Non-terrestrial networks (NTNs) using flying objects such as satellites play key roles in the next-generation wireless system (6G). The NTN links with long propagation delay and random packet losses pose a great challenge to the performance of Transmission Control Protocol (TCP), which many Internet applications rely on. Performance enhancing proxy (PEP) is an easy-to-deploy approach for improving TCP's performance. In this paper, we design and implement a novel PEP calledPEPescwhich has two distinctive features. First, it featuresretransmission-freeloss recovery, using an adaptive packet-level forward erasure correction method called streaming coding (SC). Second, as packet losses are recovered by SC, the congestion control problem is simplified to rate control and local acknowledgement between entities based on bandwidth estimation. Based on a queueing theoretic analysis of the design, we carefully devise a protocol and implement PEPesc as an open-source application. Extensive evaluations show that PEPesc can achieve much higherandsmoother goodput than the canonical TCP variants and than other existing open-source PEPs in applications includingiperfand HTTP-based adaptive streaming, and achieves similar performance in web browsing. Finally, we also present a deployment case over a real-world geostationary satellite link.

In this paper, we address the service function chaining (SFC) problem for software-defined wide area networks (SD-WANs). Due to its NP-hardness, the service chaining problem is simplified by most existing works to apply to practical-size networks. However, in SD-WAN scenarios, these simplifications may lead to link congestion due to the heterogeneity of geographically distributed networks. Different from previous studies, we propose a congestion-aware algorithm, where more comprehensive and practical constraints are considered, and load balancing is introduced to reduce link congestion. First we formulate an integer linear programming model for exact solution, then the original problem is simplified and heuristic algorithms are designed to deploy the SFC requests in batches. Specifically, load balancing is implemented by updating the routing rules according to network congestion status, and data flows from different requests are dispersed in a probabilistic manner, which to our knowledge is first adopted for load balancing in SFC problems. Simulation results show that our algorithm can significantly reduce link congestion, thus improving the acceptance rate of SFC requests and obtaining higher benefits.

The diversity of personal interest and preference of mobile users results in a wide spectrum of mobile app usage, and it is important to predict such app preference in order to provide personalized services. However, currently available individual app usage data is very limited, which does not cover a large user base. In this paper, we demonstrate that it is possible to make personalized app usage estimation by learning user's app preference from the social media, i.e., public accessible tweets, which can also reflect user's interest and make up for the sparsity of app usage data. By proposing a novel generative model named IMCF+ to transfer user interest from rich tweet information to sparse app usage, we achieve personalized app recommendations via learning the interest's correlation between apps and tweets. Based on a real-world app usage and tweet dataset over a large population, we evaluate the performance of IMCF+ with a variety of scenarios and parameters. With only 10 percent training data, our IMCF+ approach achieves 82.5 percent hitrate in predicting the top ten apps. Moreover, IMCF+ outperforms the other six state-of-the-art algorithms by 4.7 percent and 10 percent in high sparsity case and user cold-start scenario, indicating the effectiveness of our method. All these results demonstrate that our technique can reliably learn user's interest from tweets to help solve the personalized app recommendation problem. Our study is the first step forward for transferring user's interest learned from social media to app preference, which paves the way for providing higher-quality personalized app recommendation and services for mobile users.

Compensating for the considerable propagation loss, millimetre‐wave communication systems adopt large antenna arrays and beamforming technologies to obtain high antenna gains. The beamforming training is rather time‐consuming especially in multi‐user cases. To reduce the training overhead, a new fast multi‐user training scheme based on Compressed Sensing theory is proposed. This scheme includes a multi‐user training algorithm and a corresponding semi‐fixed semi‐random codebook design strategy. The base station (BS) simultaneously broadcasts the training pilots to all user equipments (UEs). Then all UEs independently conduct the proposed training algorithm from channel responses. Finally, all UEs send back the training results to the BS. Compared to the exhaustive search algorithm's training overhead , the cost of the proposed scheme is only , where and denote the number of beam patterns in the receiver and the transmitter. Simulation results show that the proposed scheme achieves excellent performance in high SNR (signal‐to‐noise ratio) cases with only performance difference from the theoretical bound. And in contrast with other Compressed Sensing schemes with random codebooks, the proposed scheme reduces the sensitivity to transmission SNR and improves approximately 3 dB performance in low SNR cases.

Accurate and comprehensive end-to-end network performance measurement is critical for the automatic troubleshooting and optimized provision of various services in Cloud. However, cloud providers and tenants still rely on rudimentary and separate tools for end-to-end performance measurement, which are inflexible, tedious, and error-prone. In this paper, we present NetWatch, a system that provides measurement as a service through open APIs for both cloud providers and tenants to measure end-to-end performance on-demand. In this system, measurement requests are first delivered to NetWatch Controller by open APIs, which transforms the request to configure specific Probes to fulfill the requests by active measurement. We make delicate design choices and address several challenges to enable NetWatch offering accurate and low-overhead measurement service for multiple users simultaneously and efficiently. A prototype implementation and experiments with diverse network settings link and traffic demonstrate that NetWatch can support flexible and accurate measurement of end-to-end network performance with small overhead.

Nowadays, human trajectories are widely collected and utilized for scientific research and business purpose. However, publishing trajectory data without proper handling might cause severe privacy leakage. A large body of works is dedicated to merging one’s trajectory with others’, so as to avoid any individual trajectory being re-identified. Yet their solutions do not provide enough protection since they cannot prevent semantic attack, which means the attackers are able to acquire individual’s private information by using the semantics features of frequently visited locations in the trajectory even without re-identification. In this paper, we are the first to recognize the semantic attack, which is another severe privacy problem in publishing trajectory datasets. We propose an algorithm providing strong privacy protection against both the semantic and re-identification attack while reserving high data utility. Extensive evaluations based on two real-world datasets demonstrate that our solution improves the quality of privacy protection by three times, sacrificing only 36% and 10% of spatial and temporal resolution, respectively.

