Showing papers in "IEEE Internet of Things Journal in 2016"

Edge Computing: Vision and Challenges

Abstract: The proliferation of Internet of Things (IoT) and the success of rich cloud services have pushed the horizon of a new computing paradigm, edge computing, which calls for processing the data at the edge of the network. Edge computing has the potential to address the concerns of response time requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy. In this paper, we introduce the definition of edge computing, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative edge to materialize the concept of edge computing. Finally, we present several challenges and opportunities in the field of edge computing, and hope this paper will gain attention from the community and inspire more research in this direction.

Fog and IoT: An Overview of Research Opportunities

Abstract: Fog is an emergent architecture for computing, storage, control, and networking that distributes these services closer to end users along the cloud-to-things continuum. It covers both mobile and wireline scenarios, traverses across hardware and software, resides on network edge but also over access networks and among end users, and includes both data plane and control plane. As an architecture, it supports a growing variety of applications, including those in the Internet of Things (IoT), fifth-generation (5G) wireless systems, and embedded artificial intelligence (AI). This survey paper summarizes the opportunities and challenges of fog, focusing primarily in the networking context of IoT.

Middleware for Internet of Things: A Survey

Abstract: The Internet of Things (IoT) envisages a future in which digital and physical things or objects (e.g., smartphones, TVs, cars) can be connected by means of suitable information and communication technologies, to enable a range of applications and services. The IoT’s characteristics, including an ultra-large-scale network of things, device and network level heterogeneity, and large numbers of events generated spontaneously by these things, will make development of the diverse applications and services a very challenging task. In general, middleware can ease a development process by integrating heterogeneous computing and communications devices, and supporting interoperability within the diverse applications and services. Recently, there have been a number of proposals for IoT middleware. These proposals mostly addressed wireless sensor networks (WSNs), a key component of IoT, but do not consider RF identification (RFID), machine-to-machine (M2M) communications, and supervisory control and data acquisition (SCADA), other three core elements in the IoT vision. In this paper, we outline a set of requirements for IoT middleware, and present a comprehensive review of the existing middleware solutions against those requirements. In addition, open research issues, challenges, and future research directions are highlighted.

Low-Altitude Unmanned Aerial Vehicles-Based Internet of Things Services: Comprehensive Survey and Future Perspectives

Abstract: Recently, unmanned aerial vehicles (UAVs), or drones, have attracted a lot of attention, since they represent a new potential market. Along with the maturity of the technology and relevant regulations, a worldwide deployment of these UAVs is expected. Thanks to the high mobility of drones, they can be used to provide a lot of applications, such as service delivery, pollution mitigation, farming, and in the rescue operations. Due to its ubiquitous usability, the UAV will play an important role in the Internet of Things (IoT) vision, and it may become the main key enabler of this vision. While these UAVs would be deployed for specific objectives (e.g., service delivery), they can be, at the same time, used to offer new IoT value-added services when they are equipped with suitable and remotely controllable machine type communications (MTCs) devices (i.e., sensors, cameras, and actuators). However, deploying UAVs for the envisioned purposes cannot be done before overcoming the relevant challenging issues. These challenges comprise not only technical issues, such as physical collision, but also regulation issues as this nascent technology could be associated with problems like breaking the privacy of people or even use it for illegal operations like drug smuggling. Providing the communication to UAVs is another challenging issue facing the deployment of this technology. In this paper, a comprehensive survey on the UAVs and the related issues will be introduced. In addition, our envisioned UAV-based architecture for the delivery of UAV-based value-added IoT services from the sky will be introduced, and the relevant key challenges and requirements will be presented.

Optimal Workload Allocation in Fog-Cloud Computing Toward Balanced Delay and Power Consumption

Abstract: Mobile users typically have high demand on localized and location-based information services. To always retrieve the localized data from the remote cloud, however, tends to be inefficient, which motivates fog computing. The fog computing, also known as edge computing, extends cloud computing by deploying localized computing facilities at the premise of users, which prestores cloud data and distributes to mobile users with fast-rate local connections. As such, fog computing introduces an intermediate fog layer between mobile users and cloud, and complements cloud computing toward low-latency high-rate services to mobile users. In this fundamental framework, it is important to study the interplay and cooperation between the edge (fog) and the core (cloud). In this paper, the tradeoff between power consumption and transmission delay in the fog-cloud computing system is investigated. We formulate a workload allocation problem which suggests the optimal workload allocations between fog and cloud toward the minimal power consumption with the constrained service delay. The problem is then tackled using an approximate approach by decomposing the primal problem into three subproblems of corresponding subsystems, which can be, respectively, solved. Finally, based on simulations and numerical results, we show that by sacrificing modest computation resources to save communication bandwidth and reduce transmission latency, fog computing can significantly improve the performance of cloud computing.

