Urban VANET (Vehicular Ad hoc NETworks) performance optimization concerns the improvement of wireless signal quality between two arbitrary selected nodes moving within along city streets. It includes three procedures: VANET architecture modeling; wireless signal simulation; and signal quality optimization techniques. The first procedure converts real-world map data into a network graph according to the requirement of the optimization algorithm. The second step analyzes a communication route between two network nodes and calculates received signal quality with the information provided by the network model. The final operation optimizes the signal quality to an expected level by choosing appropriate communication route between two wireless nodes. In this thesis, three optimization techniques are presented: EP (Evolutionary Programming), SG (Stochastic Geometry) and SW (Small World). EP is a widely applied optimization strategy based on Darwin’s natural selection and evolution theory. It is effective with an enormous number of data support, and it can provide detailed route information. However, it requires enough time to evolve to an optimal solution. SG is a statistical tool to analyze points’ distribution within a multi-dimensional space, and it was recently applied on wireless network analysis. Given the distribution characteristics of an urban area, SG can calculate average data loss rate of a communication route. However, it cannot provide detailed route information. SW is a widely accepted model to represent people’s relationship in social networks, and it can be used in VANET analysis. SW provides a simplified network architecture compared with EP an SG. However, it requests additional long-range communication equipment and consumes more energy. The thesis is divided into three parts. Chapter 1 introduces the history of VANET and its architecture (in this research, it is a combination of Ad hoc network and WSN (Wireless Sensor Network). Chapter 2 and 3 presents literature review of EP and SG. Chapter 4, 5, and 6 discusses how to implement EP, SG and SW on Boston VANET. At the end of each chapter, a conclusion is presented and a discussion on the author’s contribution is given

The vision of a smart wireless factory (SWF) demands highly flexible, low-latency, and reliable connectivity that goes beyond conventional wireless solutions. Reconfigurable intelligent surface (RIS)-empowered communications, when integrated with the open radio access network (O-RAN) architectures, have emerged as a promising enabler to meet these challenging requirements. This article introduces the methodology for the orchestration of RIS with xApps (ORIX), bringing the RIS technology into the O-RAN ecosystem through xApp-based control for SWF environments. ORIX features three key components: an O-RAN-compliant RIS service model for dynamic configuration, an RIS channel simulator that supports 3GPP indoor factory models with multiple industrial scenarios, and practical RIS optimization strategies with finite-resolution control. Together, these elements provide a realistic end-to-end emulation platform for evaluating RIS placement, control, and performance in SWF environments prior to deployment. The presented case study demonstrates how ORIX enables the evaluation of achievable performance gains, exploration of trade-offs among key RIS design parameters, and identification of deployment strategies that balance system performance with practical implementation constraints. By bridging theoretical advances with industrial feasibility, ORIX lays the groundwork for RIS-assisted O-RAN networks to power next-generation wireless communication in industrial scenarios.

Advanced Industrial Conference on Wireless Technologies (ICW 2005), August 14-17, 2005, Montreal, CanadaRecent advances in wireless sensors network (WSN) technology have made possible the manufacturing of tiny low-cost, low-power sensors with wireless multi-hop communication and sensing capabilities. Energy conservation for WSNs is a primary objective that needs to be addressed at all layers of the networking protocol stack. In many applications latency is another crucial factor to be addressed. However this must be done in the context of the energy constraints imposed by the network. In this paper we present an experimental evaluation of two node scheduling regimes within MERLIN (MAC energy efficient, routing and localization integrated), an energy-efficient low-latency integrated protocol for WSNs. In particular we contrast the X and V scheduling family schemes with respect to the following properties: network setup time, network lifetime and message latency. We conduct our experiments within the OmNet++ simulator.A

The performance of wireless communication systems is fundamentally constrained by the random and uncontrollable wireless channel. By leveraging the recent advance in digitally-controlled metasurface, intelligent reflecting surface (IRS) has emerged as a promising solution to enhance the wireless network performance by smartly reconfiguring the radio propagation environment. Despite the substantial research on IRS-aided communications, this article addresses the important issue of how to deploy IRSs in a wireless network to achieve its optimum performance. We first compare the two conventional strategies of deploying IRS at the side of base station or distributed users in terms of various communication performance metrics, and then propose a new hybrid IRS deployment strategy by combining their complementary advantages. Moreover, the main challenges in optimizing IRS deployment as well as their promising solutions are discussed. A case study is also presented to compare the performance of different IRS deployment strategies and draw useful insights for practical design.

