Large language Models (LLMs) have demonstrated remarkable performance across various natural language tasks, marking significant strides towards general artificial intelligence. While general artificial intelligence i...
详细信息
The recent proliferation of smart devices has given rise to ubiquitous computing, an emerging computing paradigm which allows anytime & anywhere computing possible. In such a ubiquitous computing environment, cust...
详细信息
In recent years, cognitive Internet of Things (CIoT) has received considerable attention because it can extract valuable information from various Internet of Things (IoT) devices. In CIoT, truth discovery plays an imp...
详细信息
作者：
Huijie ChenFan LiYu WangSchool of Computer Science
Beijing Institute of Technology Beijing Engineering Research Center for High Volume Language Information Processing and Cloud Computing Applications Beijing China Department of Computer Science
College of Computing and Informatics University of North Carolina at Charlotte Charlotte NC USA
Hand tracking systems are becoming increasingly popular as a fundamental HCI approach. The trajectory of moving hand can be estimated through smoothing the position coordinates collected from continuous localization. ...
详细信息
ISBN:
(纸本)9781509028245
Hand tracking systems are becoming increasingly popular as a fundamental HCI approach. The trajectory of moving hand can be estimated through smoothing the position coordinates collected from continuous localization. Therefore, hand localization is a key component of any hand tracking systems. This paper presents EchoLoc, which locates the human hand by leveraging the speaker array in Commercial Off-The-Shelf (COTS) devices (i.e., a smart phone plugged with a stereo speaker). EchoLoc measures the distance from the hand to the speaker array via the Time Of Flight (TOF) of the chirp. The speaker array and hand yield a unique triangle, therefore, the hand can be localized with triangular geometry. We prototype EchoLoc on iOS as an application, and find it is capable of localization with the average resolution within five centimeters of 73% and three centimeters of 48%.
Large language Models (LLMs) have demonstrated remarkable performance across various natural language tasks, marking significant strides towards general artificial intelligence. While general artificial intelligence ...
详细信息
With the prosperity of network applications, traffic classification serves as a crucial role in network management and malicious attack detection. The widely used encryption transmission protocols, such as the Secure ...
详细信息
With the prosperity of network applications, traffic classification serves as a crucial role in network management and malicious attack detection. The widely used encryption transmission protocols, such as the Secure Socket Layer/Transport Layer Security (SSL/TLS) protocols, leads to the failure of traditional payload-based classification methods. Existing methods for encrypted traffic classification suffer from low accuracy. In this paper, we propose a certificate-aware encrypted traffic classification method based on the Second-Order Markov Chain. We start by exploring reasons why existing methods not perform well, and make a novel observation that certificate packet length in SSL/TLS sessions contributes to application discrimination. To increase the diversity of application fingerprints, we develop a new model by incorporating the certificate packet length clustering into the Second-Order homogeneous Markov chains. Extensive evaluation results show that the proposed method lead to a 30% improvement on average compared with the state-of-the-art method, in terms of classification accuracy.
The multi-tier architecture is prevalently adopted by cloudapplications, such as the three-tier web application. It is highly desirable for both tenants and providers to provide virtual networks in an efficient and e...
详细信息
ISBN:
(纸本)9781467375887
The multi-tier architecture is prevalently adopted by cloudapplications, such as the three-tier web application. It is highly desirable for both tenants and providers to provide virtual networks in an efficient and elastic way, where tenant applications can automatically scale in or out with varying workloads and providers can accommodate as many requests as possible in the underlying network. However, due to potential conflicts between efficiency and elasticity, it is challenging to achieve these two goals simultaneously in abstracting tenant requirements and designing corresponding provisioning algorithms. In this paper, we propose an efficient and elastic virtual network provisioning solution called Easy Alloc, which is comprised of an elasticity-aware abstraction model and a virtual network provisioning algorithm. To accurately capture the tenant requirement and maintain the provisioning simplicity for providers, the elasticity-aware model enables two types of decoupling, i.e., Always-on VMs for normal load and on-demand VMs for dynamic scaling, and the bandwidth requirement of each VM for intra- and inter-tier communications. Then we formulate the virtual network provisioning as an overhead minimization problem, where the objective simultaneously considers the bandwidth and elasticity overhead. Due to the NP-completeness of this problem, we leverage two heuristics, slot reservation and tier iteration, to obtain an efficient algorithm. Extensive simulation results show that compared with a typical elasticity-agnostic method under a heavy load, Easy Alloc enables a 9% increase of request acceptance rate and a 16.8% improvement of the successful extension rate. To the best of our knowledge, this is the first work targeting at the elastic virtual network provisioning.
暂无评论