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OS-level virtualization is often used for server consolidation in data centers because of its high efficiency. However, the sharing of storage stack services among the colocated containers incurs contention on shared kernel data structures and locks within I/O stack, leading to severe performance degradation on manycore platforms incorporating fast storage technologies (e.g., SSDs based on nonvolatile memories). This article presents MultiLanes, a virtualized storage system for OS-level virtualization on manycores. MultiLanes builds an isolated I/O stack on top of a virtualized storage device for each container to eliminate contention on kernel data structures and locks between them, thus scaling them to manycores. Meanwhile, we propose a set of techniques to tune the overhead induced by storage-device virtualization to be negligible, and to scale the virtualized devices to manycores on the host, which itself scales poorly. To reduce the contention within each single container, we further propose SFS, which runs multiple file-system instances through the proposed virtualized storage devices, distributes all files under each directory among the underlying file-system instances, then stacks a unified namespace on top of them. The evaluation of our prototype system built for Linux container (LXC) on a 32-core machine with both a RAM disk and a modern flash-based SSD demonstrates that MultiLanes scales much better than Linux in micro- and macro-benchmarks, bringing significant performance improvements, and that MultiLanes with SFS can further reduce the contention within each single container.

Co3O4/N-doped graphene is synthesized with a one-pot and low-cost thermal decomposition in air. N-doped graphene improves their reductivity and their low-temperature catalytic performance of CO oxidation. After the treatment with dry reaction gases, the treated composites show the changed chemical structure of nitrogen species from N (C)3 structure to C N C structure. After the treatment with wet reaction gases, nitrogen species on N-doped graphene are decomposed and the anchored sites of Co3O4 nanoparticles are converted into oxygenated groups. The nitrogen sites of N (C)3 structure are beneficial to promote the reversible conversion between the reduced Co2+ ions and active Co3+ ions on Co3O4 nanoparticles at low temperature, but Co3+ ions can irreversibly be converted into the reduced Co2+ ions on Co3O4 nanoparticles anchored at the nitrogen sites of C N C structure and it is more difficult to reduce Co3O4 nanoparticles anchored at oxygenated groups from the converted nitrogen species. Since CO oxidation is promoted by the reversible conversion between Co2+ ions and Co3+ ions on Co3O4 nanoparticles, Co3O4/N-doped graphene has low-temperature catalytic activity, but the composites treated with dry reaction gases require higher temperature to show catalytic activity and the composites treated with wet reaction gases show lower catalytic performance.

Surface structures of one-dimensional CeO2 nanocrystals are tuned with different cationic ions in a facile and mild hydrothermal system with formate and carbonate. The synthetic key is to control the formation of anisotropic CeO2 precursors with the anion structure of formate and carbonate. The diluted concentration of Na+ ions with NH4+ ions can induce the formation of the CeO2 nanotube (NT) precursors, and yet Na+ ions can promote the production of the CeO2 nanorod (NR) precursors. CeO2 nanocrystals are applied in CO oxidation and show a very important effect of their surface structure on their catalytic performance. CeO2 NTs have rich cerium surface with the higher concentration of Ce3+ ions and can accelerate the mobility of more surface oxygen species than CeO2 NRs with difficultly reduced rich oxygen surface. However, after silver loading, CeO2 NRs can show the higher stability of CeO2 particles, more easily activated surface of CeO2 NRs with more Ce3+ ions, the promoted production of metallic Ag nanoparticles and higher mobility of more surface oxygen species on CeO2 surface. Therefore, CeO2 NTs have a higher catalytic activity of CO oxidation and conversely, after loading Ag, Ag/CeO2 NRs show the higher catalytic performance.

A long-standing challenge in cluster scheduling is to achieve a high degree of utilization of heterogeneous resources in a cluster. In practice there exists a substantial disparity between perceived and actual resource utilization. A scheduler might regard a cluster as fully utilized if a large resource request queue is present, but the actual resource utilization of the cluster can be in fact very low. This disparity results in the formation of idle resources, leading to inefficient resource usage and incurring high operational costs and an inability to provision services. In this paper we present a new cluster scheduling system, ROSE, that is based on a multi-layered scheduling architecture with an ability to over-subscribe idle resources to accommodate unfulfilled resource requests. ROSE books idle resources in a speculative manner: instead of waiting for resource allocation to be confirmed by the centralized scheduler, it requests intelligently to launch tasks within machines according to their suitability to oversubscribe resources. A threshold control with timely task rescheduling ensures fully-utilized cluster resources without generating potential task stragglers. Experimental results show that ROSE can almost double the average CPU utilization, from 36.37% to 65.10%, compared with a centralized scheduling scheme, and reduce the workload makespan by 30.11%, with an 8.23% disk utilization improvement over other scheduling strategies.

