Section: New Results

Wireless Networks

Participants : Eitan Altman, Abdulhalim Dandoush.

The emerging technologies of IoT (Internet of Things), SDN (Software Defined Networking), and NFV (Network Function Virtualization) have a great potential for the information service innovation in the Cloud and big data era. In [26] , Jie Li (Tsukuba Univ.) in cooperation with Eitan Altman and with Corinne Touati (Inria Grenoble-Rhône-Alpes) have studied architecture issues in Internet of Things based on SDN with NFV implementation. The contribution of the paper is in providing a view point for integrating these technologies based on their existing standards.

Self-Organizing Network (SON) technology aims at autonomously deploying, optimizing and repairing the Radio Access Networks. In [31] , Abdoulaye Tall, Zwi Altman (Orange, Issy les Moulineaux) and Eitan Altman showed that in certain cases, it is essential to take into account the impact of the backhaul state in the design of the SON algorithm. They revisit the Base Station load definition taking into account the backhaul state. They provide an analytical formula for the load along with a simple estimator for both elastic and guaranteed bit-rate traffic. They incorporate the proposed load estimator in a self-optimized Load Balancing algorithm. Simulation results for a backhaul constrained heterogeneous network illustrate how the correct load definition can guarantee a proper operation of the SON algorithm.

SON is further studied by these authors in [58] , [59] where the Vertical Sectorization (VS) is adapted. VS consists in creating vertically separated sectors in the original cell using an Active Antenna Systems (AAS) supporting two distinct beams with different downtilts. The total transmit power is split between the two sectors, while the frequency bandwidth can be reused by each sector, creating additional interference between the two sectors. For low traffic demand, VS may lead to performance degradation, while for high traffic demand in both sectors, VS is likely to bring about important capacity gains. Hence intelligent activation policy of VS is needed to fully benefit from this feature. The authors propose an approach taking advantage of the more focused downtilted beam. A dynamic alpha fair bandwidth sharing is proposed for low and medium load. It is autonomously replaced by full bandwidth reuse for high load scenarios using a threshold-based controller. A flow-level dynamic simulator is used to numerically validate the proposed mechanisms.

Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60% of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator's control, utilizing only partial information, yet achieving near-optimal solutions for the network. In [25] , Majed Haddad (UAPV), Piotr Wiecek (Institute of Mathematics and Computer Science, Wroclaw), Saidi Habib (Inria project-team Dyogene ) and Eitan Altman propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks. In particular, they investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. The authors effectively address the problem of how to intelligently configure a dynamic offset which optimizes network's global utility while users maximize their individual utilities.

Range-based localization algorithms in wireless sensor networks are more accurate but also more computationally complex than the range-free algorithms. The work on this topic by M. S. Elgamel (Arab Academy for Science, Technology & Maritime Transport, Egypt) and A. Dandoush, previously reported, has been published in [23] .