Satellite Communications Supporting Internet of Remote Things

Abstract: This paper focuses on the use of satellite communication systems for the support of Internet of Things (IoT). We refer to the IoT paradigm as the means to collect data from sensors or RFID and to send control messages to actuators. In many application scenarios, sensors and actuators are distributed over a very wide area; in some cases, they are located in remote areas where they are not served by terrestrial access networks and, as a consequence, the use of satellite communication systems becomes of paramount importance for the Internet of Remote Things (IoRT). The enabling factors of IoRT through satellite are: 1) the interoperability between satellite systems and sensors/actuators and 2) the support of IPv6 over satellite. Furthermore, radio resource management algorithms are required to enhance the efficiency of IoT over satellite. In this work, we provide an integrated view of satellite-based IoT, handling this topic as a jigsaw puzzle where the pieces to be assembled are represented by the following topics: MAC protocols for satellite routed sensor networks, efficient IPv6 support, heterogeneous networks interoperability, quality of service (QoS) management, and group-based communications.

LTE-V: A TD-LTE-Based V2X Solution for Future Vehicular Network

Abstract: Diverse applications in vehicular network present specific requirements and challenges on wireless access technology. Although considered as the first standard, IEEE 802.11p shows the obvious drawbacks and is still in the field-trial stage. In this paper, we propose long-term evolution (LTE)-V as a systematic and integrated V2X solution based on time-division LTE (TD-LTE) 4G. LTE-V includes two modes: 1) LTE-V-direct and 2) LTE-V-cell. Comparing to IEEE 802.11p, LTE-V-direct is a new decentralized architecture which modifies TD-LTE physical layer and try to keep commonality as possible to provide short range direct communication, low latency, and high reliability improvements. By leveraging the centralized architecture with native features of TD-LTE, LTE-V-cell optimizes radio resource management for better supporting V2I. LTE-V-direct and LTE-V-cell coordinate with each other to provide an integrated V2X solution. Performance simulations based on sufficient scenarios and the prototype system with typical cases are presented. Finally, future works of LTE-V are envisioned.

CSI Phase Fingerprinting for Indoor Localization With a Deep Learning Approach

Abstract: With the increasing demand of location-based services, indoor localization based on fingerprinting has become an increasingly important technique due to its high accuracy and low hardware requirement. In this paper, we propose PhaseFi, a fingerprinting system for indoor localization with calibrated channel state information (CSI) phase information. In PhaseFi, the raw phase information is first extracted from the multiple antennas and multiple subcarriers of the IEEE 802.11n network interface card by accessing the modified device driver. Then a linear transformation is applied to extract the calibrated phase information, which we prove to have a bounded variance. For the offline stage, we design a deep network with three hidden layers to train the calibrated phase data, and employ the weights of the deep network to represent fingerprints. A greedy learning algorithm is incorporated to train the weights layer-by-layer to reduce computational complexity, where a subnetwork between two consecutive layers forms a restricted Boltzmann machine. In the online stage, we use a probabilistic method based on the radial basis function for online location estimation. The proposed PhaseFi scheme is implemented and validated with extensive experiments in two representation indoor environments. It is shown to outperform three benchmark schemes based on CSI or received signal strength in both scenarios.

Twenty Security Considerations for Cloud-Supported Internet of Things

Abstract: To realize the broad vision of pervasive computing, underpinned by the “Internet of Things” (IoT), it is essential to break down application and technology-based silos and support broad connectivity and data sharing; the cloud being a natural enabler. Work in IoT tends toward the subsystem, often focusing on particular technical concerns or application domains, before offloading data to the cloud. As such, there has been little regard given to the security, privacy, and personal safety risks that arise beyond these subsystems; i.e., from the wide-scale, cross-platform openness that cloud services bring to IoT. In this paper, we focus on security considerations for IoT from the perspectives of cloud tenants, end-users, and cloud providers, in the context of wide-scale IoT proliferation, working across the range of IoT technologies (be they things or entire IoT subsystems). Our contribution is to analyze the current state of cloud-supported IoT to make explicit the security considerations that require further work.

