With the development of telecommunication technologies and the proliferation of network applications in the past decades, the traditional cloud network architecture becomes unable to accommodate such demands due to the heavy burden on the backhaul links and long latency. Therefore, edge computing, which brings network functions close to end-users by providing caching, computing and communication resources at network edges, turns into a promising paradigm. Benefit from its nature, edge computing enables emerging scenarios and use cases, such as augmented reality (AR) and Internet of Things (IowT). However, it also creates complexities to efficiently orchestrate heterogeneous services and manage distributed resources in the edge network. In this survey, we make a comprehensive review of the research efforts on service orchestration and resource management for edge computing. We first give an overview of edge computing, including architectures, advantages, enabling technologies and standardization. Next, a comprehensive survey of state-of-the-art techniques in the management and orchestration of edge computing is presented. Subsequently, the state-of-the-art research on the infrastructure of edge computing is discussed in various aspects. Finally, open research challenges and future directions are presented as well.

Thanks to the advances in wireless communication and machine learning technologies, we can envision a novel AIoT (AI + IoT) service platform that collects video data from the individuals' edge devices. Then, it transforms the video data into useful information, providing services to IoT or smart city applications. However, collecting raw video data directly to the cloud server is merely possible due to network bandwidth limitations and data privacy concerns. One possible solution is to adopt federated learning, which enables edge devices to collaboratively train a shared model without sending the raw data to the cloud. Unfortunately, this scheme cannot directly be applied to the targeted scenario since it assumes labeled data for training, and only at the cloud, we have the human power and time to label the video data. Thus, to tackle those issues, we propose an edge learning system based on semisupervised learning and federated learning technologies. The system trains AI models at edge devices using an improved semisupervised learning scheme and periodically uploads the training results to the cloud server to form a single model by adapting the federated learning technology. Then, we observe that in the real world, the data on the end devices are nonindependent and identically distributed (non-IID) such that it may cause weight divergence during training and result in a considerable decrease in the model performance. Therefore, we propose a new operation called federated swapping (FedSwap) to replace partial federated learning operations based on a few shared data during federated training to alleviate the adverse impact of weight divergence. We evaluate our system on both image classification using the state-of-the-art benchmark data and object detection using real-world video data. The experimental results show that the proposed system can have up to 5.9% higher accuracy of object detection for the video analysis applications by fully utilizing unlabeled data, compared with the situation that only labeled data are used. Moreover, the proposed FedSwap can improve the accuracy of image classification by 3.8% and the object detection task by 1.1%.

Emerging Internet of Things (IoT) applications share the same characteristics of involving multiple processing components (i.e., function modules) and requiring a massive amount of data to be processed with low latency. To meet these needs, edge/fog computing has been proposed for next-generation mobile networks to migrate the computing from the cloud to the edge of the network. Thanks to the development of Network Functions Virtualization (NFV), with which edge computing platform can virtualize function modules and deploy them on any edge devices to provide flexible services on the edge networks. However, such platform would need to deal with complicated function module calling relationship (i.e., call graph) of applications and user mobility, and both are not thoroughly considered by existing works of NFV and edge computing. In this paper, based on our previous idea of virtual local-hub (VLH), we propose a complete design of edge computing framework, which applies NFV technology on edge computing environment for IoT applications. To handle the complicated call graphs of IoT applications with better resource utilization, the VLH framework adapts the technologies of container-based virtualization and microservice architecture, which enables remote function module sharing on the edge computing environment. The framework includes the heuristic algorithm for function module allocation with the objective of minimizing total bandwidth consumption. We also present a design of protocols for system operations and mobility handling in the framework. Then we implement the framework on commodity hardware as a testbed. Via simulations under a large-scale environment with practical settings and experiments on the testbed under real-world scenarios, we demonstrate and verify the effectiveness and practicability of the proposed VLH framework for IoT application service provision.

