A survey on mobility models for performance analysis in tactical mobile networks, Journal of Telecommunications and Information Technology, 2008, nr 2

In scenarios of military operations and catastrophes – even when there is no infrastructure available or left – there is a need for communication. Due to the specific context the communication systems used in these tactical scenarios need to be as reliable as possible. Thus, the performance of these systems has to be evaluated. Beside field-tests, computer simulations are an interesting alternative concerning costs, scalability, etc. Results of simulative performance evaluation strongly depend on the models used. Since tactical networks consist of, or, at least, contain mobile devices, the mobility model used has a decisive impact. However, in common performance evaluations mainly simple random-based models are used. In the paper we will provide classification and survey of existing mobility models. Furthermore, we will review these models concerning the requirements for tactical scenarios

Resource Allocation and Performance Optimization in Wireless Networks

As wireless networks continue streaking through more aspects of our lives, it is seriously constrained by limited network resources, in terms of time, frequency and power. In order to enhance performance for wireless networks, it is of great importance to allocate resources smartly based on the current network scenarios. The focus of this dissertation is to investigate radio resource management algorithms to optimize performance for different types of wireless networks. Firstly, we investigate a joint optimization problem on relay node placement and route assignment for wireless sensor networks. A heuristic binary integer programming algorithm is proposed to maximize the total number of information packets received at the base station during the network lifetime. We then present an optimization algorithm based on binary integer programming for relay node assignment with the current node locations. Subsequently, a heuristic algorithm is applied to move the relay nodes to the locations iteratively to better serve their associated edge nodes. Secondly, as traditional goal of maximizing the total throughput can result in unbalanced use of network resources, we study a joint problem of power control and channel assignment within a wireless mesh network such that the minimal capacity of all links is maximized. This is essentially a fairness problem. We develop an upper bound for the objective by relaxing the integer variables and linearization. Subsequently, we put forward a heuristic approach to approximate the optimal solution, which tries to increase the minimal capacity of all links via setting tighter constraint and solving a binary integer programming problem. Simulation results show that solutions obtained by this algorithm are very close to the upper bounds obtained via relaxation, thus suggesting that the solution produced by the algorithm is near-optimal. Thirdly, we study the topology control of disaster area wireless networks to facilitate mobile nodes communications by deploying a minimum number of relay nodes dynamically. We first put forward a novel mobility model for mobile nodes that describes the movement of first responders within a large disaster area. Secondly, we formulate the square disk cover problem and propose three algorithms to solve it, including the two-vertex square covering algorithm, the circle covering algorithm and the binary integer programming algorithm. Fourthly, we explore the joint problem of power control and channel assignment to maximize cognitive radio network throughput. It is assumed that an overlaid cognitive radio network (CRN) co-exists with a primary network. We model the opportunistic spectrum access for cognitive radio network and formulate the cross-layer optimization problem under the interference constraints imposed by the existing primary network. A distributed greedy algorithm is proposed to seek for larger network throughput. Cross-layer optimization for CRN is often implemented in centralized manner to avoid co-channel interference. The distributed algorithm coordinates the channel assignment with local channel usage information. Thus the computation complexity is greatly reduced. Finally, we study the network throughput optimization problem for a multi-hop wireless network by considering interference alignment at physical layer. We first transform the problem of dividing a set of links into multiple maximal concurrent link sets to the problem of finding the maximal cliques of a graph. Then each concurrent link set is further divided into one or several interference channel networks, on which interference alignment is implemented to guarantee simultaneous transmission. The network throughput optimization problem is then formulated as a non-convex nonlinear programming problem, which is NP-hard generally. Thus we resort to developing a branch-and-bound framework, which guarantees an achievable performance bound

Towards MANET-based Recommender Systems for Open Facilities

Nowadays, most recommender systems are based on a centralized architecture, which can cause crucial issues in terms of trust, privacy, dependability, and costs. In this paper, we propose a decentralized and distributed MANET-based (Mobile Ad-hoc NETwork) recommender system for open facilities. The system is based on mobile devices that collect sensor data about users locations to derive implicit ratings that are used for collaborative filtering recommendations. The mechanisms of deriving ratings and propagating them in a MANET network are discussed in detail. Finally, extensive experiments demonstrate the suitability of the approach in terms of different performance metrics. © 2021, The Author(s)

Un Intergiciel de Gestion du Contexte basé Multi-Agent pour les Applications d'Intelligence Ambiante

