In designing energy-aware CPU scheduling algorithms for real-time embedded systems, dynamic slack reclamation techniques significantly improve system quality-of-service (QoS) and energy efficiency. However, the limite...
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ISBN:
(纸本)9781424419210
In designing energy-aware CPU scheduling algorithms for real-time embedded systems, dynamic slack reclamation techniques significantly improve system quality-of-service (QoS) and energy efficiency. However, the limited schemes in this domain either demand high complexity or can only achieve limited QoS. In this paper, we present a novel low complexity runtime scheduling algorithm for the imprecise computation (IC) modeled tasks. The target is to maximize system QoS under energy constraints. Our proposed algorithm, named gradient curve shifting (GCS), is able to decide the best allocation of slack cycles arising at runtime, with very low complexity. We study both linear and concave QoS functions associated with IC modelde tasks, on non-DVS and DVS processors. Furthermore, we apply the intra-task DVS technique to tasks and achieve as large as 18% more of the system QoS compared to the conventional "optimal" solution which is inter-task DVS based.
The paper proposes an energy-aware contention-based protocol for the medium access control (MAC) sub-layer for wireless sensor networks. The innovative approach with frequent sleeps proactively and aggressively reduce...
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The paper proposes an energy-aware contention-based protocol for the medium access control (MAC) sub-layer for wireless sensor networks. The innovative approach with frequent sleeps proactively and aggressively reduces the wasted energy while increasing the throughput and decreasing the latency. The proposed MAC protocol solves the energy inefficiency caused by idle listening, control-packet overhead, and overhearing. Simulation experiments have been performed to demonstrate the effectiveness of the proposed approach, especially compared to the S-MAC and T-MAC protocols.
In this paper, we evaluate and compare the performance of several spanning tree routing strategies for divisible load scheduling on arbitrary graphs and derive recommendations as to which routing strategy provides a b...
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ISBN:
(纸本)9781424449224;9781424449217
In this paper, we evaluate and compare the performance of several spanning tree routing strategies for divisible load scheduling on arbitrary graphs and derive recommendations as to which routing strategy provides a better trade-off between complexity and time performance. We consider a network comprising heterogeneous processors interconnected by heterogeneous links in an arbitrary manner. We evaluate the performance over a wide range of arbitrary dense graphs with varying connectivity and processor densities and study the effect of network scalability. In addition, we introduce a novel spanning tree routing strategy, which is referred to as minimum equivalent network spanning tree (EST), and analyze its performance. We apply the resource-aware optimal load distribution with optimal sequencing (RAOLD-OS) scheduling algorithm presented in the literature for obtaining an optimal solution. This study attempts to pool all known and applicable divisible load scheduling algorithms for arbitrary networks and presents a collective and comparative view of their performance.
The authors introduce encryption-free message authentication based entirely on the use of one-way hash functions. It is shown that fast one-way hash functions such as MD4 can be used as a foundation for some relativel...
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The authors introduce encryption-free message authentication based entirely on the use of one-way hash functions. It is shown that fast one-way hash functions such as MD4 can be used as a foundation for some relatively novel implementations of security services. In particular, simple and inexpensive secret prefix and secret suffix methods provide protection against message substitution attacks when used in conjunction with a strong one-way hash function (which itself protects against message modification).< >
Among several techniques proposed for indoor positioning using IEEE 802.11 Wireless Fidelity (Wi-Fi) based networks, those that rely on fingerprinting have been demonstrated to outperform those based on lateration, an...
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Among several techniques proposed for indoor positioning using IEEE 802.11 Wireless Fidelity (Wi-Fi) based networks, those that rely on fingerprinting have been demonstrated to outperform those based on lateration, angulation, and cell of origin in terms of accuracy. We compare and evaluate three Wi-Fi fingerprinting techniques that use the K-Nearest Neighbor (k-NN), Naive Bayes Classifier (NBC) and Support Vector Machine (SVM) algorithms. Our experiments show that SVM-based fingerprinting outperformed both k-NN and NBC-based fingerprinting, achieving accuracies of 2 meters or better within our testbed.
Group Communication System (GCS) is an important building block for reliable, fault-tolerant distributed applications. Due to highly variable and unpredictable latency in WANs, GCS needs to cope with frequent membersh...
