Longxiang Gao

A minimum disclosure approach to authentication and privacy in RFID systems

In this paper we present a novel approach to authentication and privacy in RFID systems based on the minimum disclosure property and in conformance to EPC Class-1 Gen-2 specifications. We present two security schemes that are suitable for both fixed reader and mobile/wireless reader environments, the mutual authentication and the collaborative authentication schemes respectively. Both schemes are suited to the computational constraints of EPC Class-1 Gen-2 passive RFID tags as only the cyclic redundancy check (CRC) and pseudo random number generator (PRNG) functions that passive RFID tags are capable of are used. Detailed security analysis of both our schemes show that they offer robust security properties in terms of tag anonymity, tag untraceability and reader privacy while at the same time being robust to replay, tag impersonation and desynchronisation attacks. Simulations results are also presented to study the scalability of the schemes and its impact on authentication delay. In addition, Yeh et al. (2010) 20] proposed a security scheme for EPC Class-1 Gen-2 based mobile/wireless RFID systems. We show that this scheme has a security vulnerability and is not suitable for mobile/wireless RFID systems.

Multidimensional Routing Protocol in Human-Associated Delay-Tolerant Networks

Human-associated delay-tolerant networks (HDTNs) are new networks where mobile devices are associated with humans and can be viewed from multiple dimensions including geographic and social aspects. The combination of these different dimensions enables us to comprehend delay-tolerant networks and consequently use this multidimensional information to improve overall network efficiency. Alongside the geographic dimension of the network, which is concerned with geographic topology of routing, social dimensions such as social characters can be used to guide the routing message to improve not only the routing efficiency for individual nodes, but also efficiency for the entire network. We propose a multidimensional routing protocol (M-Dimension) for the human-associated delay-tolerant networks which uses local information derived from multiple dimensions to identify a mobile node more accurately. The importance of each dimension has been measured by the weight function and it is used to calculate the best route. The greedy routing strategy is applied to select an intermediary node to forward message. We compare M-Dimension to the existing benchmark routing protocols via MIT reality Data Set and INFOCOM 2006 Data Set, which are real human-associated mobile network trace files. The results of our simulations show that M-Dimension significantly increases the average success ratio with a competitive end-to-end delay when compared with other multicast DTNs routing protocols.

Delay Tolerant Networks

This brief presents emerging and promising communication methods for network reliability via delay tolerant networks (DTNs). Different from traditional networks, DTNs possess unique features, such as long latency and unstable network topology. As a result, DTNs can be widely applied to critical applications, such as space communications, disaster rescue, and battlefield communications. The brief provides a complete investigation of DTNs and their current applications, from an overview to the latest development in the area. The core issue of data forward in DTNs is tackled, including the importance of social characteristics, which is an essential feature if the mobile devices are used for human communication. Security and privacy issues in DTNs are discussed, and future work is also discussed.

A Cooperative-Based Model for Smart-Sensing Tasks in Fog Computing

Fog computing (FC) is currently receiving a great deal of focused attention. FC can be viewed as an extension of cloud computing that services the edges of networks. A cooperative relationship among applications to collect data in a city is a fundamental research topic in FC. When considering the green cloud, people or vehicles with smart-sensor devices can be viewed as users in FC and can forward sensing data to the data center. In a traditional sensing process, rewards are paid according to the distances between the users and the platform, which can be seen as the existing solution. Because users with smart-sensing devices tend to participate in tasks with high rewards, the number of users in suburban regions is smaller, and data collection is sparse and cannot satisfy the demands of the tasks. However, there are many users in urban regions, which makes data collection costly and of low quality. In this paper, a cooperative-based model for smartphone tasks, named a cooperative-based model for smart-sensing tasks (CMST), is proposed to promote the quality of data collection in FC networks. In the CMST scheme, we develop an allocation method focused on improving the rewards in suburban regions. The rewards to each user with a smart sensor are distributed according to the region density. Moreover, for each task there is a cooperative relationship among the users; they cooperate with one another to reach the volume of data that the platform requires. Extensive experiments show that our scheme improves the overall data-coverage factor by 14.997% to 31.46%, and the platform cost can be reduced by 35.882%.

M-Dimension: Multi-characteristics based routing protocol in human associated delay-tolerant networks with improved performance over one dimensional classic models

Human associated delay-tolerant network (HDTN) is a new delay-tolerant network where mobile devices are associated with humans. It can be viewed from both their geographic and social dimensions. The combination of these different dimensions can enable us to more accurately comprehend a delay-tolerant network and consequently use this multi-dimensional information to improve overall network efficiency. Alongside the geographic dimension of the network which is concerned with geographic topology of routing, social dimensions such as social hierarchy can be used to guide the routing message to improve not only the routing efficiency for individual nodes, but also efficiency for the entire network. We propose a multi-dimensional routing protocol (M-Dimension) for the human associated delay-tolerant network which uses the local information derived from multiple dimensions to identify a mobile node more accurately. Each dimension has a weight factor and is organized by the Distance Function to select an intermediary and applies multi-cast routing. We compare M-Dimension to existing benchmark routing protocols using the MIT Reality Dataset, a well-known benchmark dataset based on a human associated mobile network trace file. The results of our simulations show that M-Dimension has a significant increase in the average success ratio and is very competitive when End-to-End Delay of packet delivery is used in comparison to other multi-cast DTN routing protocols.