Operating Systems for Low-End Devices in the Internet of Things: A Survey

Abstract: The Internet of Things (IoT) is projected to soon interconnect tens of billions of new devices, in large part also connected to the Internet. IoT devices include both high-end devices which can use traditional go-to operating systems (OSs) such as Linux, and low-end devices which cannot, due to stringent resource constraints, e.g., very limited memory, computational power, and power supply. However, large-scale IoT software development, deployment, and maintenance requires an appropriate OS to build upon. In this paper, we thus analyze in detail the specific requirements that an OS should satisfy to run on low-end IoT devices, and we survey applicable OSs, focusing on candidates that could become an equivalent of Linux for such devices, i.e., a one-size-fits-most, open source OS for low-end IoT devices.

Energy Management-as-a-Service Over Fog Computing Platform

Abstract: By introducing microgrids, energy management is required to control the power generation and consumption for residential, industrial, and commercial domains, e.g., in residential microgrids and homes. Energy management may also help us to reach zero net energy (ZNE) for the residential domain. Improvement in technology, cost, and feature size has enabled devices everywhere, to be connected and interactive, as it is called Internet of Things (IoT). The increasing complexity and data, due to the growing number of devices like sensors and actuators, require powerful computing resources, which may be provided by cloud computing. However, scalability has become the potential issue in cloud computing. In this paper, fog computing is introduced as a novel platform for energy management. The scalability, adaptability, and open source software/hardware featured in the proposed platform enable the user to implement the energy management with the customized control-as-services, while minimizing the implementation cost and time-to-market. To demonstrate the energy management-as-a-service over fog computing platform in different domains, two prototypes of home energy management (HEM) and microgrid-level energy management have been implemented and experimented.

Energy-Efficient Resource Allocation for D2D Communications Underlaying Cloud-RAN-Based LTE-A Networks

Abstract: Device-to-device (D2D) communication is a key enabler to facilitate the realization of the Internet of Things (IoT). In this paper, we study the deployment of D2D communications as an underlay to long-term evolution-advanced (LTE-A) networks based on novel architectures such as cloud radio access network (C-RAN). The challenge is that both energy efficiency (EE) and quality of service (QoS) are severely degraded by the strong intracell and intercell interference due to dense deployment and spectrum reuse. To tackle this problem, we propose an energy-efficient resource allocation algorithm through joint channel selection and power allocation design. The proposed algorithm has a hybrid structure that exploits the hybrid architecture of C-RAN: distributed remote radio heads (RRHs) and centralized baseband unit (BBU) pool. The distributed resource allocation problem is modeled as a noncooperative game, and each player optimizes its EE individually with the aid of distributed RRHs. We transform the nonconvex optimization problem into a convex one by applying constraint relaxation and nonlinear fractional programming. We propose a centralized interference mitigation algorithm to improve the QoS performance. The centralized algorithm consists of an interference cancellation technique and a transmission power constraint optimization technique, both of which are carried out in the centralized BBU pool. The achievable performance of the proposed algorithm is analyzed through simulations, and the implementation issues and complexity analysis are discussed in detail.

A Comprehensive Review of Smart Energy Meters in Intelligent Energy Networks

Abstract: The significant increase in energy consumption and the rapid development of renewable energy, such as solar power and wind power, have brought huge challenges to energy security and the environment, which, in the meantime, stimulate the development of energy networks toward a more intelligent direction. Smart meters are the most fundamental components in the intelligent energy networks (IENs). In addition to measuring energy flows, smart energy meters can exchange the information on energy consumption and the status of energy networks between utility companies and consumers. Furthermore, smart energy meters can also be used to monitor and control home appliances and other devices according to the individual consumer’s instruction. This paper systematically reviews the development and deployment of smart energy meters, including smart electricity meters, smart heat meters, and smart gas meters. By examining various functions and applications of smart energy meters, as well as associated benefits and costs, this paper provides insights and guidelines regarding the future development of smart meters.

