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Mobile ad-hoc cloud can exploit the computing resources (e.g., smartphones, vehicles, and unmanned systems) scattered in the mobile environment to form a self-organized ad-hoc local resource pool for providing opportunistic computing services. However, the highly dynamic and distributed characteristics of the mobile ad-hoc network environment bring great challenges in privacy and security in such opportunistic resource sharing. In this article, we first discuss the attractive features of blockchain for providing such resource sharing services in the mobile ad-hoc network environment in a secure and trustful way and then discuss the problems caused when using existing consensus protocols in such an environment. We accordingly devise a blockchain based trustful mobile ad-hoc cloud architecture, AdChain cloud. We describe the functions at different layers in this architecture, including the network layer, blockchain layer, and smart contract layer. To adapt to the high dynamics of the mobile ad-hoc network environment, we design a stability-aware consensus protocol at the blockchain layer. Simulation results show that our solution can achieve improved performance as compared with existing work.

The use of alkali-activated slag (AAS), an eco-friendly cementitious material, to replace ordinary Portland cement in construction can reduce the energy consumption, CO2 emissions, and solid dust pollution and promote the recycling of ground granulated blast furnace slag, which represents an industrial solid waste. However, the creep of AAS concrete is a critical long-term property that has rarely been investigated. Creep is related to the structural safety, including that of large pre-stressed concrete structures. AAS concrete exhibits a higher creep and lower elasticity modulus compared to OPC concrete, and the addition of fibres is an effective solution to this problem. In this study, the effects of fibre dosage and stress-strength ratio on the creep properties of polypropylene (PP) fibre-reinforced AAS (FRAAS) concrete were investigated. Thirty-two creep samples with four fibre dosages and four stress–strength ratios were subjected to tests for approximately 350 d. The PP FRAAS concrete did not exhibit any significant linear creep behaviour. With the increase of fibre dosage, the inhibition effect of fibres first became stronger and then became weaker. The inhibition effect of the fibres was gradually intensified with the increasing stress–strength ratio. As the fibre dosage increased from 0 to 0.9%, the creep coefficient gradually decreased. Based on the experimental results, a method of predicting the creep of PP FRAAS concrete was developed.

The shear, flexural and axial tensile bond strengths of alkali-activated slag concrete hollow block (AASCHB) masonry layered with alkali-activated slag (AAS) mortar were investigated in this study. A comprehensive experimental investigation was conducted to assess the effect of the AAS mortar strength on the bond characteristics of the masonry. The bond strength of the AASCHB masonry was found to be directly related to the compressive strength of the AAS mortar, where higher compressive strength led to higher bond strength. In addition, new expressions for the bond strength were developed for AASCHB masonry based on the compressive strength of AAS mortar.

Recently, alkali-activated slag mortars have attracted considerable attention as environmentally friendly materials. The objective of this paper was to explore the influence of an alkaline activator (NaOH or NaOH/Na2CO3 solutions) on the performance of alkali-activated slag (AAS) mortars with pottery sand as fine aggregate. Five Na2CO3-to-NaOH ratios of 0/100, 20/80, 40/60, 60/40, and 80/20, and three Na2O contents of 4%, 6%, and 8%, were used to prepare AAS mortars. The water-to-slag ratio and slag-to-aggregate ratio were kept constant, at 0.38 and 0.8, respectively. The setting time, fluidity, compressive strength, and drying shrinkage were measured. The reaction hydrates were analyzed using microscopy and elemental analysis, while the pore structures were characterized using mercury intrusion porosimetry. The experimental results showed that both the Na2CO3-to-NaOH ratio and Na2O content had a significant effect on the fresh and hardened properties of AAS mortars. A high Na2CO3-to-NaOH ratio and low Na2O content resulted in AAS mortars with longer initial and final setting times. The higher Na2CO3-to-NaOH ratios led to a higher late compressive strength of AAS mortars, where the 6% Na2O samples showed the best performance with Na2O contents of 4–8%. In addition, the drying shrinkage behavior of AAS mortars as a function of Na2CO3-to-NaOH ratio was dependent on the Na2O content. Moreover, the compressive strength and drying shrinkage have a direct relationship with the microstructure of AAS mortars.

