Unmanned Aerial Vehicles (UAVs) have seen extensive growth in both civilian and military sectors, driven by their versatility, ease of deployment, and expanding range of applications. However, this expansion has also exposed UAV systems to a growing number of cybersecurity threats. The MAVLink protocol, widely adopted for UAV-ground station communication, lacks native encryption, making it susceptible to interception and manipulation. This paper proposes a comprehensive solution based on the use of Hardware Security Modules (HSMs) to protect cryptographic keys and secure data transmission using the ChaCha20 encryption algorithm. Our approach integrates the HSM into the drone system, ensuring that sensitive keys are securely generated, stored, and accessed. We present the architecture, implementation details, and simulation results that confirm the feasibility and efficiency of the proposed solution, highlighting its potential to significantly enhance the security of UAV communications with minimal performance overhead.

In today’s business environment, companies use a wide range of methods to track and interact with customers, and one popular method is proximity marketing. In order to improve customer interaction and maybe influence purchasing decisions, proximity marketing entails the targeted delivery of material to individuals depending on their physical vicinity of a business site. However, because of this domain’s quick growth and the dearth of thorough research to date, it is difficult to establish standard operating procedures and boundaries, which makes regulation and implementation difficult. This paper proposes an improved framework for proximity marketing categorization in order to fill up the gaps. Our analysis, which is based on rigorous key performance criteria distinguishes three types of proximity marketing: context-aware, beacon-driven, and location-based. These sections are designed to give users a better-organized comprehension of the tool’s uses, encouraging a more methodical and knowledgeable approach for companies looking to maximize their client tracking tactics. This paper aims to aid practitioners, policymakers, and researchers in navigating the evolving terrain of proximity marketing and assuring the ethical and efficient use of client monitoring tools in modern corporate environments by defining clearer boundaries and standards.

A marketing strategy, which is a comprehensive plan, describes an organization's approach to promoting and selling its products and services, including target audience identification, brand message, and promotional techniques. Proximity marketing is a type of marketing strategy that uses wireless technologies to target customers based on their geographic location or proximity to a specific store or location. Businesses regularly use it to get customers to their physical locations, increase sales, and raise awareness of their brands. Using wireless technologies like Bluetooth and Wi-Fi, targeted messages are sent to customers' mobile devices when they are near a physical store in a sort of location-based marketing. Concerns around data security and privacy are one of the potential issues with proximity marketing. Customers can feel that their data is not under their control or that it is being collected and used without their consent. Businesses can take steps to address these worries, such as providing customers with the choice to opt-in or opt-out of receiving marketing messages and being explicit and honest about data collection and use. Even when customers explicitly accept the gathering and usage of their data, they may nevertheless feel uneasy about it. So we suggest a Control Algorithm (CA) inspired by the concept of the consensus algorithm in the blockchain, which would give people control over their data rather than businesses, in order to solve these concerns. And this can support the development of customer and business confidence.

Based on client location, preferences, and behavior data, proximity marketing has become a potent tool for businesses to interact with their target audience in a personalized way. However, questions regarding user control over personal data and privacy are raised by the use of customer tracking, notably through MAC addresses. We suggest a novel algorithm in this paper to improve user control and privacy protection in proximity marketing systems. Our system uses pseudonymous MAC address switching and a consensus-based methodology to give users more protection and control over their interactions. Through simulations and performance criteria including consensus correctness, convergence, and privacy protection, we assess the algorithm’s efficacy. The outcomes show how the algorithm can enhance user control, protect privacy, reduce the likelihood of tracking and profiling, and guarantee computing efficiency for proximity marketing applications. Our findings provide information for further study and practical use, as well as for the creation of privacy-enhancing proximity marketing tactics.

We formulate and study a multi-user multi-armed bandit (MAB) problem that exploits the temporal-spatial reuse of primary user (PU) channels so that secondary users (SUs) who do not interfere with each other can make use of the same PU channel. We first propose a centralized channel allocation policy that has logarithmic regret, but requires a central processor to solve a NP-complete optimization problem at exponentially increasing time intervals. To avoid the high computation complexity at the central processor and the need for SU synchronization, we propose a heuristic distributed policy that incorporates channel access rank learning in a local procedure at each SU at the cost of a higher regret. We compare the performance of our proposed policies with other distributed policies recently proposed for opportunistic spectrum access. Simulations suggest that our proposed policies significantly outperform the benchmark algorithms when spectrum temporal-spatial reuse is allowed.

