Optimization of Grouping Evacuation Strategy in High-rise Building Fires Based on Graph Theory and Computational Experiments

It is difficult to rescue people from outside, and emergency evacuation is still a main measure to decrease casualties in high-rise building fires. To improve evacuation efficiency, a valid and easily manipulated grouping evacuation strategy is proposed. Occupants escape in groups according to the shortest evacuation route is determined by graph theory. In order to evaluate and find the optimal grouping, computational experiments are performed to design and simulate the evacuation processes. A case study shown the application in detail and quantitative research conclusions is obtained. The thoughts and approaches of this study can be used to guide actual high-rise building evacuation processes in future.

A Pre-Allocation Strategy for Implement ADA95's Distrbuted Computing

In order to realize distributed computing of Ada95, this paper discusses Ada95's distributed system model and an implement model of Ada95's distributed computing-- workstation cluster model. Under this model, we presents a pre-allocation strategy for allocating the computation quantity of distributed units evenly among workstations and also reducing the communication expense between those distributed units.

CLUSTER OF WORKSTATIONS BASED ON DYNAMIC LOAD BALANCING FOR PARALLEL TREE COMPUTATION DEPTH-FIRST-SEARCH

The real problem in cluster of workstations is the changes in workstation power or number of workstations or dynmaic changes in the run time behavior of the application hamper the efficient use of resources. Dynamic load balancing is a technique for the parallel implementation of problems, which generate unpredictable workloads by migration work units from heavily loaded processor to lightly loaded processors at run time. This paper proposed an efficient load balancing method in which parallel tree computations depth first search (DFS) generates unpredictable, highly imbalance workloads and moves through different phases detectable at run time, where dynamic load balancing strategy is applicable in each phase running under the MPI(message passing interface) and Unix operating system on cluster of workstations parallel platform computing.

PARALLEL COMPUTATION OF SUPER-SONIC BLUNT BODY VISCOUS FLOWFIELDS IN PVM

Supersonic viscous flows past blunt bodies is calculated with TVD difference scheme and implicit Lower Upper Symmetric Gauss Seidel (LU SGS) method, and parallel programming designing software platform PVM is used based on message passing to distribute a large task according to some patching strategies to a large number of processors in the network. These processors accomplish this large task together. The marked improvement of computational efficiency in networks, especially in MPP system, demonstrates the potential vitality of CFD in engineering design.

A potential game-based outsourcing computation framework for multiple calculators

Outsourcing computation enables a computationally weak client to outsource the computation of a function f to a more powerful but untrusted server.The traditional outsourcing computation model forbids communication between players,but it has little effect.Based on the game theory,this paper establishes an outsourcing computation model which is more in line with the actual scene.Firstly,we construct a structural mapping relationship between security outsourcing computation and the optimization problem.Secondly,by designing the individual potential function and the global potential function,the individual goal is consistent with the global goal to ensure the correctness of the calculation results.Finally,in the information exchange environment between calculators,we construct a Zero-determinant strategy to ensure that the calculator chooses the strategy according to the predetermined target.

Adoption Strategy for Cloud Computing in Research Institutions: A Structured Literature Review

Currently, Kenyan research institutions Information Technology operations use external storage, within or without institutional network environments. This study presents a structured literature review of a cloud computing adoption strategy for research institutions in Kenya. The reviews objectives are: 1) to establish the characteristics/peculiarities and IT environments of research institutions in Kenya, 2) current cloud computing technologies, adoption approaches and drivers in the adoption of cloud computing. The findings are that there is need for an adoption strategy for Cloud computing in the Kenyan research Institutions that will use a DOI and TOE combined approach while addressing technological, organizational and environmental factors. The findings are used to propose a cloud computing adoption strategy for the Kenyan Research Institutions in future research.

