Performace analysis of mipv4 vs mipv6
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Mobile IPv4 and Mobile IPv6 were simulated in NS2 to compare their performance. Packet drop and throughput were used as metrics. For TCP traffic over 200 seconds: MIPv4 had 3 dropped packets while MIPv6 had none. MIPv4 throughput was 13.12Mbps receiving, while MIPv6 was unlimited at 2.14Gbps receiving. In conclusion, MIPv6 performed better than MIPv4 according to the simulation results.
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This document discusses SpiderCloud Wireless and enterprise small cell systems. It provides an overview of SpiderCloud, including that it is based in Silicon Valley and has been deploying scalable enterprise small cell systems since 2011. It then examines a case study of a call center deployment with small cells, finding that usage was higher than expected, backhaul capacity was the limiting factor, and the small cells offloaded 45% of users from the macro network while increasing macro data rates. It concludes by discussing how radio planning can optimize capital utilization by considering macro and indoor networks together through targeted small cell deployments.
MIPV6 PROTOCOLS: A SURVEY AND COMPARATIVE ANALYSIS
As the future generation networks are envisioned to be heterogeneous in nature, seamless
mobility in such networks is an important issue. While IETF work groups have standardized
various mobility management protocols, such as Mobile IPv6 (MIPv6), Fast Handovers for
Mobile IPv6 (Predictive FMIPv6, and Reactive FMIPv6), Hierarchical Mobile IPv6 (HMIPv6),
Proxy Mobile IPv6 (PMIPv6) and Fast Handovers for PMIPv6 (Predictive FPMIPv6, and
Reactive FPMIPv6), out of which some are host based and some are network based, the
decision regarding which protocol suits the future networks is still a research issue. The study
of various mobility management protocols in terms handover latency and the number of hops is
needed to evaluate these protocols. Even though much study has been done in literature in terms
of handover latency, study still needs performance evaluation in terms of average hop delay. In
this paper we study various mobility management protocols by applying simple numerical
analysis. The study is carried out for performance evaluation of various mobility management
protocols in terms of average hop delay, wireless link delay, wired part delay, and binding
update and registration delay. In this work, the average hop delay is estimated in terms of total
handover latency and total number of hops contributing to each protocol. The study enables us
to make a few important observations regarding the performance of these mobility management
CSIR 5G Research
The document discusses leveraging SDN and NFV technologies to support 5G networks in emerging markets. It outlines the vision of 5G including enhanced mobile broadband, massive machine communications, and ultra-reliable low latency communications. It then describes the research group's objectives to provide thought leadership, develop human capital, drive innovation, and contextualize technologies for emerging market use cases. The group is developing an SDN/NFV testbed to demonstrate network slicing, edge computing, IoT connectivity, and more.
BULK BINDING UPDATE PROCEDURE FOR PMIPV6 BASED INTELLIGENT TRANSPORTATION SYS...
Intelligent transportation system (ITS) consists of moving networks, where the network mobility
(NEMO) basic support is adopted as a mobility management protocol for moving networks.
Even though NEMO basic support (NBS) provides a basic mobility support for ITS systems, the
mobile routers (MR) need to participate in the mobility signaling. In the literature, network
based mobility management such as Proxy Mobile IPv6 (PMIPv6) based solutions are explored
for mobility management. However, the signaling overhead incurred due to this approach is still
need to be optimized. In this paper, we introduce a bulk binding update solution for the
registration of MR with local mobility anchor (LMA) in moving networks. The bulk binding
update procedure uses a group identifier for group of MRs during the periodic binding update
process which reduces the signaling overhead compared with the basic PMIPv6 based
approach. The numerical results demonstrate that the proposed approach gives a better
performance in terms of signaling overhead and handover latency than NBS, and simplePIMPv6 based solutions.
Route Optimization in MIPv6 Experimental Test bed for Network Mobility: Trade...
Route Optimization in MIPv6 Experimental Test bed for Network Mobility: Trade...IJCSIS Research Publications
Route Optimization (RO) in Mobile Internet Protocol
Version Six (MIPv6) is a technique that enables a
Mobile Node (MN) and a Corresponding Node (CN)
to communicate directly by bypassing the Home Agent
(HA). RO is usually faced with the problem of Internet
Protocol (IP) multilayer tunnels due to pinball or suboptimal
routing. The generic consideration in
designing route optimization scheme is to use
minimum signaling information in the IPv6 packet
header. In order for optimization to take place in
MIPv6, a protocol called route optimization protocol
must be introduced. Route optimization protocol is
used basically to improve performance. Also RO can
also be described as a mechanism that eliminates the
inefficiency in tunneling of packets from MRs to their
HA before being sent to CNs over the Internet.
However, Network Mobility (NEMO) can be described
as a network whose point of attachment to the Internet
varies with time.
The tradeoff between the two protocols can provide a
significant impact on the networks. Furthermore, one
potential choice of selecting any of the protocols can
increase or decrease the degree of application in used.
The tradeoff in offloading solution can vary from
mobile access network and core mobile network.
Optimizing traffic breakout and support for mobility
are paramount to service operators. The study focused
on the development and evaluation of an experimental
test bed of route optimization in MIPv6 and
NEMO.The tradeoff between the two protocols was
examined. The results of the experimental test bed
shows the benefit of next generation of Internet
system, especially for real-time applications that
need to provide seamless connection with low handoff
latency.