Licensed shared access (LSA) is one of the emerging modes of regulation for dynamic spectrum sharing management among incumbent wireless networks and secondary networks such as LTE mobile networks. This proof- of-concept demonstration of LSA exploits the Virtually Shared Spectrum Access (ViSSA) platform among various wireless networks and management entities. The ViSSA platform is an innovative integration of five parts by combining LTE small cells, emulators and management servers: i) a monitoring and management center with a spectrum repository that extends a license-exempt mode compliant geo-location database (GLDB/SR); ii) emulated incumbents that may register to GLDB/SR or directly access their spectrum; iii) a few LTE small cell networks of secondary accesses, each network having an LSA controller to communicate between GLDB/SR and its own network management; iv) feature-based sensing of incumbent signals emulated by a USRP; and v) implementation of LSRAI- and http-based communications among i) - iv) via Internet. On-site exhibition of ViSSA platform will demonstrate the novel LSA management of database-guided and sensing-based evacuation yielding to the incumbent. Demonstrations of re-activation of secondary LTE small cells in other available spectrum bands show the feasibility of completing evacuation and re-activation in 60 to 70 seconds.

Exploitation of underutilized spectrum is an effective approach to meet the explosive demand for wireless communications. When heterogeneous secondary networks (HSNs) are allowed to operate in the same underutilized spectrum, their coexistence becomes a critical issue. This paper considers a coexistence network that involves one spectrum provider (SP) sharing unused spectrum resources to multiple HSNs. To coordinate interference-free spectrum sharing among these HSNs, this paper adopts an auction-based approach and designs an Unilateral Vickrey-Clarke-Groves (VCG)-based Auction for HSNs (UVAH). UVAH has three novel designs that make it a practical and efficient solution. Firstly, effective partition of auction regions takes into account the SP's non-uniform amount of supply units in a target area. Secondly, based on the partition, UVAH provides HSNs with a highly expressive package bidding format to freely specify the amount of demand units and operating regions. Lastly virtual bidders by regions are introduced so as to resolve the revenue deficiency problem of VCG while retaining the property of truthfulness. With these three designs, UVAH maximizes the social welfare of the coexistence network without sacrificing the overall spectrum utilization. Numerical analysis shows that, compared to the existing solutions, UVAH improves spectrum utilization, spectrum revenue and HSN satisfaction by 9.96%, 17.26% and 121.73%, respectively.

The Internet of Vehicle (IoV) network refers to networking technologies that could support highly economical and effective communication channels for interactions between vehicles. The success of IoV relies on efficient vehicle-to-infrastructure (V2I) or vehicle-to-vehicle (V2V) communications. Among all existing communication standards, the IEEE 802.15.4 standard, which comprises a simple physical (PHY) layer and an energy-efficient medium access control, is a promising candidate for IoV networks. In this paper, we propose analytical models for IEEE 802.15.4 nonbeacon-enabled mode for IoV by considering two major features, i.e., non-saturated traffic pattern and large-scale network, in IoV applications. We investigate the performance of IEEE 802.15.4 nonbeacon-enabled mode for IoV. Our study can provide guidelines for vehicles to dynamically adjust the broadcasting rate and achieve a higher probability of success in such communications.

Dynamic spectrum access (DSA) is a promising technology to alleviate the exhaustion of spectral resources. To realize DSA, new technologies that enable fast discovery of the unused spectrum along with efficient spectrum management must be developed. In this paper, we propose a novel scanning algorithm and access etiquette to provide secondary devices differentiated spectrum access in a fully distributed manner. The proposed solution does not use any common control channel or require any a prior knowledge of primary devices' usage pattern. More importantly, hardware limitation such as imperfect sensing or lack of strict synchronization between secondary devices are taken into account in our design. A mathematical model and an Opnet-based implementation are also developed to evaluate the performance of the proposed solution in DSA networks.

Abstract With the emergence of Internet of Things (IoT), trillions of devices will soon be interconnected and provide new services. The success of IoT relies on the scalability of underlying machine‐to‐machine communication networks. In this paper, we propose a distributed and adaptive multichannel protocol to address the scalability issue. The proposed protocol is composed of (i) real‐time estimation of competing devices, (ii) adaptive channel access probability, and (iii) asynchronous resource reservation. The three features ensure that channel utilization is maximized even when the number of competing devices and their traffic fluctuate dramatically. Our numerical and simulation results show that the proposed protocol can achieve a channel utilization of up to 93%, especially when the number of competing machine is large. Copyright © 2014 John Wiley & Sons, Ltd.

