Academic literature on the topic 'SNA (Computer network architecture)'
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Journal articles on the topic "SNA (Computer network architecture)"
Allen, M. O., and S. L. Benedict. "SNA Management Services architecture for APPN networks." IBM Systems Journal 31, no. 2 (1992): 336–52. http://dx.doi.org/10.1147/sj.312.0336.
Full textZiemke, Tom. "Radar Image Segmentation Using Self-Adapting Recurrent Networks." International Journal of Neural Systems 08, no. 01 (February 1997): 47–54. http://dx.doi.org/10.1142/s0129065797000070.
Full textHsu, Ming-Fu, Te-Min Chang, and Sin-Jin Lin. "NEWS-BASED SOFT INFORMATION AS A CORPORATE COMPETITIVE ADVANTAGE." Technological and Economic Development of Economy 26, no. 1 (November 21, 2019): 48–70. http://dx.doi.org/10.3846/tede.2019.11328.
Full textSperanza, Nicholas A., Christopher J. Rave, and Yong Pei. "Energy-Efficient On-Platform Target Classification for Electric Air Transportation Systems." Electricity 2, no. 2 (April 6, 2021): 110–23. http://dx.doi.org/10.3390/electricity2020007.
Full textKøien, Geir M. "On Threats to the 5G Service Based Architecture." Wireless Personal Communications 119, no. 1 (February 19, 2021): 97–116. http://dx.doi.org/10.1007/s11277-021-08200-0.
Full textKaliva, Eleni, Dimitrios Katsioulas, Efthimios Tambouris, and Konstantinos Tarabanis. "Understanding Researchers Collaboration in eParticipation using Social Network Analysis." International Journal of Electronic Government Research 11, no. 4 (October 2015): 38–68. http://dx.doi.org/10.4018/ijegr.2015100103.
Full textAllen, Michael O., Sandra L. Benedict, and Marcia L. Peters. "Meeting the challenge of a peer-to-peer network: An SNA management services infrastructure for APPN." Journal of Network and Systems Management 1, no. 2 (June 1993): 189–212. http://dx.doi.org/10.1007/bf01035887.
Full textSood, Sandeep K. "SNA based QoS and reliability in fog and cloud framework." World Wide Web 21, no. 6 (January 27, 2018): 1601–16. http://dx.doi.org/10.1007/s11280-018-0525-x.
Full textGupta, Ashish. "Optimized Parallel Counting Sort Algorithm for Distinct Numeric Values on Biswapped Hyper Hexa-Cell Optoelectronic Network." International Journal of Computer Network and Information Security 14, no. 1 (February 8, 2021): 69–80. http://dx.doi.org/10.5815/ijcnis.2022.01.06.
Full textMei, Jing, Huahu Xu, Yang Li, Minjie Bian, and Yuzhe Huang. "MFCNet: Mining Features Context Network for RGB–IR Person Re-Identification." Future Internet 13, no. 11 (November 18, 2021): 290. http://dx.doi.org/10.3390/fi13110290.
Full textDissertations / Theses on the topic "SNA (Computer network architecture)"
Geha, Abbas. "Computer enhanced network design." Thesis, University of Sussex, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.344069.
Full textKatti, Sachin Rajsekhar. "Network coded wireless architecture." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/45885.
Full textIncludes bibliographical references (p. 183-197).