A scalable and automatic mechanism for resource allocation in self-organizing cloud

Taking advantage of the huge potential of consumers’ untapped computing power, self-organizing cloud is a novel computing paradigm where the consumers are able to contribute/sell their computing resources. Meanwhile, host machines held by the consumers are connected by a peer-to-peer (P2P) overlay network on the Internet. In this new architecture, due to large and varying multitudes of resources and prices, it is inefficient and tedious for consumers to select the proper resource manually. Thus, there is a high demand for a scalable and automatic mechanism to accomplish resource allocation. In view of this challenge, this paper proposes two novel economic strategies based on mechanism design. Concretely, we apply the Modified Vickrey Auction (MVA) mechanism to the case where the resource is sufficient; and the Continuous Double Auction (CDA) mechanism is employed when the resource is insufficient. We also prove that aforementioned mechanisms have dominant strategy incentive compatibility. Finally, extensive experiment results are conducted to verify the performance of the proposed strategies in terms of procurement cost and execution efficiency.

FogRoute: DTN-based data dissemination model in fog computing

Fog computing, known as “cloud closed to ground,” deploys light-weight compute facility, called Fog servers, at the proximity of mobile users. By precatching contents in the Fog servers, an important application of Fog computing is to provide high-quality low-cost data distributions to proximity mobile users, e.g., video/live streaming and ads dissemination, using the single-hop low-latency wireless links. A Fog computing system is of a three tier Mobile–Fog–Cloud structure; mobile user gets service from Fog servers using local wireless connections, and Fog servers update their contents from Cloud using the cellular or wired networks. This, however, may incur high content update cost when the bandwidth between the Fog and Cloud servers is expensive, e.g., using the cellular network, and is therefore inefficient for nonurgent, high volume contents. How to economically utilize the Fog–Cloud bandwidth with guaranteed download performance of users thus represents a fundamental issue in Fog computing. In this paper, we address the issue by proposing a hybrid data dissemination framework which applies software-defined network and delay-tolerable network (DTN) approaches in Fog computing. Specifically, we decompose the Fog computing network with two planes, where the cloud is a control plane to process content update queries and organize data flows, and the geometrically distributed Fog servers form a data plane to disseminate data among Fog servers with a DTN technique. Using extensive simulations, we show that the proposed framework is efficient in terms of data-dissemination success ratio and content convergence time among Fog servers.

Silence is Golden: Enhancing Privacy of Location-Based Services by Content Broadcasting and Active Caching in Wireless Vehicular Networks

The privacy issue of location-based service (LBS) applications represents a fundamental and critical research topic that shows distinguished challenges. Specifically, in the scenario of vehicular networks, due to connectivity transitory and throughput degradation caused by high vehicle mobility, traditional methods such as k-anonymity are not sufficient. In an effort to address this issue, we propose a framework that enhances the privacy of LBS by actively caching in the wireless vehicular network scenario. The scheme is designed under the dedicated short-range communication (DSRC) standard, with three original contributions. First, a point-of-interest (POI) query probability model for in-vehicle users is defined, considering the spatial relationship between the current location and the queried location. Second, three broadcasting content selection algorithms of the roadside unit (RSU) are proposed, including two adaptive updating methods and one knowledge-based precaching (KBPC) method. Third, we identify critical parameters that affect privacy, including RSU distance, vehicle speed, query set size of POI, size of each POI entry, and the proportion of channel capacity used for RSU broadcast (defined as channel occupancy). Finally, the proposed scheme is evaluated by extensive simulations, and the results are discussed in detail.

Fog Computing and Its Applications in 5G

With smartphones becoming our everyday companions, high-quality mobile applications have become an important integral of people’s lives. The intensive and ubiquitous use of mobile applications have led to explosive growth of mobile data traffics. To accommodate the surge mobile traffic yet providing the guaranteed service quality to mobile users represent a key issue of 5G mobile networks. This motivates the emergence of Fog computing as a promising, practical and efficient solution tailored to serving mobile traffics. Fog computing deploys highly virtualized computing and communication facilities at the proximity of mobile users. Dedicated to serving the mobile users, Fog computing explores the predictable service demand patterns of mobile users and typically provides desirable localized services accordingly. Stitching above features, Fog computing can provide mobile users with the demanded services through low-latency and short-distance local connections. In this chapter, we introduce the main features of Fog computing and describe its concept, architecture and design goals. Lastly, we discuss on the potential research issues from the perspective of 5G networking.

Complex network theoretical analysis on information dissemination over vehicular networks

How to enhance the communication efficiency and quality on vehicular networks is one critical important issue. While with the larger and larger scale of vehicular networks in dense cities, the real-world datasets show that the vehicular networks essentially belong to the complex network model. Meanwhile, the extensive research on complex networks has shown that the complex network theory can both provide an accurate network illustration model and further make great contributions to the network design, optimization and management. In this paper, we start with analyzing characteristics of a taxi GPS dataset and then establishing the vehicular-to-infrastructure, vehicle-to-vehicle and the hybrid communication model, respectively. Moreover, we propose a clustering algorithm for station selection, a traffic allocation optimization model and an information source selection model based on the communication performances and complex network theory.