This study focused on the engineering properties of alkali-activated slag (AAS) pastes prepared by mixing an activator consisting of sodium silicate and sodium hydroxide at room temperature. The water-to-slag ratio of AAS paste was kept constant at 0.35 by mass. AAS pastes were prepared using the activator with five different silicate moduli of 1, 1.2, 1.4, 1.6, and 1.8 and three different Na2O contents of 6%, 8%, and 10%. The results showed that both the silicate moduli and Na2O contents had significant effects on the engineering properties of AAS pastes. All the AAS pastes exhibited properties such as fast setting, good workability, and high early compressive strength. The final setting time varied from 9 to 36 min, and the fluidity was in the range of 147–226 mm. The 1 d compressive strength of all the AAS pastes, which could be easily achieved, had values above 55 MPa, whereas the highest strength obtained was 102 MPa with the silicate modulus of 1 and Na2O content of 8% at room temperature. The drying shrinkage increased as the silicate modulus increased. Furthermore, the hydration products and microstructures of AAS pastes were explained according to the microanalysis methods.

This study investigated the properties of alkali-activated slag (AAS) pastes with NaOH and a blend of NaOH and Na2CO3 as the alkaline activator. The effects of five different Na2CO3 to NaOH molar ratios (0:10, 0.9:10, 2.5:10, 5.7:10 and 15:10) and three different Na2O contents (4%, 6% and 8%) in the alkaline activator on the setting time, mechanical performance and drying shrinkage were tested. The water to slag ratio was 0.35 by weight. The results showed that both the Na2CO3 to NaOH molar ratios and Na2O contents are major factors influencing the fresh and hardened pastes. Higher Na2CO3 to NaOH molar ratios yielded a longer setting time and higher compressive strength. The Na2O content of 6% was more sensitive to the properties compared with 4% and 8% Na2O. When the Na2O content was 4%, the drying shrinkage increased as the Na2CO3 to NaOH molar ratio increased; however, when the Na2O content increased to 6% and 8%, the drying shrinkage decreased as the Na2CO3 to NaOH molar ratio increased. The main hydration products were C-S-H(I), hydrotalcite, calcite and gaylussite. There was a strong relationship between the drying shrinkage and pore structures of AAS. Consequently, the Na2CO3 to NaOH molar ratio of 15:10 and Na2O content of 6% can be regarded as the optimum mix proportion.

Cache-enabled device-to-device (D2D) communication has emerged as a promising paradigm for caching popular contents at user devices and using D2D communication among adjacent users to relieve cellular traffic overload. To maximize traffic offloading, optimal content-selection for caching and helper-receiver matching are two key concerns. In this paper, we deal with the two key issues by leveraging user characteristics, which are crucial to D2D content sharing but often omitted by existing work in this field. We first propose a comprehensive model that profiles user characteristics including user preference, user activity degree, and user relationship. To provide an accurate estimation of user relationship, a new metric named expected correlation coefficient (ECC) is further proposed, which can reveal the potential offloading opportunities behind the contacts between users. We then design a novel user-centric caching policy that integrates the above-mentioned models into content caching policy to optimize the caching efficiency. Furthermore, we propose an online learning algorithm by leveraging the Combinatorial Multi-Armed Bandits (CMAB) method to achieve efficient helper-receiver matching among users. Experiments based on real-world traces and content requesting records were conducted. The results demonstrate that when compared with existing algorithms, our proposed algorithm improves the offloading ratio by nearly 10% and the system utility approximately by 20%.