Since Internet was born, it has steadily evolved. New devices, new needs, new applications, new protocols, and this evolution is not going to slow down in the near future. As a result of the introduction and standardization of wireless access technology, we are living through an inevitable replacement of the old wired technology. We are going through a wireless revolution, which brings with it new ways to access information: simply, anywhere, anytime. The new Internet challenge is to embody the new generation of wireless technology, giving users mobility and ubiquitous access. Wireless technology allows to extend Internet to rural areas, building blocks, home devices. Mesh networking did grow up and did become a solid technology, and it is ready to be widely adopted. Wireless communication, though, is affected by interference, the noise signal which may significantly affect the Signal to Interference-plus-Noise Ratio (SINR), leading to transmission errors. Moreover, wireless links have their own set of transmission parameters, which have to be properly tuned in order to suit the mesh network to the traffic dynamics. Thanks to the availability of cost-effective radio interfaces, it is possible to endow each wireless node with multiple radios, thus exploiting simultaneous transmissions on the available orthogonal channels and reducing interference. However, a fundamental issue in the design of multi-radio wireless mesh networks is the joint channel assignment and routing problem. The problem consists in how to assign the available channels to the radio interfaces, and how to find the set of flow rates that have to be routed on each link in order to achieve a given objective. The joint problem, though, is NP-complete, and mainly heuristics have been proposed, which solve the two problems separately. Therefore, in this Thesis we solve the routing problem and focus on the channel assignment problem in multi-radio wireless mesh networks, trying to find a channel assignment such that a given set of nominal flow rates can be scheduled. Such problem is shown once again to be NP-complete, hence heuristics are developed. We study the influence of typical wireless parameters, like transmission data rate, transmission power and transmission frequency, on the overall performance of a wireless mesh network and present two different approaches to channel assignment. Assuming that the set of flow rates is given, we introduce a channel, rate and power assignment algorithm that aims at reducing the interference inside the mesh network, while trying to ensure scheduling for the nominal flows. Since the wireless parameters configuration depends on the set of network flow rates, when the traffic changes, then the channel assignment has to be recomputed, i.e., it has to be adapted to the new rates. Therefore, we analyze the issues that arise when channels are re-assigned without taking into consideration the current channel assignment, and present an efficient channel and rate re-assignment algorithm. Once the channel assignment and routing problems are solved, we have the proper channel configuration and the nominal set of flows to be routed on the wireless links. The traffic routing operations, though, are still performed by the network routing agent, which usually route traffic along the minimum hop-count path. In this Thesis, then, we present a routing protocol that is aware of the pre-computed flow rates, and tries to route packets in order to obtain an average link utilization that is as close as possible to the nominal one. We modify a minimum hop-count routing protocol so as to consider variable costs for each link, and we propose a local search heuristic to find the best link cost that allows to optimize the link utilization. Internet evolution has also been accompanied by new protocols, new communication paradigms and new user interactions. Peer-to-Peer applications are an exemplary case of the new trend of Internet, and they create nowadays more than half the Internet traffic. One of the most distinguishing characteristics of Peer-to-Peer applications is that they communicate by means of overlay networks, unaware of the physical network topology they are built upon. Therefore, Peer-to-Peer applications represent a strong engineering challenge for the network management, since the only way to control the traffic is to control the decisions that the applications make at the overlay level. We study the overlay/underlay issues in the wireless mesh networking context, and outline how controlling P2P traffic is even more stringent, due to the mesh configuration sensibility to traffic patterns, and to the restraint of resources. To control the Peer-to-Peer application traffic, we have to somehow guide the overlay applications in the choice of the connection end points, providing information about the physical underlying network. To propose innovative solutions to the overlay traffic optimization problem, the IETF ALTO Working Group has been recently founded. The aim of the ALTO Working Group is to define a structured architecture to support the cooperation between overlay and physical networks. In this context, then, we develop and implement a new component for the ALTO Service architecture, the ALTO Agent, designed to guide the overlay topology creation and to help the Peer-to-Peer application in selecting the best nodes inside a wireless mesh network. In order to choose the best available nodes and to evaluate the performance of wireless paths, we introduce an interference-aware path metric. With the path metric we propose, each link is penalized by taking into account the interference with previous hops on the path. Given the importance of testing our solution in a realistic scenario, we study the integration problem of OMF-based wireless testbeds into the PlanetLab testbed. Thanks to our efforts, we have been able to exploit a realistic large scale testbed to test our ALTO Agent solution. Finally, the ALTO Agent has been installed inside a wireless mesh network, and it has been used to retrieve performance metrics about end-to-end connections between peer mesh nodes. We evaluate the performance of the ALTO Agent into our integrated wireless testbed and show the improvements obtained for the application end user and the reduced costs for the network operator

