Moez Esseghir

Admission control in wireless ad hoc networks: a survey

Wireless mobile ad hoc networks (MANETs) have emerged as a key technology for next-generation wireless networking. Because of their advantages over other wireless networks, MANETs are undergoing rapid progress and inspiring numerous applications. However, many technical issues are still facing the deployment of this technology, and one of the most challenging aspects is the quality of service (QoS) provisioning for multimedia real-time applications. MANETs are expected to offer a diverse range of services to support real-time traffic and conventional data in an integrated fashion. Because of the diversified QoS requirements of these services, QoS models are needed for an efficient usage of network resources. One of the most crucial mechanisms for providing QoS support is admission control (AC). AC has the task of estimating the state of networks resources and thereby to decide which application data flows can be admitted without promising more resources than are available and thus violating previously made guarantees. In order to provide a better understanding of the AC research challenges in MANETs, this paper presents a detailed investigation of current state-of-the-art AC models in ad hoc networks. A brief outline of the admission function, feedback to route failures, as well as the advantages and drawbacks of each discussed model are given.

A continuous time Markov model for unlicensed spectrum access

Recent static spectrum allocations have created an opportunity to develop novel solutions that can efficiently share the available spectrum both in licensed and unlicensed bands. Considering the relative rarity of solutions for unlicensed spectrum access, in this paper, we propose a scheme, where the cognitive radio (CR) devices (equipped with agents) interact with their neighbors to form several coalitions over the unlicensed bands. These types of coalitions can provide a less-conflicted spectrum access as the agents mutually agree for spectrum sharing. Further, we present a continuous time Markov chain (CTMC) with queuing to model the user interactions with the movement of spectrum access process from one state to another and derive the important performance metric as the blocking probability. Numerical results are presented to observe the impact of forming multiple coalitions on the blocking probability.

Multi-Agent Systems Negotiation Approach for Handoff in Mobile Cognitive Radio Networks

The rapid growth of wireless services has imposed huge pressure on the fixed radio spectrum. The deficit in the limited radio frequency spectrum resources can be alleviated by adopting cognitive radio technology. This new concept aims to change the traditional static spectrum allocation into a dynamic one by exploiting unused frequencies. Researchers in cognitive radio context have been more interested in spectrum sensing and sharing concepts than spectrum handoff. However, node mobility still arises as a major issue. To this extend, we develop a new approach for spectrum sharing and handoff taking into account nodes mobility. Our proposal uses multi-agent systems negotiation that enables mobile cognitive radio terminals to switch to the best available spectrum band giving their applications requirements. We deploy agents on both primary and secondary users to exchange information and negotiate in order to have a better use of the spectrum, considering devices capabilities and requirements. Simulations results show that our approach achieves up to 97% of the whole spectrum utilization and reduces the number of spectrum handoffs.

A Multiagent Based Scheme for Unlicensed Spectrum Access in CR Networks

In recent wireless network domains static spectrum access is a major concern. Generally, this access leads to spectrum scarcity problem by creating empty holes or white spaces. However, the scarcity is temporary and can be alleviated if spectrum access is performed dynamically and efficiently. One important step towards dynamic spectrum access is the development of cognitive radio (CR) technology, which senses nearby spectrum portions (or bands) and tries to use them either opportunistically or by negotiating with the neighboring users. Nonetheless, dynamic spectrum access raises several challenges which need to be addressed in detail. These challenges include efficient allocation of spectrum for users in order to maximize spectrum utilization and to avoid user level conflicts both under licensed and unlicensed bands. In this paper, considering the relative rarity of solutions for unlicensed spectrum access and their inadequacy, we propose a scheme, where the CR devices (equipped with agents) interact with their neighbors to form several coalitions over the unlicensed bands. These types of coalitions can provide a less-conflicted access as the agents mutually agree for spectrum sharing and they allow other CR users to enter in their vicinity of acquired spectrum via bilateral message exchanges. Further, we present continuous time Markov chains to model the spectrum access process in continuous time and derive important performance metric as the blocking probability for without and with queuing systems. Amongst others, the important comparisons we made between analytical and simulation results in terms of blocking probability verify that our proposed model is correct. In essence, our proposed solution aims to increase dynamic spectrum usage by enabling cooperation between the users.

A Markov Chain Based Model for Congestion Control in VANETs

Vehicular networking has significant potential to enable diverse applications associated with traffic safety, traffic efficiency and infotainment. In this paper, we address the issue of congestion in Vehicular Ad Hoc Networks (VANETs). In VANETs, the periodic beacon broadcast may consume a large part of the available bandwidth, which may lead to severely affect the dissemination of the event-driven warning messages. To address this issue, we propose a novel Markov chain model that consists of four steps: priority assignment, buffer monitoring, congestion detection phase, and beacon transmission rate adjustment to facilitate emergency packets propagation. Our model brings many improvements to IEEE 802.11p as it allows anticipating congestion. The simulation tests show promising results and validate our solution.