Ranking query independent scholarly articles is a practical and difficult task, due to the heterogeneous, evolving and dynamic nature of entities involved in scholarly articles. To do this, we first propose a scholarly article ranking model by assembling the importance of involved entities (i.e., articles, venues and authors) such that the importance is a combination of prestige and popularity to capture the evolving nature of entities. To compute the prestige of articles and venues, we propose a novel Time-Weighted PageRank that extends traditional PageRank with a time decaying factor. We then develop a batch algorithm for scholarly article ranking, in which we propose a block-wise method for Time-Weighted PageRank in terms of an analysis of the citation characteristics of scholarly articles. We further develop an incremental algorithm for dynamic scholarly article ranking, which partitions graphs into affected and unaffected areas, and employs different updating strategies for nodes in different areas. Using real-life data, we finally conduct an extensive experimental study, and show that our approach is both effective and efficient for ranking scholarly articles.

The variety among massive users makes it difficult to model their retweeting activities. Obviously, it is not suitable to cover the overall users by a single model. Meanwhile, building one model per user is not practical. To this end, this paper presents a novel solution, of which the principle is to model the retweeting behavior over user groups. Our system, GruBa, consists of three key components for extracting user based features, clustering users into groups, and modeling upon each group. Particularly, we look into the user interest from different perspectives including long-term/short-term interests and explicit/implicit interests. We have evaluated the performance of GruBa using datasets of real-world social networking applications, showcasing its benefits.

Path planning is an optimization problem that is crucial for robot or UCAV. Among the optimization approaches, we focus in this paper on a new hybrid modified Rapidly Exploring Random Tree algorithm (RRTs) and Differential Evolution (DE), for solving the optimization path planning problem to generate a fast and optimal 3D collision-free path under complex environment. We demonstrate the proposed algorithm performance through comparative analysis with Improved Bat algorithm (IBA). The results demonstrated the robustness and effectiveness of the proposed algorithm for generating an optimal free collision path in a short time, which is suitable for the UCAV applications.

Container technology has been prevalent and widely-adopted in production environment considering the huge benefits to application packing, deploying and management. However, the deployment process is relatively slow by using conventional approaches. In large-scale concurrent deployments, resource contentions on the central image repository would aggravate such situation. In fact, it is observable that the image pulling operation is mainly responsible for the degraded performance. To this end, we propose Cider — a novel deployment system to enable rapid container deployment in a high concurrent and scalable manner at scale. Firstly, on-demand image data loading is proposed by altering the local Docker storage of worker nodes into all-nodes-sharing network storage. Also, the local copy-on-write layer for containers can ensure Cider to achieve the scalability whilst improving the cost-effectiveness during the holistic deployment. Experimental results reveal that Cider can shorten the overall deployment time by 85% and 62% on average when deploying one container and 100 concurrent containers respectively.

The incremental problem for a class Q of graph queries aims to compute, given a query Q in 'Q, graph G, output Q(G) and updates Δ G to G as input, changes Δ O to Q(G) such that Q(G ⊕ Δ G) = Q(G) ⊕ Δ O. It is called bounded if its cost can be expressed as a polynomial function in the sizes of Q, Δ G and Δ O. It is to reduce computations on possibly big G to small Δ G and Δ O. No matter how desirable, however, our first results are negative: for common graph queries such as graph traversal, connectivity, keyword search and pattern matching, their incremental problems are unbounded. In light of the negative results, we propose two characterizations for the effectiveness of incremental computation: (a) localizable, if its cost is decided by small neighbors of nodes in Δ G instead of the entire G; and (b) bounded relative to a batch algorithm T, if the cost is determined by the sizes of Δ G and changes to the affected area that is necessarily checked by T. We show that the incremental computations above are either localizable or relatively bounded, by providing corresponding incremental algorithms. That is, we can either reduce the incremental computations on big graphs to small data, or incrementalize batch algorithms by minimizing unnecessary recomputation. Using real-life graphs, we experimentally verify the effectiveness of our algorithms.

This position paper provides an overview of our recent advances in the study of big graphs, from theory to systems to applications. We introduce a theory of bounded evaluability, to query big graphs by accessing a bounded amount of the data. Based on this, we propose a framework to query big graphs with constrained resources. Beyond queries, we propose functional dependencies for graphs, to detect inconsistencies in knowledge bases and catch spams in social networks. As an example application of big graph analyses, we extend association rules from itemsets to graphs for social media marketing. We also identify open problems in connection with querying, cleaning and mining big graphs.

Water samples were taken from Lake Dianchi, on the Yungui Plateau of southwest China, and experiments were conducted to simulate the photochemical degradation characteristic of chromophoric dissolved organic matter (CDOM) in the lake water. Three groups of experiments under different light conditions: ultraviolet (UV) light, visible light, and dark, were done and variations of fluorescence properties, UV absorbance, and dissolved organic carbon (DOC) concentrations during the experiments were analyzed to study the photodegradation process of CDOM with time. The result showed that light irradiation led to significant photochemical degradation of CDOM, resulting in changes in florescent properties, absorbance losses, decreases in aromaticity and average molecular weight, as well as decline in DOC concentration in the water. It was also observed that UV irradiation had greater effect than visible light did. However, various fluorophores had different sensitivities to the same irradiation condition, that is, protein — like fluorophore at the low excitation wavelengths is more sensitive to UV irradiation than the other fluorophores, and is more readily to undergo photo — degradation. In addition, visible light irradiation did not have significant impact on DOC in the water, with DOC concentration decrease by 5.57%–59.9% during the experiment time. These results may provide new knowledge on the environment behavior of CDOM in the water of Lake Dianchi.