Parallel scheduling strategy of web-based spatial computing tasks in multi-core environment

In order to improve the concurrent access performance of the web-based spatial computing system in cluster,a parallel scheduling strategy based on the multi-core environment is proposed,which includes two levels of parallel processing mechanisms.One is that it can evenly allocate tasks to each server node in the cluster and the other is that it can implement the load balancing inside a server node.Based on the strategy,a new web-based spatial computing model is designed in this paper,in which,a task response ratio calculation method,a request queue buffer mechanism and a thread scheduling strategy are focused on.Experimental results show that the new model can fully use the multi-core computing advantage of each server node in the concurrent access environment and improve the average hits per second,average I/O Hits,CPU utilization and throughput.Using speed-up ratio to analyze the traditional model and the new one,the result shows that the new model has the best performance.The performance of the multi-core server nodes in the cluster is optimized;the resource utilization and the parallel processing capabilities are enhanced.The more CPU cores you have,the higher parallel processing capabilities will be obtained.

Strategic Implications for E-Business Organizations in the Ubiquitous Computing Economy

The ubiquitous economy brings both pros and cons for the organizations. The third space emerged by the development of ubiquitous computing generates new concept of community. The community is tightly coupled with people, products, and systems. Organizational strategies need to be reshaped for the changing environment in the third space and community. Organizational structure also needs to change for community serving organization. Community serving concept equipped with the standardized technology will be essential. One of the key technologies, RFID service will play a key role to acknowledge identification and services required. When the needs for sensing the environment increase, technological requirement such as the ubiquitous sensor network (USN) will be critically needed..

Research on the Basic Computer Application Learning Strategies in Rural Middle School

Fewer scholars in China fixed on the basic computer application learning strategies for rural students; in this paper,I want to discuss them for those students,and give them some helpful strategies to promote basic computer application learning in rural areas of China.

＂Smart Cafe＂： A Mobile Local Computing System Based On Indoor Virtual Cloud

With network developing and virtualization rising, more and more indoor environment （POIs） such as care, library, office, even bus and subway can provide plenty of bandwidth and computing resources. Meanwhile many people daily spending much time in them are still suffering from the mobile device with limited resources. This situation implies a novel local cloud computing paradigm in which mobile device can leverage nearby resources to facilitate task execution. In this paper, we implement a mobile local computing system based on indoor virtual cloud. This system mainly contains three key components： 1）As to application, we create a parser to generate the ＂method call and cost tree＂ and analyze it to identify resource- intensive methods. 2） As to mobile device, we design a self-learning execution controller to make offtoading decision at runtime. 3） As to cloud, we construct a social scheduling based application-isolation virtual cloud model. The evaluation results demonstrate that our system is effective and efficient by evaluating CPU- intensive calculation application, Memory- intensive image translation application and I/ O-intensive image downloading application.

Service Scheduling Based on Edge Computing for Power Distribution IoT

With the growing amounts of multi-micro grids,electric vehicles,smart home,smart cities connected to the Power Distribution Internet of Things(PD-IoT)system,greater computing resource and communication bandwidth are required for power distribution.It probably leads to extreme service delay and data congestion when a large number of data and business occur in emergence.This paper presents a service scheduling method based on edge computing to balance the business load of PD-IoT.The architecture,components and functional requirements of the PD-IoT with edge computing platform are proposed.Then,the structure of the service scheduling system is presented.Further,a novel load balancing strategy and ant colony algorithm are investigated in the service scheduling method.The validity of the method is evaluated by simulation tests.Results indicate that the mean load balancing ratio is reduced by 99.16%and the optimized offloading links can be acquired within 1.8 iterations.Computing load of the nodes in edge computing platform can be effectively balanced through the service scheduling.

