12441563
To Repair or Not To Repair: Helping Ad-hoc Routing Protocols to Distinguish Mobility from Congestion
In this paper we consider the problem of distinguishing whether frame loss at the MAC layer has occurred due to mobility or congestion. Most ad hoc routing protocols make the faulty assumption that all frame loss means the destination node has moved, resulting in significant overhead as they initiate the repair of routes that have not been broken. We design a mobility detection algorithm, MDA, that properly detects the cause of a lost frame, then coordinates with the routing protocol so that it reacts properly. This approach dramatically reduces routing protocol overhead and significantly increases application throughput. We use a simulation study to demonstrate the effectiveness of MDA and to determine the proper setting for MDA parameters.
3900881
HxH: a hop-by-hop transport protocol for multi-hop wireless networks
TCP can perform poorly in multi-hop wireless networks due to problems that arise with contention and mobility. Endto-end protocols are at an inherent disadvantage in trying to solve these problems because their feedback loop operates over multiple wireless hops, which makes it difficult to diagnose problems that occur several hops away and hinders their ability to adapt to changing network conditions. In this paper, we design HxH, a hop-by-hop transport protocol that uses credit-based congestion control and reverse ACKs to solve many of the problems observed with TCP. We use a simulation study to demonstrate that our hop-by-hop approach allows HxH to respond quickly to changing network conditions and to exploit the unique characteristics of wireless networks to reduce overhead. We show that HxH greatly increases throughput and improves fairness, as compared to several end-to-end protocols, in both mesh and mobile ad hoc networks.
8065609
Link quality prediction for wireless devices with multiple radios
Communication between wireless devices ought to be as simple as possible; they should be able to seamlessly switch between different radios and network stacks on the fly in order to better serve the user. To make this a possibility, we consider the challenging problem of predicting link quality in a changing mobile environment. In this paper we present an algorithm that uses Weighted Least Squares Regression to predict whether a given link can meet application requirements in terms of throughput, delay, and jitter. We use a simulation study to demonstrate that our algorithm is able to predict link quality accurately and stably in a frequently changing mobile environment. The prediction algorithm is more accurate than several alternative algorithms, and the overhead caused by the link measurements is negligible in terms of throughput and power consumption.
1462661
Low-power AEC-based MIMO signal processing for gigabit ethernet 1000Base-T transceivers
Presented in this paper is a low-power technique, denoted as MIMO-AEC, to reduce energy dissipation in multi-input-multi-output (MIMO) signal processing systems. The proposed technique extends a previously proposed adaptive error-cancellation (AEC) technique to MIMO systems by employing an algorithm transformation denoted as MIMO-DECOR. The purpose of MIMO-DECOR is to reduce complexity by exploiting correlations inherent in MIMO systems, thereby improving the effectiveness of AEC. We employ the MIMO-AEC in the design of a low-power Gigabit Ethernet 1000Base-T device. Simulation results demonstrate 44.3% - 25.2% overhead reduction due to MIMO-DECOR and 69.1% - 64.2% energy savings over conventional implementations with no loss in algorithmic performance.
14307736
Positive Semidefinite Metric Learning with Boosting
The learning of appropriate distance metrics is a critical problem in image classification and retrieval. In this work, we propose a boosting-based technique, termed BOOSTMETRIC, for learning a Mahalanobis distance metric. One of the primary difficulties in learning such a metric is to ensure that the Mahalanobis matrix remains positive semidefinite. Semidefinite programming is sometimes used to enforce this constraint, but does not scale well. BOOSTMETRIC is instead based on a key observation that any positive semidefinite matrix can be decomposed into a linear positive combination of trace-one rank-one matrices. BOOSTMETRIC thus uses rank-one positive semidefinite matrices as weak learners within an efficient and scalable boosting-based learning process. The resulting method is easy to implement, does not require tuning, and can accommodate various types of constraints. Experiments on various datasets show that the proposed algorithm compares favorably to those state-of-the-art methods in terms of classification accuracy and running time.
11153922
Enhancing security using legality assertions
Buffer overflows have been the most common form of security vulnerability in the past decade. A number of techniques have been proposed to address such attacks. Some are limited to protecting the return address on the stack; others are more general, but have undesirable properties such as large overhead and false warnings. The approach described in this paper uses legality assertions, source code assertions inserted before each subscript and pointer dereference that explicitly check that the referencing expression actually specifies a location within the array or object pointed at run time. A transformation system is developed to analyze a program and annotate it with appropriate assertions automatically. This approach detects buffer vulnerabilities in both stack and heap memory as well as potential buffer overflows in library functions. Runtime checking through using automatically inferred assertions considerably enhances the accuracy and efficiency of buffer overflow detection. A number of example buffer overflow-exploiting C programs are used to demonstrate the effectiveness of this approach.
14748707
Training One-class Support Vector Machines in the Primal Space
In this paper, we proposed a novel Newton-type solver for one-class support vector machines in the primal space directly. Firstly, utilizing reproducing property of kernel and Huber regression function, original constrained quadratic programming is transformed into approximate unconstrained one, which is continuous and twice differentiable. Then, we give a Newton-type training algorithm to solve it. Further analysis shows the computation complexity of our algorithm is identical with theoretical lower bound for solving one-class support vector machines. In the end, experiments on 9 UCI datasets are done to validate the affectivity of proposed algorithm, and when comparing with dual method (LIBSVM),its produces comparative testing accuracy, better training speed, and less support vectors.
13235702
Provisioning QoS guarantee by multipath routing and reservation in Ad hoc networks
In this paper, a QoS multipath source routing protocol (QoS-MSR) is proposed for ad hoc networks. It can collect QoS information through route discovery mechanism of multipath source routing (MSR) and establish QoS route with reserved bandwidth. In order to reserve bandwidth efficiently, a bandwidth reservation approach called the multipath bandwidth splitting reservation (MBSR) is presented, under which the overall bandwidth request is split into several smaller bandwidth requests among multiple paths. In simulations, the anthors introduce Insignia, an in-bind signaling system that supports QoS in ad hoc networks, and extend it to multipath Insignia (M-Insignia) with QoS-MSR and MBSR. The results show that QoS-MSR routing protocol with the MBSR algorithm can improve the call admission ratio of QoS traffic, the packet delivery ratio, and the end-to-end delay of both best-effort traffic and QoS traffic. Therefore, QoS-MSR with MBSR is an efficient mechanism that supports QoS for ad hoc networks.