In the future Internet of Things (IoT), trillions of machines will be interconnected to support various new applications and services. A huge demand for spectral resources will be created and thus, expedite the exhaustion of the wireless spectrum. Dynamic spectrum access (DSA) is a promising technology to alleviate such a problem. In this paper, we propose a DSA-based protocol for multichannel machine-to-machine (M2M) networks. Our mathematical analysis shows that the proposed protocol not only supports differentiated channel access to support applications with diverse quality-of-service (QoS) requirements, but also provides controllable fairness between machines.

With the emergence of machine-to-machine (M2M) communications, trillions of devices will soon be interconnected to support new applications and services. The success of M2M communication relies on the scalability of underlying network architectures and protocols. In this paper, an adaptive multi-channel medium access control (MAC) protocol is proposed to address the scalability issue in M2M communications. The proposed MAC protocol enables devices to (1) real-time estimate the number of competing devices and (2) adjust their operation parameters to maximize channel utilization. Our numerical results show that the proposed protocol outperforms the existing multi-channel protocols, especially when the number of competing devices is large and fluctuates with time.

Dynamic spectrum access (DSA) is a promising technology to improve spectrum utilization. One key issue in DSA is the protection of primary devices from interference caused by secondary devices. In this paper, we discuss this issue in the context of spectrum sensing. Sensing problems resulting from collocated sensing and non-sensing secondary systems — together referred to as heterogeneous DSA systems — are identified and a novel quiet period (QP) scheduling algorithm is proposed. The algorithm guarantees a sensing secondary system to detect returning primary devices in bounded time, without any communication or synchronization with collocated non-sensing secondary systems. We prove the guarantee via mathematical induction and analyze the performance. The algorithm is implemented in a universal software radio peripheral (USRP)-based test bed to demonstrate its feasibility. The results show that our solution is applicable to heterogeneous IEEE 802.22 wireless regional area networks (WRANs), ECMA-392 wireless personal area network (WPANs), and even the future IEEE 802.11af wireless local area networks (WLANs) in the UHF TV bands.

Wireless and mobile social networking service (SNS) utilizes location information to enrich user experience. A major challenge in location-aware SNS is its strict requirement in precision of user location, which generally cannot be met by the existing GPS or cellular networks. In this paper, we propose a user-level cooperative localization scheme that improves the precision of existing localization techniques. A mathematical model is developed and in-depth simulation is conducted to evaluate the performance of the proposed scheme.

New applications such as high-definition (HD) video streaming are driving the data rate of wireless links from hundreds of Mbps to multi Gbps. Among a few technologies that can provide such high rates, transmission in 60-GHz bands is considered as a very promising solution. In this paper, we identify key design challenges of wireless transmission in 60-GHz bands from the perspective of medium access control (MAC) design. Ecma TC-48 MAC protocol is used as a case study to show how these challenges are addressed in a practical and efficient manner.

Dynamic spectrum access (DSA) allows opportunistic use of licensed spectral bands by unlicensed radio devices. DSA improves the overall spectral efficiency but could result in interference between licensed and unlicensed radio devices. In this paper, we investigate the detection and avoidance (DAA) technique to mitigate such potential interference. We develop a time-domain asynchronous coordination protocol that provide silent periods for unlicensed devices to detect licensed devices. The protocol does not require any information exchange between the unlicensed devices and thus, is applicable even when the devices are hidden to each other. This new protocol can be used by ultra wide band (UWB) devices to detect and protect WiMax devices within the 3- to 5-GHz bands.