Trajectory data has been widely collected via mobile devices and publicly released for academic research and commercial purposes. One primary concern of publishing such a dataset is the privacy issue. Previous protection schemes mainly focus on preventing re-identification attack, which utilizes the uniqueness of trajectories. However, the correlation between trajectories, which has not been given much attention to before, could also give rise to serious privacy leakage. Recent studies have proved that it is possible to identify social relationship, de-anonymize trajectories or even infer user’s locations by analyzing the correlation between users’ trajectories. We identify the serious privacy problem of social relationship leakage caused by what we call social relationship attack and aim to protect social relationship information, which cannot be protected by existing algorithms. We contribute to the design of a new privacy model and an effective system to deal with social relationship attack and re-identification attack simultaneously while maintaining high data utility. We propose aSlidingWindowalgorithm to merge trajectories according to theirsocial-aware distance, which concerns both the spatiotemporal distance and social proximity. Evaluations of two trajectory datasets under different scenarios demonstrate that our system provides more than 1.84 times privacy protection at the cost of only 2.5% data utility loss.

Recent proliferation of mobile networks and smart devices drives the rapid growth of mobile video traffic. Caching popular video content at any possible place of the network near to users could significantly increase their delivery efficiency. However, fundamental problems of how cache behaves and what is the principle for cache deployment in a mobile network under large-scale video views are still unknown, which include three closely relevant problems: 1) what is the best scale of regions to deploy cache appliances; 2) how many contents should be cached; and 3) which contents should be cached. In this paper, we synthetically study these problems by analyzing 10 million video view requests of six most popular content providers, in the city of Shanghai, China. We first aggregate videos from different providers by topics to measure user interests, and divide the city into nonoverlapping regions of different sizes to investigate the influence of scale. Then, we define metrics of view concentration, popular topic number, cache revenue, and popular topic similarity to quantitatively characterize cache behaviors and consequently answer the three problems. Our studies reveal that: 1) it is effective to deploy cache in regions of a wide range of different scales; 2) the larger scale region and the regions with more views should cache more contents; and 3) different regions, especially small scale ones, should cache different contents. Furthermore, based on trace-driven evaluation, we show that the overall cache hit ratio can increase by up to 30% when we apply above guidelines for cache deployment.

Enhancing throughput gain is an important target in the development of millimeter-wave (mmWave) communications. Spatial reuse is an important approach for throughput enhancement, which works well in mmWave networks due to directional links. In addition, multicast transmissions are highly desirable in mmWave systems, and become feasible with recent advances in antenna technology. In this paper, we address the problem of spatial reuse scheduling with multicast transmissions for mmWave communications. We formulate the problem as a Mixed Integer Non-Linear Programming (MINLP) problem and propose a low-computational-complexity heuristic algorithm, where potential links are fully utilized to exploit spatial reuse gain by dividing multicast demands into multiple unicast/multicast transmissions. Extensive simulation results demonstrate that the proposed scheme achieves near-optimal performance, and obtains high throughput gain with low packet loss rate.

Nowadays, human trajectories are widely collected and utilized for scientific research and business purpose. However, publishing trajectory data without proper handling might cause severe privacy leakage. A large body of works are dedicated to merging one's trajectory with others', so as to avoid any individual trajectory being re-identified. Yet their solutions do not provide enough protection since they cannot prevent semantic attack, which means the attackers are able to acquire individual's private information by using the semantics features of frequently- visited locations in the trajectory even without re- identification. In this work, we are the first to recognize the semantic attack, which is another severe privacy problem in publishing trajectory datasets. We propose an algorithm providing strong privacy protection against both the semantic and re- identification attack while reserving high data utility. Extensive evaluations based on two real-world datasets demonstrate that our solution improves the quality of privacy protection by 3 times, sacrificing only 36% and 30% of spatial and temporal resolution, respectively.

Previous works have proposed various approaches to implement service chaining by routing traffic through the desired middleboxes according to pre-defined policies. However, no matter what routing scheme is used, the performance of service chaining depends on where these middleboxes are placed. Thus, in this paper, we study middlebox placement problem, i.e., given network information and policy specifications, we attempt to determine the optimal locations to place the middleboxes so that the performance is optimized. The performance metrics studied in this paper include the end-to-end delay and the bandwidth consumption, which cover both users’ and network providers’ interests. We first formulate it as 0-1 programming problem, and prove it is NP-hard. We then propose two heuristic algorithms to obtain the sub-optimal solutions. The first algorithm is a greedy algorithm, and the second algorithm is based on simulated annealing. Through extensive simulations, we show that in comparison with a baseline algorithm, the proposed algorithms can reduce 22 percent end-to-end delay and save 38 percent bandwidth consumption on average. The formulation and proposed algorithms have no special assumption on network topology or policy specifications, therefore, they have broad range of applications in various types of networks such as enterprise, data center and broadband access networks.

60‐GHz millimetre‐wave (mm‐wave) communication is gradually becoming a promising candidate for the next generation wireless system to meet the demands of mobile applications. To compensate for high path loss, directional links are established in mm‐wave communication system, which adds opportunity for spatial reuse. As one of its most promising protocols for commercial production, IEEE 802.11ad standard provides a mechanism to support space‐time division multiple access (STDMA) within a single network. However, the interference level among different co‐channel networks is much lower than that inside a network, which provides greater potential for spatial reuse. In this study, based on the architecture and timing structure of IEEE 802.11ad, the authors propose a spatial reuse strategy among multiple co‐channel networks. They formulate the problem as a mixed‐integer non‐linear programming problem, and then propose an inter‐network STDMA scheduling algorithm, which considers clustering frame structure in IEEE 802.11ad, and combines greedy principle and mutual interference avoidance strategy. Extensive simulation results have shown that the proposed scheme enlarges total throughput in comparison with STDMA inside each network, as well as non‐STDMA scheme. Meanwhile, it achieves the lowest packet loss rate under heavy traffic load.

