Dynamic resource provisioning is a challenging technique to meet the service level agreement (SLA) requirements of multi-tier applications in virtualization-based cloud computing. Prior efforts have addressed this challenge based on either a cost-oblivious approach or a cost-aware approach. However, both approaches may suffer frequent SLA violations under flash crowd conditions. Because they ignore the benefit gained that a multi-tier application continuously guarantees the SLA in the new con figuration. In this paper, we propose a benefit-aware approach with feedback control theory to solve this problem. Experimental results based on live workload traces show that our approach can reduce resource provisioning cost by as much as 30% compared with a costoblivious approach, and can effectively reduce SLA violations compared with a cost-aware approach.
To solve the traffic load imbalance issue in cellular networks, which is often in the form of hot-spots caused by the different user mobility levels, one of the good solutions at present is to construct heterogeneous integrated wireless networks that combine cellular networks and wireless local area networks (WLANs) together. In general, the traffic volume is significantly heavier in the hot-spots of cellular networks and a higher data transferring rate can be provided by introducing aWLAN so as to raise the utilization of the channel and achieve a good balance between user satisfaction and the efficiency of the network. In this paper, we provide a comprehensive performance comparison of the systems both before and after the integration, based on an existing mathematical model, focusing on both the qualitative and the quantitative analysis of changes in the performance of the system to validate the efficiency and superiority of the cellular/WLAN integrated systems over cellular–only systems.
Target localization is an important service in wireless visual sensor networks (WVSN). Although the problem of single target localization has been intensively studied, few consider the problem of multiple target localization without prior target information in WVSN. In this paper, we first investigate the architecture of WVSN where data transmission is reduced to only target positions. Since target matching is a key issue in the multiple target localization, we propose a statistical method to match corresponding targets to located targets in world coordinates. In addition, we also consider scenarios where occlusion or limited field of view (FOV) occurs. The proposed method utilizes target images to the greatest extent. Our experimental results show that the proposed method obtains a more accurate result in targets localization compared with the camera discard scheme, and saves significant amounts of energy compared with other feature matching schemes.
The demand for group communication using smart devices in campus environment is increasing rapidly. In this paper, we design an architecture for a mobile group communication system (MGCS) on campus by using Wi-Fi networks and smart devices. The architecture is composed of a web-based system and a smart device based mobile system. Through the systems, users on campus create community/ mobile group, maintain dynamic group membership, and reliably deliver the message to other users. We use the common features of many smart devices to develop a prototype that works on o.-the-shelf hardware. In the experimental section, we demonstrate our system using various real scenarios which can occur in university campuses.
In this paper, we intensively study the behavior of three part-based methods for handwritten digit recognition. The principle of the proposed methods is to represent a handwritten digit image as a set of parts and recognize the image by aggregating the recognition results of individual parts. Since part-based methods do not rely on the global structure of a character, they are expected to be more robust against various deformations which may damage the global structure. The proposed three methods are based on the same principle but different in their details, for example, the way of aggregating the individual results.Thus, those methods have different performances. Experimental results show that even the simplest part-based method can achieve recognition rate as high as 98.42% while the improved one achieved 99.15%, which is comparable or even higher than some state-of-the-art method. This result is important because it reveals that characters can be recognized without their global structure. The results also show that the part-based method has robustness against deformations which usually appear in handwriting.
Probabilistic latent semantic analysis (PLSA) is a topic model for text documents, which has been widely used in text mining, computer vision, computational biology and so on. For batch PLSA inference algorithms, the required memory size grows linearly with the data size, and handling massive data streams is very diffcult. To process big data streams, we propose an online belief propagation (OBP) algorithm based on the improved factor graph representation for PLSA. The factor graph of PLSA facilitates the classic belief propagation (BP) algorithm. Furthermore, OBP splits the data stream into a set of small segments, and uses the estimated parameters of previous segments to calculate the gradient descent of the current segment. Because OBP removes each segment from memory after processing, it is memory effcient for big data streams. We examine the performance of OBP on four document data sets, and demonstrate that OBP is competitive in both speed and accuracy for online expectation maximization (OEM) in PLSA, and can also give a more accurate topic evolution. Experiments on massive data streams from Baidu further confirm the effectiveness of the OBP algorithm.
In this paper, we present two forward-secure signature schemes (FSS) with untrusted update. Our constructions use ideas from the work of Abdalla et al. [1] and Kozlov and Reyzin [2] in their forward-secure digital signature schemes. Our schemes are proven to be forward-secure based on the hardness of factoring in the random oraclemodel. Both schemes use the same method to encrypt the private key and are more efficient than Libert scheme [3] without adding any burden to the original forward-secure schemes.
Recently, He et al. (Computers and Mathematics with Applications, 2012) proposed an efficient pairing-free certificateless authenticated key agreement (CL-AKA) protocol and claimed their protocol was provably secure in the extended Canetti-Krawczyk (eCK) model. By giving concrete attacks, we indicate that their protocol is not secure in the eCK model. We propose an improved protocol and show our improvement is secure in the eCK model under the gap Diffie- Hellman (GDH) assumption. Furthermore, the proposed protocol is very efficient.
The complexity and diversity of modern software demands a variety of metamodel-based modeling languages for software development. Existing languages change continuously, and new ones are constantly emerging. In this situation, and especially for metamodel-based modeling languages, a quality assurance mechanism for metamodels is needed. This paper presents an approach to assessing the quality of metamodels. A quality model, which systematically characterizes and classifies quality attributes, and an operable measuring mechanism for effectively assessing the quality of metamodels based on the quality model, are presented, using UML as the main example.
Many studies have been conducted to investigate the performance of priority queuing (PQ) systems with constant service capacity. However, due to the time-varying nature of wireless channels in wireless communication networks, the service capacity of queuing systemsmay vary over time. Therefore, it is necessary to investigate the performance of PQ systems in the presence of varying service capacity. In addition, self-similar traffic has been discovered to be a ubiquitous phenomenon in various communication networks, which poses great challenges to performance modelling of scheduling systems due to its fractal-like nature. Therefore, this paper develops a flow-decomposition based approach to performance modelling of PQ systems subject to self-similar traffic and varying service capacity. It specifically proposes an analytical model to investigate queue length distributions of individual traffic flows. The validity and accuracy of the model is demonstrated via extensive simulation experiments.
Network resource management is critical to ensure the security and optimal performance of distributed networks and information systems. Existing technologies are not capable of managing large-scale network resources because of a lack of reusability and scalability. This paper presents a matrix grammar approach for automatic distributed network resource management to alleviate these problems. A matrix grammar is proposed using WMI, CIM, and SNMP to manage network resources, and provides a generic mechanism to describe what needs to be managed and how to manage it. A scalable distributed multi-agent architecture for automatic network resource management is proposed, at its core lies a management automation engine consisting of a matrix analyzer and a recipe processor. The proposed solution has been implemented in software and applied in industrial products that achieve good technical and industrial results. It has good extensibility, scalability, and enables network management automation and software reusability.