Mapping Requests Research Articles

RETRACTED: A Global Optimal Mapping Method of Network based on Discrete Optimization Firefly Algorithm

In order to solve the current network rigidity and optimize the resource requirements of multiple virtual networks for synchronous mapping, improve the success rate of virtual network mapping requests, the long-term revenue and overhead ratio of the substrate network, node resource utilization rate and link resource utilization rate. A global optimal mapping method based on discrete optimization firefly algorithm is presented. Analyze the problem of virtual network mapping, map virtual nodes to physical nodes, and map virtual links to physical paths. According to the resource constraints of the virtual network and the substrate network, a multi-objective optimization model of the virtual network mapping is constructed, and the discrete fireflies optimization algorithm is used to obtain the global optimal solution of the virtual network mapping model to achieve the optimal allocation of global resources. The experimental results show that the discrete optimization firefly algorithm has a good performance in solving the virtual network mapping problem, and can effectively improve the virtual network request acceptance rate, node resource utilization rate, link resource utilization rate, and long-term revenue and cost ratio of the substrate network, ensuring Optimization of virtual network resources.

Increasing Use of Compassionate Use/Managed Access Channels to Obtain Medicines for Use in COVID-19.

The COVID-19 pandemic has triggered an extensive need for new therapeutics and there has been widespread use of unapproved/repurposed medicines. Several countries have regulations for access to unapproved medicines, known as compassionate use, managed/expanded access or emergency use. The Novartis Managed Access activity for COVID-19 delivered unapproved/repurposed medicines to nearly 6,000 patients over a 6-month period. With the rapid growth of such access mechanisms to address COVID-19, a better understanding of these channels is required.

A Novel Approach towards the Design and Implementation of Virtual Network Based on Controller in Future IoT Applications

The Internet of Things refers (IoT) to the billions of physical devices around the globe that are connected to the Internet, collecting and sharing data. The overall Internet of Things market is projected to be worth more than 50.6 billion U.S. dollars in 2020. IoT devices possess low processing capabilities, limited memory, limited storage, and minimal network protocol support. With the help of cloud computing technology, we can overcome the limited resources of IoT devices. A lot of research has been conducted on IoT device virtualization to facilitate remote access and control. The concept of virtualization in IoT is to provide a virtual representation of physical devices in the form of virtual objects. IoT devices are more likely to be accessed and communicate through virtual objects in the near future. In this paper, we present the design and implementation of building a virtual IoT network for a smart home. The virtual network is based on virtual objects and IoT controller. We derived the concept from Software Defined Network (SDN) and separated the control plane and data plane in the virtual IoT network. This enhanced the rapid development of diverse applications on top of the virtualization layer by establishing a dynamic end-to-end connection between IoT devices. This article briefly explains the design and development of the virtual network. Results achieved during experiments and performance analysis show that IoT controller enhances the capabilities of a virtual network by dynamically controlling the traffic congestion, handling mapping requests, and routing mechanisms.

EPVNE: An Efficient Parallelizable Virtual Network Embedding Algorithm

Virtual network embedding (VNE) problem is a key issue in network virtualization technology, and much attention has been paid to the virtual network embedding. However, very little research work focuses on parallelized virtual network embedding problems which assumes that the substrate infrastructure supports parallel computing and allows one virtual node to be mapped to multiple substrate nodes. Based on the work of Liang and Zhang, we extend the well-known VNE to parallelizable virtual network embedding (PVNE) in this paper. Furthermore, to the best of our knowledge, we give the first formulation of the PVNE problem. A new heuristic algorithm named efficient parallelizable virtual network embedding (EPVNE) is proposed to reduce the cost of embedding the VN request and increase the VN request acceptance ratio. EPVNE is a two-stage mapping algorithm, which first performs node mapping and then performs link mapping. In the node mapping phase, we present a simple and efficient virtual node and physical node sorting formula and perform the virtual node mapping in order. When mapping virtual nodes, we map virtual nodes to physical nodes that just meet the CPU requirements. Substrate nodes with more CPU resources will be retained for subsequent virtual network mapping requests. In the link mapping phase, Dijkstra’s algorithm is used to find a substrate path for each virtual link. Finally, simulations are carried out and simulation results show that our algorithm performs better than the existing heuristic algorithms.