International Journal of Computer Science and Information Security,IJCSIS ISSN 1947-5500, Pittsburgh, PA, USA
Email: ijcsiseditor@gmail.com
http://sites.google.com/site/ijcsis/
https://google.academia.edu/JournalofComputerScience
https://www.linkedin.com/in/ijcsis-research-publications-8b916516/
http://www.researcherid.com/rid/E-1319-2016Welcome to International Journal of Engineering Research and Development (IJERD)
The document presents an analytical model to reduce handoff latency in next generation wireless networks using Fast Mobile IPv6 (FMIPv6) and Hierarchical Mobile IPv6 (HMIPv6). It first provides background on mobility support in IP networks and issues with Mobile IPv4. It then summarizes various approaches proposed in literature to minimize handoff delay, including FMIPv6, HMIPv6, seamless IP, optimized smooth handoff, and approaches to reduce latency from duplicate address detection. The document focuses on modeling the handoff latency in FMIPv6 and HMIPv6 and analyzing factors that influence latency from the link and network layers during the handoff process. It aims to determine the probability distribution of handoff latency under different traffic
NovoNet Vision and Operators' Perspective for ONAP
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2) NovoNet envisions reconstructing network infrastructure, functions, and operations through technologies like NFV, SDN, and network slicing.
3) ONAP aims to be the global automation platform for network, infrastructure, and services across industries through open source components and reducing manual processes in virtualized environments like 5G.
4) The document provides details on NovoNet and ONAP goals to transform networks through virtualization, centralization, programmability, and automation.
draft-georgescu-bmwg-ipv6-tran-tech-benchmarking-00
Internet draft presentation: Benchmarking Methodology for IPv6 Transition Technologies (draft-georgescu-bmwg-ipv6-tran-tech-benchmarking-00). IETF 92, Dallas, Texas, USA
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WTSA-16_SG13_Presentation.pptx
Future networks including cloud computing, mobile and next-generation networks
This document discusses future networks and related technologies being studied by ITU-T Study Group 13, including 5G, software-defined networking, cloud computing, big data, mobility management, and more. It provides an overview of the study group's mandate, leadership structure, and work items covering requirements, architectures, and mechanisms for future networks.
Automation, Agility and NFV
Automation, Agility and NFV
The document discusses automation, agility, and network functions virtualization (NFV) in responding to over-the-top providers. It covers automation opportunities across the service lifecycle including order fulfillment, configuration, security, and analytics. Agility requires a DevOps approach using modeling languages and tools. NFV enables new services but faces challenges around integration and standards. Open source projects are important for NFV management and orchestration. Web giants like Facebook and Amazon use custom hardware and management tools rather than just commodity solutions.
ITU-T Study Group 13 Introduction
Achievements and future works of ITU-T Study Group 13 on Future networks including cloud computing, mobile and next-generation networks
Presented at WTSA-16 by Mr Leo Lehmann, Chairman of ITU-T Study Group 13
Mobility mangement rina iwcnc
The document discusses a RINA experiment evaluating mobility management in RINA networks. The experiment involved a mobile host moving between different wireless subnets and accessing applications over multiple distributed information field (DIF) layers. Mobility was managed through routing updates and designing the DIF layers to accommodate the scale and rate of change of mobile terminals. The experiment validated that RINA can support mobility without special protocols by leveraging its complete naming and addressing scheme.
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Performace analysis of mipv4 vs mipv6
- 1. Performance comparison of MIPv4 andPerformance comparison of MIPv4 and MIPv6MIPv6 Presented by: Md. Habibur Rahman (11-94853-2) Course: Mobile and Multimedia Network Instructor: Md. Manirul Islam
- 2. Introduction Mobile IP • MIPv4 • MIPv6 Simulation Environment Performance Metrics Simulation Result Conclusion AgendaAgenda
- 3. Foreign Agent (FA) Home Agent (HA) Corresponded Node (CN) Mobile Node (MN) Binding Update Data Transmission Home Network Foreign Network Mobile IPv4 (MIP)Mobile IPv4 (MIP)
- 4. Mobile IPv6 (MIPv6)Mobile IPv6 (MIPv6) Access Router (AR) Home Agent (HA) Corresponded Node (CN) Mobile Node (MN) Binding Update Data Transmission Home Network Foreign Network
- 5. MIPv4 • integrated in NS2 MIPv6 • MobiWAN Patch (ns-allinone-2.33) • Patch Link: • http://www.nicta.com.au/people/mehanio/ns misc Implementation of MIPImplementation of MIP
- 6. Network Simulator –NS2 Simulation Area 1200X1200 Simulation Time -200sec MAC/80211 Channel type - Channel/Wireless channel Two Radio propagation model Data Packet - TCP Simulation EnvironmentSimulation Environment
- 7. Simulation ParametersSimulation Parameters Parameters Values Simulation area 1200 X 1200 Mobile Host (MN) 1 Mobile IP MIPv4, MIPv6 Address Type Hierarchical Traffic type TCP Packet size 1040 bytes Simulation time 200s IEEE MAC Layer 802.11 Protocols DSDV Network interface type Phy/wirelessphy
- 11. Drop • Packet drop is equal to number of packets sent from source minus number of packet received in the path of destination i.e. Throughput • Measurement of number of packets passing through the network in a unit of time. Performance MetricPerformance Metric
- 12. Packet Type (Simulation Time 200 Sec) Mobile IP Total Sent packets Total Received packets Total dropped packets TCP MIPv4 1300 1297 3 Mipv6 29692 29692 0 Result AnalysisResult Analysis Packet Type (Simulation Time 200 Sec) Mobile IP Total Sending Throughput (kbps) Total Receiving Throughput (kbps) TCP MIPv4 131220000 129700000 Mipv6 2147483647 2147483647 Throughput Calculation Packet Drop Calculation
- 13. Simulate MIPv4 and MIPv6 in NS2 Performance compare by two metrics Require more performance analysis According to our discussion, MIPv6 performs better than MIPv4 ConclusionConclusion
- 14. Thank you