Marc St-Hilaire

A Survey of Opportunities for Free Space Optics in Next Generation Cellular Networks

Cellular wireless networks have consistently relied upon Radio Frequency (RF) channels to provide connectivity between users and base stations. RF channels have also provided, in large part, connectivity within the Radio Access Network (RAN) and the Core Network (CN) for the purpose of connecting mobile users to the Public Switched Telephone Networks (PSTN) and Internet. However, other methods may be necessary in order to provide the faster data rates required by many new and emerging applications. This paper provides a comprehensive overview of the potential role for Free Space Optical (FSO) communications within next generation cellular networks. The argument is made that the increasing number of base stations, as well as the advanced topologies supported by next generation cellular networks, pave the way for a growing reliance upon FSO communications, with a view to support the high bandwidth applications offered to mobile users.

Early detection of DDoS attacks against SDN controllers

A Software Defined Network (SDN) is a new network architecture that provides central control over the network. Although central control is the major advantage of SDN, it is also a single point of failure if it is made unreachable by a Distributed Denial of Service (DDoS) Attack. To mitigate this threat, this paper proposes to use the central control of SDN for attack detection and introduces a solution that is effective and lightweight in terms of the resources that it uses. More precisely, this paper shows how DDoS attacks can exhaust controller resources and provides a solution to detect such attacks based on the entropy variation of the destination IP address. This method is able to detect DDoS within the first five hundred packets of the attack traffic.

Expansion Model for the Controller Placement Problem in Software Defined Networks

In this letter, we propose a mathematical model for the controller placement problem in Software Defined Networks (SDN). More precisely, given a set of switches that must be managed by the controller(s), the model simultaneously determines the optimal number, location, and type of controller(s) as well as the interconnections between all the network elements. The goal of the model is to minimize the cost of the network while considering different constraints. The simulation results show that the model can be used to plan small scale SDN. When trying to solve larger instances of the problem, the solver is taking too much time and also running out of memory. The proposed model could be used by various enterprises and cloud-based networks to start integrating SDN or plan a new SDN.

The Performance of Greedy Geographic Forwarding in Unmanned Aeronautical Ad-Hoc Networks

The availability of accurate location information (for airborne purposes) in unmanned aeronautical ad-hoc networks (UAANETs) makes it possible to deploy geographic routing mechanisms as the main communication protocol in such networks. However, the performance of geographic routing is not obvious, especially for sparse networks (i.e., networks with low connectivity levels). In this paper, the main goal is to explore the effects of network sparsity on the performance of greedy geographic forwarding and to determine in different scenarios the percentage of source-destination pairs that can successfully establish communication based on greedy geographic forwarding only. To that end, Monte Carlo simulations have been performed to collect statistics in estimating the performance of UAANETs in sparse situations. Simulation results show that greedy geographic forwarding can be used for less critical applications of UAANETs. However, for applications with guaranteed delivery requirements, other alternatives should be combined with greedy geographic forwarding.

On Sensor Placement for Directional Wireless Sensor Networks

A directional sensor network is formed by directional sensors which may be oriented toward different directions. The sensing region of a directional sensor can be viewed as a sector in a two-dimensional plane. Therefore, a directional sensor can only choose one sector (or direction) at any time instant. Planning of directional sensor networks has received very little attention in the literature. In this paper, we discuss directional sensor placement which is a critical task in the planning of directional sensor networks. We also present an integer linear programming model whose goal is to minimize the number of directional sensors that need to be deployed to monitor a set of discrete targets in a sensor field. Numerical results demonstrate the viability and effectiveness of the model.

A tabu search algorithm for the global planning problem of third generation mobile networks

In this paper, we propose a tabu search (TS) algorithm for the global planning problem of third generation (3G) universal mobile telecommunications system (UMTS) networks. This problem is composed of three NP-hard subproblems: the cell, the access network and the core network planning subproblems. Therefore, the global planning problem consists in selecting the number, the location and the type of network nodes (including the base stations, the radio network controllers, the mobile switching centers and the serving GPRS (General Packet Radio Service) support nodes) as well as the interconnections between them. After describing our metaheuristic, a systematic set of experiments is designed to assess its performance. The results show that quasi-optimal solutions can be obtained with the proposed approach.

The Minimum Cost Sensor Placement Problem for Directional Wireless Sensor Networks

Unlike isotropic sensors, directional sensors have a finite angle of view and thus cannot sense the whole circular area around them. The sensing region of a directional sensor can be viewed as a sector in a 2D plane. A directional sensor network is formed by directional sensors which may be oriented toward different directions. In this paper, we present an integer linear programming model for the minimum cost sensor placement problem in directional sensor networks. The objective is to minimize the total cost of directional sensors by properly choosing the type and direction for each sensor to be installed in the sensor field. The model guarantees that all the targets are covered and sensor nodes can deliver their data to a sink node. Numerical results demonstrate the viability and effectiveness of the proposed model.

An energy optimizing scheduler for mobile cloud computing environments

In mobile cloud computing, mobile devices seek to minimize computation time and/or energy consumption based on task related or user defined constraints. In earlier work [1], we proposed to minimize the total energy consumption across all the mobile devices in a cyber foraging system using a scheduler that runs in a centralized broker node, in situations where a large number of mobile devices could be expected. In this paper, we extend our earlier task scheduling problem for a large number of mobile devices to a mobile cloud computing environment. We optimally solve the task scheduling problem for task assignment to minimize the total energy consumption across the mobile devices subject to user defined constraints. Our task scheduler model at the centralized broker optimally offloads tasks and provides significant reduction in energy consumption compared to the energy consumption when tasks are offloaded from the centralized scheduler without optimization.

Combined Reactive-Geographic routing for Unmanned Aeronautical Ad-hoc Networks

As a result of high mobility of Unmanned Aerial Vehicles (UAVs), designing a good routing protocol is challenging for Unmanned Aeronautical Ad-hoc Networks (UAANETs). Geographic-based routing mechanisms are seen to be an interesting option for routing in UAANETs due to the fact that location information of UAVs is readily available. In this paper, a combined routing protocol, called the Reactive-Greedy-Reactive (RGR), is presented for UAANET applications, which combines the mechanisms of the Greedy Geographic Forwarding (GGF) and reactive routing. The proposed RGR employs location information of UAVs as well as reactive end-to-end paths in the routing process. Simulation results show that RGR outperforms existing protocols such as Ad-hoc On-demand Distance Vector (AODV) in search UAANET missions in terms of delay and packet delivery ratio, yet its overhead is similar to traditional mechanisms.

Directional Sensor Placement with Optimal Sensing Range, Field of View and Orientation

The directional sensor placement problem is an essential part of any planning model for directional wireless sensor networks. Its goal is to find an optimal subset of locations where directional sensors should be placed so that the total network cost is minimized while the requirements of coverage and connectivity are satisfied. Directional sensors are characterized by three important parameters: sensing range, field of view and orientation. These parameters have significant impact on the overall cost of the directional sensor network. In this paper, we present an integer linear programming formulation for the directional sensor placement problem in which the goal is to minimize the network cost by appropriately choosing the values of the above parameters for each sensor to be installed in the sensor field. We show the viability and effectiveness of the proposed model through numerical results.