Enhanced MIH (media independent handover) for collaborative green wireless communications

Summary In this paper, we address the issue of energy saving in wireless communication networks; a special interest is given to heterogeneous networks (HetNets) which are supposed to be the key feature of the future communication networks, namely, the 5G cellular networks [1]. In a HetNet, different communication technologies coexist; with the use of vertical handovers, the users could switch between the different operating ones. Our work aims to make the used protocols for vertical handover collaborative, in such a way to reduce the overall network energy consumption. Our study is based on Media Independent Handover (MIH) protocol [2]. We bring modifications into this later for energy saving purposes in order to create a green collaborative MIH protocol. The proposed enhancements on MIH protocol allow gathering detailed information about network state and using them as statistics and indicators to manage network density according to traffic load and users location. Our experiments are performed using NS2.29 with National Institute of Standards and Technology (NIST) add-on which implements the MIH protocol (802.21). By comparing the results while using our proposed contribution and the conventional MIH protocol, we can see that the modifications done allow a significant improvement in terms of energy saving while maintaining reliability. Copyright

Fully Distributed Approach for Energy Saving in Heterogeneous Networks

In this paper, we study the problem of energy consumption in Heterogeneous Networks (HetNets). With the billions of connected users, the use of HetNets is one of the promising solutions for future cellular technologies as they can handle high network capacity. The aim of this work is to study and improve the energy efficiency in HetNets. The underlying idea is to perform the energy saving process on a fully distributed manner without the need to know the global network state or to exchange messages. We first express the optimization problem where the optimal cell range expansion bias must be found to maximize the energy efficiency. Seen that the problem is NP- hard, we introduce a learning approach based on Multi-Armed Bandit (MAB) allowing the operating cells to learn, through multiple iterations, the best expansion bias to use.

Distributed opportunistic spectrum access with spatial reuse in cognitive radio networks

We formulate and study a multi-user multi-armed bandit (MAB) problem for opportunistic spectrum access (OSA) that exploits the temporal-spatial reuse of PU channels so that SUs who do not interfere with each other can make use of the same PU channel. We propose a three-stage distributed channel allocation policy for OSA, where SUs collaboratively find an optimal channel access grouping, and independently learn the channel availability statistics to maximize the total expected number of successful SU transmissions. We adopt a distributed synchronous greedy graph coloring algorithm to cluster SUs into maximal independent sets, and a distributed average consensus algorithm to learn the sizes of the independent sets, with SUs belonging to a larger set being assigned a smaller access rank. Each SU then independently learns the PU channel statistics using a revised ε-greedy policy based on its assigned access rank. We provide the theoretical upper bound for the regret, and simulations suggest that our proposed policy has a significantly smaller regret than a random access policy and an adaptive randomization policy.

Energy Efficient Aggregation in Wireless Sensor Networks

Wireless sensor networks are getting more and more attention from researchers and industrial communities. They consist of distributed event-based sensors and a base station for data processing. These sensor networks have severe energy constraints. Data aggregation mechanisms are used to decrease the power consumption in these networks by combining several messages. In this paper, we present an energy efficient data aggregation mechanism. In this mechanism, the node which is aggregating and transmitting the message to the base station is chosen based on its energy and proximity to the base station. The nodes decide to participate in the aggregation process based on a participation relevance function. The efficiency of this aggregation mechanism is shown through simulation results in terms of network lifetime and reception rate.

Optimizing the wireless sensor network lifetime under reliability constraint

Both network lifetime and reliability are of major concern in wireless sensor networks. In this paper, we propose to optimize the wireless sensor network lifetime under a reliability constraint. First, we define the reliability with regards to the accuracy of observations made through sensor nodes. Then, we introduce a function that links reliability to the average amount of energy consumed by the network when reporting an event to the data collector. Based on this function, we bring out the required number of successive readings to be performed in order to optimize both network lifetime and reliability. Subsequently, we give a different definition to the reliability in order to maximize the network lifetime by relaxing the reliability constraint. In this case, the reliability is defined with regards to the number of non-reported events. We show that the network lifetime does not increase indefinitely when relaxing the reliability constraint. Finally, we conclude that new node placement strategies should be designed for wireless sensor applications that tolerate losing events (i.e. events that are not reported to the data collector), in order to maximize their network lifetime.