Wireless mesh networks promise cheap Internet access, easy deployment, and extended range. In their current form, however, these networks suffer from both limited throughput and low reliability; hence they cannot meet the demands of applications such as file sharing, high definition video, and gaming. Motivated by these problems, we explore an alternative design that addresses these challenges. This dissertation presents a network coded architecture that significantly improves throughput and reliability. It makes a simple yet fundamental switch in network design: instead of routers just storing and forwarding received packets, they mix (or code) packets' content before forwarding. We show through practical systems how routers can exploit this new functionality to harness the intrinsic characteristics of the wireless medium to improve performance. We develop three systems; each reveals a different benefit of our network coded design. COPE observes that wireless broadcast naturally creates an overlap in packets received across routers, and develops a new network coding algorithm to exploit this overlap to deliver the same data in fewer transmissions, thereby improving throughput. ANC pushes network coding to the signal level, showing how to exploit strategic interference to correctly deliver data from concurrent senders, further increasing throughput. Finally, MIXIT presents a symbol-level network code that exploits wireless spatial diversity, forwarding correct symbols even if they are contained in corrupted packets to provide high throughput reliable transfers. The contributions of this dissertation are multifold. First, it builds a strong connection between the theory of network coding and wireless system design. Specifically, the systems presented in this dissertation were the first to show that network coding can be cleanly integrated into the wireless network stack to deliver practical and measurable gains. The work also presents novel algorithms that enrich the theory of network coding, extending it to operate over multiple unicast flows, analog signals, and soft-information.
(cont.) Second, we present prototype implementations and testbed evaluations of our systems. Our results show that network coding delivers large performance gains ranging from a few percent to several-fold depending on the traffic mix and the topology. Finally, this work makes a clear departure from conventional network design. Research in wireless networks has largely proceeded in isolation, with the electrical engineers focusing on the physical and lower layers, while the computer scientists worked up from the network layer, with the packet being the only interface. This dissertation pokes a hole in this contract, disposing of artificial abstractions such as indivisible packets and point-to-point links in favor of a more natural abstraction that allows the network and the lower layers to collaborate on the common objectives of improving throughput and reliability using network coding as the building block. At the same time, the design maintains desirable properties such as being distributed, low-complexity, implementable, and integrable with the rest of the network stack.
by Sachin Rajsekhar Katti.
Ph.D.
Beverly, Robert E. 1975. "Statistical learning in network architecture." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/44210.
Full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 167-[177]).
The Internet has become a ubiquitous substrate for communication in all parts of society. However, many original assumptions underlying its design are changing. Amid problems of scale, complexity, trust and security, the modern Internet accommodates increasingly critical services. Operators face a security arms race while balancing policy constraints, network demands and commercial relationships. This thesis espouses learning to embrace the Internet's inherent complexity, address diverse problems and provide a component of the network's continued evolution. Malicious nodes, cooperative competition and lack of instrumentation on the Internet imply an environment with partial information. Learning is thus an attractive and principled means to ensure generality and reconcile noisy, missing or conflicting data. We use learning to capitalize on under-utilized information and infer behavior more reliably, and on faster time-scales, than humans with only local perspective. Yet the intrinsic dynamic and distributed nature of networks presents interesting challenges to learning. In pursuit of viable solutions to several real-world Internet performance and security problems, we apply statistical learning methods as well as develop new, network-specific algorithms as a step toward overcoming these challenges. Throughout, we reconcile including intelligence at different points in the network with the end-to-end arguments. We first consider learning as an end-node optimization for efficient peer-to-peer overlay neighbor selection and agent-centric latency prediction. We then turn to security and use learning to exploit fundamental weaknesses in malicious traffic streams. Our method is both adaptable and not easily subvertible. Next, we show that certain security and optimization problems require collaboration, global scope and broad views.
(cont.) We employ ensembles of weak classifiers within the network core to mitigate IP source address forgery attacks, thereby removing incentive and coordination issues surrounding existing practice. Finally, we argue for learning within the routing plane as a means to directly optimize and balance provider and user objectives. This thesis thus serves first to validate the potential for using learning methods to address several distinct problems on the Internet and second to illuminate design principles in building such intelligent systems in network architecture.
by Robert Edward Beverly, IV.
Ph.D.
Motiwala, Murtaza. "An architecture for network path selection." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43576.
Full textArtz, Michael Lyle 1979. "NetSPA : a Network Security Planning Architecture." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/29899.
Full textIncludes bibliographical references (leaves 93-96).
