Kien NguyenMirza Golam KibriaKentaro IshizuFumihide Kojima...
11页
查看更多>>摘要：The IEEE 802.11ad technology, which allows wireless devices to communicate in the unlicensed 60 GHz ISM band, promisingly provides multi-Gbps data rates for bandwidth-intensive applications. After years of research and development, we are now observing an increasing number of commodity IEEE 802.11ad radios that motivate researchers to exploit the IEEE 801.11ad capability for applications. This work first conducts an empirical study on the IEEE 802.11ad performance. In particular, we characterize the performance of IEEE 802.11ad links considering the variation of network parameters and interference. Secondly, we investigate the possibility of introducing IEEE 802.11ad to an evolving Wi-Fi network. The evaluation results show that our off-the-shelf IEEE 802.11ad hardware can achieve the Gbps level throughput of the transmission control protocol (TCP) and user datagram protocol (UDP). However, the evolvement is not trivial since the hardware can not well maintain the 60 GHz link. The main reason is lacking the fast switchover function between an IEEE 802.11ad and a legacy Wi-Fi link. We then seek the potential of multipath TCP (MPTCP) for the expected switchover. The default MPTCP, which enables data transmissions on both the IEEE 802.11ad and Wi-Fi links, is harmful to the IEEE 802.11ad throughput. Meanwhile, the backup mode of MPTCP, in which the Wi-Fi link acts as a backup for IEEE 802.11ad one, can maintain the comparable performance. Therefore, we propose to adopt MPTCP with the backup mode in the evolving Wi-Fi networks. The efficiency of MPTCP-based switchover is confirmed by conducting real experiments.
查看更多>>摘要：A novel energy-efficient data gathering scheme that exploits spatial-temporal correlation is proposed for clustered wireless sensor networks in this paper. In the proposed method, dual prediction is used in the intracluster transmission to reduce the temporal redundancy, and hybrid compressed sensing is employed in the intercluster transmission to reduce the spatial redundancy. Moreover, an error threshold selection scheme is presented for the prediction model by optimizing the relationship between the energy consumption and the recovery accuracy, which makes the proposed method well suitable for different application environments. In addition, the transmission energy consumption is derived to verify the efficiency of the proposed method. Simulation results show that the proposed method has higher energy efficiency compared with the existing schemes, and the sink can recover measurements with reasonable accuracy by using the proposed method.
查看更多>>摘要：SensIoT is an open-source sensor monitoring framework for the Internet of Things, which utilizes proven technologies to enable easy deployment and maintenance while staying flexible and scalable. It closes the gap between highly specialized and, therefore, inflexible sensor monitoring solutions, which are only adjusted to a specific context, and the development of every other solution from scratch. Our framework fits a variety of use cases by providing an easy to set up, extensible, and affordable solution. The development is based on our former published framework MonTreAL, whose goal is to offer an environmental monitoring solution for libraries to guarantee cultural heritage to be conserved and prevented from serious damage, for example, from mold formation in closed stocks. It is a solution with virtualized microservices delivered by a famous container technology called Docker that is solely executable on one or more single board computers like the Raspberry Pi by providing automatic scaling and resilience of all sensor services. For SensIoT we extended the capability of MonTreAL to integrate commodity servers into the cluster to enhance the ease of setup and maintainability on already existing infrastructures. Therefore, we followed the paradigm to distribute microservices on small computing nodes first, thus not utilizing well-known cloud computing concepts. To achieve resilience and fault tolerance we also based our system on a microservice architecture, where the service orchestration is solved by Docker Swarm. As proof of concept, we are able to present our current data collection of the University of Bamberg's Library that runs our system since autumn 2017. To make our system even better we are working on the integration of other sensor types and better performance management of SD-cards in Raspberry Pis.
查看更多>>摘要：Fingerprinting based on Wi-Fi Received Signal Strength Indicator (RSSI) has been widely studied in recent years for indoor localization. While current algorithms related to RSSI Fingerprinting show a much lower accuracy than multilateration based on time of arrival or the angle of arrival techniques, they highly depend on the number of access points (APs) and fingerprinting training phase. In this paper, we present an integrated method by combining the deep neural network (DNN) with improved K-Nearest Neighbor (KNN) algorithm for indoor location fingerprinting. The improved KNN is realized by boosting the weights on K-nearest neighbors according to the number of matching access points. This will overcome the limitation of the original KNN algorithm on ignoring the influence of the neighboring points, which directly affect localization accuracy. The DNN algorithm is first used to classify the Wi-Fi RSSI Fingerprinting dataset. Then these possible locations in a certain class are also classified by the improved KNN algorithm to determine the final position. The proposed method is validated inside a room within about 13*9 m~2. To examine its performance, the presented method has been compared with some classical algorithms, i.e., the random forest (RF) based algorithm, the KNN based algorithm, the support vector machine (SVM) based algorithm, the decision tree (DT) based algorithm, etc. Our real-world experiment results indicate that the proposed method is less dependent on the dense of access points and indoor radio propagation interference. Furthermore, our method can provide some preliminary guidelines for the design of indoor Wi-Fi test bed.
