查看更多>>摘要：We discuss the idea of waveform flexibility and resource allocation in future wireless networks as a promising tool for network slicing implementation down to the lowest layers of the OSI (Open Systems Interconnection) models. In particular, we consider the possibility of cognitively adjusting the shape of the waveform to the requirements associated with various network slices. Moreover, such an adjustment of waveform shape is realised jointly with the selection and allocation of the appropriate frequency bands to each slice. In our approach, the definition of the waveform, as well as the assignment of resources, is done based on the information about the surrounding environment and each slice requirement stored in a dedicated context-information database. In this paper, we present the key concept of waveform flexibility for network slicing, the proposed algorithm for waveform selection and resource allocation among slices, and the achieved simulation results.
Annalisa SocievoleAntonio CaputoFloriano De RangoPeppino Fazio...
15页
查看更多>>摘要：When the connection to Internet is not available during networking activities, an opportunistic approach exploits the encounters between mobile human-carried devices for exchanging information. When users encounter each other, their handheld devices can communicate in a cooperative way, using the encounter opportunities for forwarding their messages, in a wireless manner. But, analyzing real behaviors, most of the nodes exhibit selfish behaviors, mostly to preserve the limited resources (data buffers and residual energy). That is the reason why node selfishness should be taken into account when describing networking activities: in this paper, we first evaluate the effects of node selfishness in opportunistic networks. Then, we propose a routing mechanism for managing node selfishness in opportunistic communications, namely, SORSI (Social-based Opportunistic Routing with Selfishness detection and Incentive mechanisms). SORSI exploits the social-based nature of node mobility and other social features of nodes to optimize message dissemination together with a selfishness detection mechanism, aiming at discouraging selfish behaviors and boosting data forwarding. Simulating several percentages of selfish nodes, our results on real-world mobility traces show that SORSI is able to outperform the social-based schemes Bubble Rap and SPRINT-SELF, employing also selfishness management in terms of message delivery ratio, overhead cost, and end-to-end average latency. Moreover, SORSI achieves delivery ratios and average latencies comparable to Epidemic Routing while having a significant lower overhead cost.
查看更多>>摘要：To keep a network secure, a user authentication scheme that allows only authenticated users to access network services is required. However, the limited resources of sensor nodes make providing authentication a challenging task. We therefore propose a new method of security for a wireless sensor network (WSN). Our technique, Secure User Biometric Based Authentication Scheme (SUBBASe), is based on the user biometrics for WSNs. It achieves a higher security level as well as improved network performance. This solution consists of easy operations and light computations. Herein, the proposed technique is evaluated and compared with previous existing techniques. This scheme increases the performance of the network by reducing network traffic, defending against DOS attacks, and increasing the battery life of a node. Consequently, the functionality and performance of the entire network is improved.
Faiza QaziOsman KhalidRao Naveed Bin RaisImran Ali Khan...
15页
查看更多>>摘要：Content-Centric Networking (CCN) is a novel architecture that is shifting host-centric communication to a content-centric infrastructure. In recent years, in-network caching in CCNs has received significant attention from research community. To improve the cache hit ratio, most of the existing schemes store the content at maximum number of routers along the downloading path of content from source. While this helps in increased cache hits and reduction in delay and server load, the unnecessary caching significantly increases the network cost, bandwidth utilization, and storage consumption. To address the limitations in existing schemes, we propose an optimization based in-network caching policy, named as opt-Cache, which makes more efficient use of available cache resources, in order to reduce overall network utilization with reduced latency. Unlike existing schemes that mostly focus on a single factor to improve the cache performance, we intend to optimize the caching process by simultaneously considering various factors, e.g., content popularity, bandwidth, and latency, under a given set of constraints, e.g., available cache space, content availability, and careful eviction of existing contents in the cache. Our scheme determines optimized set of content to be cached at each node towards the edge based on content popularity and content distance from the content source. The contents that have less frequent requests have their popularity decreased with time. The optimal placement of contents across the CCN routers allows the overall reduction in bandwidth and latency. The proposed scheme is compared with the existing schemes and depicts better performance in terms of bandwidth consumption and latency while using less network resources.
查看更多>>摘要：Massive multiple-input multiple-output (MIMO) is believed to be a key technology to get 1000x data rates in wireless communication systems. Massive MIMO occupies a large number of antennas at the base station (BS) to serve multiple users at the same time. It has appeared as a promising technique to realize high-throughput green wireless communications. Massive MIMO exploits the higher degree of spatial freedom, to extensively improve the capacity and energy efficiency of the system. Thus, massive MIMO systems have been broadly accepted as an important enabling technology for 5th Generation (5G) systems. In massive MIMO systems, a precise acquisition of the channel state information (CSI) is needed for beamforming, signal detection, resource allocation, etc. Yet, having large antennas at the BS, users have to estimate channels linked with hundreds of transmit antennas. Consequently, pilot overhead gets prohibitively high. Hence, realizing the correct channel estimation with the reasonable pilot overhead has become a challenging issue, particularly for frequency division duplex (FDD) in massive MIMO systems. In this paper, by taking advantage of spatial and temporal common sparsity of massive MIMO channels in delay domain, nonorthogonal pilot design and channel estimation schemes are proposed under the frame work of structured compressive sensing (SCS) theory that considerably reduces the pilot overheads for massive MIMO FDD systems. The proposed pilot design is fundamentally different from conventional orthogonal pilot designs based on Nyquist sampling theorem. Finally, simulations have been performed to verify the performance of the proposed schemes. Compared to its conventional counterparts with fewer pilots overhead, the proposed schemes improve the performance of the system.
