Intelligent hybrid cheapest cost and mobility optimization RAT selection approaches for heterogeneous wireless networks

The evolution of wireless networks has led to the deployment of different Radio Access Technologies (RATs) such as UMTS Terrestrial Radio Access Network (UTRAN), Long Term Evolution (LTE), Wireless Local Area Network (WLAN) and Mobile Worldwide Interoperability for Microwave Access (WiMAX) which are integrated through a common platform. Common Radio Resource Management (CRRM) was proposed to manage radio resource utilization in heterogeneous wireless networks and to provide the required Quality of Service (QoS) for allocated calls. RAT selection algorithms are an integral part of the CRRM algorithms. Their role is to decide, when a new or Vertical Handover (VHO) call is requested, which of the available RATs is most suitable to fit the need of the incoming call and when to admit them. This paper extends our earlier work on the proposed intelligent mobility optimization and proposes an intelligent hybrid cheapest cost RAT selection approach which aims to increase users' satisfaction by allocation users that are looking for cheapest cost connections to a RAT that offers the cheapest cost of service. A comparison for the performance of centralized load-balancing, proposed and distributed cheapest cost and mobility optimization algorithms is presented. Simulation results show that the proposed intelligent algorithms perform better than the centralized load-balancing and the distributed algorithms. © 2014 Academy Publisher

Sélection d’interface de communication dans les réseaux de capteurs multi-technologies

National audienceLes réseaux de capteurs sont composés de systèmes généralement contraints en énergie et communiquant via des liaisons sans fil.Cependant, le déploiement d'un tel réseau est limité par la portée radio et le débit de la technologie utilisée.Pouvoir choisir la technologie la plus adaptée au scénario permettrait de dépasser cette limite et de réduire la consommation énergétique tout en permettant la différenciation des flux de données."Technique for Order of Preference by Similarity to Ideal Solution" (TOPSIS) est une méthode permettant de comparer finement des technologies basées sur des attributs contradictoires.Mais elle est limitée par un phénomène d'anomalie de classement pouvant altérer la qualité de la sélection.De plus, TOPSIS nécessite des calculs complexes, augmentant la consommation d'énergie sur du matériel contraint.Dans cet article, nous proposons une méthode TOPSIS adaptée pour la sélection d'interface de communication sur du matériel contraint.L'évaluation de notre solution avec des modules FiPy de Pycom montre une amélioration du temps de calcul de 40% tout en assurant une similarité de classement avec TOPSIS de 80%

Performance analysis of the intelligent mobility optimization CRRM approach using a markovian chain model

Due to the increasing demand of wireless services, mobile technology has rapidly progressed towards the fourth generation (4G) networking paradigm. This generation will be heterogeneous in nature and it can be achieved through the integration of different Radio Access Technologies (RATs) over a common platform. Common Radio Resource Management (CRRM) was proposed to manage radio resource utilization in heterogeneous wireless networks and to provide required Quality of Service (QoS) for allocated calls. RAT selection algorithms are an integral part of the CRRM algorithms. Their role is to decide, when a new or Vertical Handover (VHO) call is requested, which of the available RATs is most suitable to fit the need of the incoming call and when to admit them. This paper extends our earlier work on the proposed intelligent hybrid mobility optimization RAT selection approach which allocates users in high mobility to the most suitable RAT and proposes an analytical presentation of the proposed approach in a multidimensional Markov chain model. A comparison for the performance of centralized load-balancing, distributed and the proposed intelligent mobility optimization algorithms is presented in terms of new calls blocking probability, VHO calls dropping probability, users' satisfactions probability, average networks load and average system throughput. Simulation and analytical results show that the proposed algorithm performs better than the centralized loadbalancing and distributed algorithms. © 2014 ACADEMY PUBLISHER

Personalised Handoff Decision for Seamless Roaming in Next Generation of Wireless Networks

The past three decades have experienced a phenomenal emergence of several wireless networks and technologies. This next generation of wireless networks (4G) will be integrated into one IP-backbone to offer improved services to the user. The features of 4G include: wide coverage, high data rates, seamless roaming and personalisation. This paper presents a personalised handoff decision method to offer personalisation in seamless roaming for the next generation of wireless networks. This is done by assigning profiles to different users with different preferences and using these profiles to offer personalised handoff. The integration of these two important features of 4G networks will provide the end user the ability to choose their own preferred networks while they roam freely between heterogeneous networks

Scalability study of backhaul capacity sensitive network selection scheme in LTE-wifi HetNet