An Indoor Location-Aware System for an IoT-Based Smart Museum

Abstract: The new technologies characterizing the Internet of Things (IoT) allow realizing real smart environments able to provide advanced services to the users. Recently, these smart environments are also being exploited to renovate the users’ interest on the cultural heritage, by guaranteeing real interactive cultural experiences. In this paper, we design and validate an indoor location-aware architecture able to enhance the user experience in a museum. In particular, the proposed system relies on a wearable device that combines image recognition and localization capabilities to automatically provide the users with cultural contents related to the observed artworks. The localization information is obtained by a Bluetooth low energy (BLE) infrastructure installed in the museum. Moreover, the system interacts with the Cloud to store multimedia contents produced by the user and to share environment-generated events on his/her social networks. Finally, several location-aware services, running in the system, control the environment status also according to users’ movements. These services interact with physical devices through a multiprotocol middleware. The system has been designed to be easily extensible to other IoT technologies and its effectiveness has been evaluated in the MUST museum, Lecce, Italy.

RMER: Reliable and Energy-Efficient Data Collection for Large-Scale Wireless Sensor Networks

Abstract: We propose a novel event data collection approach named reliability and multipath encounter routing (RMER) for meeting reliability and energy efficiency requirements. The contributions of the RMER approach are as follows. 1) Fewer monitor nodes are selected in hotspot areas that are close to the Sink, and more monitor nodes are selected in nonhotspot areas, which can lead to increased network lifetime and event detection reliability. 2) The RMER approach sends data to the Sink by converging multipath routes of event monitoring nodes into a one-path route to aggregate data. Thus, energy consumption can be greatly reduced, thereby enabling further increased network lifetime. Both theoretical and experimental simulation results show that RMER applied to event detection outperforms other solutions. Our results clearly indicate that RMER increases energy efficiency by 51% and network lifetime by 23% over other solutions while guaranteeing event detection reliability.

Software-Defined Wireless Networking Opportunities and Challenges for Internet-of-Things: A Review

Abstract: With the emergence of Internet-of-Things (IoT), there is now growing interest to simplify wireless network controls. This is a very challenging task, comprising information acquisition, information analysis, decision-making, and action implementation on large scale IoT networks. Resulting in research to explore the integration of software-defined networking (SDN) and IoT for a simpler, easier, and strain less network control. SDN is a promising novel paradigm shift which has the capability to enable a simplified and robust programmable wireless network serving an array of physical objects and applications. This paper starts with the emergence of SDN and then highlights recent significant developments in the wireless and optical domains with the aim of integrating SDN and IoT. Challenges in SDN and IoT integration are also discussed from both security and scalability perspectives.

Mobile Phone Computing and the Internet of Things: A Survey

Abstract: As the Internet of Things (IoT) and the Web of Things (WoT) are becoming a reality, their interconnection with mobile phone computing is increasing. Mobile phone integrated sensors offer advanced services, which when combined with Web-enabled real-world devices located near the mobile user (e.g., body area networks, radio-frequency identification tags, energy monitors, environmental sensors, etc.), have the potential of enhancing the overall user knowledge, perception and experience, encouraging more informed choices and better decisions. This paper serves as a survey of the most significant work performed in the area of mobile phone computing combined with the IoT/WoT. A selection of over 100 papers is presented, which constitute the most significant work in the field up to date, categorizing these papers into ten different domains, according to the area of application (i.e., health, sports, gaming, transportation, and agriculture), the nature of interaction (i.e., participatory sensing, eco-feedback, actuation, and control), or the communicating actors involved (i.e., things and people). Open issues and research challenges are identified, analyzed and discussed.

Energy-Efficient Multi-Constraint Routing Algorithm With Load Balancing for Smart City Applications

Abstract: Many researches show that the power consumption of network devices of ICT is nearly 10% of total global consumption. While the redundant deployment of network equipment makes the network utilization is relatively low, which leads to a very low energy efficiency of networks. With the dynamic and high quality demands of users, how to improve network energy efficiency becomes a focus under the premise of ensuring network performance and customer service quality. For this reason, we propose an energy consumption model based on link loads, and use the network’s bit energy consumption parameter to measure the network energy efficiency. This paper is to minimize the network’s bit energy consumption parameter, and then we propose the energy-efficient minimum criticality routing algorithm, which includes energy efficiency routing and load balancing. To further improve network energy efficiency, this paper proposes an energy-efficient multi-constraint rerouting (E2MR2) algorithm. E2MR2 uses the energy consumption model to set up the link weight for maximum energy efficiency and exploits rerouting strategy to ensure network QoS and maximum delay constraints. The simulation uses synthetic traffic data in the real network topology to analyze the performance of our method. Simulation results that our approach is feasible and promising.