As water resources have been developed, the input of water into wetlands by rivers has decreased. Thus, these wetland ecosystems are seriously threatened. The upstream reservoir must be operated in a manner that provides downstream wetlands with their ecological water requirement. Here, a method for analysing the effects of artificial water replenishment from reservoirs on wetlands is established. A hydrodynamic mathematical model was coupled by a one-dimensional longitudinal and depth-averaged two-dimensional hydrodynamic model to simulate the water replenishment process in wetlands. The results indicate that the overflow of floodwaters into wetlands may not occur if insufficient reservoir water is discharged. In contrast, if too much water is discharged, excess water will reach the wetland and cause a water shortage upstream. Furthermore, the results showed that there is a quantitative relationship between the area of water in a wetland and the flow discharged by the upstream reservoir. This analytical method provides direct data that can be used to ensure that wetlands receive enough water from reservoirs to maintain their ecological functions and to avoid wasting the water resources of upstream reservoirs.

The Resource Description Framework (RDF) andSPARQL query language are gaining increasing popularity andacceptance. The ever-increasing RDF data has reached a billionscale of triples, resulting in the proliferation of distributed RDFstore systems within the Semantic Web community. However, theelasticity and performance issues are still far from settled inface of data volume explosion and workload spike. In addition, providers face great pressures to provision uninterrupted reliablestorage service whilst reducing the operational costs due to avariety of system failures. Therefore, how to efficiently realizesystem fault tolerance remains an intractable problem. In this paper, we introduce ScalaRDF, a distributed and elastic in-memoryRDF triple store to provision a fault-tolerant and scalable RDFstore and query mechanism. Specifically, we describe a consistenthashing protocol that optimizes the RDF data placement, dataoperations (especially for online RDF triple update operations)and achieves an autonomously elastic data re-distribution in theevent of cluster node joining or departing, avoiding the holisticoscillation of data storage. In addition, the data store is ableto realize a rapid and transparent failover through replicationmechanism which stores in-memory data replica in the next hashhop. The experiments demonstrate that query time and updatetime are reduced by 87% and 90% respectively compared to otherapproaches. For an 18G source dataset, the data redistributiontakes at most 60 seconds when system scales out and at most 100seconds for recovery when nodes undergo crash-stop failures.

Virtual machine live migration technology allows a running VM migrates from one physical host to another with no impact on users. As the scale of distributed computing gets larger and larger, hybrid cloud, which is integrated cloud service utilizing both private and public clouds to perform distinct functions within the same organization becomes a hotspot for both academia and industry. Thus, it will be vital to migrate virtual machines in hybrid clouds. The biggest issue which VM migrationinhybridcloudsfacestodayishowtotransferthelarge amount of storage data. Storage migration of virtual machine with existing mechanisms of memory migration has been studied for a long time. Unfortunately, no one can perform perfectly without modification. It is compelling to consider a newmigration model and optimization methods. In this paper, we analyze the advantage and disadvantage of classical methods, and put forward a method which combines the strengths of pre-copy and post-copy migration model and we also use disk working set to optimize virtual machines storage migration. We have developed and implemented our approach to the QEMU/KVM hypervisor and run a series of experiments. The presented technique shows a reduction of up 20.5% on average of the total transfer time for most of the selected scenario. Our approach can also reduce the migration downtime in most cases.

Aedes albopictus is a vector of several human viral diseases, including dengue, chikungunya, and Zika. New control method for Aedes albopictus is needed to replace traditional methods such as chemical insecticides which induce resistance, environmental contamination and toxicity to human. In sterile insect technique (SIT), male mosquitoes are sterilized by γ-ray or X-ray irradiation before released. In this study, the relative effectiveness of X-ray irradiation as a mosquito SIT was investigated. Both pupal and adult Aedes albopictus were subjected to different radiation doses and their emergence, survivorship, longevity, induced sterility, and male mating competitiveness were evaluated. Relative to controls, irradiation had no significant effect on emergence and survivorship but significantly reduce adult longevity. Induced sterility were essentially same for both irradiated pupal and adult. At a dose of 40 Gy, 97% and 100% sterility was respectively achieved for males and females. Mating competitiveness was reduced both in adult males and those derived from pupae exposed to 40 Gy. However, populations can be suppressed by increasing the release ratio (sterile: normal). When the release ratio was 7:1, 74% of the wild population could be suppressed. Overall, the results of the present study showed that SIT based on X-Ray irradiation is scientific and feasible to control Aedes albopictus.