This study focused on the effects of curing conditions (standard and steam curing) on the freeze–thaw resistance of geopolymer mortars containing Class C fly ash, Class F fly ash, slag, and Ca(OH)2. Geopolymer mortar specimens were prepared with water-to-Class C fly ash ratios of 0.35 and 0.40, and CaO contents of 45% and 100% with different compositions. The specimens were subjected to freeze–thaw cycles until the mass loss exceeded 5% or the relative dynamic elastic modulus was below 60%. The reaction hydrates and pore structures were analyzed using scanning electron microscopy with energy-dispersive spectrometry and mercury intrusion porosimetry, respectively. In terms of mechanical performance, steam curing condition was better than standard curing condition for the early-age strength of geopolymer mortars. The compressive strength of the geopolymer mortars at 2 d and 28 d was increased 2.2–5.1 times and 0%-40%, respectively, under steam curing condition compared with standard curing condition. The experimental results indicated that Class C fly ash geopolymer mortar (CF35) under steam curing condition and Class F fly ash-slag geopolymer mortar with 100% CaO content (SF35C100) under standard curing condition exhibited remarkable freeze–thaw resistance with a freeze–thaw resistance grade of F300 at the lowest. Moreover, the water-to-ash ratio was critical for the freeze–thaw resistance under both standard and steam-curing conditions. The mass loss of specimens with water-to-ash ratios of 0.35 and 0.40 under standard curing condition were 4.67% and 8.79%, respectively, at 25 freeze–thaw cycles, whereas that of specimens with water-to-ash of 0.35 under steam curing condition was 3.03% at 300 freeze–thaw cycles. In addition, the freeze–thaw resistance of geopolymer specimens with different compositions had a direct relationship with the microstructure of the geopolymer mortars. Furthermore, the experimental results verified that a higher compressive strength did not necessarily indicate a better freeze–thaw resistance.

Viral attachment to specific host receptors is the first step in viral infection and serves an essential function in the selection of target cells. In this study, structure analysis, neutralization assays, and cell attachment assays were carried out to evaluate the cell attachment functions of the outer capsid fiber protein of grass carp reovirus GD108 strain (GCRV-GD108). The GCRV-GD108 fiber protein contained 512 amino acids encoded by S7 segment and shared sequence similarities with mammalian reovirus cell attachment protein σ1 and adenovirus fiber. Structural analyses predicted the presence of a coiled-coil tail domain, three adenoviral shafts in the body domain, and a globular head domain, similar to other fiber proteins. Neutralization assays showed that polyclonal antibodies against the fiber protein could prevent viral infection in both fish and grass carp snout fibroblast cells (PSF), suggesting that the recombinant fiber protein could induce neutralized antibodies against GCRV-GD108. Cell attachment assays showed that recombinant fiber protein could bind to PSF cells, demonstrating that the fiber protein functioned as the cell attachment protein in GCRV-GD108. These results provided the basis for further studies of the pathogenesis of grass carp reovirus.

Small RNAs (sRNAs) are short noncoding RNAs that play roles in many biological processes, including drought responses in plants. However, how the expression of sRNAs dynamically changes with the gradual imposition of drought stress in plants is largely unknown. We generated time-series sRNA sequence data from maize ( L.) seedlings under drought stress (DS) and under well-watered (WW) conditions at the same time points. Analyses of length, functional annotation, and abundance of 736,372 nonredundant sRNAs from both DS and WW data, as well as genome copy numbers at the corresponding genomic regions, revealed distinct patterns of abundance and genome organization for different sRNA classes. The analysis identified 6646 sRNAs whose regulation was altered in response to drought stress. Among drought-responsive sRNAs, 1325 showed transient downregulation by the seventh day, coinciding with visible symptoms of drought stress. The profiles revealed drought-responsive microRNAs, as well as other sRNAs that originated from ribosomal RNAs (rRNAs), splicing small nuclear RNAs, and small nucleolar RNAs (snoRNA). Expression profiles of their sRNA derivers indicated that snoRNAs might play a regulatory role through regulating the stability of rRNAs and splicing small nuclear RNAs under drought condition.

