The effect of advances in the fields of ubiquitous computing, wireless communications and embedded system design has seen a corresponding rapid improvement of wireless sensor technology. Sensor networks have emerged a...
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ISBN:
(纸本)9781424469208
The effect of advances in the fields of ubiquitous computing, wireless communications and embedded system design has seen a corresponding rapid improvement of wireless sensor technology. Sensor networks have emerged as a platform for deployment and sustenance of critical applications that require real-time sensing and data acquisition for decision-making purposes. A significant number of malicious attacks against the security of such networks have been identified in recent times. Considering the untrusted environments of operations of such networks, the threat of distributed attacks against constrained sensory resources i.e. sensor power, computation and communication capabilities cannot be overlooked. In this paper, we propose a fuzzy logic-based approach towards achieving demarkation in the values of specific parameters of an attack detection scheme for detecting distributed node-exhaustion attacks in wireless sensor networks. Using the Unified And-Or (UAO) aggregation operator, we model and formulate a mechanism to achieve a tradeoff between frequent attack detection and sensor node energy utilization. Simulation results prove the effectiveness of our approach in addressing the issue of computing the optimal parameter values for achieving a reasonable tradeoff between attack detection rate and sensor node energy utilization rate.
parallelcomputing is increasingly exposed to the development and challenges of distributed systems, such as asynchrony, long latencies, network partitions, failures, disconnected operations, heterogeneity and protoco...
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Even though the area of parallelcomputing has existed for many decades, programming a parallel system for the execution of a single application is still a challenging problem than programming a sequential program on ...
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This paper studies the spatial correlation in the sensing data gathered by densely deployed sensors. We first show that the joint entropy of a cluster of sensor nodes can be calculated through the covariance matrix of...
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ISBN:
(纸本)9781424437092
This paper studies the spatial correlation in the sensing data gathered by densely deployed sensors. We first show that the joint entropy of a cluster of sensor nodes can be calculated through the covariance matrix of their readings when they are gaussian distributed. Then, two kinds of correlation patterns in the physical world are studied, and we show these two patterns have fundamental different impacts on joint entropy.
Since it is impossible to predict and identify all the vulnerabilities of a network, and penetration into a system by malicious intruders cannot always be prevented, intrusion detection systems (IDSs) are essential en...
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Optimal capacity analysis in multi-radio multi-channel wireless networks by nature incurs the formulation of a mixed integer programming, which is NP-hard in general. The current state of the art mainly resorts to heu...
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ISBN:
(纸本)9780769540597
Optimal capacity analysis in multi-radio multi-channel wireless networks by nature incurs the formulation of a mixed integer programming, which is NP-hard in general. The current state of the art mainly resorts to heuristic algorithms to obtain an approximate solution. In this paper, we propose a novel concept of multi-dimensional conflict graph (MDCG). Based on MDCG, the capacity optimization issue can be accurately modeled as a linear programming (LP) multi-commodity flow (MCF) problem, augmented with maximal independent set (MIS) constraints. The MDCG-based solution will provide not only the maximum throughput or utility, but also the optimal configurations on routing, channel assignment, and scheduling. Moreover, the MDCG-based optimal capacity planning can exploit dynamic channel swapping, which is difficult to achieve for those existing heuristic algorithms. A particular challenge associated with the MDCG-based capacity analysis is to search exponentially many possible MISs. We theoretically show that in fact only a small set of critical MISs, termed as critical MIS set, will be scheduled in the optimal resource allocation. We then develop a polynomial computing method, based on a novel scheduling index ordering (SIO) concept, to search the critical MIS set. Extensive numerical results are presented to demonstrate the efficiency of the MDCG-based resource allocation compared to well-known heuristic algorithm presented in [1], and the efficiency of SIO-based MIS computing compared to the widely adopted random algorithm for searching MISs.
distributed Source Coding (DSC) is one of the most promising collaborative information processing technologies for Wireless Video Sensor networks (WVSN) because its low complexity video encoder is suitable for resourc...
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The distributed-memory parallel computer has become the most popular platform for the parallel acceleration of numerical simulations in scientific computing area. However, complex system characteristics and large-scal...
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In this paper, a multi-channel MAC protocol, called M&M, with multiple channel reservation is proposed to tackle the channel conflict problem. M&M is fully distributed with no requirements of time synchronizat...
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In this paper, we propose a new algorithm for job interchange in Computational Grids that consist of autonomous and equitable HPC sites, called Shaking-G. Originally developed for balancing the sharing of video files ...
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