scholarly journals Military Simulation Big Data: Background, State of the Art, and Challenges

2015 ◽  
Vol 2015 ◽  
pp. 1-20 ◽  
Author(s):  
Xiao Song ◽  
Yulin Wu ◽  
Yaofei Ma ◽  
Yong Cui ◽  
Guanghong Gong
Keyword(s):  
Big Data ◽  
Large Scale ◽  
Rapid Development ◽  
Military Training ◽  
Great Success ◽  
Service Oriented Architectures ◽  
Weapon Systems ◽  
Service Oriented ◽  
High Resolution Models ◽  
Future Work

Big data technology has undergone rapid development and attained great success in the business field. Military simulation (MS) is another application domain producing massive datasets created by high-resolution models and large-scale simulations. It is used to study complicated problems such as weapon systems acquisition, combat analysis, and military training. This paper firstly reviewed several large-scale military simulations producing big data (MS big data) for a variety of usages and summarized the main characteristics of result data. Then we looked at the technical details involving the generation, collection, processing, and analysis of MS big data. Two frameworks were also surveyed to trace the development of the underlying software platform. Finally, we identified some key challenges and proposed a framework as a basis for future work. This framework considered both the simulation and big data management at the same time based on layered and service oriented architectures. The objective of this review is to help interested researchers learn the key points of MS big data and provide references for tackling the big data problem and performing further research.

Methodology and Software Components for E-business Development and Implementation

2013 ◽  
pp. 269-298
Author(s):  
Neven Vrcek ◽  
Ivan Magdalenic
Keyword(s):  
Open Source ◽  
Large Scale ◽  
Network Effects ◽  
Business Processes ◽  
Small And Medium Enterprises ◽  
Module Structure ◽  
Service Oriented Architectures ◽  
Service Oriented ◽  
Public Sectors ◽  
Medium Enterprises

Many benefits from implementation of e-business solutions are related to network effects which means that there are many interconnected parties utilizing the same or compatible technologies. The large-scale adoption of e-business practices in public sectors and in small and medium enterprises (SMEs)-prevailing economic environments will be successful if appropriate support in the form of education, adequate legislative, directions, and open source applications is provided. This case study describes the adoption of e-business in public sectors and SMEs by using an integrated open source approach called e-modules. E-module is a model which has process properties, data properties, and requirements on technology. Therefore e-module presents a holistic framework for deployment of e-business solutions and such e-module structure mandates an approach which requires reengineering of business processes and adoption of strong standardization that solves interoperability issues. E-module is based on principles of service-oriented architectures with guidelines for introduction into business processes and integration with ERP systems. Such an open source approach enables the spreading of compatible software solutions across any given country, thus, increasing e-business adoption. This paper presents a methodology for defining and building e-modules.

Rapid Development of Adaptable Situation-Aware Service-based Systems

2010 ◽  
pp. 104-139 ◽  
Author(s):  
S.S. Yau ◽  
S. Mukhopadhyay ◽  
H. Davulcu ◽  
D. Huang ◽  
R. Bharadwaj ◽  
...  
Keyword(s):  
Distributed Control ◽  
Homeland Security ◽  
Situation Awareness ◽  
Service Composition ◽  
Large Scale ◽  
Rapid Development ◽  
Control Flow ◽  
Agent Platform ◽  
Service Oriented ◽  
Adaptive Workflows

Service-based systems have many applications, such as collaborative research and development, e-business, health care, military applications and homeland security. In these systems, it is necessary to provide users the capability of composing appropriate services into workflows offering higher-level functionality based on declaratively specified goals. In a large-scale and dynamic service-oriented computing environment, it is desirable that the service composition is automated and situation-aware so that robust and adaptive workflows can be generated. However, existing languages for web services are not expressive enough to model services with situation awareness (SAW) and side effects. This chapter presents an approach to rapid development of adaptable situation-aware service-based systems. This approach is based on the a-logic and a-calculus, and a declarative model for SAW. This approach consists of four major components: (1) analyzing SAW requirements using our declarative model for SAW, (2) translating the model representation to a-logic specifications and specifying a control flow graph in a-logic as the goal for situation-aware service composition., (3) automated synthesis of a-calculus terms that define situation-aware workflow agents for situation-aware service composition, and (4) compilation of a-calculus terms to executable components on an agent platform. An example of applying our framework in developing a distributed control system for intelligently and reliably managing a power grid is given.

Community Structure in Service-Oriented Enterprises Collaboration Network

2011 ◽  
Vol 314-316 ◽  
pp. 2033-2036
Author(s):  
Fu Qiang Zhang ◽  
Ping Yu Jiang
Keyword(s):  
Community Structure ◽  
Large Scale ◽  
Collaboration Network ◽  
Service Oriented ◽  
Future Work ◽  
Clustering Behavior

Service-oriented manufacturing is a new manufacturing paradigm, which has appeared in large-scale enterprises cluster in recent years. In this paper, the property of community structure for service-oriented enterprises collaboration network (so-ECN) has been investigated. First, characteristics and modeling of so-ECN are presented. Then, implementing procedure of community structure is provided to evaluate the collaboration clustering behavior. Finally, the conclusions and future work are put forward.