Mobile Crowdsensing (MCS) has become an emerging paradigm to solve complex urban sensing problems by utilizing the ubiquitous sensing capacities of the crowd. One critical issue in MCS is to efficiently allocate tasks to users. We focus on addressing the task allocation problem in a distributed manner, where each user individually and freely makes his decision to undertake tasks. Existing distributed schemes simply consider users behave completely selfishly, which leads to inefficient solutions and damages the overall benefit of all users. Different from existing schemes, in this paper we integrate the social relationship into users' decision making and build a socially aware utility model for each user, which consists of both user's own utility and the weighted sum of his social neighbors' utilities. Based on this, we formulate a novel Socially Aware Task Selection (SATS) game for users in MCS. We theoretically prove the existence of pure Nash equilibrium in the SATS game with the help of a potential game framework. We further propose a distributed user selection algorithm to actually achieve the pure Nash equilibrium. Extensive simulations based on both real and synthetic social relationship graph datasets demonstrate that our approach can achieve more efficient solutions which improve users' overall benefit compared with existing schemes.

Alkali-activated materials have received considerable attention in regarding their use as environmentally sustainable alternatives to Portland cement. However, the brittleness and shrinkage cracking of these materials have hindered their wider application. An effective solution to these problems is adding fibre to the concrete. This study investigated the mechanical properties of basalt and PP fibre-reinforced alkali-activated slag (AAS) concrete. A total of 11 mixture groups with different fibre dosages and lengths were created, and 132 samples were subjected to cube compressive, prism compressive, splitting tensile, and flexural strength tests. The influence of the fibre dosage and length on the mechanical properties was determined. Owing to the different strength calculation formulas and large shrinkage of the AAS material, significant differences are observed when the tensile strength of AAS concrete is characterized analysed through splitting tensile and flexural strength tests. For the same fibre length and dosage, PP fibre did not improve the strength of AAS concrete as effectively as basalt fibre did. According to the experimental results, a mathematical method was proposed to determine an optimal solution to the bivariate problem.

Topology control is an efficient strategy for improving the performance of wireless ad hoc and sensor networks by building network topologies with desirable features. In this process, location information of nodes can be used to improve the performance of a topology control algorithm and also ease its operations. Many location-based topology control algorithms have been proposed. In this paper, we propose two location-assisted grid-based topology control GBP algorithms. The design objective of our algorithm is to effectively reduce the number of active nodes required to keep global network connectivity. In grid-based topology control, a network is divided into equally spaced squares called grids. We accordingly design cross-sectional topology control algorithm and diagonal topology control algorithm based on different network parameter settings. The key idea is to build near-minimal connected dominating set for the network at the grid level. Analytical and simulation results demonstrate that our designed algorithms outperform existing work. Furthermore, the diagonal algorithm outperforms the cross-sectional algorithm. Copyright © 2016 John Wiley & Sons, Ltd.

Backpressure-based routing and scheduling has been considered as a promising strategy for efficient resource allocation in wireless multihop networks. It has many attractive features such as throughput optimality, achievable adaptive resource allocation, support for agile load-aware routing, and simplicity. In this article, we first categorize existing backpressure-based protocols based on different design criteria and then summarize several key issues faced in the design of efficient backpressure-based protocols. We present a comprehensive survey of state-of-theart backpressure-based protocols for wireless multihop networks. We illustrate how each of the protocols works, and discuss their merits and deficiencies. Finally, we point out some future directions for supporting efficient backpressure- based routing and scheduling.