Static spectrum allocation prohibits radio devices from using spectral bands designated for others. As a result, some bands are under-utilized while other bands are over-populated with radio devices. To remedy this problem, the concept of spectrum agility has been considered so as to enable devices to opportunistically utilize others' spectral bands. In order to help realize this concept, we establish an analytical model to derive performance metrics, including spectrum utilization and spectrum-access blocking time in spectral-agile communication systems. We then propose three basic building blocks for spectral-agile systems, namely spectrum opportunity discovery, spectrum opportunity management, and spectrum usage coordination, and develop protocols for each blocks. These protocols are integrated with the IEEE 802.11 protocol, and simulated using ns-2 to evaluate the protocol overhead. The simulation results show that our proposed protocols can improve the throughput of an IEEE 802.11 wireless LAN by 90% for the simulated scenarios, and the improvements matched well our analytical model. These results demonstrate the great potential of using spectrum agility for improving spectral utilization in an efficient, distributed, and autonomous manner

Radio spectrum is very scarce today because a considerable amount of the spectrum is set aside for licensed wireless applications. With the rapid growth of wireless technologies, spectrum scarcity has become a serious problem as more and more wireless applications compete for very little spectrum. On the other hand the licensed spectrum allocated to applications like television, cellular telephony and public safety show very little usage over time at different geographical locations. The evolution of newer technologies has been seriously impaired because of current regulatory constraints on the operation of these networks in licensed spectrum, such as TV bands, and is being addressed by FCC through its recent rule making. With the goal of ubiquitous communication in mind, we look into spectrum agile radio, a new technology enabled by such FCC rule making, and study its advantages over conventional radios. In this paper, we first show the utilization achievable by agile radios through simple analysis. Then we will outline two types of agile radios and derive their maximum capacities. Then we will go ahead and derive the rules that increase the spectrum utilization using agile radios. We then highlight how spectrum agile radio impacts quality of service as defined in conventional sense.

To support the transmission of (high-rate and oftenbursty) multimedia data with performance guarantees in an IEEE 802.11e wireless local area network (LAN), it is crucial to design judicious algorithms for admission control and resource allocation. The traffic specification element (TSPEC) of the new IEEE 802.11e standard is used to facilitate the design of the admission control. Based on the traffic profile given in the TSPEC and the dual-token bucket regulation, a guaranteed rate is derived for our airtime-based admission control. The admission control is integrated with the contention-based enhanced distributed channel access (EDCA), which together can provide so-called "parameterized QoS" - as in the polling-based HCF controlled channel access (HCCA) - via a new distributed, quantitative control of stations' airtime usage. We also extend the current QoS signaling of HCCA defined in IEEE 802.11e to perform admission control for this enhanced EDCA. Furthermore, we extend the integrated scheme for QoS provisioning in ad hoc wireless LANs and design appropriate signaling procedures. We evaluate via simulation the effectiveness of this parameterized QoS-capable EDCA scheme, and demonstrate its advantages over the centralized, polling-based HCCA scheme.

Packet buffering-and-forwarding is a simple but essential mechanism and has been widely used with other mechanisms to provide seamless handoffs in many wireless/mobile networks. However, some undesirable side effects of this mechanism, if not managed appropriately, can easily diminish its effectiveness in providing seamless inter-cell transitions during a handoff. We first examine these side effects and show how inappropriate buffer management by a mobility agent could affect the TCP performance. The throughput of TCP is then studied with special emphasis on the effects of a handoff. We enhance the conventional buffering-and-forwarding by proposing the last-come-first-drop (LCFD) buffer management policy (to be employed by mobility agents) and post-handoff acknowledgement suppression (to be used by mobile nodes). Our enhancements are backward compatible and suitable for the gradual/incremental deployment. By deriving an analytical model and conducting numerical analysis, we show that our scheme can improve the TCP throughput up to 30%. Finally, we conduct the ns-2 based simulation to confirm these numerical results, and demonstrate the applicability of the analytic model for predicting TCP throughput in other handoff schemes.

An enhanced IEEE 802.11 inter-access point protocol (IAPP) is proposed to provide a unified solution for both intra and intersubnet handoff processes. The proposed enhancement relies on the access point's (AP's) interoperability with other APs, provided by the IP-based IAPP, so as to enable the intra and intersubnet link-layer frame buffering-and-forwarding. This enhancement not only eliminates frame losses during an intrasubnet handoff but, more importantly, realizes loss-free, fast intersubnet handoffs without modifying the IP-mobility protocols such as mobile IP. Our ns-2-based simulation results show that the intersubnet handoff process is transparent to the mobile host's TCP session. Moreover, the enhanced IAPP supports higher user mobility and achieves a higher TCP throughput - up to 50 percent improvement over the original IAPP.

