The last two decades have seen a clear trend toward crafting intelligent vehicles based on the significant advances in communication and computing paradigms, which provide safer, stress-free, more enjoyable driving experience. Moreover, emerging applications services necessitate massive volumes of data, real-time data processing, ultrareliable low-latency (URLLC). However, capability current is minimal, making it challenging to meet delay-sensitive computation-intensive demand such...

Vehicular edge computing (VEC) is an innovative paradigm with exceptional ability to improve the vehicles’ capacity manage computation-intensive applications both low latency and energy consumption. Vehicles require make task offloading decisions in dynamic network conditions obtain maximum computation efficiency. In this article, we analyze efficiency a VEC scenario, where vehicle offloads its tasks maximize as tradeoff between time Although, it quite challenge ensure quality of experience...

Abstract Vehicular edge computing (VEC) is a promising paradigm to offload resource-intensive tasks at the network edge. Owing time-sensitive and computation-intensive vehicular applications high mobility scenarios, cost-efficient task offloading in environment still challenging problem. In this paper, we study partial problem an urban scenario. Where vehicle computes some part of locally, remaining nearby VEC server subject maximum tolerable delay vehicle’s stay time. To make it...

Emerging vehicular applications with strict latency and reliability requirements pose high computing requirements, current vehicles' computational resources are not adequate to meet these demands. In this scenario, vehicles can get help process tasks from other resource-rich platforms, including nearby vehicles, fixed edge servers, remote cloud servers. Nonetheless, different communication network (VCN) modes need be utilized access resources, improving networks' performance quality of...

The Internet of Things (IoT) is undergoing significant advancements, driven by the emergence backscatter communication (BC) and artificial intelligence (AI). BC an energy-saving cost-effective method where passive devices (BDs) communicate modulating ambient radio-frequency (RF) carriers. AI has potential to transform our way communicating interacting represents a powerful tool for enabling next generation IoT networks. By integrating with BC, we can create new opportunities energy-efficient...

The rapid growth of Automotive-Industry 5.0 and its emergence with beyond fifth-generation (B5G) communications, is making vehicular edge computing networks (VECNs) increasingly complex. latency constraints modern automotive applications make it difficult to run complex on vehicle on-board units (OBUs). While multi-access (MEC) can facilitate task offloading execute these applications, still a challenge access them promptly optimally. Traditional algorithms struggle guarantee accuracy in...

Ensuring dependable quality of service (QoS) and experience (QoE) for computation-intensive delay-sensitive applications in vehicles can be a challenging task that impacts performance. While multi-access edge computing (MEC) based vehicular network (VECN) cloudlets (VC) enable offloading, but their prompt optimal accessibility is another challenge. The conventional wireless technologies may not suffice to meet the stringent ultra-low latency cost constraints such applications. Nonetheless,...

Vehicular edge computing (VEC) is a potential field that distributes computational tasks between VEC servers and local vehicular terminals, hence improve services. At present, vehicles’ intelligence capabilities are rapidly improving, which will likely support many new exciting applications. The network resources well-utilized by exploiting neighboring available while mitigating the server’s heavy burden. However, due to mobility, topology, change rapidly, difficult predict. To tackle this...

Automotive-Industry 5.0 will use Beyond Fifth-Generation (B5G) communications to provide robust, abundant computation resources and energy-efficient data sharing among various Intelligent Transportation System (ITS) entities. Based on the vehicle communication network, Internet of Vehicles (IoV) is created, where vehicles' resources, including processing, storage, sensing, units, can be leveraged construct Vehicular Cloudlet (VC) realize resource sharing. As Connected Autonomous (CAV)...

The increasing complexity of modern automotive applications presents difficulties when running them on the on-board units (OBUs) vehicles. While 5G/6G vehicular edge computing networks (VECNs) offer potential solutions through computation task offloading, ensuring prompt, energy-efficient access to these remains a significant challenge. To overcome challenges, reconfigurable intelligent surfaces (RIS) can play an important role in 6G networks. With RIS, provide better connectivity, increased...

<p>This paper brings these two technologies together to investigate the current state of AI-powered BC. </p> <p>We begin with an introduction BC and overview AI algorithms employed in Then, we delve into recent advances AI-based BC, covering key areas such as backscatter signal detection, channel estimation, jammer control ensure security, mitigate interference, improve throughput latency. We also explore exciting frontiers using B5G/6G technologies, including...

Unmanned aerial vehicles (UAVs) play an important role within mobile edge computing (MEC) networks in improving communications for ground users during emergency situations. However, sustaining high-quality service extended periods is challenging because of constraints on battery capacity and capabilities UAVs. To address this issue, we leverage zero-energy reconfigurable intelligent surfaces (ze-RIS) UAV-MEC introduce a comprehensive strategy that combines task offloading resource sharing. A...

<p>Ensuring dependable quality of service (QoS) and experience (QoE) for computation-intensive delay-sensitive applications in vehicles can be a challenging task that impacts performance. While multi-access edge computing (MEC) based vehicular network (VECN) cloudlets (VC) enable offloading, but their prompt optimal accessibility is another challenge. The conventional wireless technologies may not suffice to meet the stringent ultra-low latency cost constraints such applications....

<p>This paper brings these two technologies together to investigate the current state of AI-powered BC. </p> <p>We begin with an introduction BC and overview AI algorithms employed in Then, we delve into recent advances AI-based BC, covering key areas such as backscatter signal detection, channel estimation, jammer control ensure security, mitigate interference, improve throughput latency. We also explore exciting frontiers using B5G/6G technologies, including...

<p>Ensuring dependable quality of service (QoS) and experience (QoE) for computation-intensive delay-sensitive applications in vehicles can be a challenging task that impacts performance. While multi-access edge computing (MEC) based vehicular network (VECN) cloudlets (VC) enable offloading, but their prompt optimal accessibility is another challenge. The conventional wireless technologies may not suffice to meet the stringent ultra-low latency cost constraints such applications....