In this paper, a parametric experimental study developing the alkali-activated slag concrete hollow block (AASCHB) is discussed. Fourteen trial mixes of alkali-activated slag concrete containing pottery sand and ceramsite with different water-to-slag ratios, sand ratios, silicate moduli, and Na2O contents were evaluated to determine the optimal mix for high compressive strength and low drying shrinkage. All four factors evaluated were found to be significant for the desired properties. A series of 390 &times, 190 &times, 190 mm3 AASCHBs were prepared using the optimal mix with a water-to-slag ratio of 0.35, sand ratio of 0.64, silicate modulus of 1.2, and Na2O content of 8%. The compressive strength, flexural strength, water absorption, and moisture content tests of these blocks indicate that the resulting AASCHB can be classified under the strength grade of MU15 as a load-bearing hollow concrete block. The proposed AASCHBs appear to provide a viable solution to the environmental problems of industrial waste and cement production emissions, leading to more sustainable buildings without compromising structural performance.

UAV networks often partition into separated clusters due to the high node and link dynamic. As a result, network connectivity recovery is an important issue in this area. Existing solutions always need excessive movement of nodes and thus lead to low recovery efficiency in terms of the time and energy consumption. In this paper, we for the first time study the issue of how to utilize cooperative communication technology to improve the connectivity recovery efficiency in UAV networks. We propose a Cooperative Communication based Connectivity Recovery algorithm for UAV Networks, named C3RUN. The key novelty is C3RUN not only uses cooperative communication to enlarge node's communication range and thus achieve quick repair of network connectivity, but also enables nodes to proactively move to better places for ensuring the establishment of cooperative communication links. We conduct extensive simulations to evaluate the performance of C3RUN. The simulation results reveal that C3RUN can not only achieve connectivity recovery with less nodes and shorter distance to move, but also always finish recovery with less time, when comparing with existing work. Furthermore, C3RUN can achieve 100% success ratio for connectivity recovery.

Small RNAs (sRNAs) are short noncoding RNAs that play roles in many biological processes, including drought responses in plants. However, how the expression of sRNAs dynamically changes with the gradual imposition of drought stress in plants is largely unknown. We generated time-series sRNA sequence data from maize seedlings under drought stress and under well-watered conditions at the same time points. Analyses of length, functional annotation, and abundance of 736,372 non-redundant sRNAs from both drought and well-watered data, as well as genome copy number and chromatin modifications at the corresponding genomic regions, revealed distinct patterns of abundance, genome organization, and chromatin modifications for different sRNA classes of sRNAs. The analysis identified 6,646 sRNAs whose regulation was altered in response to drought stress. Among drought-responsive sRNAs, 1,325 showed transient down-regulation by the seventh day, coinciding with visible symptoms of drought stress. The profiles revealed drought-responsive microRNAs, as well as other sRNAs that originated from ribosomal RNAs (rRNAs), splicing small nuclear RNAs, and small nucleolar RNAs (snoRNA). Expression profiles of their sRNA derivers indicated that snoRNAs might play a regulatory role through regulating stability of rRNAs and splicing small nuclear RNAs under drought condition.

Sample scheduling is a crucial issue in wireless sensor networks (WSNs). The design objectives of efficient sample scheduling are in general two-folds: to achieve a low sample rate and also high sensing quality. Recently, compressive sensing (CS) has been regarded as an effective paradigm for achieving high sensing quality at a low sample rate. However, most existing work in the area of CS for WSNs use fixed sample rates, which may make sensor nodes in a WSN unable to capture significant changes of target phenomenon, unless the sample rate is sufficiently high, and thus degrades the sensing quality. In this paper, to pursue high sensing quality at low sample rate, we propose an adaptive CS based sample scheduling mechanism (ACS) for WSNs. ACS estimates the minimum required sample rate subject to given sensing quality on a per-sampling-window basis and accordingly adjusts sensors' sample rates. ACS can be useful in many applications such as environment monitoring, and spectrum sensing in cognitive sensor networks. Extensive trace-driven experiments are conducted and the numerical results show that ACS can obtain high sensing quality at low sample rate.