Abstract Millimeter wave (mmWave) communications in 60 GHz band have become a hot topic in wireless communications. New medium access control (MAC) protocols are needed because of the fundamental differences between mmWave communications and existing other communication systems. In mmWave wireless personal area networks, the channel transmission rates of links vary significantly because of the difference in the distance between nodes, the accuracy of beamforming, and the existence of obstructions. Owning to the directivity of mmWave links, spatial reuse should be exploited to improve network capacity. In this paper, we develop a channel transmission rate aware directional MAC protocol, termed RDMAC, in which both the multirate capability of links and spatial reuse are exploited to improve network performance. RDMAC has two stages. The first stage measures the channel transmission rates of links, and a heuristic algorithm is proposed to compute near‐optimal measurement schedules with respect to the total number of measurements. The second stage accommodates the traffic demand of links, and a heuristic transmission scheduling algorithm is proposed to compute near‐optimal transmission schedules with respect to the total transmission time. Simulations under various traffic modes show that compared with existing protocols, RDMAC has lower network latency, higher network throughput, and also a good fairness performance. Copyright © 2014 John Wiley & Sons, Ltd.

Due to the requirement of establishing several independent links, multi-device multi-path beamforming (BF) training becomes rather time-consuming in 60-GHz millimeterwave communications. To reduce training overhead, a novel BF training scheme is proposed in this paper. The scheme includes a simultaneous training strategy for multiple devices and multiple paths, and a corresponding multi-path beam-pair detection algorithm. The training pilot of the source device is broadcasted to all destination devices. Subsequently, in each destination device, the proposed detection is separately conducted to detect significant-path-related beam pairs from the channel responses, via exploiting the time resolvability and space sparsity of physical paths. Finally, the training results are successively fed back to the source device. The proposed scheme achieves simultaneous training of multiple devices and multiple paths, and obtains significant reduction of overhead. Comprehensive simulations are presented to verify the effectiveness of this scheme.

Owing to the requirement of power‐hungry ultra‐high‐speed analogue‐to‐digital converters (ADCs), 60 GHz wireless local area network systems face the challenge of high energy consumption in idle listening (IL). To cope with this problem, a 1 bit‐sampling IL (1BS‐IL) scheme is proposed in this paper. This scheme includes a mixed 1/ M ‐bit‐sampling receiver, and a corresponding packet detection algorithm termed 1BS generalised likelihood ratio test (1BS‐GLRT). The receiver enables packet detection in IL with a 1 bit ADC, which considerably lowers down the energy consumption; besides, the 1BS‐GLRT algorithm guarantees promising performance on packet detection. Once detecting the arrival of a packet, the receiver switches to an original multi‐bit sampling precision, that is, M ‐bit, ADC to demodulate the packet, which maintains the demodulation performance. Comparisons show that 1BS‐IL not only significantly reduces energy consumption, but also achieves competitive detection performance.

With the explosive growth of mobile data demand, there has been an increasing interest in deploying small cells of higher frequency bands underlying the conventional homogeneous macrocell network, which is usually referred to as heterogeneous cellular networks, to significantly boost the overall network capacity. With vast amounts of spectrum available in the millimeter-wave (mmWave) band, small cells at mmWave frequencies are able to provide multigigabit access data rates, whereas the wireless backhaul in the mmWave band is emerging as a cost-effective solution to provide high backhaul capacity to connect access points of the small cells. In order to operate the mobile network optimally, it is necessary to jointly design the radio access and backhaul networks. Meanwhile, direct transmissions between devices should be also considered to improve system performance and enhance user experience. In this paper, we propose a joint transmission scheduling scheme for the radio access and backhaul of small cells in the mmWave band, termed D2DMAC, where a path selection criterion is designed to enable device-to-device transmissions for performance improvement. In D2DMAC, a concurrent transmission scheduling algorithm is proposed to fully exploit spatial reuse in mmWave networks. Through extensive simulations under various traffic patterns and user deployments, we demonstrate that D2DMAC achieves near-optimal performance in some cases and outperforms other protocols significantly in terms of delay and throughput. Furthermore, we also analyze the impact of path selection on the performance improvement of D2DMAC under different selected parameters.

Groups of people with mobile phones using short-range connections such as WiFi and Bluetooth to propagate messages can be modeled as, with regard to regular absence of end-to-end connection, mobile social networks (MSNs), which can be exploited to offload a significant amount of mobile content from the overloaded infrastructure networks such as 3G. The study of content transmission delay for the applications of mobile content dissemination in MSNs is an important problem, because to enhance the network capacity, the traffic is offloaded at the cost of inducing longer delay. In contrast to existing works, which ignore the factors of contact duration limits and large content size, we present a contact duration aware framework to model the content dissemination process in MSNs, give an explicit expression for the average content dissemination delay, and reveals its relationship with various system parameters of content size, users' selfishness, number of involved subscribers, infecting ratio, and so on. We apply our proposed model to real-life traces to assess its reliability by comparing the theoretical results with measured statistics and present extensive upshots to evaluate the influence of various parameters on system performance. The results demonstrate the accuracy of our proposed framework and reveal that system parameters of content size, system infecting ratio and intragroup transmission are the most important factors to influence the content dissemination delay.

Various network optimization and management goals in cloud data centers can be achieved by re-mapping VMs to the substrate servers. Live VM migration is used to implement such re-mapping by moving VMs from the initial servers to the target ones. For efficiency and usability considerations, these migration tasks are expected to be completed as soon as possible, which can be achieved by planning multiple VMs to be migrated simultaneously. However, the available resources of computation and bandwidth limits the number of VMs that can be migrated at the same time. Besides, the available resources change with the progress of migration process, which makes VM migration planning a challenge problem. Considering both resources constraints and the dependence between the migration plan and the total migration time, in this paper, we investigate the problem of virtual machine migration planning to minimize the total migration time. We formulate VM migration planning as an optimization problem considering both computation and bandwidth constraints. Our formulation is based on a step-by-step migration scheme, where multiple VMs can be migrated simultaneously as long as the resource constraints are satisfied. The solution of the optimization problem outputs the migration plan which achieves the minimum time to finish the migration task. Moreover, we verify the effectiveness of the optimal migration plan through extensive simulations and comparison with the best algorithm in existing works.

