Team dionysos

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Section: New Results

Wireless networks

Participants : Nizar Bouabdallah, Yassine Hadjadj Aoul, Adlen Ksentini, Bruno Sericola.

Wireless communications continues to pervade all aspects of our lives: wireless distribution of audio and video around the home, wireless solutions for logistics, wireless ticketing and access control, wireless sensors for agriculture, medical applications, etc. Meanwhile, audio/video streaming applications impose stringent requirements on communication QoS metrics and Quality of Experience (QoE). To cope with these aspects, operators are looking for efficient and cost effective solutions that ensure the scalability of their systems, the quality (QoS and QoE) of the supported services and their security. However, studies indicate that security mechanisms require extra resources at both the network and end-users, often impacting the perceived quality and sometimes degrading the overall system performance. In this line, we proposed in [52] an “agile” framework, dubbed as QoS2 (i.e., Quality of Service and Security), that protects the network from malicious usage and attacks. The proposed framework provides an adjustable level of security to ensure acceptable QoS/QoE employing a Multi Attribute Decision Model (MADM) approach. In [72] , we presented a delay-based admission control algorithm in IEEE 802.11. We presented an accurate delay estimation model to adjust the contention window size in real-time basis by considering key network factors, MAC queue dynamics, and application-level QoS requirements. Based on the abovementioned delay-based CW size we introduced a fully distributed admission control protocol to guarantee QoS.

While there have been many important advances in wireless technology in recent years, there are economic challenges in providing high-speed wireless access to less populated areas. A key technology which can help is satellite communications as it can be used in areas where there is no terrestrial alternative. Two critical issues arise when considering satellite systems in this context: firstly, satellite systems are very costly in general; and secondly, there are challenges in integrating satellite and terrestrial networks, particularly when terminal mobility is necessary. In [28] we give some insights towards solving both of these problems. Specifically, we focused on interworking between the satellite part of the network and its terrestrial counterpart. Interworking related operations are performed at newly defined entities called Interworking Gateways (IGWs). We defined modules of the technological solutions that will be incorporated in IGWs and to evaluate their performances via computer simulations.

Efficient mobility management is one of the major challenges for next-generation mobile systems. Indeed, a mobile node (MN) within an access network may cause excessive signaling traffic and service disruption due to frequent handoffs. The two latter effects need to be minimized to support QoS requirements of emerging multimedia applications. In our work, we propose a new adaptive micro-mobility management scheme designed to track efficiently the mobility of nodes so as to minimize both handoff latency and total signaling cost while ensuring the MNs QoS requirements [41] . We introduce the concept of residing area. Accordingly, the micro-mobility domain is divided into virtual residing areas where the MN limits its signaling exchanges within this local region instead of communicating with the relatively far away root of the domain at each handoff occurrence. A key distinguishing feature of our solution is its adaptive nature since the virtual residing areas are constructed according to the current network state and the QoS constraints. To evaluate the efficiency of our proposal, we compared our scheme with existing solutions using both analytical and simulation approaches. Numerical and simulation results show that our proposed scheme can significantly reduce registration updates and link usage costs and provide low handoff latency and packet loss rate under various scenarios.

Multi-hop wireless networks, called also wireless mesh networks (WMNs), has gained a large interest this last decade. One of the main advantages of WMN is their ability to increase the radio coverage as regards to the one-hop wireless networks. One concern with WMN is the radio resource utilization efficiency, which can be enhanced by managing efficiently the mobility of users as well as the interference effect among neighboring links. Our main objective is therefore to route efficiently the traffic generated by mobile nodes including the signaling messages in order to optimize network radio resource utilization. In other words, we aim at minimizing the total signaling cost by controlling the number of registration updates with the root of the domain. To achieve this, we propose new micro-mobility management schemes based on clustering techniques to track efficiently the mobility of nodes within the network. These mechanisms are conceived to minimize the total signaling cost of exchanged messages needed to manage the mobility of nodes as well as to optimize the link usage cost of the data traffic generated by each mobile user [40] .

As a second alternative to increase the capacity of wireless mesh networks, we propose using the cognitive radio (CR) capabilities. The capacity of a WMN is indeed dependent on the spectrum resources it has, and the efficiency with which it uses them [13] . In our work, we considered the use of cognitive radio to improve this efficiency, by allowing networks belonging to different service providers to share both spectrum and infrastructure resources according to several different models. Using an ILP based problem formulation, this approach is demonstrated to yield significant benefits to the networks, by increasing QoS or allowing the networks to decrease their spectrum requirements.

In large scale multi-hop wireless networks, flat architectures are typically not scalable. Clustering was introduced to support self-organization and enable hierarchical routing. When dealing with multi-hop wireless networks, robustness is a crucial issue due to the dynamism of such networks. Several algorithms have been designed for clustering. In [14] , we show that a clustering algorithm that previously exhibited good robustness properties, is actually self-stabilizing. We propose several enhancements to the scheme to reduce the stabilization time and thus improve stability in a dynamic environment. The key technique to these enhancements is a localized self-stabilizing algorithm for Directed Acyclic Graph (DAG) construction. We provide extensive studies (both theoretical and experimental) that show that our approach enables efficient yet adaptive clustering in wireless multi-hop networks.

On the other hand, Self-stabilization protocols are a useful technique to provide self-organization but their stabilizing time is related to the size of the network. A wide range of problems such as TDMA assignment or clustering may be solved thanks to local coloring on a graph model but with a tradeoff between the coloring time and the stabilization time of the protocol using the coloring. This stabilization time is related to the height of a directed acyclic graph induced by the colors, thus to the longest strictly ascending sequence of colors. In [24] , we model this height by the longest increasing contiguous sequence of non-independent uniform random variables. Then using a Markov chain approach, we obtain a theoretical upper bound on the stabilization time. More precisely, our results show the scalability properties of such a protocol, but also that using a large number of colors does not impact its stabilization time. In [23] , we show that a clustering algorithm, known for its good robustness properties, is actually self-stabilizing. We propose several enhancements to the scheme to reduce the stabilization time and thus improve stability in a dynamic environment. The key technique to these enhancements is a localized self-stabilizing algorithm for directed acyclic graph construction. We provide extensive studies (both theoretical and experimental) that show that our approach enables efficient yet adaptive clustering in wireless multihop networks.


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