Live virtual machine migration is a technique often used to migrate an entire OS with running applications in a non-disruptive fashion. Prior works concerned with one-to-one live migration with many techniques have been proposed such as pre-copy, post-copy and log/replay. In contrast, we propose VMScatter, a one-to-many migration method to migrate virtual machines from one to many other hosts simultaneously. First, by merging the identical pages within or across virtual machines, VMScatter multicasts only a single copy of these pages to associated target hosts for avoiding redundant transmission. This is impactful practically when the same OS and similar applications running in the virtual machines where there are plenty of identical pages. Second, we introduce a novel grouping algorithm to decide the placement of virtual machines, distinguished from the previous schedule algorithms which focus on the workload for load balance or power saving, we also focus on network traffic, which is a critical metric in data-intensive data centers. Third, we schedule the multicast sequence of packets to reduce the network overhead introduced by joining or quitting the multicast groups of target hosts. Compared to traditional live migration technique in QEMU/KVM, VMScatter reduces 74.2% of the total transferred data, 69.1% of the total migration time and achieves the network traffic reduction from 50.1% to 70.3%.

Software as a Service (SaaS) is a software delivery and business model widely used by Cloud computing. Instead of purchasing and maintaining a software suite permanently, customers only need to lease the software on-demand. The domain of high assurance distributed systems has focused greatly on the areas of fault tolerance and dependability. In a multi-tenant context, it is particularly important to store, manage and provision data services to customers in a highly efficient and dependable manner due to a large number of file operations involved in running such services. It is also desirable to allow a user group to share and cooperate (e.g., co-edit) on some specific data. In this paper we present a dependable data provisioning service in a multitenant Cloud environment. We describe a metadata management approach and leverage multiple replicated metadata caching to shorten the file access time, with the improved efficiency of data sharing. In order to reduce frequent data transmission and data access latency, we introduce a distributed cooperative disk cache mechanism that supports effective cache placement and pull-push cache synchronization. In addition, we use efficient component failover to enhance the service dependability whilst avoiding negative impact from system failures. Our experimental results show that our system can significantly reduce both unused data transmission and response latency. Specifically, over 50% network transmission and operational latency can be saved for random reads while 28.24% network traffic and 25% response latency can be reduced for random write operations. We believe that these findings are demonstrating positive results along the right direction of resolving storage-related challenges in a multitenant Cloud environment.

As the sizes of IT infrastructure continue to grow, cloud computing is a natural extension of virtualisation technologies that enable scalable management of virtual machines over a plethora of physically connected systems. The so-called virtualisation-based cloud computing paradigm offers a practical approach to green IT/clouds, which emphasise the construction and deployment of scalable, energy-efficient network software applications (NetApp) by virtue of improved utilisation of the underlying resources. The latter is typically achieved through increased sharing of hardware and data in a multi-tenant cloud architecture/environment and, as such, accentuates the critical requirement for enhanced security services as an integrated component of the virtual infrastructure management strategy. This paper analyses the key security challenges faced by contemporary green cloud computing environments, and proposes a virtualisation security assurance architecture, CyberGuarder, which is designed to address several key security problems within the 'green' cloud computing context. In particular, CyberGuarder provides three different kinds of services; namely, a virtual machine security service, a virtual network security service and a policy based trust management service. Specifically, the proposed virtual machine security service incorporates a number of new techniques which include (1) a VMM-based integrity measurement approach for NetApp trusted loading, (2) a multi-granularity NetApp isolation mechanism to enable OS user isolation, and (3) a dynamic approach to virtual machine and network isolation for multiple NetApp's based on energy-efficiency and security requirements. Secondly, a virtual network security service has been developed successfully to provide an adaptive virtual security appliance deployment in a NetApp execution environment, whereby traditional security services such as IDS and firewalls can be encapsulated as VM images and deployed over a virtual security network in accordance with the practical configuration of the virtualised infrastructure. Thirdly, a security service providing policy based trust management is proposed to facilitate access control to the resources pool and a trust federation mechanism to support/optimise task privacy and cost requirements across multiple resource pools. Preliminary studies of these services have been carried out on our iVIC platform, with promising results. As part of our ongoing research in large-scale, energy-efficient/green cloud computing, we are currently developing a virtual laboratory for our campus courses using the virtualisation infrastructure of iVIC, which incorporates the important results and experience of CyberGuarder in a practical context.

A muon facility—EMuS (Experimental Muon Source)—at China Spallation Neutron Source (CSNS) has been studied since 2007. CSNS, which is designed to deliver a proton beam power of 100 kW at Phase-I, and will serve multidisciplinary research based on neutron scattering techniques, has just completed construction, and is ready to open to general users from September 2018. As an additional platform to CSNS, EMuS aims to provide different muon beams for multiple applications, among which, magnetism study by μSR techniques is a core part. By using innovative designs, such as a long target in conical shape situating in superconducting capture solenoids and forward collection method, EMuS can provide very intense muon beams with a proton beam of 5 kW and 1.6 GeV, from surface muons, decay muons, and high momentum muons to slow muons. In this article, the design aspects of EMuS, including general design, target station, muon beamlines, and μSR spectrometer, as well as prospects for applications on magnetism studies, will be reviewed.