Data collection is key issue in vehicular networks since it is vital for supporting many applications in vehicular environments. With the explosive growth of sensing data in urban area, however, strategies for efficient collection of big data in vehicular networks are still far from being well studied. In this paper, we focus on studying this issue and accordingly propose a Software Defined Vehicular Networks (SDVN) architecture. On this architecture, a predictive data collection algorithm is proposed. In this algorithm, packet delivery is fulfilled by cooperative cellular and ad hoc network interfaces, in which collections of big data always adopts ad hoc based multi-hop relaying whenever applicable to forward packets to Road Side Units (RSUs). Cellular networks are used for data uploading only when no multi-hop relaying opportunity is available. Our proposed SDVN architecture enables such efficient cooperative communications, in which predictive routing decisions are made based on real-time network status other than empirical knowledge. Simulation results demonstrate that our algorithm outperforms existing algorithms in terms of packet delivery ratio and transmit efficiency.

In plants, calcineurin B-like proteins (CBLs) play crucial roles in regulating calcium-signaling in response to various abiotic stresses by interacting with specific CBL-interacting protein kinases (CIPKs). However, the identities and functions of CBL gene family members in maize are largely unknown. Here, we identified from the maize genome 12 CBL genes. All 12 CBLs have conserved EF-hand domains, and half harbor myristoylation motifs. We further characterized the function of one CBL gene, ZmCBL9, which can be induced by salt, dehydration, glucose and abscisic acid (ABA) treatments. Overexpression of ZmCBL9 enhanced resistance or tolerance to ABA, glucose, salt and osmotic stress in Arabidopsis and complemented the hypersensitive phenotype of the Arabidopsis cbl9 mutant in response to ABA and abiotic stress. The ZmCBL9 gene negatively regulates the expression of genes in the ABA signaling, biosynthesis and catabolism pathways. Moreover, the ZmCBL9 protein is found to interact with eight maize CIPKs and these ZmCIPK genes were up-regulated by different stress treatments, including salt, dehydration, glucose, low potassium and ABA. These results suggest that ZmCBL9 may interact with various ZmCIPKs to regulate the abiotic stress and ABA response signaling in plants.

Backpressure based scheduling has been considered as a promising technique for improving the throughput of a wide range of communication networks. However, this scheduling technique has not been well studied for heterogeneous wireless networks. In this paper, we propose a virtual-queue based backpressure scheduling (VQB) algorithm for heterogeneous multi-hop wireless networks. The VQB algorithm introduces a simple virtual queue for each flow at a node for backpressure scheduling, whose length depends on the cache size of the node. When calculating flow weights and making scheduling decisions, the length of a virtual queue is used instead of the length of a real queue. We theoretically prove that VQB is throughput-optimal. Simulation results show that the VQB algorithm significantly outperforms a classical backpressure scheduling algorithm in heterogeneous multi-hop wireless networks in terms of the packet delivery ratio, packet delivery time, and average sum of the queue lengths of all nodes per timeslot.

Much previous work had demonstrated the remarkable performance of backpressure based routing and scheduling algorithms in wireless sensor networks (WSNs). However, the absence of consideration on energy use efficiency in the design of existing backpressure based algorithms makes them difficult to be deployed in resource-limited WSNs. In this paper, we study how to improve the energy use efficiency of backpressure based algorithm. For this purpose, we propose an energy efficient backpressure routing and scheduling algorithm (EBP) for WSNs. In EBP, a new link weight calculation method is designed, based on which nodal energy status is considered when making decisions on backpressure based transmission scheduling. In EBP, packets are encouraged to be forwarded to nodes with more residual energy while the throughput-optimality of backpressure based algorithm is still preserved. Simulation results show that EBP can obtain significant performance improvements in terms of energy use efficiency, network throughput, and packet delivery ratio as compared with existing work.