Radio spectrum allocation is undergoing radical rethinking. Regulators, government agencies, industry, and the research community have recently established many initiatives for new spectrum policies and seek approaches to more efficiently manage the radio spectrum. In this paper, we examine new approaches, namely, spectrum agile radios, for opportunistic spectrum usage. Spectrum agile radios use parts of the radio spectrum that were originally licensed to other radio services. A spectrum agile radio device seeks opportunities, i.e. unused radio resources. Devices communicate using the identified opportunities, without interfering with the operation of licensed radio devices. The identification of spectrum opportunities is coordinated by policies, which are defined by, and under the control of, the radio regulator. Our approach is motivated by the publications of the next generation communications, XG, research project of the USA-based Defense Advanced Research Projects Agency, DARPA. We focus on IEEE 802.11k for radio resource measurements as an approach to facilitate the development of spectrum agile radios.

With the proliferation of Internet services, many solutions have emerged to provide quality-of-service (QoS) guarantees when the demands for the hosted services exceed the server's capacity. We take an analytical approach to answering key questions in the design and performance of application-level QoS techniques, especially those that are based on the multi-threading or multi-processing abstraction. Key to our analysis is the integration of the effects of concurrency into the interactions between multi-threaded services. To this end, we extend traditional time-sharing models to develop the multi-threaded round-robin (MTRR) servers, a more accurate model of operation of typical multi-threaded Internet services. For this model, we first develop powerful, yet computationally-efficient, mathematical relationships that describe the performance (in terms of throughput and response time) of multi-threaded services. We then apply optimization techniques to derive the optimal allocation of threads given specific QoS objective functions. Using realistic workloads on a typical Web server, we show the efficacy and accuracy of the proposed new methodology.

A wireless/mobile network supporting multilevel quality of service (QoS) is considered. In such a network, users or applications can tolerate a certain degree of QoS degradation. Bandwidth allocation to users can, therefore, be adjusted dynamically according to the underlying network condition so as to increase bandwidth utilization and service provider's revenue. However, arbitrary QoS degradation may be unsatisfactory or unacceptable to the users, hence resulting in their subsequent defection. Instead of only focusing on bandwidth utilization or blocking/dropping probability, two new user-perceived QoS metrics, degradation ratio and upgrade/degrade frequency, are proposed. A Markov model is then provided to derive these QoS metrics. Using this model, we evaluate the effects of adaptive bandwidth allocation on user-perceived QoS and show the existence of trade offs between system performance and user-perceived QoS. We also show how to exploit adaptive bandwidth allocation to increase system utilization (for the system administrator) with controlled QoS degradation (for the users). By considering various mobility patterns, the simulation results are shown to match our analytical results, demonstrating the applicability of our analytical model to more general cases.

In this paper, we present a link-layer packet forwarding scheme to reduce packet losses during a handoff in IEEE 802.11 WLAN. Through a novel scheme utilizing buffer and image queues in the device driver, the scheme is able to recover most packets that would otherwise be lost during the handoff, including those held in the network interface card. Our experimental results from a test-bed show that the proposed scheme can eliminate or significantly reduce the packet losses in UDP traffic, and help preserve throughput for TCP traffic when the retransmission time out (RTO) is large. To achieve the maximum benefit, we propose to apply the forwarding scheme adaptively depending on the traffic type.

An analytical model is developed for cellular networks with a combined adaptive bandwidth allocation and traffic-restriction mechanism. Instead of focusing only on the bandwidth utilization and forced-termination probability, we derive two important quality-of-service (QoS) metrics, degradation ratio and upgrade/degrade frequency. We show numerically that these two metrics must be taken into account in order to support the QoS specified by each client. The effects of system loads and clients' mobility on system performance are also investigated. Even under the various distributions of mobility, the simulation results are shown to match our analytical results, implying the applicability of our analytical model to more general cases.