Due to human blockage and device mobility, 60GHz wireless local-area network (WLAN) faces the challenge of communication-link outage. To cope with this problem, a double-link beam tracking scheme is proposed in this paper. This scheme includes a search strategy of transmission and alternative links, and an in-packet double-link tracking and switching method. The transmission and alternative links are simultaneously tracked against device mobility, through probing neighboring beams; once the human blockage is detected in transmission link, the system can thus switch to the alternative link directly. Besides, the proposed scheme finds the finish of human blockage quickly through in-packet double-link tracking, and enables the system to communication in the maximal received-power link. The comparison between the proposed scheme and the IEEE 802.11ad scheme is conducted. The comparison shows that the proposed scheme significantly reduces the probability of outage, and achieves an improved throughput.

Power amplifier (PA) non‐linearity is extremely significant for 60 GHz millimetre‐wave communications, which distorts signal constellation seriously. In dealing with this problem, the commonly used digital predistortion (DPD) becomes unaffordable for 60 GHz systems in both power consumption and price. This study proposes to handle PA non‐linearity with distorted constellation (DCS) estimation and demodulation for 60 GHz systems with single‐carrier frequency‐domain equalisation transmission, which has a low implementation cost. Employing the least‐square (LS) algorithm, the DCS is estimated both before and after equalisation, where LS after equalisation has a lower computational complexity than LS before equalisation. Subsequently, the estimated DCS, instead of the standard constellation, is used as a criterion for demodulation, which is shown to achieve a significant improvement on the symbol‐error‐rate (SER) performance, especially when the non‐linear distortion is severe. Moreover, compared with DPD, the proposed method achieves a better SER performance and behaves more robustly in the low range of input power back‐off (IBO), whereas achieving a close SER performance in the high‐IBO range.

As malware attacks become more frequently in mobile networks, deploying an efficient defense system to protect against infection and to help the infected nodes to recover is important to prevent serious spreading and outbreaks. The technical challenges are that mobile devices are heterogeneous in terms of operating systems, the malware infects the targeted system in any opportunistic fashion via local and global connectivity, while the to-be-deployed defense system on the other hand would be usually resource limited. In this paper, we investigate the problem of how to optimally distribute the content-based signatures of malware, which helps to detect the corresponding malware and disable further propagation, to minimize the number of infected nodes. We model the defense system with realistic assumptions addressing all the above challenges that have not been addressed in previous analytical work. Based on the framework of optimizing the system welfare utility, which is the weighted summation of individual utility depending on the final number of infected nodes through the signature allocation, we propose an encounter-based distributed algorithm based on Metropolis sampler. Through theoretical analysis and simulations with both synthetic and realistic mobility traces, we show that the distributed algorithm achieves the optimal solution, and performs efficiently in realistic environments.

Owing to the uncertainty of transmission opportunities between mobile nodes, the routing in delay tolerant networks (DTNs) exploits the mechanism of store-carry-and-forward. In this routing mechanism, mobility plays an important role, and we need to control the mobility of nodes around the network to help with carrying messages from the source to the destination. This is a difficult problem because the nodes in the network may move arbitrarily and it is difficult for us to determine when the nodes should move faster to help the data transmission while considering the complicated energy consumption in such a network. At the same time, for most DTNs, the system energy is limited, and energy efficient algorithms are crucial to maximizing the message delivery probability while reducing the delivery cost. In this paper, we investigate the problem of energy efficient mobility speed control in epidemic routing of DTN. We model the message dissemination process under variable mobility speed by a continuous-time Markov model. With this model, we then formulate the optimization problem of the optimal mobility control for epidemic routing and obtain the optimal policy from the solution of this optimization problem. Furthermore, extensive numerical results demonstrate that the proposed optimal policy significantly outperforms the static policy with constant speed, in terms of energy saving. Copyright © 2012 John Wiley & Sons, Ltd.

Data plane programmability is regarded as an essential feature of future Internet. However, the flexibility of programmability has not been carefully considered. We present GrainFlow, a hardware-based packet processing platform supporting customization on every header bit's processing and adapting to packet header length variation. We evaluate GrainFlow on a Virtex-5 FPGA board. Experiment results show that users can flexibly redefine the data plane with only 10-20 rules and data plane forwarding rate can achieve wire-speed with acceptable latency increase.

Due to the extremely high oscillation frequency of 60 GHz systems, phase noise (PN) imported at both transmitter (Tx) and receiver (Rx) is significant, which degrades the transmission performance. This paper proposes an architecture employing iterative Tx and Rx PN compensation (ITR-PNC) for 60 GHz systems with single-carrier frequency-domain equalization (SC-FDE) transmission. The ITR-PNC iteratively performs PNC before equalization (PNC-BE) and PNC after equalization (PNC-AE), which are mainly set to manage Rx PN (RPN) and Tx PN (TPN), respectively. The PNC-BE and PNC-AE both exploit the one-tap least mean square (LMS) algorithm for PN extraction (PNE). In PNC-AE, the decision feedback result is used as the reference signal for PNE. And in PNC-BE, the reference signal is the signal replica, which is generated via the decision result and the estimated TPN of last iteration, and the estimated channel response. Comprehensive simulations indicate that the proposed architecture employing the proposed ITR-PNC achieves competitive bit-error-rate (BER) performance with only two iterations, for the cases whether only RPN or both TPN and RPN are taken into consideration.

A significant concern for cloud operators is to provide global network performance isolation for concurrent tenants. To address this, we propose M2cloud, a software defined framework providing scalable network control for multi-site data centers (DCs). M2cloud employs two-level controllers with decoupled functions, providing each tenant with flexible virtualization support in both intra- and inter-DC networks.

