Rapid urbanization creates new challenges and issues, and the smart city concept offers opportunities to rise to these challenges, solve urban problems and provide citizens with a better living environment. This paper presents an exhaustive literature survey of smart cities. First, it introduces the origin and main issues facing the smart city concept, and then presents the fundamentals of a smart city by analyzing its definition and application domains. Second, a data-centric view of smart city architectures and key enabling technologies is provided. Finally, a survey of recent smart city research is presented. This paper provides a reference to researchers who intend to contribute to smart city research and implementation.

A literature survey on smart cities

As a key technique for enabling artificial intelligence, machine learning (ML) is capable of solving complex problems without explicit programming. Motivated by its successful applications to many practical tasks like image recognition, both industry and the research community have advocated the applications of ML in wireless communication. This paper comprehensively surveys the recent advances of the applications of ML in wireless communication, which are classified as: resource management in the MAC layer, networking and mobility management in the network layer, and localization in the application layer. The applications in resource management further include power control, spectrum management, backhaul management, cache management, and beamformer design and computation resource management, while ML-based networking focuses on the applications in clustering, base station switching control, user association, and routing. Moreover, literatures in each aspect is organized according to the adopted ML techniques. In addition, several conditions for applying ML to wireless communication are identified to help readers decide whether to use ML and which kind of ML techniques to use. Traditional approaches are also summarized together with their performance comparison with ML-based approaches, based on which the motivations of surveyed literatures to adopt ML are clarified. Given the extensiveness of the research area, challenges and unresolved issues are presented to facilitate future studies. Specifically, ML-based network slicing, infrastructure update to support ML-based paradigms, open data sets and platforms for researchers, theoretical guidance for ML implementation, and so on are discussed.

Application of Machine Learning in Wireless Networks: Key Techniques and Open Issues

Mobile crowdsensing (MCS) has gained significant attention in recent years and has become an appealing paradigm for urban sensing. For data collection, MCS systems rely on contribution from mobile devices of a large number of participants or a crowd. Smartphones, tablets, and wearable devices are deployed widely and already equipped with a rich set of sensors, making them an excellent source of information. Mobility and intelligence of humans guarantee higher coverage and better context awareness if compared to traditional sensor networks. At the same time, individuals may be reluctant to share data for privacy concerns. For this reason, MCS frameworks are specifically designed to include incentive mechanisms and address privacy concerns. Despite the growing interest in the research community, MCS solutions need a deeper investigation and categorization on many aspects that span from sensing and communication to system management and data storage. In this paper, we take the research on MCS a step further by presenting a survey on existing works in the domain and propose a detailed taxonomy to shed light on the current landscape and classify applications, methodologies, and architectures. Our objective is not only to analyze and consolidate past research but also to outline potential future research directions and synergies with other research areas.

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A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities

In mobile ad hoc networks (MANETs), the provision of quality of service (QoS) guarantees is much more challenging than in wireline networks, mainly due to node mobility, multihop communications, contention for channel access, and a lack of central coordination. QoS guarantees are required by most multimedia and other time- or error-sensitive applications. The difficulties in the provision of such guarantees have limited the usefulness of MANETs. However, in the last decade, much research attention has focused on providing QoS assurances in MANET protocols. The QoS routing protocol is an integral part of any QoS solution since its function is to ascertain which nodes, if any, are able to serve applications? requirements. Consequently, it also plays a crucial role in data session admission control. This document offers an up-to-date survey of most major contributions to the pool of QoS routing solutions for MANETs published in the period 1997?2006. We include a thorough overview of QoS routing metrics, resources, and factors affecting performance and classify the protocols found in the literature. We also summarize their operation and describe their interactions with the medium access control (MAC) protocol, where applicable. This provides the reader with insight into their differences and allows us to highlight trends in protocol design and identify areas for future research.

A survey of QoS routing solutions for mobile ad hoc networks

This first chapter intends to review and analyze the powerful new Harmony Search (HS) algorithm in the context of metaheuristic algorithms. We will first outline the fundamental steps of HS, and show how it works. We then try to identify the characteristics of metaheuristics and analyze why HS is a good metaheuristic algorithm. We then review briefly other popular metaheuristics such as particle swarm optimization so as to find their similarities and differences with HS. Finally, we will discuss the ways to improve and develop new variants of HS, and make suggestions for further research including open questions.