We formulate and study a multi-user multi-armed bandit problem that exploits the temporal–spatial opportunistic spectrum access (OSA) of primary user (PU) channels, so that secondary users (SUs) who do not interfere with each other can make use of the same PU channel. We first propose a centralized channel allocation policy that has logarithmic regret, but requires a central processor to solve an NP-complete optimization problem at exponentially increasing time intervals. To overcome the high computation complexity at the central processor, we also propose heuristic distributed policies that, however, have linear regrets. Our first distributed policy utilizes a distributed graph coloring and consensus algorithm to determine SUs’ channel access ranks, while our second distributed policy incorporates channel access rank learning in a local procedure at each SU at the cost of a higher regret. We compare the performance of our proposed policies with other distributed policies recently proposed for temporal (but not spatial) OSA. We show that all these policies have linear regrets in our temporal–spatial OSA framework. Simulations suggest that our proposed policies have significantly smaller regrets than the other policies when spectrum temporal–spatial reuse is allowed.

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In a cognitive radio network, a primary user (PU) shares its spectrum with secondary users (SUs) temporally and spatially, while allowing for some interference. We consider the problem of estimating the no-talk region of the PU, i.e., the region outside which SUs may utilize the PU's spectrum regardless of whether the PU is transmitting or not. We propose a distributed boundary estimation algorithm that allows SUs to estimate the boundary of the no-talk region collaboratively through message passing between SUs, and analyze the trade-offs between estimation error, communication cost, setup complexity, throughput and robustness. Simulations suggest that our proposed scheme has better estimation performance and communication cost trade-off compared to several other alternative benchmark methods, and is more robust to SU sensing errors, except when compared to the least squares support vector machine approach, which however incurs a much higher communication cost.

Wireless technologies are becoming an essential part of our daily life. These technologies are expected to provide a wide variety of real-time applications; hence, there is a vital need to provide quality-of-Service (QoS) support. One of the key mechanisms to support QoS is traffic regulation. The basic idea behind traffic regulation is to measure the network state (e.g., load) in order to adapt the rate of carefully selected application flows. In this paper, we propose a novel model, called FuzzyWMN, which can be used to implement traffic adaptation in Wireless Mesh Networks (WMNs).The objective of FuzzyWMN is to compute the rate adaptation to apply to application flows according to the current network state; it relies on two parameters to meet this objective: (1) packet delays between sources and destinations; and (2) buffer occupancy of network nodes. The proposed model combines the essential notions of both fuzzy logic theory and Petri nets; this enables FuzzyWMN to realize traffic adaptation in networks characterized by information uncertainty and imprecision due to the dynamic traffic behavior, channel interferences, etc. Extensive simulations show that FuzzyWMN achieves stable end-to-end delay and good throughput under different network conditions.

It has been reported that the IEEE 802.11 MAC protocol and the TCP congestion control are highly problematic in terms of flow starvation in wireless mesh networks (WMNs). However, the economic features of IEEE 802.11 make it the commonly-used MAC protocol in WMNs. Therefore, solving starvation at the transport layer seems to be more appropriate. Indeed, the main starvation cause in TCP is that congestion is managed as a link-based problem. However, since bandwidth is a spatially-shared resource in WMNs, congestion is a neighborhood phenomenon that should be handled using mutual cooperation within a congested neighborhood. Such cooperation considerably consumes the already scarce bandwidth of WMNs causing more congestion. In this paper, we propose a neighborhood-aware and overhead-free congestion control scheme (NICC) that solves the starvation problem without impacting the scarce bandwidth of WMNs. NICC makes use of some underexploited fields in the IEEE 802.11 frame header, without modifying the standard frame size, to provide an overhead-free multi-bit congestion feedback; being overhead-free, this feedback allows performing neighborhood cooperation without generating control overhead. Furthermore, being multi-bit, it yields source nodes a fine-grained indication of the congestion degree, providing accurate rate control. The NICC performance in terms of starvation avoidance and bandwidth efficiency is proven through extensive simulations.