The complexity and magnitude of Ambient Intelligence scenarios imply that attributes such as modeling expressiveness, flexibility of representation and deployment, as well as ease of configuration and development become central features for context management systems.However, existing works in the literature seem to explore these development-oriented attributes at a low degree.Our goal is to create a flexible and well configurable context management middleware, able to respond to different scenarios. To this end, our solution is built on the basis of principles and techniques of the Semantic Web and Multi-Agent Systems.We use the Semantic Web to provide a new context meta-model, allowing for an expressive and extensible modeling of content, meta-properties (e.g. temporal validity, quality parameters) and dependencies (e.g. integrity constraints).In addition, we develop a middleware architecture that relies on Multi-Agent Systems and a service component based design. Each agent of the system encapsulates a functional aspect of the context provisioning processes (acquisition, coordination, distribution, use).We introduce a new way to structure the deployment of agents depending on the multi-dimensionality aspects of the application's context model. Furthermore, we develop declarative policies governing the adaptation behavior of the agents managing the provisioning of context information.Simulations of an intelligent university scenario show that appropriate tooling built around our middleware can provide significant advantages in the engineering of context-aware applications.La complexité et l'ampleur des scénarios de l'Intelligence Ambiante impliquent que des attributs tels que l'expressivité de modelisation, la flexibilité de representation et de deploiement et la facilité de configuration et de developpement deviennent des caracteristiques centrales pour les systèmes de gestion de contexte. Cependant, les ouvrages existants semblent explorer ces attributs orientés-developpement a un faible degré.Notre objectif est de créer un intergiciel de gestion de contexte flexible et bien configurable, capable de répondre aux différents scenarios. A cette fin, notre solution est construite a base de techniques et principes du Web Semantique (WS) et des systèmes multi-agents (SMA).Nous utilisons le WS pour proposer un noveau meta-modèle de contexte, permettant une modelisation expressive et extensible du contenu, des meta-proprietés (e.g. validité temporelle, parametres de qualité) et des dépendances (e.g. les contraintes d'integrité) du contexte.De plus, une architecture a base de SMA et des composants logiciels, ou chaque agent encapsule un aspect fonctionnel du processus de gestion de contexte (acquisition, coordination, diffusion, utilisation) est developpée.Nous introduisons un nouveau moyen de structurer le deploiement d'agents selon les dimensions du modèle de contexte de l'application et nous elaborons des politiques déclaratives gouvernant le comportement d'adaptation du provisionnement contextuel des agents. Des simulations d'un scenario d'université intelligente montrent que un bon outillage construit autour de notre intergiciel peut apporter des avantages significatifs dans la génie des applications sensibles au contexte

Understanding O-RAN: Architecture, Interfaces, Algorithms, Security, and Research Challenges

The Open Radio Access Network (RAN) and its embodiment through the O-RAN Alliance specifications are poised to revolutionize the telecom ecosystem. O-RAN promotes virtualized RANs where disaggregated components are connected via open interfaces and optimized by intelligent controllers. The result is a new paradigm for the RAN design, deployment, and operations: O-RAN networks can be built with multi-vendor, interoperable components, and can be programmatically optimized through a centralized abstraction layer and data-driven closed-loop control. Therefore, understanding O-RAN, its architecture, its interfaces, and workflows is key for researchers and practitioners in the wireless community. In this article, we present the first detailed tutorial on O-RAN. We also discuss the main research challenges and review early research results. We provide a deep dive of the O-RAN specifications, describing its architecture, design principles, and the O-RAN interfaces. We then describe how the O-RAN RAN Intelligent Controllers (RICs) can be used to effectively control and manage 3GPP-defined RANs. Based on this, we discuss innovations and challenges of O-RAN networks, including the Artificial Intelligence (AI) and Machine Learning (ML) workflows that the architecture and interfaces enable, security and standardization issues. Finally, we review experimental research platforms that can be used to design and test O-RAN networks, along with recent research results, and we outline future directions for O-RAN development.Comment: 33 pages, 16 figures, 3 tables. Submitted for publication to the IEE

Efficient Passive Clustering and Gateways selection MANETs

Passive clustering does not employ control packets to collect topological information in ad hoc networks. In our proposal, we avoid making frequent changes in cluster architecture due to repeated election and re-election of cluster heads and gateways. Our primary objective has been to make Passive Clustering more practical by employing optimal number of gateways and reduce the number of rebroadcast packets

Journal of Telecommunications and Information Technology, 2008, nr 2

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