Wireless Heterogeneous Network (HetNet) with small cells presents a new backhauling challenge which differs from those of experienced by conventional macro-cells. In practice, the choice of backhaul technology for these small cells whether fiber, xDSL, point–to-point and point-to-multipoint wireless, or multi-hop/mesh networks, is often governed by availability and cost, and not by required capacity. Therefore, the resulting backhaul capacity of the small cells in HetNet is likely to be non-uniform due to the mixture of backhaul technologies adopted. In such an environment, a question then arises whether a network selection strategy that considers the small cells’ backhaul capacity will improve the end users’ usage experience. In this paper, a novel Dynamic Backhaul Capacity Sensitive (DyBaCS) network selection schemes (NSS) is proposed and compared with two commonly used network NSSs, namely WiFi First (WF) and Physical Data Rate (PDR) in an LTE-WiFi HetNet environment. The proposed scheme is evaluated in terms of average connection or user throughput1and fairness among users. The effects of varying WiFi backhaul capacity (uniform and non-uniform distribution), WiFi-LTE coverage ratio, user density and WiFi access points (APs) density within the HetNet form the focus of this paper. Results show that the DyBaCS scheme generally provides superior fairness and user throughput performance across the range of backhaul capacity considered. Besides, DyBaCS is able to scale much better than WF and PDR across different user and WiFi densities

Lightweight network interface selection for reliable communications in multi-technologies wireless sensor networks

International audienceWireless sensor networks (WSN) are composed of hardware constrained and battery-powered devices that communicate wirelessly. WSN find more and more applications, but their deployment is limited among others by the range and the throughput of the communication technology used. Several technologies are available nowadays, with various performances, cost and coverage. One solution to overcome the deployment limitations and in some cases extend the coverage would be to dynamically select the technology based on the data requirements, environment, geographic location, etc. Thus we need multitechnologies WSN devices and efficient algorithms to select the best available technology in an autonomous and local way. This issue is known as Network Interface Selection (NIS). Multi-Attribute Decision Making (MADM) methods are an efficient tool to tackle NIS. Among MADM methods is Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). However, TOPSIS suffers from a rank reversal issue, which may alter the ranking quality. Furthermore, TOPSIS method is computationally heavy, which might increase the energy consumption of the constrained devices and the latency of the network. In this paper, we introduce a lightweight TOPSIS-based method tailored for NIS in WSN, allowing more reliable communications. Experimental results obtained on real hardware, i.e., Pycom FiPy modules, show an improvement in computation time of 38% while maintaining a selection similar to TOPSIS in 82% of runs

Delphi: A Software Controller for Mobile Network Selection

This paper presents Delphi, a mobile software controller that helps applications select the best network among available choices for their data transfers. Delphi optimizes a specified objective such as transfer completion time, or energy per byte transferred, or the monetary cost of a transfer. It has four components: a performance predictor that uses features gathered by a network monitor, and a traffic profiler to estimate transfer sizes near the start of a transfer, all fed into a network selector that uses the prediction and transfer size estimate to optimize an objective.For each transfer, Delphi either recommends the best single network to use, or recommends Multi-Path TCP (MPTCP), but crucially selects the network for MPTCP s primary subflow . The choice of primary subflow has a strong impact onthe transfer completion time, especially for short transfers.We designed and implemented Delphi in Linux. It requires no application modifications. Our evaluation shows that Delphi reduces application network transfer time by 46% for Web browsing and by 49% for video streaming, comparedwith Android s default policy of always using Wi-Fi when it is available. Delphi can also be configured to achieve high throughput while being battery-efficient: in this configuration, it achieves 1.9x the throughput of Android s default policy while only consuming 6% more energy

Integrated mobility and resource management for cross-network resource sharing in heterogeneous wireless networks using traffic offload policies

The problem of efficient use of resources in wireless access networks becomes critical today with users expecting continuous high-speed network access. While access network capacity continues to increase, simultaneous operation of multiple wireless access networks presents an opportunity to increase the data rates available to end-users even further using intelligent cross-network resource sharing. This paper introduces a new integrated mobility and resource management (IMRM) framework for automatic execution of policies for cross-network resource sharing using traffic offload and pre-emptive resource reservation algorithms. The presented framework enables both mobile-initiated and network-initiated resource sharing policies to be executed. This paper presents the framework in detail and analyses its performance using extensive ns-2 simulations of the operation of a set of static policies based on measured signal strength, and dynamic pre-emptive network-initiated policies in a WiFi/WiMAX scenario. The detailed evaluation of the static policies clearly shows that the quality of voice applications shows large deviation, mostly due to very different levels of delay in access networks. Based on these conclusions, this paper presents a design of two new dynamic policies and shows that such policies, when efficiently implemented using the new IMRM framework can greatly improve the capacity of the network to serve voice traffic with a minimal impact on the data traffic and with a very low signalling overhead