Approaches to Improving the Efficiency of Data Centers

Methods for improving the efficiency of using data center resources are proposed. They are based on expanding the functional capabilities and improving the accuracy of mapping requests to physical resources in the scheduler used in the cloud platform.

A multi-layered policy generation and management engine for semantic policy mapping in clouds

The long awaited cloud computing concept is a reality now due to the transformation of computer generations. However, security challenges have become the biggest obstacles for the advancement of this emerging technology. A well-established policy framework is defined in this paper to generate security policies which are compliant to requirements and capabilities. Moreover, a federated policy management schema is introduced based on the policy definition framework and a multi-level policy application to create and manage virtual clusters with identical or common security levels. The proposed model consists in the design of a well-established ontology according to security mechanisms, a procedure which classifies nodes with common policies into virtual clusters, a policy engine to enhance the process of mapping requests to a specific node as well as an associated cluster and matchmaker engine to eliminate inessential mapping processes. The suggested model has been evaluated according to performance and security parameters to prove the efficiency and reliability of this multi-layered engine in cloud computing environments during policy definition, application and mapping procedures.

Opportunistic content diffusion in mobile ad hoc networks

Opportunistic wireless content sharing via Mobile Ad hoc NETworks (MANETs) can increase throughput, lower latency, extend network coverage and reduce load on infrastructure. While the benefits of content diffusion clearly depend on the underlying movement dynamics and content demand, the impact of these factors on diffusion remains largely unexplored. We analyze content sharing potential based on device encounters inferred from a large multi-site wireless LAN trace. We explore the impact of time, location, and number of sources on diffusion, finding that contexts with higher activity generally promote faster diffusion, while additional content sources improve diffusion mainly in the short-term. We then apply real-world demand patterns from a popular campus maps application to content diffusion simulations. We find that up to 70% of map requests could theoretically be served from the peer network over the first 12 h. Finally, our analysis of the impact of trace uncertainties and individual device variation on diffusion potential reveals large differences based on the selected assumption and chosen source devices. We discuss these results and their implications for content-diffusion in MANETs.

A balanced decomposition approach to real-time visualization of large vector maps in CyberGIS

With the dramatic development of spatial data infrastructure, CyberGIS has become significant for geospatial data sharing. Due to the large number of concurrent users and large volume of vector data, CyberGIS faces a great challenge in how to improve performance. The real-time visualization of vector maps is themost common function in CyberGIS applications, and it is time-consuming especially when the data volume becomes large. So, how to improve the efficiency of visualization of large vector maps is still a significant research direction for GIScience scientists. In this research, we review the existing three optimization strategies, and determine that the third category strategy (i.e., parallel optimization) is appropriate for the real-time visualization of large vector maps. One of the key issues of parallel optimization is how to decompose the real-time visualization tasks into balanced sub tasks while taking into consideration the spatial heterogeneous characteristics. We put forward some rules that the decomposition should conform to, and design a real-time visualization framework for large vector maps. We focus on a balanced decomposition approach that can assure efficiency and effectiveness. Considering the spatial heterogeneous characteristic of vector data, we use a "horizontal grid, verticalmultistage" approach to construct a spatial point distribution information grid. The load balancer analyzes the spatial characteristics of the map requests and decomposes the real-time viewshed into multiple balanced sub viewsheds. Then, all the sub viewsheds are distributed to multiple server nodes to be executed in parallel, so as to improve the realtime visualization efficiency of large vector maps. A group of experiments have been conducted by us. The analysis results demonstrate that the approach proposed in this research has the ability of balanced decomposition, and it is efficient and effective for all geometry types of vector data.