In a cognitive radio network, a primary user (PU) shares its spectrum with secondary users (SUs) temporally and spatially, while allowing for some interference. We consider the problem of estimating the interference coverage region of the PU, i.e., the region outside of which SUs may utilize the PU's spectrum regardless of whether the PU is transmitting or not. We propose a distributed boundary estimation algorithm that allows SUs to estimate the boundary of the coverage region collaboratively through message passing between SUs. We also propose a spatial spectrum sensing scheme based on the estimated boundary. Simulation results suggest that our proposed scheme has better estimation performance and communication cost trade-offs compared to centralized boundary estimation methods, and has better weighted throughputs than traditional fusion center based collaborative spectrum sensing methods.

Wireless mesh networks (WMNs) have recently emerged as a promising technology for next-generation of wireless communications. In WMNs, admission control is deployed to control traffic loads and to prevent the wireless mesh backbone from being overloaded. Existing admission control protocols could be classified as either stateful or stateless approaches, based on network state information. Both the approaches have their limitations; the stateful models suffer from the scalability issue, while the stateless ones have the false admission problem. This paper introduces a hybrid admission control model for WMNs, based on a temporal resource reservation and three traffic regulation schemes. In particular, we propose an analytical model to compute the appropriate regulation ratio for accepted flows and to guarantee that the congestion at intermediate nodes does not exceed a threshold value. In our model, the congested node may specify the moment of session re-establishment, besides of the new rate at which the session should transmit its data packets. Using extensive simulations, we demonstrate that our model achieves high resource utilization by computing new sessions rates in a dynamic traffic-load environment, and by satisfying the quality of service (QoS) constraints in terms of delay and packets loss.

While systems for collaborative distributed works focus on enhancing distributed work group productivity, little attention has been paid to their architecture. In fact, most of these systems rely on centralized ones for both user communications and data hosting. These architectures raise issues about the administrative control, maintenance and management of the central entity. In this paper, we present a new architecture based on peer-to-peer (P2P) model driven by user relationship. In our architecture, users choose the trusted co-workers they are connected with. Thus, only the most trusted users manage to obtain a high number of connections which grant them a relative authority inside the system.

In this paper, we propose a decentralized Self-Adaptive Aggregation Mechanism (SAAM) that adapts itself to the supporting network operational behavior by dynamically selecting the best aggregation approach to use. SAAM is based on (1) a fuzzy-based model that estimates the cost and performance of each aggregation scheme and (2) Multiple Attribute Decision Making (MADM) to make decisions on the best approach to use in this context. We validate SAAM by evaluating its fuzzy model and adaptation cost, and by comparing its utility to the one of existing situated and global schemes.

Severe unfairness and even complete starvation may occur when using TCP-like congestion control in IEEE 802.11-based Wireless Mesh Networks (WMNs). Indeed, IEEE 802.11 is inherently unfair; however, economies of scale make it the commonly used MAC protocol in WMNs. Moreover, TCP-like protocols do not account for links interdependency within a neighborhood. In WMNs, congestion should be mutually handled using explicit coordination among neighboring contending links. Furthermore, the set of flows that should be regulated, to control congestion, must include all those traversing a congested neighborhood. However, neighborhood coordination and flows notification significantly consume the already scarce bandwidth. In this paper, we propose NICC as neighborhood-based and overhead-free congestion control protocol aiming to avoid starvation without disturbing the bandwidth resources. Instead of experiencing IEEE 802.11 as a handicap, NICC proposes a lightweight optimization of some underexploited fields in the 802.11 frames header so as to provide implicit multi-bit congestion feedback. Such feedback ensures accurate rate control without inducing additional overhead. The effectiveness of NICC in terms of starvation avoidance and bandwidth efficiency is proved through in-depth simulation.

Wireless Mesh Networks have been traditionally deployed to offer Internet access. Following the general trend of convergence, they must increasingly provide customers with communication services whose quality constraints are heterogeneous. For large scale deployments, access to the Internet is provided by multiple gateways installed at different points in the network. Each gateway may be connected to the Internet with different technologies (ADSL, Ethernet, satellite, HF link) offering several alternatives to get out of the network with heterogeneous and dynamic performances. Routing QoS-constrained flows so that they always benefit from the best quality available is a challenging task. In addition to an intelligent gateway selection, it requires a forwarding system able to dynamically balance each flow towards the most suitable gateway. Existing candidates generate unnecessary complexity and overhead. In this paper, we propose a distributed and lightweight tag-based forwarding scheme that brings the flexibility required to work at the flow level, and supports dynamic traffic balancing among gateways with various bandwidth, delay or jitter characteristics. We implemented our forwarding scheme on an experimental testbed and applied it to the enforcement of simple gateway selection strategies. Results demonstrate the interest of our approach and its efficiency to dynamically forward specific flows among competing gateways.

