Millimeter wave communication (mmWave) is a promising technology that can be used to satisfy the high data rate and low latency requirements of emerging smart factory automation. In an mmWave network, to ensure reliable uplink and downlink connectivity for a large number of devices anywhere on a factory floor, the base station (BS) deployment must be carefully determined. The BS-to-device assignment configuration must also be considered to optimize the network throughput for a certain deployment. In this paper, we introduce a method to identify the optimal base station count and placement for a given factory floor layout with known obstacles, and an algorithm to optimally assign BSs to devices. The simulation results show that the proposed BS assignment method outperforms existing methods and that the BS placement method surpasses manual placement, improving both the average throughput and coverage probability of the network. The BS assignment algorithm extends the Worst Connection Swapping method from prior work, and the BS placement method is based on the Particle Swarm Optimization algorithm. Our methods consider the directional beam interference, blockage effects, and load balancing between BSs to accurately optimize the network performance for the given factory environment.

Unmanned-aerial-vehicle (UAV)-assisted multiaccess edge computing (MEC) networks can effectively broaden the application scope of the Internet of Things (IoT) in complex scenarios, such as maritime operations, military communications, and emergency commands. However, uncertain factors, such as weather changes and temporary airspace control, pose great challenges to UAV flight safety. Obstacles resulting from these uncertain factors may intersect with UAVs with preplanned flight paths, leading to accidents. Therefore, generating the optimal flight trajectory to avoid these obstacles is key in the successful operation of this fuzzy system. In this article, we present a heuristic trajectory generation scheme for complex offshore environments that can generate optimal trajectories according to complex terrain conditions and avoid uncertain obstacles. First, we build a complex terrain model based on a 3-D offshore environment to simulate the conditions in UAV-assisted MEC networks. Second, we propose a network performance optimization objective function that is based on UAV characteristics. Third, we improve the existing ant colony optimization (ACO) algorithm by introducing chaotic mapping, polarizing the pheromone recording rule, and implementing a simulated annealing screening mechanism to efficiently generate trajectories. Finally, we design an efficient obstacle avoidance algorithm for different combinations of obstacle regions. The simulation results show that our proposed trajectory generation scheme can efficiently avoid obstacles and significantly improve the total trajectory loss rate compared with that of baseline schemes.

In this study, we introduce a novel theoretical framework for detecting and decoding Terahertz (THz) frequency chip-scale wireless communication signals. By considering the quantum behavior of charge carriers exposed to intense time-periodic radiation, we employ Floquet engineering techniques for system analysis. Using a two-dimensional semiconductor quantum well (2DSQW) based voltage divider, we showcase the detection and decoding of frequency modulated signals at nanoscale dimensions. Exploring noise impact within the Floquet-2DSQW framework, we identify voltage shifts that compromise data demodulation in single signaling setups. To address this challenge, we suggest a dynamic dual-signaling Floquet-2DSQW architecture that adapts the reference voltage to prevalent noise effects in chip-scale environments. Through a numerical analysis configured for Gigabit per second (Gbps) data transmission in the THz carrier frequency range, we show that our dual-signaling approach surpasses conventional single signaling setups, significantly reducing the bit error rate across various signal-to-noise ratio (SNR) values. A comprehensive parametric study emphasizes the importance of correlated noise effects at two 2DSQW receivers for enhanced performance. Our findings offer valuable insights for advancing nanoscale wireless communication within or between chips in noisy conditions, with potential applications in high-speed, reliable data transfer.

Optical wireless communication (OWC) is emerging as a potential solution for the deployment of 5G and beyond! 6G heterogeneous networks as it can reach physical layer data rates exceeding 10 Gbps. However, the upper layer protocols of OWC are not yet fully developed to support multi user communication and emerging applications. Hence, the development of proper upper layer protocols and network architectures to support such communication under the multi-gigabit capabilities becomes a matter of the utmost importance. In this paper, we propose a contention-free medium access control (MAC) protocol within the Full-duplex Split-plane Optical Wireless Network (FLOWN) architecture to offer users a guaranteed channel access. The proposed protocol is equipped with split-plane operation, full-size IP packet support with high aggregation, and adaptive beacon interval adjustment. Through simulations, we demonstrate that the proposed MAC protocol can simultaneously serve upcoming high demanding multi-gigabit and delay-stringent applications by satisfying their quality of experience requirements.