查看更多>>摘要：The Narrowband Internet of Things (NB-IoT) is a main stream technology based on mobile communication system. The combination of NB-IoT and WSNs can active the application of WSNs. In order to evaluate the influence of node heterogeneity on malware propagation in NB-IoT based Heterogeneous Wireless Sensor Networks, we propose a node heterogeneity model based on node distribution and vulnerability differences, which can be used to analyze the availability of nodes. We then establish the node state transition model by epidemic theory and Markov chain. Further, we obtain the dynamic equations of the transition between nodes and the calculation formula of node availability. The simulation result is that when the degree of node is small and the node vulnerability function is a power function, the node availability is the highest; when the degree of node is large and the node vulnerability function satisfies the exponential function and the power function, the node availability is high. Therefore, when constructing a NBIOT-HWSNs network, node protection is implemented according to the degree of node, so that when the node vulnerability function satisfies the power function, all nodes can maintain high availability, thus making the entire network more stable.
查看更多>>摘要：Nowadays, due to the rapid development and wide deployment of handheld mobile devices, the mobile users begin to save their resources, access services, and run applications that are stored, deployed, and implemented in cloud computing which has huge storage space and massive computing capability with their mobile devices. However, the wireless channel is insecure and vulnerable to various attacks that pose a great threat to the transmission of sensitive data. Thus, the security mechanism of how the mobile devices and remote cloud server authenticate each other to create a secure session in mobile cloud computing environment has aroused the interest of researchers. In this paper, we propose an efficient and provably secure anonymous two-factor user authentication protocol for the mobile cloud computing environment. The proposed scheme not only provides mutual authentication between mobile devices and cloud computing but also fulfills the known security evaluation criteria. Moreover, utilization of ECC in our scheme reduces the computing cost for mobile devices that are computation capability limited and battery energy limited. In addition, the formal security proof is given to show that the proposed scheme is secure under random oracle model. Security analysis and performance comparisons indicate that the proposed scheme has reasonable computation cost and communication overhead at the mobile client side as well as the server side and is more efficient and more secure than the related competitive works.
Nasreddine LagraaAbderrahmane LakasMohamed El Amine FekairAhmed Korichi...
18页
查看更多>>摘要：With the deployment of multimedia services over VANETs, there is a need to develop new techniques to insure various levels of quality of services (QoS) for real time applications. However, in such environments, it is not an easy task to determine adequate routes to transmit data with specific application QoS requirements. In this paper, we propose CBQoS-Vanet, a new QoS-based routing protocol tailored towards vehicular networks in a highway scenario. This protocol is based on the use of two techniques: first a clustering technique which organizes and optimizes the exchange of routing information and, second, a bee colony inspired algorithm, which calculates the best routes from a source to a destination based on given QoS criteria. In our approach, clusters are formed around cluster heads that are themselves elected based on QoS considerations. The QoS criteria here are based on the two categories of metrics: QoS metrics and mobility metrics. The QoS metrics consists of the available bandwidth, the end-to-end delay, and the jitter. The mobility metrics consists of link expiration time and average velocity difference. We have studied the performance of CBQoS-Vanet through simulation and compared it to existing approaches. The results that we obtained show that our technique outperforms, in many aspects, the approaches that it was compared against.
查看更多>>摘要：The continuous increase of mobile data traffic volume creates new challenges for telecommunication network operators. As a possible solution, many traffic offloading techniques have been proposed. In parallel, there is a trend to handle all the access techniques under the umbrella of IP, including non-3GPP networks (e.g., Wi-Fi), mainly with the help of IPv6. In this paper we provide a new architectural proposal in Evolved Packet Core (EPC) described as flow-based and operator-centric dynamic mobility management with Proxy Mobile IPv6 (PMIPv6). This new approach is supported by current EPC entities including Policy and Charging Rules Function (PCRF), Access Network Discovery and Selection Function (ANDSF), and Local Mobility Anchor (LMA) and by defining a novel communication scheme between them. The proposal was evaluated in a virtual testbed environment, and measurements based simulations were carried out where the solution showed significant benefits by enhancing operator flexibility, increasing user experience, and decreasing signaling overhead due to its highly dynamic operation and optimized flow-level behavior.
查看更多>>摘要：With the exploding amount of mobile traffic data and unprecedented demands of computing, executing the ever increasingly complex applications in resource-constrained mobile devices becomes more and more challenging. Future wireless communications will be very complex with heterogeneous radio access technologies, transmission links, and network slices. More intelligent technologies are required to address those complex scenarios and to adapt to dynamic mobile environments. Recently, deep learning has attracted much attention in the field of wireless communication and mobile computing. Deep learning driven algorithms and models can facilitate wireless network analysis and resource management, benefit in coping with the growth in volumes of communication and computation for emerging mobile applications. However, how to customize deep learning techniques for heterogeneous mobile environments is still under development. Learning algorithms in mobile wireless systems are immature and inefficient. In this special issue on deep learning driven wireless communication and mobile computing, we have accepted seven papers that include both theoretical contributions and practical research related to the new technologies, analysis, and applications with the help of artificial intelligence and deep learning.
查看更多>>摘要：The ROLL working group proposed the RPL (IPv6 routing protocol for low-power and lossy networks) to respond to the requirements of low-power and lossy networks (LLNs). In this paper, we propose a new approach to assess the RPL performances based on its main components, namely, the objective function (OF) and the trickle algorithm. To this end, we compare between the RPL-EC (RPL based combined ETX and energy consumption) and the RPL-FL (RPL based on the flexible trickle algorithm). This paper compares the two implementations to assess the weight of each proposed improvement against the standard RPL. The results show that RPL performances are greatly influenced by the change of both the objective function and trickle algorithm. RPL-FL provides best values in terms of overhead, packet delivery ratio (PDR), and energy consumption, while RPL-EC acts better with the convergence time and the network lifetime compared to the standard RPL.
NSTL
Wiley-Hindawi