The Impact of Mobility Agent Based Micro Mobility on the Capacity of Wireless Access Networks

Pragad, A. Dev; Friderikos, Vasilis; Pangalos, Paul; Aghvami, Hamid

doi:10.1109/glocom.2007.947

Cited by 12 publications

(11 citation statements)

References 9 publications

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“…The Network Element Cognitive Manager (NECM) implements the MDE cycle at the NE level, whilst the Network Domain Cognitive Manager (NDCM) manages a set of NECMs, thus implementing sophisticated MDE cycle features. In order to test the key functionalities of the proposed solution, specific NM problems have been taken into account, under the wider scope of wireless networks coverage and capacity optimization family [32]. In the proposed test-bed, a heterogeneous wireless network environment has been deployed, consisting of several IEEE 802.11 Soekris access points (AP) [33] and an IEEE 802.16 Base Station (BS) [34], each embedding a NECM.…”

Section: Experimental Results For Network Coverage and Optimizationmentioning

confidence: 99%

Challenges for Enhanced Network Self-Manageability in the Scope of Future Internet Development

Chochliouros

Spiliopoulou

Alonistioti

2011

The Future Internet

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Abstract. The work examines perspectives from the inclusion of the autonomicity and self-manageability features in the scope of Future Internet's (FI) deployment. Apart from the strategic importance for further evolution, we also discuss some major future challenges among which is the option for an effective network management (NM), as FI should possess a considerably enhanced network manageability capability. We examine a new network manageability paradigm that allows network elements (NEs) to: be autonomously interrelated/controlled; be dynamically adapted to changing environments, and; learn the desired behaviour over time, based on the original context of the Self-NET research project effort. As self-organizing and self-managing systems have a considerable market impact, we identify benefits for all market actors involved. In addition, we incorporate some recent, but very promising experimental findings, mainly based on the context of a specific use-case for network coverage and capacity optimization, highlighting the way towards developing specific NM-related solutions, able to be adopted by the real market sector. We conclude with some essential arising issues.

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Section: Experimental Results For Network Coverage and Optimizationmentioning

confidence: 99%

Challenges for Enhanced Network Self-Manageability in the Scope of Future Internet Development

Chochliouros

Spiliopoulou

Alonistioti

2011

The Future Internet

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“…The MAs can become the source of bottleneck in the network as all traffic (both high and low QoS requirement traffic) within the network have to flow through these selected few nodes. The presence of MA also creates under utilized paths within the network that are disjoint from the path MA is located and preventing the usage of these paths reduces the capacity of the access network [4]. Figure 1 shows the effect MAs can have within an access network.…”

Section: Problem Description and Motivationmentioning

confidence: 97%

“…We follow the initial MCFP model for analyzing a network with MAs given in [4] and extend it to cover MA and non MA traffic and derive the M/M/1 queue based average packet delay within the network. We model the access network starting from the gateway to the ARs as a network with the gateway as the source and each AR as the destination.…”

Section: Analytical Model Of Access Networkmentioning

confidence: 99%

“…In other words, the objective of MCFP is to provide the maximum possible flows to satisfy the demands requested at each AR at the same time minimizing the network congestion. More detailed information and definitions are given in [4], [10]. Where, λ represents the maximum congestion in the network and is defined as, λ = max e∈E λ(e).…”

Section: A Mcfp Problem Definitionmentioning

confidence: 99%

“…Nevertheless, in such an architecture as shown in [4] the presence of MAs may reduce the capacity of the access network and increase the congestion. The location and the number of MAs have a direct impact on the loss in network capacity and congestion.…”

Section: Introductionmentioning

confidence: 98%

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Dynamic QoS Aware Route Optimization for Networks with Mobility Agents

Pragad

Pangalos

Friderikos

et al. 2009

2009 6th IEEE Consumer Communications and Networking Conference

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To minimize the large handover delays associated with Mobile IPv6 numerous micro-mobility protocols were proposed. In this paper, we consider the Mobility Agent (MA) based family of micro-mobility protocols such as Hierarchical Mobile IPv6 and Proxy Mobile IPv6 and focus on the issue of the bottlenecks that MAs can lead up to under high network load. We propose a Dynamic QoS aware Route Optimization with the aim of reducing the bottlenecks around MAs. We exploit the fact that not all classes of IP traffic require low handover latency support; for example, P2P traffic, web browsing, etc. do not require high QoS and are delay tolerant. Hence, such traffic classes can be forced to establish a direct connection with the CN and the routing policies at edge routers can ensure these traffic classes bypass the MA. The number of traffic classes that are to bypass the MA increases dynamically according to the congestion of the network. Results show that by implementing the dynamic route optimization the network utilization increases and the average packet delay in the network are reduced.

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QoS aware dynamic route optimization for Proxy Mobile IPv6 networks

Pragad¹,

Friderikos²,

Pangalos³

et al. 2011

Wireless Communications

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Proxy Mobile IPv6 is a network based mobility management solution and was proposed to address the shortcomings of the existing set of mobility management protocols. The presence of local mobility anchors (LMA) in PMIPv6 networks can lead constrained routing and create areas of bottleneck. This is due to all traffic to the mobile nodes (MNs) in the PMIPv6 domain having to flow to and from the LMA. Future IP networks will support a wide variety of sessions ranging for high QoS Video conferencing to FTP and P2P download. Providing the same level of mobility support for all of these sessions can lead to the resources of LMA being drained. To avoid this, we propose the QoS aware Dynamic Route Optimization scheme where the network identifies the lower QoS sessions and establishes a binding update with the correspondant node (CN) rather than with the LMA. To achieve this a flow based binding approach is followed. The level of congestion in the network is also considered as part of the mechanism. To ensure optimal performance of the proposed mechanism, routing policies are proposed. Simulation results show considerable benefit to the network in terms of reduction in blocking probability as well as reduction in tunnelling overhead cost in comparisons to no route optimization (RO) and adaptive route optimization (ARO) being deployed in the PMIPv6 networks.

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The Impact of Mobility Agent Based Micro Mobility on the Capacity of Wireless Access Networks

Cited by 12 publications

References 9 publications

Challenges for Enhanced Network Self-Manageability in the Scope of Future Internet Development

Challenges for Enhanced Network Self-Manageability in the Scope of Future Internet Development

Dynamic QoS Aware Route Optimization for Networks with Mobility Agents

QoS aware dynamic route optimization for Proxy Mobile IPv6 networks

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