Rachid El Azouzi

Energy Power-Aware Routing in OLSR Protocol

In ad hoc networks, where there is no infrastructure, batteries lifetime are scare resource. However, many routing protocols in ad hoc networks have been proposed to provide and maintain routes without taking into account energy consumption. Recently, power control in mobile ad-hoc networks has been the focus of extensive research. In this paper, we propose a new scheme to make energy aware routing in OLSR (optimized link state routing protocol). OLSR is one of the routing protocols under study by the IETF MANET Working Group. We develop a new heuristic that allow OLSR to find an optimal power path in which the maximum energy consumption on that path is smaller among the maximum energy consumption of all possible paths. We discuss via simulation the interplay between routing in new OLSR protocol and the medium access control (MAC). Also we study the overhearing impact on the energy power-aware routing protocol. Simulation results show that our scheme improves classical OLSR routing while taking into account lifetime of the network.

User Association and Resource Allocation Optimization in LTE Cellular Networks

As the demand for higher data rates is growing exponentially, homogeneous cellular networks have been facing limitations when handling data traffic. These limitations are related to the available spectrum and the capacity of the network. Heterogeneous networks (HetNets), composed of macro cells (MCs) and small cells (SCs), are seen as the key solution to improve spectral efficiency per unit area and to eliminate coverage holes. Due to the large imbalance in transmit power between MCs and SCs in HetNets, intelligent user association (UA) is required to perform load balancing and to favor some SCs attraction against MCs. As long term evolution (LTE) cellular networks use the same frequency sub-bands, user equipment may experience strong intercell interference (ICI), especially at cell edge. Therefore, there is a need to coordinate the resource allocation (RA) among the cells and to minimize the ICI. In this paper, we propose a generic algorithm to optimize UA and RA in LTE networks. Our solution, based on game theory, permits to compute cell individual offset and a pattern of power transmission over frequency and time domain for each cell. Simulation results show significant benefits in the average throughput and also cell edge user throughput of 40% and 55% gains respectively. Furthermore, we also obtain a meaningful improvement in energy efficiency.

Coordinated scheduling via frequency and power allocation optimization in LTE cellular networks

Due to Orthogonal Frequency Division Multiple Access (OFDMA) mechanism adopted in LTE cellular networks, intra-cell interference is nearly absent. Yet, as these networks are designed for a frequency reuse factor of 1 to maximize the utilization of the licensed bandwidth, inter-cell interference coordination remains an important challenge. In both homogeneous and heterogeneous cellular networks, there is a need for scheduling coordination techniques to efficiently distribute the resources and mitigate inter-cell interference. In this paper, we propose a dynamic solution of inter-cell interference coordination performing an optimization of frequency sub-band reuse and transmission power in order to maximize the overall network utility. The proposed framework, based on game theory, permits to dynamically define frequency and transmission power patterns for each cell in the coordinated cluster. Simulation results show significant benefits in average throughput and also cell edge user throughput of 40% and 55% gains when performing the frequency sub-band muting and power control. Furthermore, we also obtain a meaningful improvement in energy efficiency.

Identifying a volunteer-like dilemma in cooperative sensing-empowered cognitive radio networks

Cooperative sensing is a promising technique that enables secondary users (SUs) to combine their channel observations in order to improve the spectrum sensing accuracy. However, in an adversarial environment where the secondary nodes are particularly selfish and the spectrum sensing is energy costly, selfish SUs can easily exploit the spectrum sensing result without participating in the sensing process. In this paper, we model the cooperative sensing as a volunteer dilemma where SUs have the choice to volunteer in order to sense and share the spectrum sensing results, or to free ride the spectrum sensing and achieve possibly a higher profitability. We mainly give a full characterization of the Nash equilibria and prove a counterintuitive property that claims: the probability of volunteering decreases when the number of SUs increases. Additionally, we propose a practical negotiation algorithm in order to select efficiently one SU to access to the channel. Finally, we propose a distributed algorithm that converges to Nash equilibria and show its performance through simulation results.

Evolutionary dynamics of cooperative sensing in cognitive radios under partial system state information

Cooperative sensing enables secondary users to combine individual sensing results in order to attain sensing accuracies beyond those achieved by consumer RF devices. However, due to sensing costs, secondary users may prefer not to cooperate to the sensing task, leading to higher false alarm probability. In this paper, we study how information about the presence of cooperators affects the dynamics of cooperative sensing schemes. We consider two scenarios, namely the case when SUs cannot detect the presence of other potential cooperators, and the case when SUs have prior information on the presence of other SUs in radio range. Using an evolutionary game framework, we demonstrate that protocols delivering such type of information to SUs reduce cooperation and ultimately lead to degraded network performance. Finally, a learning process based on the replicator dynamics is proposed which is capable to drive the system to the evolutionary stable solution. The results of the paper are illustrated through numerical simulations.

Optimal Control of Storage Regeneration with Repair Codes

High availability of containerized applications requires to perform robust storage of applications’ state. Since basic replication techniques are extremely costly at scale, storage space requirements can be reduced by means of erasure and/or repairing codes.In this paper we address storage regeneration using repair codes, a robust distributed storage technique with no need to fully restore the whole state in case of failure. In fact, only the lost servers’ content is replaced. To do so, new clean-slate storage units are made operational at a cost for activating new storage servers and a cost for the transfer of repair data.Our goal is to guarantee maximal availability of containers’ state files by a given deadline. Upon a fault occurring at a subset of the storage servers, we aim at ensuring that they are repaired by a given deadline. We introduce a controlled fluid model and derive the optimal activation policy to replace servers under such correlated faults. The solution concept is the optimal control of regeneration via the Pontryagin minimum principle. We characterize feasibility conditions and we prove that the optimal policy is of threshold type. Numerical results describe how to apply the model for system dimensioning and show the tradeoff between activation of servers and communication cost.

Poster: aging control for smartphones in hybrid networks

The demand for Internet services that require frequent updates through small messages has tremendously grown in the past few years. Users of microblogging applications join interest groups and aim at receiving small messages from editors. As messages age, they get outdated and their utilities decrease. As a consequence, users must control when to receive updates. A user willing to receive an update activates his mobile device (e.g., iPhone), which then broadcasts periodic beacons to inform demands to service providers. Let the age of a message held by a user be the duration of the interval of time since the message was downloaded by such user. If a user activates his mobile device and is in the range of a service provider (WiFi access point or 3G antenna), an update is received and the age of the message held by the user is reset to one, at the expense of monetary and energy costs. Thus, users face a tradeoff between energy and monetary costs and their messages aging. To cope with such a tradeoff, users decide, based on the age of the stored message, whether to activate the mobile device, and if so, which technology to use (WiFi or 3G). We refer to a policy which determines activation decisions as a function of message ages as an aging control policy [1]. The goal of this paper is to devise efficient aging control policies.

A Taylor Series Expansion for H∞ Control of Perturbed Markov Jump Linear Systems

In a recent paper, Pan and Basar [19] have studied the H ∞ control of large scale Jump Linear systems in which the transitions of the jump Markov chain can be separated into sets having strong and weak interactions. They obtained an approximating reduced-order aggregated problem which is the limit as the rate of transitions of the faster time scale (which is a multiple of some parameter 1/∈) goes to infinity. In this paper we further investigate the solution of that problem as a function of the parameter ϵ. We show that the related optimal feedback policy and the value admit a Taylor series in terms of ϵ, and we compute its coefficients.