Dynamic spectrum sharing is a promising technique to optimize the spectrum utilization. It allows the cognitive radio (CR) nodes to access the available spectrum dynamically, without being restricted to static usage. In this paper, we propose multiagent system (MAS) based solutions to achieve licensed and unlicensed dynamic spectrum sharing. Firstly, we present a cooperative approach where the CR nodes embarked with agents are capable of performing spectrum sharing by exchanging a series of messages with the neighboring licensed devices. While analyzing the performance of this proposal under ad-hoc wireless conditions, we show that it achieves good performance in term of spectrum access, without incurring greater communication cost. Then, we focus on enabling unlicensed spectrum sharing between the CR users. Our proposed solutions can achieve good performance while maintaining fair spectrum distribution.

Wireless mesh networks (WMNs) are expected to be a next step toward future generation of wireless networks due to their rapidly deployable nature and to the wide variety of their potential use. On the other hand, the daily increase of multimedia applications over wireless networks has generated a vital need to provide Quality of Service (QoS) support in WMNs, and works in this area are not sufficient for the moment. In this paper, we propose a QoS model, named WiRS, to support real time traffic over WMNs. WiRS consists of an admission control and two traffic regulation schemes. The admission control is based on a temporary reservation process allowing multiple flows to opportunistically benefit from reserved resources when they are not used by their correspondent flow. The traffic regulation schemes aim to dynamically adjust the injected traffic into the mesh backbone in order to avoid the congestion and to maintain the QoS requirements. A service differentiation mechanism is provided also through one of the regulation schemes in order to control the best effort traffic. Extensive simulations show that our proposal is able to provide stable end-to-end delay, high throughput and improved packet delivery ratio.

In the context of autonomous network management, the Autonomic Managers (AMs) need to collect management information from other elements in order to infer an overall state of the network considered by the decision making process. Two concurrent strategies are commonly used to achieve this operation. On one hand, approaches based on a situated view only gather information in a bounded neighborhood, thus providing a high reactivity to AMs for control operations. On the other hand, approaches based on a global view provide a good accuracy at the cost of a larger convergence time. Being able to choose the best approach in a given context is crucial to ensure the efficiency of an autonomous management system. Thus, in this paper, we perform an exhaustive performance analysis of these approaches by considering typical schemes of both of them, namely a one-hop and two-hops situated view against gossip- and tree-based global aggregation schemes. Metrics we consider are the convergence time, communication and computation cost, scalability and the accuracy of estimated aggregates. Given them, we show under which conditions an approach outperforms the others.

In recent years, Peer-to-Peer (P2P) architectures have emerged as a scalable, low cost and easily deployable solution for live video streaming applications. In these systems, the load of video transmission is distributed over end-hosts by enabling them to relay the content to each other. Since end-hosts are controlled by users, their behavior directly impact the performance of the system. To understand it, massive measurement campaigns covering large-scale systems and long time periods have been performed. In this paper, we gathered and synthesized results obtained through these measurements and propose a Bayesian network that captures and integrates all of them into a synthetic model. We apply this model to the anticipation of peer departures which is an important challenge toward the performance improvement of these systems and especially churn resilience. The validation of our proposal is performed through intensive simulations that consider a streaming system composed of thousand users over two hundred days. We especially study two deployment scenarios: a system-scale one and a local one. We also compare our proposal with two standard estimators and we show under which conditions an estimator outperforms the others.

The emergence of real-time applications and their widespread usage in communication have generated the need to provide quality-of-Service (QoS) support in wireless networks environments. One of the most crucial mechanisms of a model for providing QoS support is the traffic regulation. In the aim of better representing and analyzing the decision making policy of the traffic adaptation process in wireless mesh networks (WMN), we propose a novel model named FuzzyWMN. The proposed model combines the essential notions of both fuzzy logic theory and Petri nets; this enables FuzzyWMN to achieve the traffic adaptation process in the context of dynamic network events characterized by the uncertainty and imprecision information, due to the dynamic traffic behavior, channels interference, etc. The evaluation of FuzzyWMN performances, compared to AIMD-SWAN and IEEE 802.11, was studied under different network and traffic conditions. The promising results obtained from extensive simulations confirm that the traffic adaptation based on the fuzzy design can achieve stable end-to-end delay, and good throughput under different network conditions.