With the rapid growth of the demands for mobile data, wireless network faces several challenges, such as lack of efficient interconnection among heterogeneous wireless networks, and shortage of customized QoS guarantees between services. The fundamental reason for these challenges is that the radio access network (RAN) is closed and ossified. We propose OpenRAN, an architecture for software-defined RAN via virtualization. It achieves complete virtualization and programmability vertically, and benefits the convergence of heterogeneous network horizontally. It provides open, controllable, flexible and evolvable wireless networks.

The newly emerged vehicular communication network is seen as a key technology for solving the increasingly serious vehicular traffic congestion as well as improving road safety, and applications of vehicular networks are also emerging at the same time. Predicting vehicular visiting time is vital to both solving the vehicular system problem and building efficient vehicular networking. It is an open and unsolved problem that how much the vehicular staying duration of visits to different areas can be predicted. In this paper, we use real vehicular traces in Beijing and Shanghai and an area partition model to explore the limit of predictability of the vehicular visiting time in different areas in large scale cities and analyze the effect of different precision and slot time on predictability. We conclude that using a proper time slot is an efficient way of prediction and a higher predictability can be achieved if the requirement for precision is reduced. Among all the cases we study, we find the highest potential predictability in Beijing and Shanghai in the case with smallest slot time and lowest requirement for precision.

The direct-conversion transceiver is an attractive architecture for 60 GHz wireless systems to meet the low-cost and low-power-consumption requirements, but it suffers from the IQ imbalance problem seriously. This paper adopts secondorder moment estimation to extract frequency-independent IQ imbalance parameters, and performs IQ compensation based on the estimation results. In order to achieve robust estimation, we employ a specific preamble sequence, where adjacent symbols have a fixed phase difference of π/2. The proposed estimation excels in the following aspects: (1) it completely eliminates the impact of inter-symbol interference (ISI) and carrier phase offset (CPO); (2) it is not degraded by carrier frequency offset (CFO), since the impact of which only lies in the negligible phase offset during only a symbol duration; (3) it has low computational complexity and can be implemented on hardware platform expediently. Simulation results indicate that the estimation algorithm has competitive performance over a large range of IQ imbalance, and with IQ compensation the bit-error-rate (BER) performance can be improved to that of the ideal case.

Vehicular Delay Tolerant Networks (VDTN) are used to distribute a large amount of mobile data by high-capacity device-to-device communication. Given a number of available vehicles in VDTN, the current vehicular data sharing models always utilize all of them to achieve the best effect, failing to balance the performance gained and cost of employing them. Taking the cost into account, we study the problem of the optimal number of vehicles to be deployed in the data sharing system, which considers using erasure codes to further increase the system efficiency if possible. By establishing the system goal which consists both the effectiveness and the cost of the vehicular network mathematically, we formulate the above problem as a utility function minimization problem. Finally, we solve the problem by theoretical derivation, and demonstrate the efficiency of the obtained solution through simulations using real vehicular traces of Beijing and Shanghai.

Network virtualization provides an alternative for wireless testbed to support multiple experiments simultaneously, as its properties of isolation, customization and efficiency are able to improve network resources utilization significantly. However, complex radio environment makes the employment of virtualization in wireless networks become a difficult problem, in which strict isolation across different experiments is hard to maintain. What is more, present radio experimental systems mostly exploit only Time Division Multiplexing, which may cause resources waste when the scale of experiments is relatively small. In this paper, we propose a time-space combined resources allocation scheme by taking advantage of both Time Division Multiplexing and Space Division Multiplexing. In this scheme, we first select a new time slot and some unscheduled experiments. Then we adopt Space Division Multiplexing to fit in as many experiments as possible in a time slot while ensuring required isolation across them. Extensive simulation shows that our scheme improves experimental resources utilization effectively, while each experiment in the same time slot have enough bandwidth among all nodes and the fairness of resources utility is also ensured.

Contact interval between moving vehicles is one of the key metrics in vehicular ad hoc networks (VANETs), which is important to routing schemes and network capacity. In this work, by carrying out an extensive experiment involving tens of thousands of operational taxis in Beijing city, we find an invariant character that the contact interval can be modeled by a three-segmented distribution, and there exists a characteristic time point, up to which the contact interval obeys a power law distribution, while beyond which it decays as an exponential one. This property is in sharp contrast to the recent empirical data studies based on Shanghai vehicular mobility, where the contact interval exhibits only exponential distribution.

Groups of people with mobile phones using short range connections like WiFi and Bluetooth to propagate messages can be modeled as, with regard to regular absence of end-to-end connection, Delay Tolerant Networks (DTNs). The study of message transmission speed in such kind of networks has attracted increasing attention in recent years. In this paper, we present a realistic framework to model the message propagation process, and give a detailed expression of average information dissemination delay based on message size, users' selfishness, number of involved subscribers and other related parameters. We apply our model to real-life traces to assess its reliability by comparing the theoretical results with measured statistics, and present extensive upshots to evaluate the influence of various parameters on system performance.

Network community needs a flexible platform for network experiment of new architectures, algorithms and protocols in the process of network innovation. However, building such a platform faces lots of challenges due to complicate requirements. In this paper, we present ExpoNet, a platform for rapid concurrent experiment of network innovation on the virtualized programmable infrastructure. ExpoNet integrates both software- and hardware-based router virtualization technologies to provide a flexible approach to configure and customize both the control plane and data plane while satisfying various experiment requirements. We implement ExpoNet, and design a management system to efficiently provide the users with convenient interface to access the platform. Based on its implementation, we present a live network experiment of Network Tomography, which infers the network inner performance according to the observed results of outside nodes. The experiment design and related results show the flexibility and effectiveness of our ExpoNet.