Nowadays, various promising paradigms of distributed computing over the Internet, such as Grids, P2P and Clouds, have emerged for resource sharing and collaboration. To enable resources sharing and collaboration across different domains in an open computing environment, virtual organizations (VOs) often need to be established dynamically. However, the dynamic and autonomous characteristics of participating domains pose great challenges to the security of virtual organizations. In this paper, we propose a secure collaboration service, called PEACE-VO, for dynamic virtual organizations management. The federation approach based on role mapping has extensively been used to build virtual organizations over multiple domains. However, there is a serious issue of potential policy conflicts with this approach, which brings a security threat to the participating domains. To address this issue, we first depict concepts of implicit conflicts and explicit conflicts that may exist in virtual organization collaboration policies. Then, we propose a fully distributed algorithm to detect potential policy conflicts. With this algorithm participating domains do not have to disclose their full local privacy policies, and is able to withhold malicious internal attacks. Finally, we present the system architecture of PEACE-VO and design two protocols for VO management and authorization. PEACE-VO services and protocols have successfully been implemented in the CROWN test bed. Comprehensive experimental study demonstrates that our approach is scalable and efficient.

Variations in phosphorus (P) speciation were compared for two types of pilot scale wetlands: a blast furnace slag-based constructed wetland (SCW), and a gravel-based constructed wetland (GCW). Synthetic secondary effluent was used as the influent of the wetlands, which contained 1.1 mg/L P with more than 95% present as soluble reactive P (SRP). However, dissolved organic phosphorus (DOP) and particulate phosphorus (PP) emerged in the water along both wetlands. The levels of these three P species varied between the two wetlands. The GCW was more efficient than SCW at removing SRP, but showed a different trend. SRP decreased continually in the SCW, while it increased at the end of the GCW due to biological release. DOP was constant in SCW and GCW, and the mean value was 0.023 and 0.020 mg/L, respectively. The mean values of PP in the GCW ranged between 0.093 and 0.216 mg/L; much higher than the 0.05 ± 0.01 mg/L measured in the SCW. Sequential extractions showed that iron bound PP (Fe-PP), aluminum bound PP (Al-PP), organic PP (Org-PP) and occluded PP (Oc-PP) were the major components of PP at most locations of the GCW. Fe-PP decreased from 0.53 to 0.14 mg/L in the upper layer, with DO steady at about 0.15 mg/L at the bottom. Oc-PP increased at each layer. Al-PP and Org-PP were steady in the first 140 cm of the GCW, but decreased sharply at the end. Considering the variation of SRP, DOP and PP fractionations, it can be seen that PP exchanged intensively with SRP in the GCW, and might act as an intermediate in the P removal process. Part of the SRP was first transformed into PP, and then absorbed by substrates or deposited in the wetlands. P removal was mainly via Ca precipitation in the SCW, but involved multiple mechanisms in the GCW, such as precipitation, adsorption and biological interactions. The multiple P removal mechanisms might be the reason for the low proportion of SRP, and the better P removal efficiency observed in the GCW.

Phosphorus (P) removal efficiency was compared between two types of wetlands: a blast furnace slag (BFS)-based constructed wetland (SCW) and a gravel-based constructed wetland (GCW). Both wetlands were 2.4 m long, 0.4 m wide, and 0.65 m high. Synthetic water to be reclaimed contained 1.1 mg·L−1 P. Hydraulic retention time (HRT) was set at 1 day in the first four phases and then increased to 2 days in the last two phases. Results showed that P removal with 1 day HRT application decreased from 80.4 to 56.4% in SCW and from 73.0 to 61.6% in GCW. With the increase of HRT, P removal decreased continually to 54.6% in SCW while it increased to 88.6% in GCW. The lower amount of P removed by SCW in the latter phases was mainly the result of substrates. P adsorption capacities did not show much difference between BFS and gravel in the batch experiment with a low initial P concentration less than 1.4 mg·L−1. However, chemical properties of substrates presented an obvious impact on P removal in the pilot exp...

As hydrogen, deuterium and tritium storage materials, a series of investigations of mechanical and thermal properties of titanium hydrides, deuterides and tritides have been performed, however, very limited theoretical studies of thermodynamic properties for them can be found. Based on density-functional theory (DFT) and density-functional perturbation theory (DFPT) we have discussed systematically the hydrogen isotope effects on the thermodynamic properties of TiX2 (X = H, D, and T) system. Our calculations indicate that for evaluating accurately their physical properties at absolute zero temperature, such as the equilibrium lattice constants, bulk modulus, and heat of formation, the zero-point energy correction must be taken into account. By performing the phonon calculation within quasiharmonic approximation (QHA), we obtain their vibrational free energies, vibrational entropies, and temperature dependence of specific heat, thermal expansion, and bulk modulus. Those results demonstrate that comparing with TiH2, TiT2 and TiD2 are more stable and the zero-point effects play an important role in their thermal expansion. The increase in the force constant between Ti and H causes the higher value of specific heat of TiH2 during the phase transition from FCC to FCT. In addition, comparing with available experimental values, we can conclude that QHA is feasible for describing the thermal properties of TiX2. (C) 2006 Elsevier B.V. All rights reserved.