Large-scale Performance Evaluation of e-Homecare Architectures Using the WS-NS Simulator

2011 ◽  
Vol 50 (05) ◽  
pp. 408-419 ◽  
Author(s):  
B. Volckaert ◽  
B. Dhoedt ◽  
F. De Turck ◽  
S. Van Hoecke
Keyword(s):  
Large Scale ◽  
Response Times ◽  
Service Selection ◽  
Network Simulator ◽  
Service Oriented Architectures ◽  
Selection Strategies ◽  
Service Oriented ◽  
Multiple Sclerosis Patients ◽  
Time Critical ◽  
Selection Algorithms

SummaryBackground: E-homecare creates opportunities to provide care faster, at lower cost and higher levels of convenience for patients. As e-homecare services are time-critical, stringent requirements are imposed in terms of total response time and reliability, this way requiring a characterization of their network load and usage behavior. However, it is usually hard to build testbeds on a realistic scale in order to evaluate large-scale e-home-care applications.Objective: This paper describes the design and evaluation of the Network Simulator for Web Services (WS-NS), an NS2-based simulator capable of accurately modeling service-oriented architectures that can be used to evaluate the performance of e-homecare architectures.Methods: WS-NS is applied to the Coplintho e-homecare use case, based on the results of the field trial prototype which targeted diabetes and multiple sclerosis patients. Network-unaware and network-aware service selection algorithms are presented and their performance is tested.Results: The results show that when selecting a service to execute the request, suboptimal decisions can be made when selection is solely based on the service’s properties and status. Taking into account the network links interconnecting the services leads to better selection strategies. Based on the results, the e-homecare broker design is optimized from a centralized design to a hierarchical region-based design, resulting in an important decrease of average response times.Conclusions: The WS-NS simulator can be used to analyze the load and response times of large-scale e-homecare architectures. An optimization of the e-homecare architecture of the Coplintho project resulted in optimized network overhead and more than 45% lower response times.

scholarly journals Evaluation of big data frameworks for analysis of smart grids

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Mohammad Hasan Ansari ◽  
Vahid Tabatab Vakili ◽  
Behnam Bahrak
Keyword(s):  
Big Data ◽  
Smart Grid ◽  
Cyber Security ◽  
Smart Grids ◽  
Large Scale ◽  
Rapid Development ◽  
Massive Data ◽  
Grid Data ◽  
Data Generator ◽  
And Performance

AbstractWith the rapid development of smart grids and increasing data collected in these networks, analyzing this massive data for applications such as marketing, cyber-security, and performance analysis, has gained popularity. This paper focuses on analysis and performance evaluation of big data frameworks that are proposed for handling smart grid data. Since obtaining large amounts of smart grid data is difficult due to privacy concerns, we propose and implement a large scale smart grid data generator to produce massive data under conditions similar to those in real smart grids. We use four open source big data frameworks namely Hadoop-Hbase, Cassandra, Elasticsearch, and MongoDB, in our implementation. Finally, we evaluate the performance of different frameworks on smart grid big data and present a performance benchmark that includes common data analysis techniques on smart grid data.

Peer-to-Peer Search Techniques for Service-Oriented Computing

2010 ◽  
pp. 44-63
Author(s):  
Lu Liu ◽  
Duncan Russell ◽  
Jie Xu
Keyword(s):  
Service Discovery ◽  
Large Scale ◽  
Resource Discovery ◽  
Peer To Peer ◽  
Great Success ◽  
P2p Networks ◽  
Search Techniques ◽  
P2p Systems ◽  
Service Oriented ◽  
And Performance

Peer-to-peer (P2P) networks attract attentions worldwide with their great success in file sharing networks (e.g., Napster, Gnutella, BitTorrent, and Kazaa). In the last decade, numerous studies have been devoted to the problem of resource discovery in P2P networks. Recent research on structured and unstructured P2P systems provides a series of useful solutions to improve the scalability and performance of service discovery in large-scale service-based systems. In this chapter, the authors systematically review recent research studies on P2P search techniques and explore the potential roles and influence of P2P networking in dependable service-based military systems.

Application research of urban subway traffic mode based on behavior entropy in the background of big data

2021 ◽  
pp. 1-14
Author(s):  
Wanxin Hu ◽  
Fen Cheng
Keyword(s):  
Big Data ◽  
Large Scale ◽  
Transportation Networks ◽  
Transportation Network ◽  
Rapid Development ◽  
Urban Transportation ◽  
Transportation System ◽  
Urban Traffic ◽  
Time Optimization ◽  
The City