Wireless Body Area Networks (WBANs) have gained a lot of research attention in recent years since they offer tremendous benefits for remote health monitoring and continuous, real-time patient care. However, as with any wireless communication, data security in WBANs is a challenging design issue. Since such networks consist of small sensors placed on the human body, they impose resource and computational restrictions, thereby making the use of sophisticated and advanced encryption algorithms infeasible. This calls for the design of algorithms with a robust key generation / management scheme, which are reasonably resource optimal. This paper presents a security suite for WBANs, comprised of IAMKeys, an independent and adaptive key management scheme for improving the security of WBANs, and KEMESIS, a key management scheme for security in inter-sensor communication. The novelty of these schemes lies in the use of a randomly generated key for encrypting each data frame that is generated independently at both the sender and the receiver, eliminating the need for any key exchange. The simplicity of the encryption scheme, combined with the adaptability in key management makes the schemes simple, yet secure. The proposed algorithms are validated by performance analysis.

In the first part of this thesis, we exploit wireless broadcast across different layers in wireless networks. The wireless channel is distinguished by its broadcast nature. Wireless broadcast provides a fertile ground to improve the efficiency of existing wireless networks and design new ones. Specifically, we first consider relaying strategies for memoryless two-way relay channels at the physical layer. We generalize networking layer network coding operating on a finite field to physical layer network coding, which is a mapping from the relay's received signal to its transmitted signal. We analyze the symbol-error performance of several relay strategies, and optimize the relay function via functional analysis. Our results indicate that the interference caused by wireless broadcast can be exploited to improve the spectrum efficiency. We then develop a cross-layer framework with wireless broadcast, which integrates rate control, network coding and scheduling in transport, network and link layers. Under the primary interference model, we show that the link scheduling problem is the maximum weighted hypergraph matching problem, which is NP-complete. We propose several distributed approximation algorithms and bound their worst case performance. Next, we describe a new class of medium access control (MAC) protocol, which uses successive interference cancelation to resolve packet collision due to wireless broadcast. Each user is allowed to transmit at different data rates chosen randomly from an appropriately determined set of rates. We characterize the throughput of the proposed protocol compared to that with a centralized controller. A game-theoretic framework along with the dynamic algorithms is proposed to achieve the desired throughput optimal equilibrium, which provides a valuable perspective to understand existing MAC protocols and a general framework to design new ones to improve the system performance. In the second part of this thesis, we consider the problem of secure transmission in the presence of a wiretapper. Due to wireless broadcast, wireless signals are particularly easy to jam and intercept. We derive the secrecy capacity region for the case when the location of the wiretapped links is known and propose several achievable strategies for the case when such information is unknown. We give an example to show that the secrecy capacities of the two cases are generally unequal and show that in both cases computing the secrecy capacity is NP-complete.</p

Content caching in small base stations or wireless infostations is considered to be a suitable approach to improve the efficiency in wireless content delivery. Placing the optimal content into local caches is crucial due to storage limitations, but it requires knowledge about the content popularity distribution, which is often not available in advance. Moreover, local content popularity is subject to fluctuations since mobile users with different interests connect to the caching entity over time. Which content a user prefers may depend on the user's context. In this paper, we propose a novel algorithm for context-aware proactive caching. The algorithm learns context-specific content popularity online by regularly observing context information of connected users, updating the cache content and observing cache hits subsequently. We derive a sublinear regret bound, which characterizes the learning speed and proves that our algorithm converges to the optimal cache content placement strategy in terms of maximizing the number of cache hits. Furthermore, our algorithm supports service differentiation by allowing operators of caching entities to prioritize customer groups. Our numerical results confirm that our algorithm outperforms state-of-the-art algorithms in a real world data set, with an increase in the number of cache hits of at least 14%.