V-TerraFly: large scale distributed spatial data visualization with autonomic resource management

GIS application hosts are becoming more and more complicated. Theses hosts’ management is becoming more time consuming and less reliabale decreases with the increase in complexity of GIS applications. The resource management of GIS applications is becoming increasingly important in order to deliver to the user the desired Quality of Service. Map systems often serve dynamic web workloads and involve multiple CPU- and I/O-intensive tiers, which makes it challenging to meet the response time targets of map requests while using the resources efficiently. This paper proposes a virtualized web map service system, v-TerraFly, and its autonomic resource management in order to address this challenge. Virtualization facilitates the deployment of web map services and improves their resource utilization through encapsulation and consolidation. Autonomic resource management allows resources to be automatically provisioned to a map service and its internal tiers on demand. Specifically, this paper proposes new techniques to predict the demand of map workloads online and optimize resource allocations considering both response time and data freshness as the QoS target. The proposed v-TerraFly system is prototyped on TerraFly, a production web map service, and evaluated using real TerraFly workloads. The results show that v-TerraFly can accurately predict the workload demands: 18.91% more accurate; and efficiently allocate resources to meet the QoS target: improves the QoS by 26.19% and saves resource usages by 20.83% compared to traditional peak-load-based resource allocation.

An Efficient Approach to Load Balancing of Vector Maps in CyberGIS Cluster Environment

The real-time visualization of vector maps is the most common function in CyberGIS, and it is timeconsuming, especially as the data volume becomes larger. How to improve the efficiency of visualization of large vector maps is still a significant research direction for GIS scientists. In this research, we point out that parallel optimization is appropriate for the real-time visualization of large vector maps. The main purpose of this research is to investigate a balanced decomposition approach which can balance the load of each server node in a CyberGIS cluster environment. The load balancer analyzes the spatial characteristics of the map requests and decomposes the real-time viewshed into multiple balanced sub viewsheds, so as to balance the load of all the server nodes in the cluster environment. The test results demonstrate that the approach proposed in this research has the ability to balance the load in CyberGIS cluster environment.

Pareto optimal mapping for tile-based network-on-chip under reliability constraints

Mapping for network-on-chip (NoC) is one of the key steps of NoC design. To improve the performance and reliability of NoC architectures, we present a comprehensive optimization algorithm with multiple objectives. We propose to find the Pareto optimal solutions, rather than a single solution usually obtained through scalarization, e.g. weighting the objective functions. In order to meet the NoC mapping requests and strengthen the capability of searching solutions, the standard particle swarm optimization (PSO) algorithm is improved and a fault-tolerant routing is proposed. These methods help to solve the tradeoff between high performance and system reliability. We present a mathematical analysis of the convergence of the improved algorithms, and prove sufficient conditions of convergence. The improved algorithms are implemented on the Embedded Systems Synthesis Benchmarks Suite (E3S). Experimental results show our algorithms achieve high performance and reliability compared with the standard PSO.

Concatenated coding and hybrid automatic repeat request for wiretap channels

In this study, the authors propose an equivocation scheme for wiretap channels, which is composed of bit-extension mapping, coset coding and hybrid automatic repeat request (HARQ). The inner bit-extension code and outer coset code are used for equivocation of a wiretapper channel, whereas the HARQ scheme is to mitigate noisy errors in a main legitimate channel. These concatenated codes and HARQ are effective and practical for various channel conditions. The average equivocation and the probability of causing imperfect secrecy are analysed for finite codeword lengths. As a function of channel conditions, they investigate the block error rate at the legitimate receiver and the information leakage to the wiretapper. From simulation results, they further determine the minimum requirements of code design for some target values of the `residual' block error rate and information leakage at maximum retransmission.