Nowadays, real time traffic over wireless networks is increasing sharply. In addition, network scale is larger due to new facilities as offered by wireless mesh networks. However, the differences between (1) the infrastructure capacities, (2) the end users devices technologies, (3) the number of users, and (4) the number of real time applications are implying the need of more dynamic quality of service (QoS) models. Traditional QoS models are not always suitable to fill out the gap between the four cited points. We are mentioning more QoS degradation due to network congestion. Therefore, in this paper, we propose a novel, dynamic and persistent traffic adaption model, called FTAM. Its main role is to avoid as maximum as possible network congestion. FTAM is based on the fuzzy logic, which is known by its dynamicity and efficiency in uncertain environment. By monitoring the nodes queues evolution, FTAM estimates network congestion and makes the suitable traffic adaptation step. Extensive simulations have proved the efficiency of FTAM in terms of real time traffic QoS guarantee and preventive congestion control.

In the context of forest fire management, wireless communication is an indispensable tool. It insures events information transmission and communication between fire defenders. Traditionally, cellular networks (CNs) are used during crisis. However due to the lack of population in far forests, CNs suffer from coverage problems. In addition, the experience has proved some reachability and capacity problems of CNs. In this paper, we propose a mesh and sensor network model as a wireless communication support for forest fire management. The sensor nodes (SNs) penetrate dangerous zones to aggregate events' data and to guide rescuers to safe paths. The mesh nodes (MNs) insure communication between rescuers, and data and video transfer. Our models are empowered by a multi-agent system (MAS) to enforce the autonomy of the nodes and a fuzzy logic model to guarantee the quality of service (QoS). The simulations have proved the efficiency of our models to help in the management of forest fire.

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.

One of the vision of next generation networks is an all-IP network supporting heterogeneous access technologies for the purpose of providing the mobile user with roaming capability across different networks. To enable this type of mobility known as vertical handover (VHO), an intelligent technique is needed in order to perform the service continuity. This paper presents a multi-agent based approach for the VHO. We propose to introduce the agents in the mobile nodes (MNs) and Access Points (APs) to collect the necessary information from the environment. Based on this information, agents will anticipate the handover in order to reduce the handover latency. We have defined three behaviors (Network Monitoring, Decision, and Network Selection) for the agents that will assist us in anticipating the handover.

In this paper we are interested in solving the problems of continuity of service using a Multiagent System (MAS) deployed on Mobile Ad-Hoc Networks (MANETs). We investigate the aspects of mobility and the losses it costs in terms of continuity of service. The aim of this research is the development of agents' coordination protocols for these highly dynamic environments like MANETs. One of the difficulties in MANETs is the spontaneous mobility of nodes, especially when devices with limited resources are used. All the constraints of agents' development thus have to be re-examined in order to be adapted to these situations. In this paper, we propose two protocols Pessimistic Ad-hoc Coordination Protocol (PACP) and Optimistic Ad-hoc Coordination Protocol (OACP)) to provide coordination amongst the agents. In our considered ad-hoc scenario, the nodes represent the chargers and the wheelchairs upon which the intelligent agents are deployed. These protocols have been evaluated and tested using this scenario.

During a crisis situation, the incident commanders have to tackle several problems simultaneously, e.g., (1) the monitoring of a crisis evolution, (2) guiding and tracking of rescue persons and intervention robots, (3) monitoring rescue persons' health, etc. Thus, several solutions based on wireless sensor networks (WSNs) and cellular networks have been proposed. However, the real life experience has proved that the cellular networks' base stations may be collapsed or unreachable during a crisis situation. In addition, the WSNs have been generally deployed for one application, e.g., monitoring of an occurring event. However, today technologies offer sensor nodes (SN) with higher processing and communication capacity. Based on these capacities, this paper proposes a WSN solution, for crisis management, which is not based on any base station infrastructure. This solution proposes a tracking and data aggregation methods that could be run simultaneously to treat the three above mentioned problems. It is also empowered by a multi-agent system (MAS), which allows the SNs to cooperate and to better manage their batteries. Finally, the proposed solution has proved, through successive simulations, its efficiency in terms of tracking precision, end-to-end communication delay and power optimization.