Due to the uncertainty of transmission opportunities between mobile nodes, Delay Tolerant Networks (DTNs) exploits the opportunistic forwarding mechanism. This mechanism requires nodes to forward messages in a cooperative and selfish way. However, in the real word, most of the nodes exhibit selfish behaviors such as individual and social selfishness. At the same time, the energy is usually limited in such networks. In this paper, we investigate how the selfish behaviors affect the performance of two-hop relaying multicast in energy-constrained DTN. We model the message delivery process under selfish behaviors and system energy constraint by a three- dimensional continuous time Markov chain. In terms of multicast performance, we investigate the average message transmission delay and transmission cost. Numerical results show that different selfish behaviors may have opposite impacts on different performance metrics in the energy-constrained DTN.

Mobility plays an important role in the message transmission of Disruption Tolerant Networks (DTNs), and we need to control the mobility of nodes around the network to efficiently carry and relay messages around the network. This is a challenging problem since the nodes in the network may move arbitrarily and it is hard for us to determine how the nodes should move, faster or slower, to help with the data transmission. Moreover, in such network, the energy is usually limited, and we need to consider its complicated energy consumption. In this paper, we investigate the problem of energy-constrained mobility velocity control in epidemic routing of DTN. We first model the message dissemination process under variable mobility velocity by a continuous-time Markov model, then formulate the optimal mobility control problem, and finally obtain the optimal threshold policy from the solution of this optimization problem. Furthermore, extensive numerical results demonstrate that the proposed optimal threshold policy significantly outperforms the static policy with constant velocity, in terms of energy saving.

This paper presents channel measurements for wireless body area network (WBAN) and provides performance evaluation using the model derived from measurement and the model in the final document of the IEEE802.15.6 channel modeling subcommittee. We measure the radio propagation from 3.0GHz to 5.0GHz which falls in ultra-wideband (UWB) frequency range in an anechoic chamber and give out a static model. 10 positions for medical entertainment and sports application are chosen to conduct measurement on a fat body, a normal body and a thin body in order to compare different path loss of different types of body for Chinese people. Moreover, we compare the bit error ratio (BER) of a single carrier UWB (SC-UWB) system which employs different receiving policies such as rake, equalizer and channel coding. The results show that slimmer people cause less path loss in the valid distance from 100mm to 1000mm. The measured model we derived has less multi-path effect than that of the model in the final report given by IEEE802.15.6 channel modeling subcommittee. Even though, rake receiver, equalizer and channel coding are needed to get a satisfying system performance.

In order to provide communication services in Delay Tolerant Networks (DTNs) where it lacks of end-to-end paths between the communication sources and destinations, a variety of routing schemes have been proposed. Consequently it is significant to accurately evaluate their performance to show their advantages and inferiority. At the same time, the energy is very limited in a large number of DTNs, such as sparse mobile sensor networks and emergency ad hoc networks, and it impacts the routing performance significantly. However, current related works ignore the influence of the energy constraint on the routing. In this paper, we investigate the performance of routing schemes for the energy-constrained DTNs. First, we model the two-hop relaying, epidemic routing and K-hop forwarding with energy constraint based on a two-dimensional continuous time Markov chain. Then, we obtain the system performance of message delivery delay and delivery cost by explicit expressions. By both simulation and numerical results, we demonstrate the accuracy of our proposed model and reveal that the energy constraint can actually avoid the message storms which are harmful to the systems in term of delivery cost and transmission contention.

In Delay Tolerant Networks (DTNs), there exists only intermittent connectivity between communication sources and destinations. In order to provide successful communication services for these challenged networks, a variety of relaying and routing algorithms have been proposed with the assumption that nodes are homogeneous in terms of contact rate and delivery cost. However, various applications of DTN have shown that mobile nodes can be divided into different classes in terms of their energy requirements and communication ability, and real application data have revealed the heterogeneous contact rates between node pairs. In this paper, we design an optimal relaying scheme for DTNs, which takes into account nodes' heterogeneous contact rates and delivery costs when selecting relays to minimise the delivery cost while satisfying the required message delivery probability. Extensive results based on real traces demonstrate that our relaying scheme requires the least delivery cost and achieves the largest maximum delivery probability, compared with the schemes that neglect nodes' heterogeneity.

The applications of dynamic content updates for a group of users, for example weather report and traffic congestion broadcast, have been shown to benefit significantly from Delay Tolerant Networks (DTN) communication mechanisms such as opportunistic contact and user sharing. In this paper, we study the dynamic content updates over energy-constrained DTN, and focus on its asymptotic properties about stability and scalability on the time and network size dimensions respectively. By introducing a continuous time Markov framework, we characterize the content dissemination system by both the source update & node sharing process and energy constraint. Based on this framework, we prove the system is stable when the time t approaches to infty, and the convergence rate is exponential. At the same time, by simulation we find that the content's average stable age decreases as Θ(√N) as the number of users N increases. Moreover, through extensive numerical results, we demonstrate the correctness of the theoretically obtained properties of stability.

We present TUNIE, a network platform for rapid concurrent experiment of network innovation on virtualized programmable infrastructure. TUNIE integrates both software-and hardware-based router virtualization technologies to provide a flexible approach to configure and customize both the control plane and data plane, and at the same time satisfied various experiment designing requirements. We implement TUNIE, and deploy it in Tsinghua University. Early experiment of algorithm evaluation verifies the efficiency TUNIE.