The paper proposes wireless sensor clustering routing protocol based on ant colony algorithm(ACO). The method firstly uses the network self-topology to get a stable cluster structure based on modularity clustering algorithm; secondly make a new cluster-head selection function according to each cluster node residual energy and the distribution of cluster node; then we propose inter-cluster multi-hop routing algorithm based on ant colony optimization, which in order to balance the energy between consumption on the transmission path and residual one of cluster-head node, developing new ant transmission probability and pheromone updating strategy, we verify the validity of algorithm through simulation.

A global approach for realistic network-aware joint source and channel system optimization for wireless video transmission is described in this paper. After a description of the information to be exchanged among the system component blocks, the concept of "JSCC/D controllers" is introduced and the implementation of the first "basic chain" demonstrator realized in the framework of the PHOENIX project is described. Simulation results obtained with such first software demonstration platform confirm the validity of the described approach

The optimal design of wireless networks has been widely studied in the literature and many optimization models have been proposed over the years. However, most models directly include the signal-to-interference ratios representing service coverage conditions. This leads to mixed-integer linear programs with constraint matrices containing tiny coefficients that vary widely in their order of magnitude. These formulations are known to be challenging even for state-of-the-art solvers: the standard numerical precision supported by these solvers is usually not sufficient to reliably guarantee feasible solutions. Service coverage errors are thus commonly present. Though these numerical issues are known and become evident even for small-sized instances, just a very limited number of papers has tried to tackle them, by mainly investigating alternative non-compact formulations in which the sources of numerical instabilities are eliminated. In this work, we explore a new approach by investigating how recent advances in exact solution algorithms for linear and mixed-integer programs over the rational numbers can be applied to analyze and tackle the numerical difficulties arising in wireless network design models.

In this paper we present an energy-efficient cross layer protocol for providing application specific reservations in wireless senor networks called the “Unified Clustering and Communication Protocol ” (UCCP). Our modular cross layered framework satisfies three wireless sensor network requirements, namely, the QoS requirement of heterogeneous applications, energy aware clustering and data forwarding by relay sensor nodes. Our unified design approach is motivated by providing an integrated and viable solution for self organization and end-to-end communication is wireless sensor networks. Dynamic QoS based reservation guarantees are provided using a reservation-based TDMA approach. Our novel energy-efficient clustering approach employs a multi-objective optimization technique based on OR (operations research) practices. We adopt a simple hierarchy in which relay nodes forward data messages from cluster head to the sink, thus eliminating the overheads needed to maintain a routing protocol. Simulation results demonstrate that UCCP provides an energy-efficient and scalable solution to meet the application specific QoS demands in resource constrained sensor nodes. Index Terms — wireless sensor networks, unified communication, optimization, clustering and quality of service

Mathematical optimization is now widely regarded as an indispensable modeling and solution tool for the design of wireless communications systems. While optimization has played a significant role in the revolutionary progress in wireless communication and networking technologies from 1G to 5G and onto the future 6G, the innovations in wireless technologies have also substantially transformed the nature of the underlying mathematical optimization problems upon which the system designs are based and have sparked significant innovations in the development of methodologies to understand, to analyze, and to solve those problems. In this paper, we provide a comprehensive survey of recent advances in mathematical optimization theory and algorithms for wireless communication system design. We begin by illustrating common features of mathematical optimization problems arising in wireless communication system design. We discuss various scenarios and use cases and their associated mathematical structures from an optimization perspective. We then provide an overview of recently developed optimization techniques in areas ranging from nonconvex optimization, global optimization, and integer programming, to distributed optimization and learning-based optimization. The key to successful solution of mathematical optimization problems is in carefully choosing or developing suitable algorithms (or neural network architectures) that can exploit the underlying problem structure. We conclude the paper by identifying several open research challenges and outlining future research directions.