Attack scenario graphs provide a concise way of displaying all possible sequences of attacks a malicious user can execute to obtain a desired goal, such as remotely achieving root undetected on a critical host machine. NETSPA, the Network Security Planning Architecture, is a C++ system that quickly generates worst-case attack graphs using a forward-chaining depth-first search of the possible attack space using actions modeled with REM, a simple attack description language. NETSPA accepts network configuration information from a database that includes host and network software types and versions, intrusion detection system placement and types, network connectivity, and firewall rulesets. It is controlled by command line inputs that determine a critical goal state, trust relationships between hosts, and maximum recursive depth. NETSPA was shown to efficiently provide easily understood attack graphs that revealed non-obvious security problems against a realistic sample network of 17 representative hosts using 23 REM defined actions. The largest useful graph was generated within 1.5 minutes of execution. NETSPA-executes faster and handles larger networks than any existing graph generation system. This allows NETSPA to be practically used in combination with other security components to develop and analyze secure networks.
by Michael Lyle Artz.
M.Eng.
Lefelhocz, Christopher James. "Investigation of a preemptive network architecture." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/36457.
Full textIncludes bibliographical references (p. 81-82).
by Christopher Jame Lefelhcz.
M.S.
Umeh, Njideka Adaku. "Security architecture methodology for large net-centric systems." Diss., Rolla, Mo. : University of Missouri-Rolla, 2007. http://scholarsmine.mst.edu/thesis/Umeh_09007dcc8049b3f0.pdf.
Full textVita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed December 6, 2007) Includes bibliographical references (p. 60-63).
Iqneibi, Sami M. Carleton University Dissertation Engineering Electrical. "A blackboard architecture to support network fault diagnosis." Ottawa, 1992.
Find full textZheng, Xijia Ph D. Massachusetts Institute of Technology. "Cognitive optical network architecture in dynamic environments." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/126997.
Full textCataloged from the official PDF of thesis.
Includes bibliographical references (pages 149-154).
Emerging network traffic requires a more agile network management and control system to deal with the dynamic network environments than today's networks use. The bursty and large data transactions introduced by new technological applications can cause both high costs and extreme congestion in networks. The prohibitive cost of massive over-provisioning will manifest as huge congestions during peak demand periods. The network management and control system must be able to sense the traffic changes and reconfigure in a timely manner (in tens of milliseconds instead of minutes or hours) to use network resources efficiently. We propose the use of cognitive techniques for fast and adaptive network management and control of future optical networks. The goal of this work is to provide timely network reconfigurations in response to dynamic traffic environments and prevent congestion from building up.
We make a simplified model of the expected traffic arrival rate changes as a multistate Markov process based on the characteristics of the dynamic, bursty, and high granularity traffic. The traffic is categorized into different network traffic environments by the length of the network coherence time, which is the time that the traffic is unvarying. The tunneled network architecture is adopted due to its supremacy in reducing the control complexity when the traffic volume is at least one wavelength. In the long coherence time regime where traffic changes very slowly, the traffic detection performances of two Bayesian estimators and a stopping-trial (sequential) estimator are examined, based on the transient behaviors of networks. The stopping trial estimator has the fastest response time to the changes of traffic arrival statistics. We propose a wavelength reconfiguration algorithm with continuous assessment where the system reconfigures whenever it deems necessary.
The reconfiguration can involve addition or subtraction of multiple wavelengths. Using the fastest detection and reconfiguration algorithm can reduce queueing delays during traffic surges without over-provisioning and thus can reduce network capital expenditure and prevent wasting resources on erroneous decisions when surges occur. For traffic with moderate coherence time (where traffic changes at a moderate rate) and the short coherence time (where traffic changes quickly), the stopping-trial estimator still responds to the traffic changes with a short detection time. As long as the inter-arrival times of traffic transactions are independent, the algorithm is still optimum. The algorithm provides no prejudice on the exact network traffic distribution, avoiding having to sense and estimate detailed arrival traffic statistics.
