, and residual lifetime of a randomly selected user), derive several closed-form results on the transient behavior of in-degree, and eventually obtain the joint in/out degree isolation probability as a simple extension of the out-degree model.
3433910
Residual-Based Measurement of Peer and Link Lifetimes in Gnutella Networks
Existing methods of measuring lifetimes in P2P systems usually rely on the so-called create-based method (CBM), which divides a given observation window into two halves and samples users "created" in the first half every Delta time units until they die or the observation period ends. Despite its frequent use, this approach has no rigorous accuracy or overhead analysis in the literature. To shed more light on its performance, we flrst derive a model for CBM and show that small window size or large Delta may lead to highly inaccurate lifetime distributions. We then show that create-based sampling exhibits an inherent tradeoff between overhead and accuracy, which does not allow any fundamental improvement to the method. Instead, we propose a completely different approach for sampling user dynamics that keeps track of only residual lifetimes of peers and uses a simple renewal-process model to recover the actual lifetimes from the observed residuals. Our analysis indicates that for reasonably large systems, the proposed method can reduce bandwidth consumption by several orders of magnitude compared to prior approaches while simultaneously achieving higher accuracy. We finish the paper by implementing a two-tier Gnutella network crawler equipped with the proposed sampling method and obtain the distribution of ultrapeer lifetimes in a network of 6.4 million users and 60 million links. Our experimental results show that ultrapeer lifetimes are Pareto with shape a alpha ap 1.1; however, link lifetimes exhibit much lighter tails with alpha ap 1.9.
1202188
Load-Balancing Performance of Consistent Hashing: Asymptotic Analysis of Random Node Join
Balancing of structured peer-to-peer graphs, including their zone sizes, has recently become an important topic of distributed hash table (DHT) research. To bring analytical understanding into the various peer-join mechanisms based on consistent hashing, we study how zone-balancing decisions made during the initial sampling of the peer space affect the resulting zone sizes and derive several asymptotic bounds for the maximum and minimum zone sizes that hold with high probability. Several of our results contradict those of prior work and shed new light on the theoretical performance limitations of consistent hashing. We use simulations to verify our models and compare the performance of the various methods using the example of recently proposed de Bruijn DHTs.
41225271
On Internal Cardinal Direction Relations
Internal Cardinal Direction (ICD) relations can be considered as the refinement to the contains/within topological relation. It is widely used to describe the position of an object in a region. In this paper, three ICD models with varying degrees of details are presented – ICD-5, ICD-9 and ICD-13. In each of these, the notion of a “middle part” is defined using Minimum Bounding Rectangles (MBR). Then focusing on ICD-9, three representation methods are discussed. They are major portion, point set of intersections and proportions of intersections respectively. The ICD-9 model is validated by a cognitive experiment, which helped to determine the size of the middle part in ICD-9 and validate the MBR-based partition method. Based on a psychological theory about vague predicates, conceptual neighborhood and intersection of ICD relations are also discussed briefly.
37286032
A Random Key Management Scheme for Wireless Sensor Networks
The establishment of shared keys between communicating neighbor nodes in wireless sensor networks is a challenge due to resource-constrained sensor networks. Several key pre-distribution schemes have been proposed in literatures to establish pairwise keys between sensor nodes. However, many of them are either too complicated to fit for wireless sensor networks or insecure for some common aggressions. In this paper, we propose a random key management scheme based on random key pre-distribution for wireless sensor networks. To achieve better performance and security, the proposed scheme employs two different phases to establish enhanced pairwise keys between neighboring nodes. Compared with other existing random key pre-distribution schemes, our scheme has better resilience against node capture and also performs better in terms of network connectivity and scalability with appropriate memory, computation and communication overheads.
37107541
Ant Colony Optimization-Based Location-Aware Routing for Wireless Sensor Networks
The routing for Wireless Sensor Networks (WSNs) is a key and hard problem, and it is a research topic in the field of WSN applications. Based on Ant Colony Optimization (ACO), this paper proposes a novel adaptive intelligent routing scheme for WSNs. Following the proposed scheme, a high performance routing algorithm for WSNs is designed. The proposed routing scheme is very different from the existing ACO based routing schema for WSNs. On one hand, in the proposed scheme, the search range for an ant to select its next-hop node is limited to a subset of the set of the neighbors of the current node. On the other hand, by fusing the residual energy and the global and local location information of nodes, the new probability transition rules for an ant to select its next-hop node are defined. Compared with other ACO based routing algorithms for WSNs, the proposed routing algorithm has a better network performance on aspects of energy consumption, energy efficiency, and packet delivery latency.
205494087
A uniformly dissipative scheme for stationary statistical properties of the infinite Prandtl number model
The purpose of this short communication is to announce that a class of numerical schemes, uniformly dissipative approximations, which uniformly preserve the dissipativity of the continuous infinite dimensional dissipative complex (chaotic) systems possess desirable properties in terms of approximating stationary statistics properties. In particular, the stationary statistical properties of these uniformly dissipative schemes converge to those of the continuous system at vanishing mesh size. The idea is illustrated on the infinite Prandtl number model for convection and semi-discretization in time, although the general strategy works for a broad class of dissipative complex systems and fully discretized approximations. As far as we know, this is the first result on rigorous validation of numerical schemes for approximating stationary statistical properties of general infinite dimensional dissipative complex systems.
14457115
General Method to Build Deterministic Small-World Networks Based on Cayley Graph
Many real-life networks, such as the WWW, biological realms, and social networks are small-world networks. Most previous researches on small-world networks have been based on probabilistic methods. In this paper, we present a general method by using Cayley graph to build deterministic small-world networks. We also analyze the cluster topology of the Cayley graph with small world properties by constructing its left Coset graph. This method has great value in constructing interconnection networks model and analyzing many other real network models.