Music-Inspired Harmony Search Algorithm

Opportunistic routing has recently attracted much attention as it is considered a promising direction for improving the performance of wireless ad hoc and sensor networks. With opportunistic routing, intermediate nodes collaborate on packet forwarding in a localized and consistent manner. Opportunistic routing greatly increases transmission reliability and network throughput by taking advantage of the broadcast nature of the wireless medium. In this article we first illustrate the basic idea behind opportunistic routing, and then categorize current research work based on different criteria. We illustrate how different protocols work, and discuss their merits and drawbacks. Finally, we point out potential issues and future directions in opportunistic routing for wireless ad hoc and sensor networks.

Opportunistic routing for wireless ad hoc and sensor networks: Present and future directions

QoS routing plays an important role for providing QoS in wireless ad hoc networks. The goals of QoS routing are in general twofold: selecting routes with satisfied QoS requirement(s), and achieving global efficiency in resource utilization. In this article we first discuss some key design considerations in providing QoS routing support, and present a review of previous work addressing the issue of route selection subject to QoS constraint(s). We then devise an on-demand delay-constrained unicast routing protocol. Various strategies are employed in the protocol to reduce the communication overhead in acquiring cost-effective delay-constrained routes. Simulation results are used to verify our expectation of the high performance of the devised protocol. Finally, we discuss some possible future directions for providing efficient QoS routing support in wireless ad hoc networks.

QoS routing for wireless ad hoc networks: problems, algorithms, and protocols

Wireless sensor networks with mobile sinks, mWSNs, have attracted a lot of attention recently. This is because sink mobility can greatly alleviate the hotspot issue in WSNs and further prolong the network lifetime. However, sink mobility also causes unexpected changes in network topology and data routing paths, which can largely affect the routing performance in such networks. Design of efficient routing protocols for mWSNs has been a critical issue, and much work has been carried out in this aspect. In this article, we first classify existing protocols based on different design criteria and then present a survey of the state-of-the-art routing protocols in this area. We illustrate how each of the protocols works, and discuss their advantages and disadvantages. Finally, we point out some future directions for efficient routing in mWSNs.

Routing protocols for wireless sensor networks with mobile sinks: a survey

With the increasing popularity of wireless local area network infrastructure, WiFi fingerprint based indoor positioning systems have received considerable attention in recent years. In the literature, most existing work in this area focuses on techniques that match the vector of radio signal strength (RSS) values reported by a mobile device to the fingerprints collected at predetermined reference points (RPs) by comparing the similarity (measured based on RSS difference) between them. However, these existing techniques fail to consider the fact that equal RSS differences at different RSS levels may not mean equal distances in reality. To address this issue, in this paper, we propose a feature scaling based k-nearest neighbor algorithm (FS-kNN) for improved localization accuracy. In FS-kNN, we build a novel RSS-based feature scaling model, which introduces signal-level-scaled weights in the calculation of effective signal distance between signal vector reported by mobile device and existing fingerprints. Experimental results show that FS-kNN can achieve an average error distance as low as 1.93 meters, which is superior to previous work.

A feature scaling based k-nearest neighbor algorithm for indoor positioning system

Opportunistic routing is a new routing paradigm that takes advantage of the broadcast characteristic of a wireless channel for data delivery in a wireless mesh network. Network coding has recently emerged as a new coding paradigm that can significantly improve the throughput performance of a WMN. In this article we explore the combination of opportunistic routing and network coding for improving the performance of a WMN. We first review existing opportunistic routing and coding-aware routing protocols, respectively, classify these protocols based on different criteria, and discuss their merits and drawbacks. We then propose a coding-aware opportunistic routing mechanism that combines hop-by-hop opportunistic forwarding and localized inter-flow network coding for improving the throughput performance of a WMN. Through opportunistic forwarding, CORE allows the next-hop node with the most coding gain to continue the packet forwarding. Through localized network coding, CORE attempts to maximize the number of packets that can be carried in a single transmission. Simulation results show that CORE can significantly improve the throughput performance of a WMN as compared with existing protocols.

Baoxian Zhang

Papers

Opportunistic routing for wireless ad hoc and sensor networks: Present and future directions

QoS routing for wireless ad hoc networks: problems, algorithms, and protocols

Routing protocols for wireless sensor networks with mobile sinks: a survey

A feature scaling based k-nearest neighbor algorithm for indoor positioning system

CORE: a coding-aware opportunistic routing mechanism for wireless mesh networks [Accepted from Open Call]