Network lifetime is a critical metric in the design of energy-constrained wireless sensor networks. In this paper, we consider the joint cross layer optimization of the physical layer, medium access control layer and routing layer to maximize network lifetime of a multi-sources and single-sink wireless sensor network with energy constraints. We focus on synchronous small-scale sensor network with interference-free link scheduling and practical MPSK link transmission scheme. As the network lifetime maximization problem is a constrained non-convex optimization problem that is difficult to be solved, and the particle swarm optimization algorithm is a good intelligent algorithm, we employ it to solve the problem mentioned above effectively in this paper. The penalty function technique is brought in to work out the constrained optimization problem by converting it to an unconstrained optimization problem. Simulation results show the effectiveness of the proposed algorithm in energy saving and network lifetime maximization, and the particle swarm optimization can solve the network lifetime maximization problem fast and efficiently.

When planning a wireless local area network, there are design issues that need to be considered. In this paper, the fundamentals of planning a wireless local area network are introduced and discussed to highlight the requirements involved. Network constraints, as their relevance to wireless network design is investigated. The paper concludes with an overview of wireless network planning solutions including commercial and free software, and an introduction to the author’s research

Intelligent reflecting surface (IRS) is a new and promising paradigm to substantially improve the spectral and energy efficiency of wireless networks, by constructing favorable communication channels via tuning massive low-cost passive reflecting elements. Despite recent advances in the link-level performance optimization for various IRS-aided wireless systems, it still remains an open problem whether the large-scale deployment of IRSs in wireless networks can be a cost-effective solution to achieve their sustainable capacity growth in the future. To address this problem, we study in this paper a new hybrid wireless network comprising both active base stations (BSs) and passive IRSs, and characterize its achievable spatial throughput in the downlink as well as other pertinent key performance metrics averaged over both channel fading and random locations of the deployed BSs/IRSs therein based on stochastic geometry. Compared to prior works on characterizing the performance of wireless networks with active BSs only, our analysis needs to derive the power distributions of both the signal and interference reflected by distributed IRSs in the network under spatially correlated channels, which exhibit channel hardening effects when the number of IRS elements becomes large. Extensive numerical results are presented to validate our analysis and demonstrate the effectiveness of deploying distributed IRSs in enhancing the hybrid network throughput against the conventional network without IRS, which significantly boosts the signal power but results in only marginally increased interference in the network. Moreover, it is unveiled that there exists an optimal IRS/BS density ratio that maximizes the hybrid network throughput subject to a total deployment cost given their individual costs, while the conventional network without IRS is generally suboptimal in terms of throughput per unit cost.

Radio Frequency Identification (RFID) systems facilitate detection and identification of objects that are not easily detectable or distinguishable. However, they do not provide information about the condition of the objects they detect. Wireless sensor networks (WSNs), on the other hand provide information about the condition of the objects as well as the environment. The integration of these two technologies results in a new type of smart network where RFID-based components are combined with sensors. This research proposes an integration technique that combines conventional wireless sensor nodes, sensor-tags, hybrid RFID-sensor nodes and a base station into a smart network named Hybrid RFID-Sensor Network (HRSN)

Existing designs for content dissemination do not fully explore and exploit potential caching and computation capabilities in advanced wireless networks. In this paper, we propose two partition-based caching designs, i.e., a coded caching design based on Random Linear Network Coding and an uncoded caching design. We consider the analysis and optimization of the two caching designs in a large-scale successive interference cancelation (SIC)-enabled wireless network. First, under each caching design, by utilizing tools from stochastic geometry and adopting appropriate approximations, we derive a tractable expression for the successful transmission probability in the general file size regime. To further obtain design insights, we also derive closed-form expressions for the successful transmission probability in the small and large file size regimes, respectively. Then, under each caching design, we consider the successful transmission probability maximization in the general file size regime, which is an NP-hard problem. By exploring structural properties, we successfully transform the original optimization problem into a Multiple-Choice Knapsack Problem (MCKP), and obtain a near optimal solution with 1/2 approximation guarantee and polynomial complexity. We also obtain closed-form asymptotically optimal solutions. The analysis and optimization results show the advantage of the coded caching design over the uncoded caching design, and reveal the impact of caching and SIC capabilities. Finally, by numerical results, we show that the two proposed caching designs achieve significant performance gains over some baseline caching designs.