We collect data trace from taxis with GPS devices installed to study some important metrics of vehicle mobile networks. Such study may contribute to the future intelligent transportation systems and wireless communication protocols or algorithms designs. To our knowledge, only a few works in this area have been done before since such experiment is usually a huge cost. We took experiments on operative taxis in Beijing, who sent the geographical informations to the console automatically. In this paper, we focus on two of the most important metrics called flight length and pause time distribution in vehicle networks. Through analyzing our own trace datas as well as those collected by Shanghai Jiaotong University, we draw a conclusion that vehicle moving pattern actually shares some resemblances with the previous achievements on Levy-walk nature in human walk. In another word, cars run like human. Index Terms—Flight length; pause time; truncated pareto; Vehicle networks

As malware attacks become more frequent in mobile networks, deploying an efficient defense system to protect against infection and to help the infected nodes to recover is important to contain serious spreading and outbreaks. The technical challenges are that mobile devices are heterogeneous in terms of operating systems, and the malware can infect the targeted system in any opportunistic fashion via local and global connectivity, while the to-be-deployed defense system on the other hand would be usually resource limited. In this paper, we investigate the problem of optimal distribution of content-based signatures of malware to minimize the number of infected nodes, which can help to detect the corresponding malware and to disable further propagation. We model the defense system with realistic assumptions addressing all the above challenges, which have not been addressed in previous analytical work. Based on the proposed framework of optimizing the system welfare utility through the signature allocation, we provide an encounter-based distributed algorithm based on Metropolis sampler. Through extensive simulations with both synthetic and real mobility traces, we show that the distributed algorithm achieves the optimal solution, and performs efficiently in realistic environments.

With the development of mobile networks, terminals' locations become increasingly valuable for both the whole system performance and terminals' applications or services. As knowing the knowledge of terminals' location information in advance would provide extern preparation time to accelerate response to terminals' requirements, location prediction plays a quite important role. Since most of the mobile terminals are human-carried devices, terminals' location prediction is actually the persons' location prediction. On the other hand, the research on social networks has experienced a fast development and provided a new kind of view on prediction. In our paper, we propose a location prediction scheme based on the idea of social correlation which is a kind of link between different terminals weighted by statistic results of history information.We also model topologies as sequences of snapshots to guide prediction. Few limits on the format of history location information record makes sure a strong adaptiveness of our scheme to various application's requirements.

Due to the lack of end-to-end paths between the communication sources and destinations, the routing of Delay Tolerant Networks (DTN) exploits the store-carry-and-forward mechanism. In this new routing mechanism, how to efficiently integrate forwarding and replication mechanisms is significant for achieving high message delivery ratio while requiring low delivery cost. In this paper, by using famous social properties such as communities and centrality, we design a routing scheme efficiently Integrating Forwarding and Replication (IFR), which allow node to replicate messages in the same community and to forward messages outside the community according to delivery weight obtained from node centrality. Realistic traces based simulations show that our scheme IFR is efficient in improving the message delivery performance on the tradeoff between the delivery success ratio and total delivery cost.

In order to provide communication service in the Intermittently Connected Mobile Networks (ICMN) where there is only intermittent connectivity between mobile nodes, a variety of epidemic-style routing algorithms have been proposed to achieve high message delivery probability. However, current works do not address the realistic environment that a message is split into multi frames to be transmitted. In this paper, we investigate the problem of optimal multi-frame message transmission for the ICMN. First, we formulate the optimization problem by introducing a continuous time Markov framework. Then, we theoretically derive the optimal policies for the message transmission by solving the formulated problem. Finally, we investigate the performance of the proposed optimal policies through extensive numerical results. We conclude that our optimal policies give the best performance in the multi-frame message transmission.

Running multiple virtual networks over a shared physical network is a promising way to support diverse applications, consequently network virtualization is viewed as the keystone of the next-generation architecture. However, decoupling the role of traditional ISPs into Infrastructure Providers (InPs) and Service Providers (SPs), also brings some new challenges to us. For example, how to fairly and efficiently share the sacred physical resources of InPs among multiple SPs is a key problem. The interaction between InPs and SPs, such as cooperation and competition, makes this topic even more complicated. In this paper, we develop a novel approach to encourage efficient behavior in solving the interaction between InPs and SPs by introducing economic incentives, in the form of Game Theory. Based on the non-cooperative game model, a bandwidth allocation scheme in the network virtualization environment is established, using the concept of the Nash Equilibrium. Then we propose an iterative algorithm to find the Nash Equilibrium and solve the bandwidth allocation problem. Finally, we demonstrate the convergence and the effectiveness of our scheme in the experiments.

Tracking constitutes a major challenge in Ultra-Wideband (UWB)communications due to dense multipath environment and low power consumption. Most of the existing studies on tracking fall within low rate Impulse Radio UWB (IR-UWB) scope, with the assumption that Inter-Frame Interference (IFI) or Inter-Symbol Interference (ISI) is absent. In this paper, we settle on high rate Direct-Sequence UWB (DS-UWB) systems, in which ISI is inevitable. A Periodical-Pilot-Assisted Tracking Loop with RAKE combining, which we termed PPATL, is proposed for high rate DS-UWB scenario. The proposed tracking loop can effectively combat ISI and capture multipath energy. Analytical expressions of Probability Density Function (PDF) of timing error in locked state, Mean Square Error (MSE, or termed timing jitter) and Mean Time to Lose Lock (MTLL) are derived. Numerical results are presented and then confirmed by means of extensive computer simulation results. These results corroborate our theoretical analysis. Additionally, this proposed PPATL has been used and justified in our realistic DS-UWB system.

Due to the uncertainty of transmission opportunities between mobile nodes, Delay Tolerant Networks (DTN) routing exploits the opportunistic forwarding mechanism. Optimal policies for opportunistic forwarding are crucial to maximizing the message delivery probability while reducing the forwarding cost. In this paper, we investigate the optimal opportunistic forwarding policies for the energy- constrained DTN by introducing a continuous time Markov framework to model the message dissemination. Based on this framework, we obtain the optimal static and dynamic policies by theoretical analysis and proof. Through extensive numerical results, we conclude that the performance of the optimal dynamic policy is better than that of the static policy. Among the dynamic policies, we find that the negative power function based optimal policy provides the best performance.