The main goal of our key project, the CROWN Grid, is to empower in-depth integration of resources and the cooperation of researchers nationwide and worldwide. CROWN exploits a service-oriented architecture based on OGSA. In CROWN, remote service deployment is highly desirable. To the best of our knowledge, however, there is no successful solution to ensure the enabling remote and hot service deployment in grid systems. Traditionally, remote deployment is supported in a cold fashion, which results in many disadvantages, such as low efficiency. Moreover, since the deployer and the target container may be in different domains, great security challenges arise when a service is deployed to a remote container. In this paper, we present ROST, an original scheme of Remote and hOt Service deployment with Trustworthiness. By dynamically updating runtime environment configurations, ROST avoids restarting the runtime system during deployment. In addition, we include trust negotiation in ROST, which greatly increases the flexibility and security of the CROWN Grid. ROST has been successfully implemented. We conduct comprehensive experiments with real applications, and the results show that ROST is viable and significantly improves the service efficiency and quality of CROWN. We believe that the wide deployment of ROST would also benefit other grid systems.

Information service plays a key role in grid system, handles resource discovery and management process. Employing existing information service architectures suffers from poor scalability, long search response time, and large traffic overhead. In this paper, we propose a service club mechanism, called S-Club, for efficient service discovery. In S-Club, an overlay based on existing Grid Information Service (GIS) mesh network of CROWN is built, so that GISs are organized as service clubs. Each club serves for a certain type of service while each GIS may join one or more clubs. S-Club is adopted in our CROWN Grid and the performance of S-Club is evaluated by comprehensive simulations. The results show that S-Club scheme significantly improves search performance and outperforms existing approaches.

Based on a proposed Web service-based grid architecture, a service grid middleware system called CROWN is designed in this paper. As the two kernel points of the middleware, the overlay-based distributed grid resource management mechanism is proposed, and the policy-based distributed access control mechanism with the capability of automatic negotiation of the access control policy and trust management and negotia- tion is also discussed in this paper. Experience of CROWN testbed deployment and ap- plication development shows that the middleware can support the typical scenarios such as computing-intensive applications, data-intensive applications and mass information processing applications.

In this paper, for the first time, we tackle the scalability problem of Influence Maximization (IM) via distributed computing. First, we propose a distributed IM algorithm based on IRIE, one of the most state-of-the-art IM algorithms. Then an incremental updating method is proposed to reduce the overhead of repeated computation. Furthermore, based on some new insights, we redesign our algorithm with a strategy, which we call reservoir, to accumulate increments and delay exchange between machines. Experiments on real-world and synthetic networks show our redesigned algorithm, i.e. dIRIEr (distributed IRIE with Reservoir), reduces communication traffic dramatically and speeds up continuously as more machines are added in. dIRIEr can handle giant networks with hundreds of millions of nodes where centralized algorithms become infeasible.

Virtualization is one of the most fascinating techniques because it can facilitate the infrastructure management and provide isolated execution for running workloads. Despite the benefits gained from virtualization and resource sharing, improved resource utilization is still far from settled due to the dynamic resource requirements and the widely-used over-provision strategy for guaranteed QoS. Additionally, with the emerging demands for big data analytic, how to effectively manage hybrid workloads such as traditional batch task and long-running virtual machine (VM) service needs to be dealt with. In this paper, we propose a system to combine long-running VM service with typical batch workload like MapReduce. The objectives are to improve the holistic cluster utilization through dynamic resource adjustment mechanism for VM without violating other batch workload executions. Furthermore, VM migration is utilized to ensure high availability and avoid potential performance degradation. The experimental results reveal that the dynamically allocated memory is close to the real usage with only 10% estimation margin, and the performance impact on VM and MapReduce jobs are both within 1%. Additionally, at most 50% increment of resource utilization could be achieved. We believe that these findings are in the right direction to solving workload consolidation issues in hybrid computing environments.

With the rapid proliferation of camera-equipped smart devices (e.g., smartphones, pads, tablets), visible light communication (VLC) over screen-camera links emerges as a novel form of near-field communication. Such communication via smart devices is highly competitive for its user-friendliness, security, and infrastructure-less (i.e., no dependency on WiFi or cellular infrastructure). However, existing approaches mostly focus on improving the transmission speed and ignore the transmission reliability. Considering the interplay between the transmission speed and reliability towards effective end-to-end communication, in this paper, we aim to boost the throughput over screen-camera links by enhancing the transmission reliability. To this end, we propose RDCode, a robust dynamic barcode which enables a novel packet-frame-block structure. Based on the layered structure, we design different error correction schemes at three levels: intra-blocks, inter-blocks and inter-frames, in order to verify and recover the lost blocks and frames. Finally, we implement RDCode and experimentally show that RDCode reaches a high level of transmission reliability (e.g., reducing the error rate to 10%) and yields a at least doubled transmission rate, compared with the existing state-of-the-art approach COBRA.