To deal with fast-changing traffic, we model the transient convergent behaviors of network traffic drift as a result of traffic transition rate changes and validate the feasibility and utility of the traffic prediction. In a simple example when the network traffic rate changes monotonically in a linear model, the sequential maximum likelihood estimator will capture the traffic trend with a small number of arrivals. The traffic trend prediction can help to provide fast reconfiguration, which is very important for maintaining quality of service during large traffic shifts. We further investigate the design of an efficient rerouting algorithm to maintain users' quality of service when the incremental traffic cannot be accommodated on the primary path. The algorithm includes the fast reconfiguration of wavelengths in the existing lit and spatially routed fibers, and the setting up and lighting of new fibers.
Rerouting is necessary to maintain users' quality of service when the queueing delay on the primary path (determined by shortest path routing) exceeds the requirement. Our algorithm triggers reconfiguration when a queueing delay threshold is crossed on the primary path. The triggering by a threshold on the queueing delay is used due to its simplicity, and it is directly measurable by the exact traffic transaction sizes and the queue size, which reflect both the current network traffic environment and the network configurations. A dynamic rerouting algorithm implemented with a shortest path algorithm is proposed to find the secondary paths for rerouting. We make the conjecture that it is desirable that the alternate paths for rerouting have small numbers of hops and are disjoint with other busy paths when the hops on the path are independent. In addition, the conjecture suggests that a good candidate network topology should have high edge-connectivity.
Wavelength reservation for rerouted traffic does not maximize wavelength utilization. We make the conjecture that traffic with different sizes should be broken up into multi-classes with dedicated partitioned resources and the queueing delay should be normalized by the transmission time for rerouting triggering to realize better network utilization.
by Xijia Zheng.
Ph. D. in Computer Science and Engineering
Ph.D.inComputerScienceandEngineering Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
Wiedenhoeft, Paul Eric. "Analysis of the Naval Postgraduate School computer network architecture." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA289749.
Full textThesis advisor(s): A. Schoenstadt, James C. Emery. "September 1994." Bibliography: p. 153-161. Also available online.
Books on the topic "SNA (Computer network architecture)"
Coover, Edwin R. Systems network architecture (SNA) networks. Los Alamitos, Calif: IEEE Computer Society Press, 1992.
Find full text1947-, Czubek Donald H., ed. SNA: IBM's systems network architecture. New York: Van Nostrand Reinhold, 1992.
Find full textJames, Martin. SNA: IBM's networking solution. Englewood Cliffs, N.J: Prentice-Hall, 1987.
Find full textSchäfer, Werner, and Werner Schäfer. Systems network architecture. Workingham, England: Addison-Wesley, 1992.
Find full textKapoor, Atul. SNA: Architecture, protocols, and implementation. New York: McGraw-Hill, 1992.
Find full textBook chapters on the topic "SNA (Computer network architecture)"
Chang, Jiho, Jongsu Yi, and JunSeong Kim. "A Switch Wrapper Design for SNA On-Chip-Network." In Advances in Computer Systems Architecture, 405–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11572961_32.
Full textWeik, Martin H. "network architecture." In Computer Science and Communications Dictionary, 1084. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_12207.
Full textCole, Robert. "Network Systems Architecture." In Computer Communications, 104–18. London: Macmillan Education UK, 1986. http://dx.doi.org/10.1007/978-1-349-18271-8_8.
Full textWeik, Martin H. "system network architecture." In Computer Science and Communications Dictionary, 1721. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_18902.
Full textWeik, Martin H. "open network architecture." In Computer Science and Communications Dictionary, 1144. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_12812.
Full textBarksdale, William J. "Network Protocol and Architecture." In Practical Computer Data Communications, 319–84. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4684-5164-1_10.
Full textBhushan, Abhay K., and Dennis G. Frahmann. "Xerox Network Systems Architecture." In Computer Network Architectures and Protocols, 417–47. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4613-0809-6_15.