Microlocation for Internet-of-Things-Equipped Smart Buildings

Abstract: Microlocation is the process of locating any entity with a very high accuracy (possibly in centimeters), whereas geofencing is the process of creating a virtual fence around a point of interest (PoI). In this paper, we present an insight into various microlocation enabling technologies, techniques, and services. We also discuss how they can accelerate the incorporation of Internet of Things (IoT) in smart buildings. We argue that micro-location-based location aware solutions can play a significant role in facilitating the tenants of an IoT-equipped smart building. Also, such advanced technologies will enable the smart building control system through minimal actions performed by the tenants. We also highlight the existing and envisioned services to be provided by using microlocation enabling technologies. We describe the challenges and propose some potential solutions, such that microlocation enabling technologies and services are thoroughly integrated with IoT-equipped smart building.

A Survey of Traffic Issues in Machine-to-Machine Communications Over LTE

Abstract: Machine-to-machine (M2M) communication, also referred to as Internet of Things (IoT), is a global network of devices such as sensors, actuators, and smart appliances which collect information, and can be controlled and managed in real time over the Internet. Due to their universal coverage, cellular networks and the Internet together offer the most promising foundation for the implementation of M2M communication. With the worldwide deployment of the fourth generation (4G) of cellular networks, the long-term evolution (LTE) and LTE-advanced standards have defined several quality-of-service classes to accommodate the M2M traffic. However, cellular networks are mainly optimized for human-to-human (H2H) communication. The characteristics of M2M traffic are different from the human-generated traffic and consequently create sever problems in both radio access and the core networks (CNs). This survey on M2M communication in LTE/LTE-A explores the issues, solutions, and the remaining challenges to enable and improve M2M communication over cellular networks. We first present an overview of the LTE networks and discuss the issues related to M2M applications on LTE. We investigate the traffic issues of M2M communications and the challenges they impose on both access channel and traffic channel of a radio access network and the congestion problems they create in the CN. We present a comprehensive review of the solutions for these problems which have been proposed in the literature in recent years and discuss the advantages and disadvantages of each method. The remaining challenges are also discussed in detail.

Deceptive Attack and Defense Game in Honeypot-Enabled Networks for the Internet of Things

Abstract: In modern days, breakthroughs in information and communications technologies lead to more and more devices of every imaginable type being connected to the Internet. This also strengthens the need for protection against cyber-attacks, as virtually any devices with a wireless connection could be vulnerable to malicious hacking attempts. Meanwhile, honeypot-based deception mechanism has been considered as one of the methods to ensure security for modern networks in the Internet of Things (IoT). In this paper, we address the problem of defending against attacks in honeypot-enabled networks by looking at a game-theoretic model of deception involving an attacker and a defender. The attacker may try to deceive the defender by employing different types of attacks ranging from a suspicious to a seemingly normal activity, while the defender in turn can make use of honeypots as a tool of deception to trap attackers. The problem is modeled as a Bayesian game of incomplete information, where equilibria are identified for both the one-shot game and the repeated game versions. Our results show that there is a threshold for the frequency of active attackers, above which both players will take deceptive actions and below which the defender can mix up his/her strategy while keeping the attacker’s success rate low.

An Improved Three-Layer Low-Energy Adaptive Clustering Hierarchy for Wireless Sensor Networks

Abstract: Topology control in wireless sensor networks (WSNs) balances the communication load on sensor devices and increases the network lifetime and scalability. Hierarchical or cluster-based design is one of the approaches to conserve the energy of the sensor networks in which the nodes with the higher residual energy could be used to gather data and route the information. However, most of the previous work on clustering has adopted a two-layer hierarchy, and only few methods studied a three-layer scheme instead. Based on a three-layer hierarchy, this paper has proposed a semi-distributed clustering approach by considering a hybrid of centralized gridding for the upper level head selection and distributed clustering for the lower level head selection. The simulation results show that the proposed approach is more efficient than other distributed algorithms. Therefore, the technique presented in this paper could be further applied to large-scale WSNs.