Visible light communication (VLC) over screen-camera links emerges as a novel form of near-field communication, and it offers a user-friendly, infrastructure-less and secure communication, which is highly competitive for one-time file transfer [1 - 4]. However, the limitations of smart devices and the uncertainty of user behaviors seriously impair the transmission reliability and hinder its applicability. Worse still, existing approaches [1, 2, 4]mostly focus on improving the transmission speed and ignore the transmission reliability. Hence, RDCode is proposed to boost the throughput over screen-camera links, by making use of a novel barcode design and several effective techniques to enhance the transmission reliability. In this demo, we show that our RDCode prototype system addresses many practical challenges. A short video on our prototype system is accessible from http://mashuai.buaa.edu.cn/demo/RDCode.mp4.

Virtualization is one of the main technologies currently used to deploy computing systems due to the high reliability and rapid crash recovery it offers in comparison to physical nodes. These features are mainly achieved by continuously producing snapshots of the status of running virtual machines. In earlier works, the snapshot of each individual VM is performed independently, ignoring the memory similarities between VMs within the cluster. When the size of the virtual cluster becomes larger or snapshots are frequently taken, the size of snapshots can be extremely large, consuming large amount of storage space. In this paper, we introduce an innovative snapshot approach for virtual cluster that exploits shared memory pages among all the component VMs to reduce the size of produced snapshot and mitigate the I/O bottleneck. The duplicate memory pages are effectively discovered and stored only once when the snapshot is taken. In addition, our approach can be not only applied to the stop-copy snapshot but also to the pre-copy mechanism as well. Experiments on both snapshot methods are conducted and the result shows our method can reduce the total memory snapshot files by an average of 30% and reach 63% reduction of the snapshot time compared with the default KVM approach with little overhead of rollback time.

On one hand, compared with traditional relational and XML models, graphs have more expressive power and are widely used today. On the other hand, various applications of social computing trigger the pressing need of a new search paradigm. In this article, we argue that big graph search is the one filling this gap. To show this, we first introduce the application of graph search in various scenarios. We then formalize the graph search problem, and give an analysis of graph search from an evolutionary point of view, followed by the evidences from both the industry and academia. After that, we analyze the difficulties and challenges of big graph search. Finally, we present three classes of techniques towards big graph search: query techniques, data techniques and distributed computing techniques.

Mobile computing is increasingly growing in terms of massive computation as well as user demand and use of mobile devices. Remote execution techniques enrich the service experience of mobile devices by leveraging the resource pools of computation and storage capabilities of the cloud data center. However, the user experience and quality of service will be severely affected due to the inherent high latency and low bandwidth of a WAN environment. In this paper, we introduce a cloud base station "CloudAP" which is a small-scale computing infrastructure close to mobile users with local network access. In addition, we present a two-tier architecture consisting of CloudAP and Cloud center and show how to synthesize them to form a general computing environment. Furthermore, we propose a prompt execution environment migration scheme implemented by an efficient whole-system VM migration. It makes the execution environment move following the location of mobile device. Our experimental results demonstrate that the proposed architecture is effective and the execution environment migration scheme is efficient, consisting of up to 10ms and 30s for service downtime and execution environment switch time respectively. These improvements make vital contributions to user experience and QoS in mobile pervasive environment.

The combination of cloud computing and virtualization technology introduces a new pattern on resource allocation and utilization. Memory scanning deduplication techniques based on eliminating duplicated pages among virtual machines can promote the resource utilization, and decrease the total cost of ownership. However, the existing memory deduplication technologies lack the supporting of isolation and trustworthiness mechanism. This paper proposes a memory sharing mechanism based on user groups. This mechanism guarantees isolation between the different users on the same host. In addition, we designed a sampling hash algorithm to make the memory scanning process more efficient. We have implemented our approach in Linux by modifying the KSM scanning mechanism and splitting the global ksmd thread into per-group ksmds. The experiment results show the work can optimize the memory-intensive VMs, and efficiently accelerate the memory scanning process.

With the convergence of cloud computing and mobile computing, mobile devices can access remote applications in a cloud environment. However, existing research work mostly focused on leveraging cloud capabilities to enhance mobile clients. Particularly, in order to access different cloud platforms and applications, specific version of clients such as Web portal, Remote Desktop, are generally required. The original display and interaction experience on the client local system are changed. This paper presents an approach named screen which keeps a consistent display and interaction experience between local and remote applications in a mobile cloud computing environment. screen consists of a three-factor merging framework including windows merging, meta-info merging and interaction merging for applications. We developed a prototype of screen for Windows applications to allow thin clients to seamlessly access remote cloud windows applications. Experimental studies show that screen can effectively merge local desktop with remote display, and mobile clients can achieve 20 frames per second when running a remote video playback application. The bandwidth usage of screen is reduced by about 10% compared to Ultra VNC. It performs better especially under high-motion scenarios.

