A new networking paradigm, Vehicular Edge Computing (VEC), has been introduced in recent years to the vehicular network augment its computing capacity. The ultimate challenge fulfill requirements of both communication and computation is increasingly prominent, with advent ever-growing modern applications. With breakthrough VEC, service providers directly host services close proximity smart vehicles for reducing latency improving quality (QoS). This paper illustrates VEC architecture, coupled...

A huge amount of data, generated by Internet Things (IoT), is growing up exponentially based on nonstop operational states. Those IoT devices are generating an avalanche information that disruptive for predictable data processing and analytics functionality, which perfectly handled the cloud before explosion growth IoT. Fog computing structure confronts those disruptions, with powerful complement functionality framework, deployment micro clouds (fog nodes) at proximity edge sources....

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...

Multiaccess edge computing (MEC) is considered as a backbone for the 5G network. The successive MEC network combines networking and computation at of to achieve Quality Services (QoS) with ultralow latency. devices mobility feature, whether hand-held or vehicles move from one server (ES) location another ES, creates nonoptimal environment in long run. To maintain QoS avoid service disruptions, existing topologies do not fulfill requirement. Hence, unique traffic steering dynamic path...

As more investors adopt to enter the field of blockchain investment, Ponzi scheme, a traditional investment scam, has emerged as hidden fraud in smart contracts. Although some proposed solutions have paid attention detecting schemes blockchain, two problems remain: features for are incomplete, and algorithms not sufficiently efficient. Therefore, we innovatively extract bytecode feature combine it with user transaction opcode frequencies get comprehensive features. With these features,...

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...

Unmanned aerial vehicles (UAVs) have attracted much attention for civil and military uses because of their high mobility adaptable deployment capabilities in open spaces. They facilitate agile communications ubiquitous connectivity. UAVs benefit from dominant line-of-sight communication links but are more susceptible to adversary eavesdropping attacks. Since upper-layer cryptography methods may be insufficient, physical-layer security (PLS) is an attractive alternative. PLS capitalizes on...

Multicollinearity and influential cases in semiparametric regression models lead to biased unreliable estimates distorting leverage residual patterns. To address these challenges, we propose modified penalized least squares estimators (MPLSEs). We use Cook’s distance a case deletion approach evaluate their performance. The effectiveness of MPLSEs is demonstrated through the Longley dataset, where applied estimated coefficients, fitted values, residuals, leverages, using ridge parameter. In...

Unmanned aerial vehicles (UAVs) have become essential in advancing multi-access edge computing (MEC), providing flexible platforms that enhance network capacity, coverage, and efficiency while reducing latency improving communication quality. Integrating reconfigurable intelligent surfaces (RIS) with UAV-based MEC systems further elevates these capabilities, delivering significant gains computational power, energy (EE), physical layer security (PLS). However, managing the complexity of RIS...

Milk is an essential component of human nutrition, particularly for the growth and cognitive development children in undernourished populations. In Pakistan, milk production has more than doubled, with country now third-largest producer world. Most however, consumed form unpackaged loose not only making hygiene issue but logistical as well. An optimized route planner caters to cost-effective environmentally friendly delivery dairy products. Vehicle routing played a minor role large-scale,...

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...

Summary Timely acquisition of judicious amounts data and their continual evaluation are foundational to sound reservoir management. To ensure technical success avoid economic waste, an experienced multi-disciplinary team should have ongoing responsibility for identifying acquiring these from all available sources, assessing quality representability, evaluating (analyzing, reducing, synthesizing) them properly consistently.

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...

Mathematics is the engine, vehicle, driver, and language of today’s initiatives, innovations, human endeavors. In this mathematical-driven world, ability to perform mathematical tasks logical reasoning also essential in solving quotidian problems. Therefore, competency problem-solving skills are kept as an integral component almost every educational curriculum around globe. However, there numerous stumbling blocks along way successful teaching, conducive learning environment, good student...

Mobile edge computing (MEC) has produced incredible outcomes in the context of computationally intensive mobile applications by offloading computation to a neighboring server limit energy usage user equipment (UE). However, choosing pool application components offload addition volume data transfer along with latency communication is an intricate issue. In this article, we introduce novel energy-efficient scheme based on deep neural networks. The proposed trains intelligent decision-making...