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Group Communication System (GCS) is an important building block for reliable, fault-tolerant distributed applications. Due to highly variable and unpredictable latency in WANs, GCS needs to cope with frequent membership changes. It results in diminishing the scalability of GCS. In this paper we propose a new scheme that improves the scalability of group membership service for WANs by exploiting dedicated membership servers configured into multiple layers and reaching global agreement on the view through layered servers. It improves the scalability of a process group of N member processes from O(N/sup 2/) to O(N/sup 3/) with three layers, where N is the number of processes in the group. computer simulation verifies that the proposed scheme requires much smaller number of message exchanges for reaching an agreement on a next view and does that much quicker. In addition, the proposed scheme prevents applications from being blocked until reaching the final view agreement if the applications permit temporary inconsistency.
This paper proposes an architecture to classify traffic flows of IP access networks, and signalize to hybrid optical network the most appropriate paradigm, Optical Circuit Switching (OCS) and Optical Burst Switching (...
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This paper proposes an architecture to classify traffic flows of IP access networks, and signalize to hybrid optical network the most appropriate paradigm, Optical Circuit Switching (OCS) and Optical Burst Switching (OBS), to be used. The concept of software defined networks, more specifically the OpenFlow technology, was used to enable the architecture. Furthermore, a performance evaluation and feasibility of the proposed architecture are presented through experiments.
Mobile ad hoc network (MANET) is a type of wireless network consisting of a set of self-configured mobile hosts that can communicate with each other using wireless links without the assistance of any fixed infrastruct...
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Mobile ad hoc network (MANET) is a type of wireless network consisting of a set of self-configured mobile hosts that can communicate with each other using wireless links without the assistance of any fixed infrastructure. This has made it possible for us to create distributed mobile computing applications and has also brought several new challenges in the field of distributed algorithm design. Checkpointing is a well explored fault tolerance technique for the wired and cellular mobile networks. However, it is not directly applicable to MANET owing to its dynamic topology, limited availability of stable storage, partitioning and the absence of fixed infrastructure. In this paper, we propose an adaptive, coordinated and non-blocking checkpointing algorithm to provide fault tolerance in cluster-based MANET, where only a minimum number of mobile hosts in the cluster should take checkpoints. The performance analysis and simulation results show that the proposed scheme requires less coordinating-message cost and performs well compared to the related previous works. Copyright ? 2018 Inderscience Enterprises Ltd.
Social bots are defined as computer algorithms that generate massive amounts of obnoxious or meaningful information. Most bot detection methods leverage multitudinous characteristics, from network features, temporal d...
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Social bots are defined as computer algorithms that generate massive amounts of obnoxious or meaningful information. Most bot detection methods leverage multitudinous characteristics, from network features, temporal dynamics features, activities features, and sentiment features. However, there has been fairly lower work exploring lexicon measurement and linguistic indicators to detect bots. The main purpose of this research is to recognize the social bots through their writing style. Thus, we carried out an exploratory study on the effectiveness of only a set of linguistic features (17 features) exploitable for bot detection, without the need to resort to other types of features. And we develop a novel framework in a hybrid fashion of Mixing Engineered Linguistic features based on Autoencoders (Hybrid-MELAu). The semi-supervised Hybrid-MELAu framework is composed of two essential constituents: the features learner and the predictors. We establish the features learner innovated on two powerful structures: a) the first is a Deep dense Autoencoder fed by the Lexical and the Syntactic content (DALS) that represents the high order lexical and syntactic features in latent space, b) the second one is a Glove-BiLSTM autoencoder, which sculpts the semantic features;subsequently, we generate elite elements from the pre-trained encoder part from each latent space with transfer learning. We consider a sample of 1 Million from Cresci datasets to conduct our linguistic analysis comparison between the writing style of humans and bots. With this dataset, we observe that the bot's textual lexical diversity median is greater than the human one and the syntactic analysis based on speech-tagging shows a creative behavior in human writing style. Finally, we test the model's robustness on several public dataset (celebrity, pronbots-2019, and political bots). The proposed framework achieves a good accuracy of 92.22%. Overall, the results shown in this paper, and the related discussion, ar
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