A Survey of Cyber-Physical Advances and Challenges of Wind Energy Conversion Systems: Prospects for Internet of Energy

Abstract: Wind energy has the biggest market share of renewable energy around the world. High growth and development rates of wind energy lead to a massive increase in complexity and scale of wind energy conversion systems (WECSs). Therefore, it is required to upgrade methods and strategies for design and implementation of WECS. Considering WECS as cyber-physical systems (CPSs) will enable wind energy for the Internet of Energy (IoE). IoE is a cloud network where power sources with embedded and distributed intelligence are interfaced to smart grid and mass of consumption devices like smart buildings, appliances, and electric vehicles. Research trends of CPS for energy applications are mainly focusing on smart grids and energy systems for demand-side management and smart buildings with less attention given to generation systems. This paper introduces potentials of cyber-physical (CP) integration of next-generation WECS. In addition, this paper surveys the advances and state-of-the-art technologies that enable WECS for IoE. Challenges and new requirements of future WECS as CPS like abstractions, networking, control, safety, security, sustainability, and social components are discussed.

Joint Clustering and Routing Design for Reliable and Efficient Data Collection in Large-Scale Wireless Sensor Networks

Abstract: For data collection in large-scale wireless sensor networks (WSNs), dynamic clustering provides a scalable and energy-efficient solution, which uses cluster head (CH) rotation and cluster range assignment algorithms to balance the energy consumption. Nevertheless, most existing works consider the clustering and routing as two isolated issues, which is harmful to the connectivity and energy efficiency of the network. In this paper, we provide a detailed analysis on the relations between clustering and routing, and then propose a joint clustering and routing (JCR) protocol for reliable and efficient data collection in large-scale WSN. JCR adopts the backoff timer and gradient routing to generate connected and efficient intercluster topology with the constraint of maximum transmission range. The relations between clustering and routing in JCR are further exploited by theoretical and numerical analyses. The results show that the multihop routing in JCR may lead to the unbalanced CH selection. Then, the solution is provided to optimize the network lifetime by considering the gradient of one-hop neighbor nodes in the setting of backoff timer. Theoretical analysis and simulation results prove the connectivity and efficiency of the network topology generated by JCR.

Security, Privacy, and Incentive Provision for Mobile Crowd Sensing Systems

Abstract: Recent advances in sensing, computing, and networking have paved the way for the emerging paradigm of mobile crowd sensing (MCS). The openness of such systems and the richness of data MCS users are expected to contribute to them raise significant concerns for their security, privacy-preservation and resilience. Prior works addressed different aspects of the problem. But in order to reap the benefits of this new sensing paradigm, we need a holistic solution. That is, a secure and accountable MCS system that preserves user privacy, and enables the provision of incentives to the participants. At the same time, we are after an MCS architecture that is resilient to abusive users and guarantees privacy protection even against multiple misbehaving and intelligent MCS entities (servers). In this paper, we meet these challenges and propose a comprehensive security and privacy-preserving architecture. With a full blown implementation, on real mobile devices, and experimental evaluation we demonstrate our system’s efficiency, practicality, and scalability. Last but not least, we formally assess the achieved security and privacy properties. Overall, our system offers strong security and privacy-preservation guarantees, thus, facilitating the deployment of trustworthy MCS applications.

Scalable Cloud–Sensor Architecture for the Internet of Things

Abstract: Recent advances in the Internet of Things (IoT) and pervasive and ubiquitous computing provide a glimpse into the future of our planet and reveal exciting visions of many smart things: smart cities, smart homes, smart cars, and other smart spaces such as malls, workplaces, hotels, schools, and much more. Driven by a technological revolution offering “low-power many things and wireless almost everything,” we could, in only a decade, envision and prototype impressive smart space systems that improve quality of life, enhance awareness of resources and the environment, and enrich users’ experience. However, prototyping is one thing and actual large-scale deployments are another. The massive scale of sensors and devices that will be deployed in smart cities of the future will be challenging. Without an ecosystem and a scalable architecture in place, it will be extremely difficult to manage or program such an expanding and massive IoT. In this paper, we introduce the Cloud-Edge-Beneath (CEB) architecture and present its salient scalability features. We also present a validation study based on an event-driven programming model demonstrating CEB’s scaling behavior in face of IoT expansion and under dynamically increasing loads.