In this paper we do some researches on the ARQ mechanism which provides the probability of involving the relay nodes into the UWB multi-hop network. The ARQ mechanism we designed combines PWMR ARQ and Relay ARQ, which can perform on both the end nodes and relay nodes. Then we make a theoretical analysis of the indoor UWB channel model and give a Finite-state Markov linker layer model. With the simulation results, we can get the conclusion that using ARQ mechanism designed in this paper significant enhances throughput, time delay and bandwidth utilization of the UWB multi-hop network.

Both Wireless Mesh Network (WMN) and Wireless Sensor Network (WSN) are multi-hop wireless networks. WMN is an emerging community based integrated broadband wireless network which ensures high bandwidth ubiquitous internet provision to users, while, WSN is application specific and ensures large scale real-time data processing in complex environment. Both these wireless networks have some common vulnerable features which may increase the chances of different sorts of security attacks. Wireless sensor nodes have computation, memory and power limitations, which do not allow for implementation of complex security mechanism. In this paper, we discuss the common limitations and vulnerable features of WMN and WSN, along with the associated security threats and possible countermeasures. We also propose security mechanisms keeping in view the architecture and limitations of both. This article will serve as a baseline guide for the new researchers who are concern with the security aspects of WMN and WSN

Wireless body area networks are wireless sensor networks whose adoption has recently emerged and spread in important healthcare applications, such as the remote monitoring of health conditions of patients. A major issue associated with the deployment of such networks is represented by energy consumption: in general, the batteries of the sensors cannot be easily replaced and recharged, so containing the usage of energy by a rational design of the network and of the routing is crucial. Another issue is represented by traffic uncertainty: body sensors may produce data at a variable rate that is not exactly known in advance, for example because the generation of data is event-driven. Neglecting traffic uncertainty may lead to wrong design and routing decisions, which may compromise the functionality of the network and have very bad effects on the health of the patients. In order to address these issues, in this work we propose the first robust optimization model for jointly optimizing the topology and the routing in body area networks under traffic uncertainty. Since the problem may result challenging even for a state-of-the-art optimization solver, we propose an original optimization algorithm that exploits suitable linear relaxations to guide a randomized fixing of the variables, supported by an exact large variable neighborhood search. Experiments on realistic instances indicate that our algorithm performs better than a state-of-the-art solver, fast producing solutions associated with improved optimality gaps.

Broadband wireless networks are providing internet and related services to end users. The three most important broadband wireless technologies are IEEE 802.11, IEEE 802.16, and Wireless Mesh Network (WMN). Security attacks and vulnerabilities vary amongst these broadband wireless networks because of differences in topologies, network operations and physical setups. Amongst the various security risks, Denial of Service (DoS) attack is the most severe security threat, as DoS can compromise the availability and integrity of broadband wireless network. In this paper, we present DoS attack issues in broadband wireless networks, along with possible defenses and future directions

We consider the design of wireless queueing network control policies with particular focus on combining stability with additional application-dependent requirements. Thereby, we consequently pursue a cost function based approach that provides the flexibility to incorporate constraints and requirements of particular services or applications. As typical examples of such requirements, we consider the reduction of buffer underflows in case of streaming traffic, and energy efficiency in networks of battery powered nodes. Compared to the classical throughput optimal control problem, such requirements significantly complicate the control problem. We provide easily verifyable theoretical conditions for stability, and, additionally, compare various candidate cost functions applied to wireless networks with streaming media traffic. Moreover, we demonstrate how the framework can be applied to the problem of energy efficient routing, and we demonstrate the aplication of our framework in cross-layer control problems for wireless multihop networks, using an advanced power control scheme for interference mitigation, based on successive convex approximation. In all scenarios, the performance of our control framework is evaluated using extensive numerical simulations.