In this paper, we study how to effectively reduce the average end-to-end (E2E) packet delay in backpressure based scheduling in wireless multi-hop networks. We accordingly propose a virtual gradient based back-pressure scheduling algorithm, referred to as VBR. In VBR, intentional virtual queue, whose length (called virtual gradient) depends on the distance to destination, is first built at nodes in a network in the network configuration phase. In this way, virtual gradient is established at nodes in the network. In the network operation phase, the scheduling decision at each node needs to jointly consider both real queue length and virtual queue length. Simulation results show that VBR can obtain significant performance improvement on back-pressure based routing and scheduling, in terms of packet delivery ratio and average E2E delay.

In this paper, we design a new virtual queue-based back-pressure scheduling algorithm (VBR) for achieving significant delay reduction in wireless sensor networks (WSN). Our algorithm design comes from an observation that classical back-pressure scheduling algorithm usually needs a long period of time to form a queue backlog-based gradient in a network, which decreases towards the sink in the network, before achieving stable packet delivery performance. To address this issue, VBR is designed to pre-build proper virtual queue-based gradient at nodes in a WSN, which is chosen to be a function of traffic arrival rate, link rate, and distance to sink, in order to be adaptive to different network and application environments while achieving high network performance. Moreover, the queue backlog differential between each pair of neighbor nodes is decided by their actual queue lengths and also their virtual queue lengths (gradient values). We prove that VBR can maintain back-pressure scheduling’s throughput optimality. Simulation result shows that VBR can obtain significant performance improvement in terms of packet delivery ratio, average end-to-end delay, and average queue length as compared with existing work.

Backpressure based scheduling has revealed remarkable performance in wireless multihop networks as reported in a lot of previous work. However, its lack of consideration on energy use efficiency is still an obstacle for backpressure based algorithms to be deployed in resource-constrained wireless sensor networks (WSNs). In this paper, we focus on studying the design of energy efficient backpressure based algorithm. For this purpose, we propose a gradient-assisted energy-efficient backpressure scheduling algorithm (GRAPE) for WSNs. GRAPE introduces a new link-weight calculation method, based on which gradient information and nodal residual energy are taken into account when making decisions on backpressure based transmission scheduling. According to the decisions made by this new method, packets are encouraged to be forwarded to nodes with more residual energy. We theoretically prove the throughput-optimality of GRAPE. Simulation results demonstrate that GRAPE can achieve significant performance improvements in terms of energy use efficiency, network throughput, and packet delivery ratio as compared with existing work.

Positioning technique has become an indispensable part of our daily lives. Compared with the well-solved positioning issue in outdoor areas, indoor positioning is still far from being well explored, and existing techniques in this area are still far from being sufficiently mature to be widely used in practice. Recently, visible light communication based indoor positioning, also referred to as visible light based positioning, has attracted great attention and much work has been carried out, which reveals remarkable positioning accuracy. In this article, we provide a comprehensive survey of visible light based positioning. We first introduce some fundamental issues in visible light based positioning and further categorize existing systems in this field according to different design criteria. We then give a comprehensive survey of state-of-the-art systems, and introduce how each of the systems works and discuss their merits and deficiencies. Finally, we discuss challenging issues in this area and also point out future directions.

Summary Back-pressure scheduling has been considered as a promising strategy for resource allocation in wireless multi-hop networks. However, there still exist some problems preventing its wide deployment in practice. One of the problems is its poor end-to-end (E2E) delay performance. In this paper, we study how to effectively use inter-flow network coding to improve E2E delay and also throughput performance of back-pressure scheduling. For this purpose, we propose an efficient network coding based back-pressure algorithm (NBP), and accordingly design detailed procedure regarding how to consider coding gain in back-pressure based weight calculation and how to integrate it into next hop decision making in the NBP algorithm. We theoretically prove that NBP can stabilize the networks. Simulation results demonstrate that NBP can not only improve the delay performance of back-pressure algorithm, but also achieve higher network throughput. Copyright © 2016 John Wiley & Sons, Ltd.