MEC-Assisted Flexible Transcoding Strategy for Adaptive Bitrate Video Streaming in Small Cell Networks

Adaptive bitrate video streaming(ABR)has become a critical technique for mobile video streaming to cope with time-varying network conditions and different user preferences.However,there are still many problems in achieving high-quality ABR video streaming over cellular networks.Mobile Edge Computing(MEC)is a promising paradigm to overcome the above problems by providing video transcoding capability and caching the ABR video streaming within the radio access network(RAN).In this paper,we propose a flexible transcoding strategy to provide viewers with low-latency video streaming services in the MEC networks under the limited storage,computing,and spectrum resources.According to the information collected from users,the MEC server acts as a controlling component to adjust the transcoding strategy flexibly based on optimizing the video caching placement strategy.Specifically,we cache the proper bitrate version of the video segments at the edge servers and select the appropriate bitrate version of the video segments to perform transcoding under jointly considering access control,resource allocation,and user preferences.We formulate this problem as a nonconvex optimization and mixed combinatorial problem.Moreover,the simulation results indicate that our proposed algorithm can ensure a low-latency viewing experience for users.

Design of Underwater Robot Lines Based on a Hybrid Automatic Optimization Strategy

In this paper, a hybrid automatic optimization strategy is proposed for the design of underwater robot lines. Isight is introduced as an integration platform. The construction of this platform is based on the user programming and several commercial software including UG6.0, GAMBIT2.4.6 and FLUENT12.0. An intelligent parameter optimization method, the particle swarm optimization, is incorporated into the platform. To verify the strategy proposed, a simulation is conducted on the underwater robot model 5470, which originates from the DTRC SUBOFF project. With the automatic optimization platform, the minimal resistance is taken as the optimization goal;the wet surface area as the constraint condition; the length of the fore-body, maximum body radius and after-body＇s minimum radius as the design variables. With the CFD calculation, the RANS equations and the standard turbulence model are used for direct numerical simulation. By analyses of the simulation results, it is concluded that the platform is of high efficiency and feasibility. Through the platform, a variety of schemes for the design of the lines are generated and the optimal solution is achieved. The combination of the intelligent optimization algorithm and the numerical simulation ensures a global optimal solution and improves the efficiency of the searching solutions.

Path Computing Scheme with Low-Latency and Low-Power in Hybrid Cloud-Fog Network for IIoT

With the rapid development of the Industrial Internet of Things(IIoT),the traditional centralized cloud processing model has encountered the challenges of high communication latency and high energy consumption in handling industrial big data tasks.This paper aims to propose a low-latency and lowenergy path computing scheme for the above problems.This scheme is based on the cloud-fog network architecture.The computing resources of fog network devices in the fog computing layer are used to complete task processing step by step during the data interaction from industrial field devices to the cloud center.A collaborative scheduling strategy based on the particle diversity discrete binary particle swarm optimization(PDBPSO)algorithm is proposed to deploy manufacturing tasks to the fog computing layer reasonably.The task in the form of a directed acyclic graph(DAG)is mapped to a factory fog network in the form of an undirected graph(UG)to find the appropriate computing path for the task,significantly reducing the task processing latency under energy consumption constraints.Simulation experiments show that this scheme’s latency performance outperforms the strategy that tasks are wholly offloaded to the cloud and the strategy that tasks are entirely offloaded to the edge equipment.

On the Problems of Computer Network Maintenance and Security

伴随我国计算机网络事业的快速发展，我们的生活已与网络紧密相联，但随着数据网络的传播，安全问题也开始出现。网络安全所涉及到的知识面较广，其中与网络安全存在着重要关联的就是计算机网络维护工作的质量。为此，本文就通过计算机网络维护保障网络安全的具体策略展开了进一步探讨，希望能为行业发展提供一定参考。

Parallel Computing of Ocean General Circulation Model

This paper discusses the parallel computing of the third generation Ocean General Circulation Model (OGCM) from the State Key Laboratory of Numerical Modeling for Atmospheric Science and Geophysical Fluid Dynamics(LASG),Institute of Atmosphere Physics(IAP). Meanwhile, several optimization strategies for parallel computing of OGCM (POGCM) on Scalable Shared Memory Multiprocessor (S2MP) are presented. Using Message Passing Interface (MPI), we obtain super linear speedup on SGI Origin 2000 for parallel OGCM(POGCM) after optimization.