Anomaly detection and response approach based on mapping requests

ABSTRACTThere is an increasing consensus that the locator/identifier separation of IP address is necessary to resolve the scalability issues of current Internet routing architecture. After identifiers are separated from locators, an identifier‐to‐locator mapping service must be employed to map identifiers onto locators. From this point, this paper proposes an anomaly detection and response approach based on mapping requests. By using the cumulative sum algorithm for change point detection, this approach introduces the anomalous traffic detection of mapping requests to diagnose the aberrant network behaviors. Once alarming, two effective response methods can be chosen to control the anomalous attack traffic in real time. Furthermore, in order to decouple the mapping request traffic from the mapping cache, this approach not only takes into account the mapping cache timeout but also puts forward a practical mapping request threshold algorithm. In particular, our simulation results show that, compared with the anomaly detection approach based on network traffic, the proposed approach is more advantageous and efficient. In addition, we also discuss the possible false positive and false negative problems, which may be caused by some accidental phenomena. Copyright © 2014 John Wiley & Sons, Ltd.

Multicast virtual network mapping for supporting multiple description coding-based video applications

Video applications have gradually become one of the mainstreams of Internet traffic along with the technological advances in recent years. In parallel, network virtualization technique allows Internet Service Providers (ISPs) to be decoupled from the physical network infrastructure operators to provide various video services to customers through tailored Virtual Networks (VNs). In a video multicast VN, the ISP could appropriately determine and configure the virtual nodes and links to deliver customized video service to the affiliated end users. However, available multicast tree mapping algorithms are based on the strong assumption that the locations of source and a collection of destination nodes are known a priori. Also, they have not taken any intermediate nodes between source and destinations into the VN mapping request. These assumptions greatly limit the adoption of advanced video coding techniques. In this paper, the multicast networks mapping for enabling Multiple Description Coding (MDC) based video applications is explored. A novel multicast mapping algorithm, MMPC, is proposed based on path convergence to flexibly identify and configure nodes (with automatic intermediate nodes identification) in multicast trees to meet certain criteria. The suggested approach is described in details and its key characteristics are analyzed through a set of analytical proves. Extensive simulation experiments are carried out to assess its performance (e.g. acceptance ratio, mapping cost and mapping time) against a range of multicast VN request scenarios. The simulation results demonstrate the superiority of MMPC algorithm in terms of multicast mapping efficiency and cost by using the conventional two-phase VN mapping algorithm as a comparison benchmark.

SMashQ: spatial mashup framework for k-NN queries in time-dependent road networks

The k-nearest-neighbor (k-NN) query is one of the most popular spatial query types for location-based services (LBS). In this paper, we focus on k-NN queries in time-dependent road networks, where the travel time between two locations may vary significantly at different time of the day. In practice, it is costly for a LBS provider to collect real-time traffic data from vehicles or roadside sensors to compute the best route from a user to a spatial object of interest in terms of the travel time. Thus, we design SMashQ, a server-side spatial mashup framework that enables a database server to efficiently evaluate k-NN queries using the route information and travel time accessed from an external Web mapping service, e.g., Microsoft Bing Maps. Due to the expensive cost and limitations of retrieving such external information, we propose three shared execution optimizations for SMashQ, namely, object grouping, direction sharing, and user grouping, to reduce the number of external Web mapping requests and provide highly accurate query answers. We evaluate SMashQ using Microsoft Bing Maps, a real road network, real data sets, and a synthetic data set. Experimental results show that SMashQ is efficient and capable of producing highly accurate query answers.