Optical wireless communication has emerged as a promising candidate for future high data rate indoor applications such as virtual reality. Even though physical layer of optical wireless networks has rapidly developed during last decade, upper layer architecture that harness the physical layer capabilities has not yet been developed in the same pace. To this end, the authors develop a novel contention‐based medium access control (MAC) protocol that accompanies a service differentiation mechanism and a dynamic contention window tuning algorithm. The proposed service differentiation mechanism can identify the diverse traffic types and facilitate their throughput and delay requirements. To add more robustness to the contention‐based MAC protocol which depends on contention windows to avoid collisions, the authors also propose an algorithm that dynamically changes the contention window sizes to suit the congestion level. They analyse the performance of the proposed MAC protocol under diverse network configurations and they show that it is far more effective to use end‐user network metrics such as throughput in dynamic adaptation algorithms in addition to collision rate due to the wide range of traffic types present in the network. The proposed results demonstrate that the proposed MAC protocol can handle next‐generation traffic types and their stringent latency requirements in an effective manner.

Existing optical and wireless networks designed to support today's services may not be suitable for the emerging services, such as machine-to-machine applications of the Internet-of-Things paradigm and tactile-haptic applications of the Tactile Internet paradigm. Some of these applications must adhere to stringent quality of service requirements, especially an ultra-low end-to-end latency constraint of approximately 1 ms. In this paper, we investigate the feasibility of the wireless local area network (WLAN) infrastructure, specifically the IEEE 802.11 HCF Controlled Channel Access (HCCA) media access control (MAC) protocol, in supporting low-latency applications. The scenario considered is tactile-haptic data transmission between body-worn data collection devices and a wireless access point. In particular, we focus on uplink direction rather than downlink direction, because uplink data transmission forms a latency bottleneck of this particular network. In this paper, we first formulate an analytical model of the HCCA using a queuing theory to evaluate the average uplink latency. We then carry out global sensitivity analyses to understand the implications of various timing and network parameters on the uplink latency. Using these insights, we propose a novel strategic parameter selection (SPS) algorithm that effectively reduces uplink latency of the IEEE 802.11 WLAN. This paper provides insights into WLAN design such that latency-sensitive applications can be supported in the near future.

Approximately half the world's population is online with the rest is yearning to be connected. Two out of 3 people on Earth communicate with a mobile phone, while two-fifths use social media to keep contacts up-to-date. [1]. Many things in our lives, phones, cameras, sensors in our homes and offices, and cars are being connected to the Internet. Our world is becoming hyper-connected.

The Internet has evolved a long way from transporting basic web data to transporting traffic instigated by new emerging applications that are available today. One such application is remote human-to-machine interaction, in which touch and actuation related information is delivered over the network. These applications are extremely sensitive to latency, with some reporting latency requirements in the millisecond range. Therefore, it is crucial to minimize latency experienced in each and every segment of the network. In this paper, we consider a scenario in which tactile body-worn devices are connected using the IEEE 802.11 network, and analyze the wireless transmission latency from these devices to the wireless access point, when the hybrid coordination function controlled channel access (HCCA) MAC protocol is used. In particular, we use queuing theory based approach to derive closed-form expressions for the average latency. We use the insights gained from our latency analysis to propose a new service interval selection method that outperforms the HCCA reference design. We show for the first time the parameters that have significant impact on latency and how these can be manipulated to meet the stringent latency constraints.

The rapid growth in the energy consumption of mobile networks has become a major concern for mobile operators. Today's mobile networks' usage is dominated by over-the-top (OTT) applications, and operators are keen to determine the network energy consumed by these OTT applications. With a recent shift in user behavior toward a preference for instant messaging (IM) applications over conventional mobile services, operators are interested in exploring what impact OTT IM applications such as WeChat will have on the energy consumption of a network when compared with a corresponding conventional mobile service. Here, we present for the first time energy assessment models for mobile services based on real network and service measurements to address this need. Using WeChat as an OTT IM application example, our results show that WeChat consumes more network energy than conventional mobile services for both light users and heavy text users due to the network signaling energy overhead. In comparison, for heavy voice users, WeChat consumes less network energy since voice messages are first recorded and then sent in packet bursts. Our findings provide a quantitative analysis of the energy consumption of mobile services, which should be valuable for mobile operators and OTT application developers to improve the energy-efficiency of mobile applications and services.