Ghost-in-ZigBee: Energy Depletion Attack on ZigBee-Based Wireless Networks

Abstract: ZigBee has been widely recognized as an important enabling technique for Internet of Things (IoT). However, the ZigBee nodes are normally resource-limited, making the network susceptible to a variety of security threats. This paper closely investigates a severe attack on ZigBee networks termed as ghost , which leverages the underlying vulnerabilities of the IEEE 802.15.4 security suites to deplete the energy of the nodes. We show that the impact of ghost is very large and that it can facilitate a variety of threats including denial of service and replay attacks. We highlight that merely deploying a standard suite of advanced security techniques does not necessarily guarantee improved security, but instead might be leveraged by adversaries to cause severe disruption in the network. We propose several recommendations on how to localize and withstand the ghost and other related attacks in ZigBee networks. Extensive simulations are provided to show the impact of the ghost and the performance of the proposed recommendations. Moreover, physical experiments also have been conducted and the observations confirm the severity of the impact by the ghost attack. We believe that the presented work will aid the researchers to improve the security of ZigBee further.

An Internet-of-Things Enabled Connected Navigation System for Urban Bus Riders

Abstract: A key challenge for rapidly growing cities of today is to provide effective public transport services to satisfy the increasing demands for urban mobility. Toward this goal, the Internet of Things (IoT) has great potential to overcome existing deficiencies of public transport systems given its ability to embed smart technology into real-life urban contexts. In this paper, we show how this paradigm can be applied to the public transport domain and present the Urban Bus Navigator (UBN), an IoT enabled navigation system for urban bus riders. UBN provides two novel information services for bus users: 1) micro-navigation and 2) crowd-aware route recommendation. Micro-navigation refers to fine-grained contextual guidance of passengers along a bus journey by recognizing boarded bus vehicles and tracking the passenger’s journey progress. Crowd-aware route recommendation collects and predicts crowd levels on bus journeys to suggest better and less crowded routes to bus riders. We present the technical system behind the UBN and report on results from an in-the-wild study in Madrid, Spain, that indicates removed barriers for public transport usage and a positive impact on how people feel about bus journeys.

One Integrated Energy Efficiency Proposal for 5G IoT Communications

Abstract: To further enhance the energy efficiency (EE) performance of fifth generation (5G) Internet of Things systems, an integrated structure is proposed in this paper. That is, other than prior studies that separately study the wireless and wired parts, the wireless and wired parts are holistically combined together to comprehensively optimize the EE of the whole system. The integrated system structure is introduced beforehand with the proposed unified control center components for better deployment of the select-and-sleep mechanism. In addition, in the wireless part, one cellular partition zooming (CPZ) mechanism is proposed. In contrast, in the wired part, a precaching mechanism is introduced. With these proposals, the proposed system EE performance is investigated. Comprehensive computer-based simulation results demonstrate that the proposed schemes display better EE performance. This is due to the fact that system power consumption is further reduced with these schemes as compared to the prior work.

A Feature-Scaling-Based $k$ -Nearest Neighbor Algorithm for Indoor Positioning Systems

Abstract: With the increasing popularity of WLAN infrastructure, WiFi fingerprint-based indoor positioning systems have received considerable attention recently. Much existing work in this aspect adopts classification techniques that match a vector of radio signal strengths (RSSs) reported by a mobile station (MS) to pretrained reference fingerprints sampled from different access points (APs) at different reference points (RPs) with known positions. However, in the calculation of signal distances between different RSS vectors, existing techniques fail to consider the fact that equal RSS differences at different RSS levels may not mean equal differences in geometrical distances in complex indoor environment. To address this issue, in this paper, we propose a feature-scaling-based $k$ -nearest neighbor (FS- $k$ NN) algorithm for achieving improved localization accuracy. In FS- $k$ NN, we build a novel RSS-level-based FS model, which introduces RSS-level-based scaling weights in the computation of effective signal distances between signal vector reported by a MS and reference fingerprints in a radio map. Experimental results show that FS- $k$ NN can achieve an average location error as low as 1.70 m, which is superior to existing work.