Checkpoint-recovery based on system virtualization is an attractive approach for providing the transparent and economic fault tolerance service in virtualized environments. The previous approaches introduce either great performance degradation or complex implementation issues. In this work, we propose a whole system hot-mirroring platform, namely Radiata, to provide fault-tolerance for any type of service by encapsulating the service instance into a virtual machine, and hot-mirroring the state changes of the virtual machine via the continual state replication. Our approach exploits three key optimizations for further reduction of the performance overhead: the asynchronous state replication, the COW-based memory checkpoint and the dirty page prediction. Based on the KVM platform, we have implemented the prototype system. The comprehensive evaluations under a variety of workloads demonstrate that Radiata is able to effectively support rapid and transparent fail-over in case of unexpected hardware failure, and outperforms the existing mechanisms in terms of the performance degradation in failure-free condition.

Compared to the conventional physical cluster, the virtual cluster technology has features such as flexible configuration, easy management and high system security, which provides users with an easily customized computing environment. Virtual machine image files as the most important stored objects in the virtual computing environment include all the information about the whole life cycle of virtual machine. The storage of the virtual machine images is an important part of virtual computing. There are mainly two ways to store the images, which include local storage and networking storage. This paper proposes a mechanism to manage the distributed image files to support the virtual computing environment. It uses the computing nodes` local storage as a chunk server in a distributed file system, and regards the distribution of the image files as a primary factor to choose the computing node to deploy virtual machine and to implement a backup mechanism of distributed images based on historical records of image files. Functional test and performance test results show that it can effectively support the virtual computing environment and has great values of applications and research.

Efficient resource management in the virtualized data center is always a practical concern and has attracted significant attention. In particularly, economic allocation mechanism is desired to maximize the revenue for commercial cloud providers. This paper uses overbooking from Revenue Management to avoid resource over-provision according to its runtime demand. We propose an economic model to control the overbooking policy while provide users probability based performance guarantee using risk estimation. To cooperate with overbooking policy, we optimize the VM placement with traffic-aware strategy to satisfy application's QoS requirement. We design GreedySelePod algorithm to achieve traffic localization in order to reduce network bandwidth consumption, especially the network bottleneck bandwidth, thus to accept more requests and increase the revenue in the future. The simulation results show that our approach can greatly improve the request acceptance rate and increase the revenue by up to 87% while with acceptable resource confliction.

This work was conducted to evaluate the effectiveness and influence factors of vegetation on phosphorus (P) removal from reclaimed water in constructed wetlands. Comparisons were conducted between one pilot scale subsurface flow wetland (P-SSFW) and two demonstration subsurface flow wetlands, which were series-wound and named as first subsurface flow wetland (F-SSFW), and second subsurface flow wetland (S-SSFW), respectively. The three wetlands had the same vegetation and substrate, but different pH values, total dissolved solids (TDS) and P loads. Results showed that the P content in the vegetation shoots of the F-SSFW was 2.16 mg/g, while 2.31 mg/g in the S-SSFW and 2.69 mg/g in the P-SSFW. These differences were likely caused by the higher pH and TDS in the reclaimed water. The P content also differed among the tissues of the plant, which were 5.94-6.44 mg/g, 2.20-2.77 mg/g, 1.31-1.46 mg/g and 1.53-1.88 mg/g in the flowers, leaves, stems, and roots, respectively. The greatest discrepancy was observed in the leaves, indicating that the environment of the wetlands had the greatest influence on the leaves. When the total phosphorus (TP) load was lower, the proportion of P removed by vegetation assimilation was 16.17% in the P-SSFW, 12.90% in the F-SSFW and 13.29% in the S-SSFW. However, the relative removal efficiency by vegetation among the three wetlands did not vary greatly from that observed in other studies. Moreover, the influence of pH, TDS and TP load was not as great as the influence of the vegetation species, type of substrate, influent style or climate.

With the cloud computing and virtualization technology popularizing and developing, the Software as a Service (SaaS), has become an innovative software delivery model. In this environment, if the virtual software runs in traditional way, that is to start up after completely downloaded, it will be time-consuming and greatly influence the users' experience. However, the streaming execution mode will enable the virtual software to start up while downloading. According to this conception, we design and implement a virtual file system for streaming delivery of software. The experimental results show that the first startup times of virtualized software have reduced by 20% to 60% and the users' experience has been improved effectively.

Recent years we have witnessed the rapid advent of mobile cloud computing, in which remote software is delivered as a service and accessed by mobile device users over the Internet. However, most existing remote display technologies for high motion application (e.g, movie) have defects in latency and bandwidth. In this paper, we designed an adaptive multimedia streaming enabled remote interactivity system, Muse, to utilize remote resources with reduced display update traffic and response latency. A window-aware updating mechanism is designed as an adaptation scheme, which allows users to focus on the current application in use and also enable them to switch between applications on the fly. Besides, a windowed display encoder using H.264 video codec is integrated into the remote frame buffer protocol to achieve high performance in compression to address the high latency limitation of mobile Internet. Experimental results show that the windowed display Muse mechanism can successfully reduce network traffic, loading time and response latency of remote display and interaction. Our system can achieve in average 22fps of 1024*768 desktop multimedia playbacks with good video quality under 1 Mbit/s of bandwidth limitation.