Designing an automated FAQ answering system for farmers based on hybrid strategies

Purpose: The purpose of this study is to develop an automated frequently asked question(FAQ) answering system for farmers. This paper presents an approach for calculating the similarity between Chinese sentences based on hybrid strategies.Design/methodology/approach: We analyzed the factors influencing the successful matching between a user's question and a question-answer(QA) pair in the FAQ database. Our approach is based on a combination of multiple factors. Experiments were conducted to test the performance of our method.Findings: Experiments show that this proposed method has higher accuracy. Compared with similarity calculation based on TF-IDF,the sentence surface forms and the semantic relations,the proposed method based on hybrid strategies has a superior performance in precision,recall and F-measure value.Research limitations: The FAQ answering system is only capable of meeting users' demand for text retrieval at present. In the future,the system needs to be improved to meet users' demand for retrieving images and videos.Practical implications: This FAQ answering system will help farmers utilize agricultural information resources more efficiently.Originality/value: We design the algorithms for calculating similarity of Chinese sentences based on hybrid strategies,which integrate the question surface similarity,the question semantic similarity and the question-answer similarity based on latent semantic analysis(LSA) to find answers to a user's question.

Latency Aware and Service Delay with Task Scheduling in Mobile Edge Computing

In a traditional Mobile Cloud Computing (MCC), a stream of data produced by mobile users (MUs) is uploaded to the remote cloud for additional processing throughout the Internet. Though, due to long WAN distance it causes high End to End latency. With the intention of minimize the average response time and key constrained Service Delay (network and cloudlet Delay) for mobile users (MUs), offload their workloads to the geographically distributed cloudlets network, we propose the Multi-layer Latency Aware Workload Assignment Strategy (MLAWAS) to allocate MUs workloads into optimal cloudlets, Simulation results demonstrate that MLAWAS earns the minimum average response time as compared with two other existing strategies.

Teaching mechanism empowered by virtual simulation: Edge computing–driven approach

With the rapid development of network and communication techniques,the teaching forms have become diversified.To enhance the education experience and improve the teaching environment,an increasing number of educational institutions have adopted virtual simulation technology.A typical teaching mechanism is to exploit Virtual Reality(VR)technology,which affords participants an immersive experience.Unquestionably,such a VRbased mode is highly approved.However,the performance of this technology requires further optimization.On one hand,for VR 360video,the current intraframe decision cannot adapt to rapid response demands.On the other hand,the generated data size is considerably large and fast computation may not be realized,depending on the local VR device.Therefore,this study proposes an improved teaching mechanism empowered by edge computing–driven VR,called VE4T,that involves two parts.First,an intraframe decision algorithm for VR 360videos is devised to realize the rapid responses.Second,an edge computing framework is proposed to offload some tasks to an edge server for computation,where a task scheduling strategy is developed to check whether a task needs to be offloaded.Finally,experiments are performed using a practical teaching scenario with some VR devices.The obtained results demonstrate that VE4T is more efficient than existing mechanisms.

Implementing an Information System Strategy: A Cost, Benefit, and Risk Analysis Framework for Evaluating Viable IT Alternatives in the US Federal Government

In the US Federal government, an analysis of alternatives (AoA) is required for a significant investment of resources. The AoA yields the recommended alternative from a set of viable alternatives for the investment decision. This paper presents an integrated AoA and project management framework for analyzing new or emerging alternatives (e.g., Cloud computing), as may be driven by an information system strategy that incorporates a methodology for analyzing the costs, benefits, and risks of each viable alternative. The case study in this paper, about a business improvement project to provide public health and safety services to citizens in a US Federal agency, is a practical application of this integrated framework and reveals the benefits of this integrated approach for an investment decision. The decision making process in the framework—as an integrated, organized, and adaptable set of management and control practices—offers a defensible recommendation and provides accountability to stakeholders.