查看更多>>摘要：Introduction: The ability of smart objects to stay connected to the Internet for purposes of transmitting and receiving data is referred to as the Internet of Things (IoT). As per recent estimates, the number of IoT devices will surpass 50 billion by 2020. Unsurprisingly, this mushrooming of IoT devices has drawn the attention of attackers who seek to exploit them for their own benefit, with the Mirai botnet being perhaps the most prominent example of IoT specific malware [1, 2]. Basically, IoT brings along a plethora of potential security and privacy risks to the end-users, including the unsanctioned access and abuse of private information, the enabling and strengthening of assaults against other systems, and the breeding of risks pertaining to personal safeness [3]. Especially, IoT facilitates the creation of an assortment of privacy risks to the consumer associated with the collection of personal and sensitive information, like their preferences, locations, habits, and so on. In the mid- or long-run these pieces of data can be used to, say, profile or impersonate the user or group of interest. On the other hand, such risks to security, privacy, and trust may significantly diminish end-user's confidence in IoT and therefore impede its full realization.
查看更多>>摘要：IoT enabled smart car era is expected to begin in the near future as convergence between car and IT accelerates. Current smart cars can provide various information and services needed by the occupants via wearable devices or Vehicle to Everything (V2X) communication environment. In order to provide such services, a system to analyze wearable device information on the smart car platform needs to be designed. In this paper a real time user recognition method using 2D ECG (Electrocardiogram) images, a biometric signal that can be obtained from wearable devices, will be studied. ECG (Electrocardiogram) signal can be classified by fiducial point method using feature points detection or nonfiducial point method due to time change. In the proposed algorithm, a CNN based ensemble network was designed to improve performance by overcoming problems like overfitting which occur in a single network. Test results show that 2D ECG image based user recognition accuracy improved by 1%~1.7% for the fiducial point method and by 0.9%~2% for the nonfiducial point method. By showing 13% higher performance compared to the single network in which recognition rate reduction occurs because similar characteristics are shown between classes, capability for use in a smart vehicle platform based user recognition system that requires reliability was demonstrated by the proposed method.
查看更多>>摘要：Underwater Wireless Sensor Networks (UWSNs) contain several components such as vehicles and sensors that are deployed in a specific acoustic area to perform collaborative monitoring and data collection tasks. These networks are used interactively between different nodes and ground-based stations. Presently, UWSNs face issues and challenges regarding limited bandwidth, high propagation delay, 3D topology, media access control, routing, resource utilization, and power constraints. In the last few decades, research community provided different methodologies to overcome these issues and challenges; however, some of them are still open for research due to variable characteristics of underwater environment. In this paper, a survey of UWSN regarding underwater communication channel, environmental factors, localization, media access control, routing protocols, and effect of packet size on communication is conducted. We compared presently available methodologies and discussed their pros and cons to highlight new directions of research for further improvement in underwater sensor networks.
查看更多>>摘要：Currently, big data is a new and hot object of research. In particular, the development of the Internet of things (IoT) results in a sharp increase in data. Enormous amounts of networking sensors are constantly collecting and transmitting data for storage and processing in the cloud including remote sensing data, environmental data, geographical data, etc. Road information extraction from remote sensing data is mainly researched in this paper. Roads are typical man-made objects. Extracting roads from remote sensing imagery has great significance in various applications such as GIS data updating, urban planning, navigation, and military. In this paper a multistage and multifeature method to extract roads and detect road intersections from high-resolution remotely sensed imagery based on tensor voting is presented. Firstly, the input remote sensing image is segmented into two groups including road candidate regions and nonroad regions using template matching; then we can obtain preliminary road map. Secondly, nonroad regions are removed by geometric characteristics of road (large area and long strip). Thirdly, tensor voting is used to overcome the broken roads and discontinuities caused by the different disturbing factors and then delete the nonroad areas that are mixed into the road areas due to mis-segmentation, improving the completeness of extracted roads. And then, all the road intersections are extracted by using tensor voting. The experiments are conducted on different remote sensing images to test the effectiveness of our method. The experimental results show that our method can get more complete and accurate extracted results than the state-of-the-art methods.
Milos StojmenovicTom GedeonHeng QiSeyed M. Buhari...
1页
查看更多>>摘要：Applying mobile and wireless technologies to the health informatics arena has proven to be a timely topic of interest here. Our special issue has chosen 9 publications from a field of competitive submissions, which we feel best reflect reader's interests, include a high level of novelty, and capture the essence of the topic. We feel that the scope of this special issue will remain of significant interest to the scientific community in the future as the potential applications of these technologies in the field of medicine have not nearly been exhaustively explored.
NSTL
Wiley-Hindawi