Full textPozefsky, Diane P., Daniel A. Pitt, and James P. Gray. "IBM’s Systems Network Architecture." In Computer Network Architectures and Protocols, 449–509. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4613-0809-6_16.
Full textYang, Yuanyuan, and Cong Wang. "Network Architecture and Principles." In SpringerBriefs in Electrical and Computer Engineering, 9–15. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17656-7_2.
Full textWang, Shuangbao Paul. "I/O and Network Interface." In Computer Architecture and Organization, 99–128. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5662-0_5.
Full textConference papers on the topic "SNA (Computer network architecture)"
Jiang, Hongxun, and Zongbin Li. "Architecture Model of Enterprise Computing Networks Based on SNA Methodology." In 2009 WRI World Congress on Computer Science and Information Engineering. IEEE, 2009. http://dx.doi.org/10.1109/csie.2009.796.
Full textBen Ahmed, Achraf, and Abderazek Ben Abdallah. "PHENIC: silicon photonic 3D-network-on-chip architecture for high-performance Heterogeneous many-core system-on-chip." In 14th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA2013). IEEE, 2013. http://dx.doi.org/10.1109/sta.2013.6914696.
Full textJoung, Junegak, and Harrison M. Kim. "Importance-Performance Analysis of Product Attributes Using Explainable Deep Neural Network From Online Reviews." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22382.
Full textMao, Min, and Xi Cheng. "Evolution Analysis of Foreign Trade Network Structructure Based on Complex Network SNA." In EBIMCS '19: 2019 2nd International Conference on E-Business, Information Management and Computer Science. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3377817.3377839.
Full textLiu, Ping. "A Space-time Analysis of Global Trade Network Based on SNA." In EBIMCS 2020: 2020 3rd International Conference on E-Business, Information Management and Computer Science. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3453187.3453306.
Full textKallappa, Pattada, and Haftay Hailu. "Automated Contingency and Life Management for Integrated Power and Propulsion Systems." In ASME Turbo Expo 2005: Power for Land, Sea, and Air. ASMEDC, 2005. http://dx.doi.org/10.1115/gt2005-68587.
Full text"Network Architecture." In Proceedings of 15th International Conference on Computer Communications and Networks. IEEE, 2006. http://dx.doi.org/10.1109/icccn.2006.286240.
Full textQadeer, Mohammed A., Afaq H. Khan, Juned A. Ansari, and Sariya Waheed. "IMS Network Architecture." In 2009 International Conference on Future Computer and Communication (ICFCC). IEEE, 2009. http://dx.doi.org/10.1109/icfcc.2009.106.
Full textBarla, Isil Burcu, Dominic Axel Schupke, and Georg Carle. "Virtual Network Simulator Architecture." In 2012 UKSim 14th International Conference on Computer Modelling and Simulation (UKSim). IEEE, 2012. http://dx.doi.org/10.1109/uksim.2012.96.
Full text"Computer architecture/network security [session events]." In 2012 Fourth International Conference on Advanced Computing (ICoAC). IEEE, 2012. http://dx.doi.org/10.1109/icoac.2012.6416878.
Full textReports on the topic "SNA (Computer network architecture)"
Johannes, James D., Andrew Fanning, Kyle Hoover, Tim Lewis, and Marsha Robinson. Computer Network Security and Directory Services Architecture. Fort Belvoir, VA: Defense Technical Information Center, March 2000. http://dx.doi.org/10.21236/ada392366.
Full textBelzer, M. R., and Y. M. Cho. Micro-Computer Network Architecture for Range Instrumentation Applications. Fort Belvoir, VA: Defense Technical Information Center, March 1988. http://dx.doi.org/10.21236/ada196971.
Full textMarkova, Oksana, Serhiy Semerikov, and Maiia Popel. СoCalc as a Learning Tool for Neural Network Simulation in the Special Course “Foundations of Mathematic Informatics”. Sun SITE Central Europe, May 2018. http://dx.doi.org/10.31812/0564/2250.
Full text