This work presents a knowledge-based handover anticipation scheme. We propose to construct a knowledge plane using intelligent agents. Agents are delegated to information collection for nourishing the knowledge plane and also, handover decision and a proper network selection. We use the parameters of RSS, bandwidth, cost, user preferences, and mobility pattern of the mobile user. We estimate the future attachment point for the mobile user and anticipate the handover. Finally, we analyze the performance of our approach for (1) assuring the quality of service for different types of ongoing sessions during the handover, (2) reducing handover latency, (3) reducing the ping-pong effect and (4) signaling overhead.

The self-organizing and decentralized features of wireless mobile ad hoc networks make them suitable for a wide variety of applications. In this paper, we explore their use in rescue and relief applications in emergency situations. We propose to study the efficiency of some routing and MAC protocols under the client-server architecture. The presence of dynamic and adaptive routing and MAC protocols will enable ad hoc networks to be formed quickly, and ensure communications during the rescue operations. Extensive simulations were performed to show the impact of both the routing and MAC layer choice over multiple QoS parameters (delay, throughput, energy, etc.) in small and large scales rescue areas. We conclude the paper by some remarks that may be very useful for the relevant agencies to enhance the efficiency of rescue and relief operations.

The basic role of a wireless sensor network (WSN) is to collect information from the environment by many sensor nodes (SNs). The SN typically has a finite battery life and nodes' failures can lead to network partition. Therefore, it is important to minimize the energy usage of each sensor node and to manage the power of SN in critical position that their failure could divide the network. The current paper proposes a data aggregation scheme based on a multi-agent system to reduce the amount of communicated information and hence to reduce the power consumption. In addition, this approach manages the power of each SN following several criteria like its resident power, the importance of its information, the network density and its position within the WSN. Through successive simulations, in different network scales, the proposed algorithm proved interesting results in term of power consumption optimization and power management of nodes in critical positions.

Autonomic communications seek to improve the ability of network and services to cope with unpredicted change, including changes in topology, load, task, the physical and logical characteristics of the networks that can be accessed, and so forth. Broad-ranging autonomic solutions require designers to account for a range of end-to-end issues affecting programming models, network and contextual modeling and reasoning, decentralised algorithms, trust acquisition and maintenance---issues whose solutions may draw on approaches and results from a surprisingly broad range of disciplines. We survey the current state of autonomic communications research and identify significant emerging trends and techniques.

This paper reports on the quality of service (QoS) requirements and the performance of virtual environment (VE) applications deployed in IP networks. We are interested specifically in systems that support communication with end-user through force feedback devices known as haptic interfaces. Little is known about networked haptic interfaces in VE. Our goal is to understand such application QoS requirements as well as the effect of other traffic when they co-exist in the same network. In this paper, we compare the peer-to-peer model with the client-server model. Our motivation is to deploy distributed haptic VE applications (DHVE) over a network connecting two departments of Queen's University of Belfast. This deployment will be used for educational purposes and for implementing further research in this area, and will be evaluated by end-users; hence, the essential realization of network-based DHVE under realistic network conditions. A set of experiments was conducted to achieve this aim and their results are presented in this paper.

The Internet does not offer a priori definition and maintenance of quality of service to applications. Efforts to change this reality are being deployed by IETF, with IntServ and Diffserv. However, traffic behavior is still not well known. Consequently, each management mechanism has its advantages and disadvantages, and its applicability may depend on service behaviors. The objective of this article is to present simulated behavior of distinct network services submitted to different traffic management mechanisms. We also empirically evaluate mechanisms' behaviors when traffic conditions change. Traffic behavior is varied in terms of charge and nature. Finally, we map traffic conditions with best-fit mechanisms and configurations.

In this paper, we propose a time-based channel reservation algorithm (TCRA) suitable for handover and call admission control procedures in future mobile satellite systems. These systems are characterized by a high rate of handover attempts, which can degrade significantly their performance. Therefore, we propose TCRA, a scheme that guarantees a null handover failure probability by using a channel reservation strategy in the cells to be crossed by the user. The performance of TCRA has been compared to the guaranteed handover scheme. The TCRA reservation method has the advantage of a better channel utilization by locking the resources only for their expected time of use. A mathematical model has been developed for both schemes, and its results have been validated through simulations.

