12758700
Distributed cache updating for the dynamic source routing protocol
On-demand routing protocols use route caches to make routing decisions. Due to mobility, cached routes easily become stale. To address the cache staleness issue, prior work in DSR used heuristics with ad hoc parameters to predict the lifetime of a link or a route. However, heuristics cannot accurately estimate timeouts because topology changes are unpredictable. In this paper, we propose proactively disseminating the broken link information to the nodes that have that link in their caches. We define a new cache structure called a cache table and present a distributed cache update algorithm. Each node maintains in its cache table the information necessary for cache updates. When a link failure is detected, the algorithm notifies all reachable nodes that have cached the link in a distributed manner. The algorithm does not use any ad hoc parameters, thus making route caches fully adaptive to topology changes. We show that the algorithm outperforms DSR with path caches and with Link-MaxLife, an adaptive timeout mechanism for link caches. We conclude that proactive cache updating is key to the adaptation of on-demand routing protocols to mobility.
8830976
A distributed adaptive cache update algorithm for the dynamic source routing protocol
On-demand routing protocols use route caches to make routing decisions. Due to mobility, cached routes easily become stale. To address the cache staleness issue, prior work in DSR used heuristics with ad hoc parameters to predict the lifetime of a link or a route. However, heuristics cannot accurately predict timeouts because topology changes are unpredictable. In this paper, we propose to proactively disseminate the broken link information to the nodes that have that link in their caches. We define a new cache structure called a cache table and present a distributed cache update algorithm. Each node maintains in its cache table the information necessary for cache updates. When a link failure is detected, the algorithm notifies all reachable nodes that have cached the link in a distributed manner. The algorithm does not use any ad hoc parameters, thus making route caches fully adaptive to topology changes. We show that the algorithm outperforms DSR with path caches and with Link-MaxLife, an adaptive timeout mechanism for link caches. We conclude that proactive cache updating is the key to the adaptation of on-demand routing protocols to mobility.
11486473
Circumference of Graphs with Bounded Degree
Karger, Motwani, and Ramkumar Algorithmica, 18 (1997), pp. 82--98] have shown that there is no constant approximation algorithm to find a longest cycle in a Hamiltonian graph, and they conjectured that this is the case even for graphs with bounded degree. On the other hand, Feder, Motwani, and Subi [SIAM J. Comput., 31 (2002), pp. 1596--1607] have shown that there is a polynomial time algorithm for finding a cycle of length $n^{\log_32}$ in a 3-connected cubic n-vertex graph. In this paper, we show that if G is a 3-connected n-vertex graph with maximum degree at most d, then one can find, in O(n3) time, a cycle in G of length at least $\Omega(n^{\log_b2})$, where $b=2(d-1)^2+1$.
7132341
HASE: A Hybrid Approach to Selectivity Estimation for Conjunctive Predicates
Current methods for selectivity estimation fall into two broad categories, synopsis-based and sampling-based. Synopsis-based methods, such as histograms, incur minimal overhead at query optimization time and thus are widely used in commercial database systems. Sampling-based methods are more suited for ad-hoc queries, but often involve high I/O cost because of random access to the underlying data. Though both methods serve the same purpose of selectivity estimation, their interaction in the case of selectivity estimation for conjuncts of predicates on multiple attributes is largely unexplored. Our work aims at taking the best of both worlds, by making consistent use of synopses and sample information when they are both present. To achieve this goal, we propose HASE, a novel estimation scheme based on a powerful mechanism called generalized raking. We formalize selectivity estimation in the presence of single attribute synopses and sample information as a constrained optimization problem. By solving this problem, we obtain a new set of weights associated with the sampled tuples, which has the nice property of reproducing the known selectivities when applied to individual predicates. We discuss different variants of the optimization problem and provide algorithms for solving it. We also provide asymptotic error bounds on the estimate. Extensive experiments are performed on both synthetic and real data, and the results show that HASE significantly outperforms both synopsis-based and sampling-based methods.
26301648
Data Integrity Framework and Language Support for Active Web Intermediaries
With the maturity of content adaptation technologies (such as I-CAP and OPES) in web intermediaries and of content personalization in the network, data integrity has already become a key concern when such technologies are deployed. To address this issue, we propose a data integrity framework with the following functionalities: (i) a server can specify its authorizations, (ii) active web intermediaries can provide value-added services in accordance with the server’s intentions, and more importantly, (iii) a client is facilitated to verify the received message with the server’s authorizations and intermediaries’ footprints. With the actual implementation of our data integrity framework in web (content and proxy) servers and clients, we show the feasibility and practicability of our proposed design through its low performance overhead and possible data (re)use.
1886676
Monitoring k-nearest neighbor queries over moving objects
Many location-based applications require constant monitoring of k-nearest neighbor (k-NN) queries over moving objects within a geographic area. Existing approaches to this problem have focused on predictive queries, and relied on the assumption that the trajectories of the objects are fully predictable at query processing time. We relax this assumption, and propose two efficient and scalable algorithms using grid indices. One is based on indexing objects, and the other on queries. For each approach, a cost model is developed, and a detailed analysis along with the respective applicability is presented. The object-indexing approach is further extended to multi-levels to handle skewed data. We show by experiments that our grid-based algorithms significantly outperform R-tree-based solutions. Extensive experiments are also carried out to study the properties and evaluate the performance of the proposed approaches under a variety of settings.
316842
Cycles in 4-connected planar graphs
Let G be a 4-connected planar graph on n vertices. Previous results show that G contains a cycle of length k for each k ∈ {n, n - 1,n - 2, n - 3} with k ≥ 3. These results are proved using the "Tutte path" technique, and this technique alone cannot be used to obtain further results in this direction. One approach to obtain further results is to combine Tutte paths and contractible edges. In this paper, we demonstrate this approach by showing that G also has a cycle of length k for each k ∈ {n - 4, n - 5, n - 6} with k ≥ 3. This work was partially motivated by an old conjecture of Malkevitch.