Hierarchical virtual network mapping algorithm for large-scale network virtualisation

Virtual network(VN) mapping deals with the allocation of network resources from the shared physical substrate to individual VNs is one of the key challenges for the application of realising network virtualisation. Whereas a variety of state-of-the-art algorithms have attempted to address this issue from different aspects, the challenge still remains for mapping VNs across multiple network domains which only maintain partial information of the overall substrate network. A novel hierarchical algorithm to address this issue by formulating such VN mapping problem as a hierarchical linear programme model has been presented. Through the use of the primal decomposition and subgradient optimisation technique, in conjunction with the proposed hierarchical algorithm, the substrate network resource can be appropriately allocated to the VN instances with enhanced scalability, because of the parallelism in individual domains. In addition, the algorithm could find the best trade-off between the number of optimisation iterations (computation time) and cost by selecting an appropriate number of iterations. The proposed method has been assessed through a collection of numerical simulation experiments for a range of network scenarios and the result shows that nearly optimal performance as well as improved VN mapping request acceptance ratio and revenue can be achieved.

Optimizing the stretch of independent tasks on a cluster: From sequential tasks to moldable tasks

This paper addresses the problem of scheduling non-preemptive moldable tasks to minimize the stretch of the tasks in an online non-clairvoyant setting. To the best of the authors’ knowledge, this problem has never been studied before. To tackle this problem, first the sequential subproblem is studied through the lens of the approximation theory. An algorithm, called DASEDF, is proposed and, through simulations, it is shown to outperform the first-come, first-served scheme. Furthermore, it is observed that machine availability is the key to getting good stretch values. Then, the moldable task scheduling problem is considered, and, by leveraging the results from the sequential case, another algorithm, DBOS, is proposed to optimize the stretch while scheduling moldable tasks. This work is motivated by a task scheduling problem in the context of parallel short sequence mapping which has important applications in biology and genetics. The proposed DBOS algorithm is evaluated both on synthetic data sets that represent short sequence mapping requests and on data sets generated using log files of real production clusters. The results show that the DBOS algorithm significantly outperforms the two state-of-the-art task scheduling algorithms on stretch optimization.

SIDMAP:A Service-oriented Mapping System for Loc/ID split Internet Naming

While locator/identifier split makes Internet routing more scalable, the promise of a mapping system that resolves a service to corresponding location is yet to be realized. Part of the challenge is due to most current approaches only focusing on how to find the location of a host, not the location of a service, which make these systems rely on extra naming system to provide applications the requested service's location and introduce complex load interactions between the locator/identifier mapping system and naming system. Another challenge is due to the vast majority of current Internet usage changed from host-centric applications to data retrieval and service access, traditional domain name system (DNS) is unable to support today's Internet needs such as service migration and composition. We introduce SIDMAP--a novel,efficient service-oriented naming scheme for incorporating service identifier/identifier mapping system that returns appropriate locators in response to mapping requests for specific service identifiers,service migration and service composition into one system. According to the result of evaluations, our mechanism has good scalability and low resolution latency.

Adaptive TTL schemes for load balancing of distributed Web servers

With ever increasing web traffic, a distributed Web system can provide scalability and flexibility to cope with growing client demands. Load balancing algorithms to spread the load across multiple Web servers are crucial to achieve the scalability. Various domain name server (DNS) based schedulers have been proposed in the literature, mainly for multiple homogeneous servers. DNS provides (logical) host name to IP-address mapping (i.e., the server assignment), but the mapping is not done for each server access. This is because the address mapping is cached for a time-to-live (TTL) period to reduce network traffic. The presence of heterogeneous Web servers not only increases the complexity of the DNS scheduling problem, but also makes previously proposed algorithms for homogeneous distributed systems such as round robin not directly applicable. This leads us to propose new policies, called adaptive TTL algorithms, that take both the uneven distribution of client request rates and heterogeneity of Web servers into account to adaptively set the TTL value for each address mapping request. Extensive simulation results show that these strategies are effective in balancing load among geographically distributed heterogeneous Web servers.

Map use in a small academic map library

A record was made of map requests for one year in the Geography Department's map library at Sheffield University. This is compared with other surveys of map use in university map libraries. The results show that the greatest use of the library is by students, mainly geography students, and that there was a relatively high use of thematic maps. The differences between the libraries compared are mainly due to the differing status and purposes of the libraries within their universities and thus their differing resources.