Spectrum handoff strategies for multiple channels cognitive radio network

International audienceThis paper proposes a new spectrum handoff approach for multiple channels cognitive radio networks to support delay sensitive applications such as VoIP. The delay probability is estimated to determine whether and how to perform the handoff operation. Moreover, traffic prediction on licensed channels is also required in order to estimate the impairment in the delay. Since, the error of prediction still cannot be solved totally, therefore the backup channel solution is proposed to reduce the harmfulness of this impact. The delay probability density function is through various strategies of spectrum handoff for multiple channels cognitive radio

PiCasso: enabling information-centric multi-tenancy at the edge of community mesh networks

© 2019 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Edge computing is radically shaping the way Internet services are run by enabling computations to be available close to the users - thus mitigating the latency and performance challenges faced in today’s Internet infrastructure. Emerging markets, rural and remote communities are further away from the cloud and edge computing has indeed become an essential panacea. Many solutions have been recently proposed to facilitate efficient service delivery in edge data centers. However, we argue that those solutions cannot fully support the operations in Community Mesh Networks (CMNs) since the network connection may be less reliable and exhibit variable performance. In this paper, we propose to leverage lightweight virtualisation, Information-Centric Networking (ICN), and service deployment algorithms to overcome these limitations. The proposal is implemented in the PiCasso system, which utilises in-network caching and name based routing of ICN, combined with our HANET (HArdware and NETwork Resources) service deployment heuristic, to optimise the forwarding path of service delivery in a network zone. We analyse the data collected from the Guifi.net Sants network zone, to develop a smart heuristic for the service deployment in that zone. Through a real deployment in Guifi.net, we show that HANET improves the response time up to 53% and 28.7% for stateless and stateful services respectively. PiCasso achieves 43% traffic reduction on service delivery in our real deployment, compared to the traditional host-centric communication. The overall effect of our ICN platform is that most content and service delivery requests can be satisfied very close to the client device, many times just one hop away, decoupling QoS from intra-network traffic and origin server load.Peer ReviewedPostprint (author's final draft

Hybrid Spectrum Sharing through Adaptive Spectrum Handoff and Selection

International audienceSpectrum sharing is a key function to provide fairness allocation as well as service satisfaction across multiple users in cognitive radio networks. Even though spectrum sharing can benefit from spectrum handoff to enhance rate performance by switching from unavailable channels to available ones, the negative impact on handoff delay can cause significant service degradation. In this work, we present a hybrid spectrum sharing strategy that includes novel static and dynamic spectrum sharing algorithms based essentially on a rate compensation approach and adapted best fit algorithms. The static scheme is applicable for some specific network configurations where spectrum handoff is not necessary. Conversely, the dynamic scheme can benefit from spectrum handoff to increase the achieved rate and also compensate for the lost rate from the unavailable periods. These two sharing schemes are operated adaptively according to the current network environment. We compare our hybrid strategy with a fully dynamic one and an optimization framework. The proposed hybrid spectrum sharing demonstrates its effectiveness in terms of improving the overall service satisfaction and reducing the number of handoffs while the achieved rate is fulfilling compared to the optimal

Sélection et transfert de spectre adaptatifs dans les réseaux de radio cognitive

Cognitive radio is proposed as a promising solution for the next generation of wireless communication networks. Cognitive radio users are required to perform spectrum handoff from a wireless channel to another in order to cope with the dynamic spectrum environment imposed by licensed users. Spectrum handoff can cause transmission interruptions leading to the degradation of services. We study and develop efficient spectrum management strategies that aim to provide diverse service requirements for cognitive radio users. First, we propose novel spectrum handoff and selection strategies in order to satisfy a delay requirement. In particular, we estimate the delay of arrival packets based on the prior packets in the queue and compare it to a maximum delay bound. Then, we use the expected delays to estimate a delay violation ratio that guides the spectrum handoff and selection decisions. Our strategies reduce the number of spectrum handoff significantly compared to existing approaches while the delay requirement is guaranteed. Second, we consider the rate requirement by investigating the interaction between spectrum handoff and spectrum sharing through an optimization framework. The results provide useful insights and guidelines for designing efficient spectrum sharing heuristics that take into account spectrum handoff and selection strategies. Finally, we develop a heuristic for spectrum sharing that includes novel static and dynamic spectrum sharing algorithms based essentially on a rate compensation approach and adapted best fit algorithms. Our heuristic reduces the number of handoffs significantly while the achieved rate is fulfilling compared to the optimal.La radio cognitive est proposée comme une solution prometteuse pour la prochaine génération de réseaux de communication sans fil. Les utilisateurs de radio cognitive sont tenus d'effectuer des sauts entre les différents canaux sans fil non utilisés. Cependant il devra interrompre ses communications lorsqu'un utilisation licencié souhaitera utiliser ce canal. Les sauts de fréquences peuvent provoquer des interruptions de transmission conduisant à la dégradation des services. Nous étudions et développons des stratégies efficaces de gestion de spectre qui veillent aux divers besoins des services utilisant la radio cognitive. Tout d'abord, nous proposons un nouvel algorithme de transfert de spectre ainsi que de nouvelles stratégies de sélection de spectre afin de respecter les impératifs de délai. Nous estimons notamment le retard des paquets d'arrivée basé sur les paquets précédents dans la file d'attente en les comparant à un délai maximal limite. Ensuite, nous utilisons ces retards pour estimer un seuil de guidant les sauts de fréquence et les décisions de sélection. Puis, nous mettons l'accent sur les garanties de débit en examinant les intéractions autre les sauts de fréquences et le partage de spectre. Ces résultats nous donnent des indications et des lignes directrices afin de concevoir des heuristiques de partage de spectre prenant en compte les stratégies de sélection de canaux et les sauts de fréquences. Enfin, nous développons une heuristique pour le partage de spectre basé sur de nouveaux algorithmes du partage statique et dynamique du spectre. Ils sont basés essentiellement sur une approche de compensation de débit et de Best Fit Algorithms.PARIS-BIUSJ-Mathématiques rech (751052111) / SudocSudocFranceF

Efficient Dynamic Spectrum Sharing Through Rate Compensation and Spectrum Handoff

International audienceIn this work, we propose a heuristic for dynamic spectrum sharing in cognitive radio networks. The concept of rate compensation is introduced so that cognitive radio users are able to achieve their rate requirement by performing adequately spectrum handoffs. Indeed, performing spectrum handoff can increase the achieved rate obtained by moving from unavailable channels to available ones. However, handoffs should also be reduced to decrease handoff delays and access contention in the network which can in turn impact the achieved rate

Hybrid spectrum sharing through adaptive spectrum handoff for cognitive radio networks

International audienceSharing available resources in cognitive radio networks can benefit from spectrum handoff to enhance the rate performance by switching from current unavailable channels to the available ones. However, spectrum handoff can cause transmission interruptions leading to the degradation of services. In this work, we aim to balance the tradeoff between benefits of spectrum handoff and their negative impacts on spectrum sharing. Therefore, we develop an adaptive hybrid strategy that includes novel static and dynamic spectrum sharing based essentially on a rate compensation concept. The former is suitable when spectrum handoff is not necessary. The latter allows performing spectrum handoff to compensate the lost rate from the unavailable periods and improve the rate performance. We compare our hybrid strategy with a fully dynamic one and an optimization framework. Through simulations, we show that our strategy reduces the number of handoffs significantly while the achieved rate is fulfilling compared to the optimal