The evolution towards the broadband integrated services digital network (B-ISDN) is influenced by many factors. The most significant one is the emergence of a great number of services requiring different levels of QoS and bandwidth availability. The main services are video on demand (VoD), videoconference, data and voice transfer. It is particularly important to ensure quality of service is critical moments such as congestions in a fixed network or handover in a mobile environment. We particularly focused our work on traffic routing and we dealt with the problem of maintaining communications and sending traffic to mobile users in a WATM network. Many solutions can be adopted such as increasing the number of frequencies, choosing a transmission technique adapted to multiservice, optimizing the bandwidth on the fixed part of the mobile network. We particularly investigated the last solution and the way of making the bandwidth available by rerouting connection during a handoff execution. Our work concerns the mechanism which optimize the bandwidth utilization in a multi-services context with MSRA (multi-service rerouting algorithm). Discrete event simulations were run in order to validate our algorithm. It is shown that the use of such techniques leads to good performance results in terms of cell loss probability, new call blocking rate and dropping handover probability.

The third generation of wireless networks will be broadband and thus will be able to support several services with different constraints on their QoS such as transit delay for time sensitive connections or cell loss probability for non real time applications. However, in such networks, the mobile may traverse several cells during the communication. Thus, if the newly visited cell does not have enough radio resources then some data may be lost or in a worst case the connection can be dropped. Since handovers are obviously critical moments then researchers have mainly investigated the bandwidth allocation problem on the radio interface and ignored the impact of mobility effects on the fixed part of the network. In this study we present a new rerouting algorithm for WATM networks called RA-NRTT, which aims to reroute non real time traffic data in the wired part of the mobile network while avoiding loops. Performance evaluation of this algorithm has been done while considering two buffer sharing strategies: complete sharing (CS) and complete partitioning (CP), and two scheduling policies; first in first out (FIFO) and weighted round robin (WRR).

This paper deals with the performance evaluation of different channel resource management techniques in low Earth orbit (LEO) satellite systems based on an Earth-fixed cell concept. Both fixed and mobile users have been considered resulting in several classes of users. Each class requires a given quality of service (QoS) and thus a fixed part of the shared resource. Two channel allocation techniques have been investigated: fixed channel allocation (FCA) and dynamic channel allocation (DCA). An analytical model has been derived to analyse the performance of the FCA scheme supporting different kinds of users. A performance comparison of FCA and DCA strategies has also been carried out by simulations as regards the blocking probabilities of each type of users.

In this paper, D-CAPC (dynamic-congestion avoidance using proportional control) scheme is proposed as an extension of the standardized CAPC. In the proposed mechanism, some parameters, which are fixed in CAPC, are tuned dynamically according to the switch load. This task is filled by intelligent agents which are embedded in the switching nodes. Simulation results show that D-CAPC exhibits better performance than the standardized CAPC and encourage the trend towards a dynamic approach for network traffic control.

Over the past five years, the subject of Intelligent Network (IN) focused on architecture and introduction of new services. In parallel, TMN was introduced as a generic management-oriented architecture to be used for all kinds of management services. The integration of IN and TMN is a candidate to solve the problem of management of the IN. Unfortunately, this concept of integration is not sufficient to bring a flexible and adaptable management system. This paper describes a model based on Distributed Artificial Intelligence concepts able to manage the Intelligent Network. This model can be integrated in the different layers of the Intelligent Network architecture. We investigate four possibilities: at the physical plane, at the distributed functional plane, at the global functional plane and at the service plane. We compare the advantages and drawbacks of implementing the management process at those levels.

The goal is first to introduce performance monitoring aspects of asynchronous transfer mode (ATM) networks and then to focus on traffic and congestion control schemes. To deal with this performance monitoring management, a framework for defining a generic intelligent and integrated model for network management is described. As an example of the efficiency of this intelligent management architecture, we measure the performance of a new congestion control scheme. This scheme uses the cell loss priority (CLP) bit, the explicit forward congestion indicator and the explicit backward congestion indicator. The intelligent management uses different parameters and builds a complex but efficient control scheme. We show that this new control scheme allows performance to be increased by an order of magnitude.

In recent years, there has been growing use of distributed systems, and therefore a growing demand for tools able to manage them. However, these tools are not always well suited to their task, in part because of the lack of built-in intelligence. This paper discusses how to introduce intelligence to distributed systems management and control. To do so we analyse requirements for distributed systems management and focus on management tasks from the architecture and model points of view. Intelligence is introduced through distributed artificial intelligence concepts and multiagent systems. We illustrate the application of our techniques with an example based on traffic and congestion control in ATM networks.