Many acquisition schemes have been proposed and investigated for Ultra-Wideband (UWB) systems, however, most of them setup for low duty-cycle Impulse Radio UWB (IR-UWB) signals, with the assumption that the pulse repetition time is greater than the maximum excess delay of channels, so that intra- and inter-frame interference can be bypassed. This assumption limits the transmission rate and cannot hold in high-rate Direct-Sequence UWB (DS-UWB) systems. In this paper, we propose a two-step data-aided acquisition scheme for high-rate DS-UWB systems. The first step is to quickly acquire an arbitrary train sequence; a two-stage correlation architecture is employed to combat Inter-Symbol Interference (ISI) and collect multipath energy, so as to speed up acquisition. Correspondingly, the second step is to search for the first arriving path with a maximum gap based search method (also new proposed), so as to improve Bit Error Rate (BER) performance. Closed-form expressions of Mean Acquisition Time (MAT), Overall Acquisition Probability (OAP) and False Alarm Rate (FAR) are derived. Based on them, parameter selections that minimize MAT and maximize OAP are discussed under certain FAR constrain. Simulations corroborate our theoretical results.

Resilience issue in Ethernet is becoming even more important when Ethernet is becoming more pervasive. The authors propose a local recovery scheme, named Ethernet ultra-fast switching (EUFS), to address this issue. EUFS is based on the multiple spanning tree protocol, which is the basics of both load balancing and fast recovery mechanisms in large-scale Ethernet networks. For each node, the authors construct a pair of protection trees rooted at this node. Normally, the traffic is forwarded along the working trees. When a link or node fails, the immediate upstream node switches the traffic, which intends to pass through the failed link or node, from the working trees to one of the protection trees rooted at itself. EUFS has the following features. First, it achieves an ultra-fast recovery from any single failure in two-connected networks. Second, it supports backward compatibility, because switches implementing EUFS can inter-operate with the legacy Ethernet switches.

Proxy mobile IPv6 (PMIPv6), a network-based IP mobility solution, is a promising approach for mobility management in all-IP wireless networks. How to enhance its handoff-related performance, such as handoff delay and signaling cost, is an important issue. Current solutions rely on approaches such as fast handoff, routing optimization and paging extension. However, the case of many correlated mobile nodes (MNs) moving together and taking handoffs at the same time has not been considered. In this paper, we propose a group-based handoff scheme for correlated MNs to enhance the performance of PMIPv6. We first propose a correlated MNs detection algorithm to detect MNs as groups. Based on this algorithm, we propose a group-based handoff procedure, and discuss its benefits and limitations. Furthermore, we evaluate the performance of PMIPv6 and our proposal through the analysis and simulation. The results show that the proposed scheme is very efficient in reducing both the handoff delay and signaling cost.

Delay Tolerant Networks (DTNs) are able to provide communication services in challenged networks where the end-to-end path between the source and destination does not exist. In order to increase the probability of delivery, DTN routing mechanisms may require nodes in the network to store and carry messages in their local buffer and replicate many copies. When the limited buffer is consumed, choosing the appropriate messages to drop is critical to maximizing the system performance. Current methods for this are sub-optimal or assume unrealistic conditions. In this paper, we propose an adaptive optimal buffer management scheme for DTN in the situations where the bandwidth is limited and messages vary in size. In our proposal, the mobility model is adjusted according to the nodes' historical meeting information, and the message dropping policies are designed to optimize certain network performance goals, such as maximizing the average delivery rate or minimizing the average delivery delay. Furthermore, we theoretically prove that the designed message dropping policies are optimal to achieve the best system performance.

Network-on-Chip (NoC) design methodology is considered as an important trend for large System-on-Chip design because of the bandwidth and power constraints in traditional synchronous bus architecture. In the design of packet-based NoC, packetizing mechanism has great effect on communication performance, area, and energy consumption of NoC. In this paper, we carry out detailed simulation to evaluate several kinds of packetizing mechanisms of NoC based on topology of Ring and Spidergon. Simulation results show that Condition-Waiting adaptive packetizing mechanism (CW-APM) is the best trade-off packetizing mechanism in NoC design.

Proxy Mobile IPv6 (PMIPv6), a network-based local mobility management solution, is being actively discussed and standardized by IETF recently. Compared with the host-based mobility protocols such as mobile IPv6, PMIPv6 separates mobile node from the involvement of handover procedure and promises easier deployment and better handover performance. The system performance analysis of PMIPv6 is significant to its design and deployment. However, current related work is either restricted to a single performance metric or not considered in a realistic network environment. In this paper, we propose an analytical framework based on IP-based cellular networks. Based on the framework, we investigate the performance of PMIPv6 with respect to various metrics, including signaling cost, handover delay and packet loss, and compare it with host-based mobility management protocols, such as Mobile IPv6, FMIPv6 and HMIPv6. The simulation results demonstrate the salient performance of PMIPv6.

Proxy mobile IPv6 (PMIPv6) is being actively standardized by IETF, and its salient features, such as supporting unmodified mobile node (MN), expedite the real deployment of IP mobility management. However, current research and development mainly focus on its unicast mechanism. In this paper, we propose two multicast listener mobility mechanisms for PMIPv6, named LMA-MLM and MAG-MLM, by drawing a lesson from the designing of Mobile IP (MIP) based multicast solutions. Moreover, we present qualitative and quantitative comparison between MlP-based solutions and our proposals. Although the research of PMIPv6-based multicast mobility is at an early stage yet, it is strongly expected to be a promising candidate solution for multicast mobility in the wireless mobile IP networks.

The accuracy of interconnect delay estimations can be improved by the method presented in this paper, in which the first two moments are obtained with ABCD matrix and a stable model to incorporate effects of transport delay into the delay estimate is developed. Simulation results show that the method share the same accuracy with traditional methods when rise time delay is much longer than transport delay and more accurate when the two are of the same order.

In this paper, a hierarchical cluster-based irregular topology customization method is proposed for Networks-on-Chip (NoC). This method contains three steps: (1) partitioning IPs into many hierarchical clusters; (2) generating a core network; (3) deleting redundant edge routers. Results show that the irregular topologies generated by our hierarchical cluster-based method consume less power when satisfying the bandwidth and port number constraints. Compared with the previous method, our method can save about 15.41% of power averagely for all benchmark applications. Particularly, for MPEG 4 decoder, our method can save 31.62% of power.