Today, video-on-demand (VoD) systems are challenged by a growing number of users, growing sizes of libraries, and increasing video streaming rates. Therefore, scalability and the bandwidth efficiency of VoD systems have become important considerations. In this paper, we propose a scalable and bandwidth efficient delivery scheme for VoD systems, which optimally exploits the storage and multicast capabilities to reduce the consumption of server capacity resources. Our proposed scheme, which we call prepopulation assisted batching with multicast patching (PAB-MP), facilitates video multicast from the server by strategic preplacement of initial segments of videos at the end-users' devices. Using an analytical approach, we show how the parameters for the PAB-MP scheme can be selected to achieve optimal performance. Moreover, we propose methods to replicate and place the initial video segments (IVSs) across the end-users' devices such that load arising from IVSs is evenly distributed among user-nodes. Using simulations, we show that our proposed scheme effectively reduces the load on the server especially under high load, while imposing less burden on individual user nodes. Simulation results indicate that our proposed PAB-MP scheme is significantly more scalable than the other popular approaches that exploit multicast and storage.

Video on Demand (VoD) service has become an increasingly popular service in recent years as a result of the rapid deployment of Fiber-to-the-Home networks. Due to its enormous bandwidth and stringent quality of service requirements, deploying an efficient and scalable VoD service still remains a challenge. In this paper, we propose a peer-to peer (P2P) VoD distribution scheme for PONs in which the P2P delivery is localized to within the same access network and in which a selected set of movies is pre-fetched into the customer premises equipment during off-peak hours. The proposed delivery scheme mitigates the load from the VoD server by exploiting the participation of the customer equipment in VoD distribution. In turn, this optimizes bandwidth consumption of the VoD service in both core and metro networks as the P2P video traffic is localized within the access network. We formulate movie pre-fetching as an optimization problem which determines the number of copies of each movie to be pre-fetched, and we propose a heuristic algorithm to solve it. Using simulations we show that our proposed replication algorithm performs much better than existing popularity based replication algorithm that has been proposed for similar purposes. Moreover, we show that our proposed delivery scheme effectively reduced the server load in busy hours while having high but random server load reduction in off-peak hours of service.

We present energy consumption models of video-on-demand (VoD) services delivered through newly proposed localized hybrid peer-to-peer (P2P) and localized peer-assisted patching with multicast video delivery methods over optical access networks. In this paper, we demonstrate through simulations that the localized peer-assisted patching with multicast video delivery method consumes the lowest network transport energy for popular VoD channels while localized hybrid P2P method consumes the lowest network transport energy for less popular channels. Nevertheless, both schemes outperform the conventional server centric content distribution network in term of overall network energy consumption.

Video on Demand (VoD) service is regarded as one of the most promising services over increasingly deployed next generation broadband access networks. The distributed server architecture, in which the popular content is cached at a location closer to the viewer, is a widely used methodology to optimize the transport capacity of VoD delivery. However, due to the dynamic (change with time) nature of movie popularity distribution, identifying the popular content and updating the cache servers accordingly is not straightforward. In this paper, using a novel caching architecture for Passive Optical Networks (PON), we discuss the need for a fast caching algorithm that can respond to time changing movie popularity distribution, and we propose a novel Last-k caching algorithm, which identifies the popular content using the most recent statistics. The proposed algorithm estimates movie popularity using most recent inter-arrival times of movie requests and updates the cache accordingly such that the most popular content at any given time would reside in the cache. Simulations indicate that the proposed algorithm out-performs existing algorithms by effectively responding to the dynamic nature of movie popularity distribution.

In this paper, we propose a simple active remote node (RN) with layer two forwarding scheme for EPON. The RN discards unwanted frames and redirects local-intra-subnet traffic to increase the network efficiency. We analyze and discuss the functionalities of the RN in detail and present simulations using an EPON structure of 16 ONUs with 4 splits to prove the feasibility of the scheme. The simulation results show a large improvement in latency and capacity with active RN structure. We also explain the use of EPON protocols such as MPCP and DBA is crucial in the implementation of this scheme.