With the development of society and the Internet and the advent of the cloud era, people began to pay attention to big data. The background of big data brings opportunities and challenges to the research of urban intelligent transportation networks. Urban transportation system is one of the important foundations for maintaining urban operation. The rapid development of the city has brought tremendous pressure on the traffic, and the congestion of urban traffic has restricted the healthy development of the city. Therefore, how to improve the urban transportation network model and improve transportation and transportation has become an urgent problem to be solved in urban development. Specific patterns hidden in large-scale crowd movements can be studied through transportation networks such as subway networks to explore urban subway transportation modes to support corresponding decisions in urban planning, transportation planning, public health, social networks, and so on. Research on urban subway traffic patterns is crucial. At the same time, a correct understanding of the behavior patterns and laws of residents’ travel is a key factor in solving urban traffic problems. Therefore, this paper takes the metro operation big data as the background, takes the passenger travel behavior in the urban subway transportation system as the research object, uses the behavior entropy to measure the human behavior, and actively explores the urban subway traffic mode based on the metro passenger behavior entropy in the context of big data. At the same time, the congestion degree of the subway station is analyzed, and the redundancy time optimization model of the subway train stop is established to improve the efficiency of the subway operation, so as to provide important and objective data and theoretical support for the traveler, planner and decision maker. Compared to the operation graph without redundant time, the total travel time optimization effect of passengers is 7.74%, and the waiting time optimization effect of passengers is 6.583%.

scholarly journals Hybrid Mobile-App. on Multi-MEC Platforms in NFV Environment

2018 ◽  
Vol 7 (4.38) ◽  
pp. 383
Author(s):  
Jinsul Kim ◽  
Akm Ashiquzzaman ◽  
Van Quan Nguyen ◽  
Sang Woo Kim
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Large Scale ◽  
Web Applications ◽  
Rapid Development ◽  
Query Languages ◽  
Vital Role ◽  
Mobile App ◽  
Network Function Virtualization ◽  
Nosql Databases

In recent times, practicality of web applications has become more reliant upon big-data orientated materials such 4K videos, hi-def. resolution images, lossless audios and massive texts. Structured Query Languages (SQL) faces compatibility issues with large scale databases. Because of this data storage problem, NoSQL databases are used for storing big-data. NoSQL databases have been recently gaining traction with many options such MongoDB, CouchDB, Redis and Apache Cassandra. One of the major restrictions companies, enterprises and developers encounter during developing an application is multiplicative cost of building a native programing across different platforms. Besides, network Function Virtualization (NFV) plays a vital role for providing services for utilizing such applications in larger and more effective scale. Hence, in this paper, we discussed our main motivation behind selecting Iconic Framework, a hybrid system for rapid development real-time application based on Firebase in the NFV environment cooperating with Mobile Edge Computing (MEC). As a result, this approach provides comparatively flexible features.  

SERVICE ORIENTED TECHNOLOGY MANAGEMENT TO IMPROVE ORGANIZATIONAL AGILITY

2009 ◽  
Vol 06 (01) ◽  
pp. 1-16 ◽  
Author(s):  
HALUK DEMIRKAN ◽  
MICHAEL GOUL
Keyword(s):  
Large Scale ◽  
Business Processes ◽  
Assessment Process ◽  
Service Orientation ◽  
Paradigm Shifts ◽  
Service Oriented Architectures ◽  
Services Computing ◽  
Business Environments ◽  
Critical Issues ◽  
Service Oriented

The service orientation — coupled with dynamic choreography of business processes, service oriented architectures and service oriented infrastructures — is a developing structure that carries with it the potential to improve agility in today's complex business environments. But because of the newness of the concept and the limited number of large-scale organizations ready or willing to be "early adopters," it is difficult to predict the organizational and technical impacts, understand the critical issues, or perform rigorous research on services computing. So, how should a company begin assessing the real impacts of these service orientation paradigm shifts? In this article, we established an integrated assessment process for creating an organizational roadmap to realize visions of how to deliver reliable, scalable enterprise processes built upon services-computing.

scholarly journals STLIS: A Scalable Two-Level Index Scheme for Big Data in IoT

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Yonglin Leng ◽  
Zhikui Chen ◽  
Yueming Hu
Keyword(s):  
Big Data ◽  
Large Scale ◽  
Rapid Development ◽  
Storage Space ◽  
Important Challenge ◽  
Rdf Data ◽  
The Internet Of Things ◽  
Dramatic Growth ◽  
High Storage ◽  
Effective Representation

The rapid development of the Internet of Things causes the dramatic growth of data, which poses an important challenge on the storage and quick retrieval of big data. As an effective representation model, RDF receives the most attention. More and more storage and index schemes have been developed for RDF model. For the large-scale RDF data, most of them suffer from a large number of self-joins, high storage cost, and many intermediate results. In this paper, we propose a scalable two-level index scheme (STLIS) for RDF data. In the first level, we devise a compressed path template tree (CPTT) index based on S-tree to retrieve the candidate sets of full path. In the second level, we create a hierarchical edge index (HEI) and a node-predicate (NP) index to accelerate the match. Extensive experiments are executed on two representative RDF benchmarks and one real RDF dataset in IoT by comparison with three representative index schemes, that is, RDF-3X, Bitmat, and TripleBit. Results demonstrate that our proposed scheme can respond to the complex query in real time and save much storage space compared with RDF-3X and Bitmat.

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