With the voluminous information being produced by Internet of Things (IoT) smart gadgets, consumers with their countless service requests are also growing rapidly. As there is a huge distance between IoT devices and Cloud datacenter, some latency incurred in communication datacenter. This can be reduced introducing Fog layer therefore, it paramount to offload those tremendous data leverage overloaded storage computation Cloud-based systems Fog-assisted nodes. Moreover, these heavy...

Abstract Task scheduling and load balancing are a concern for service providers in the cloud computing environment. The problem of tasks loads is categorized under an NP-hard problem. Thus, it needs efficient algorithm that not only allocates onto appropriate VMs but also maintains trade-off amidst VMs. It should keep equilibrium among way reduces makespan while maximizing utilization resources throughput. In response to it, authors propose inspired by mimicking behavior flock birds, which...

Offloading the dynamic tasks with fog computing is envisioned as a viable option for prolonging resource-limited constraints and improving computational communicational latency delay-sensitive IoT applications. Besides, priority of target layers offloading them to minimize incurred service prime concern in layered architecture. To leverage efficiency underlying nodes tasks' heterogeneity requirements deadline constraints, this article presents fuzzy logic technique prioritize based on their...

The demand for vehicular networks is prolifically emerging as it supports advancing in capabilities and qualities of vehicle services. However, this network cannot solely carry out latency-sensitive compute-intensive tasks, the slightest delay may cause any catastrophe. Therefore, fog computing can be a viable solution an integration to address aforementioned challenges. Moreover, complements Cloud reduces incurred latency ingress traffic by shifting resources edge network. This work...

The fast proliferation of internet-enabled devices generates massive amounts data every day from aspect life. These lack the storage, processing power, and capacity necessary to handle store this amount accurate volumetric data. Cloud computing has been proposed as a compelling substitute process these requests. However, ingress traffic is huge which causes latency overhead due gap that exists between end datacentre. Additionally, dynamic heterogeneous requests with disparate requirements...

In today's world, maintaining good health has become increasingly paramount. The global prevalence of diabetes surged due to the stress modern life and unhealthy dietary habits. Detecting at an early stage imperative. Leveraging advancements in Cloud Fog computing, we can create Internet-enabled Medical framework that incorporates Machine Learning (ML) techniques predict diagnose its inception. This prediction diagnosis would enable remote medical assistance for individuals living far from...

Datacenters receive dynamic workloads with disparate specifications to be scheduled on virtual machines (VMs). These unpredictable, alarmingly growing varying resource may bring down the servers of datacenters into an imbalanced state. Thus, resulting in low utilization and high energy consumption among servers. To cater need fluctuating on-demand provisioning, it is essential scale up ability capacityof existing infrastructure through virtualization. Moreover, due involvement conflicting...

Abstract Detecting potholes and traffic signs is crucial for driver assistance systems autonomous vehicles, emphasizing real-time accurate recognition. In India, approximately 2500 fatalities occur annually due to accidents linked hidden overlooked signs. Existing methods often overlook water-filled illuminated potholes, as well those shaded by trees. Additionally, they neglect the perspective (nighttime) To address these challenges, this study introduces a novel approach employing cascade...

Nowadays, with the advent of many new technologies, data is alarmingly generated by widespread internet devices in this world. Cloud computing seems a viable option for scheduling dynamic disparate specifications. However, execution time increases due to computationally-limited resources causing latency overhead. So, Fog has evolved as promising paradigm complement computing. Therefore, effectively utilizing underlying enormous tasks latency-sensitive applications critical issue. Hence, cope...

The ever-increasing use of Internet Things (IoT) devices like smartphones, PDAs, smartwatches, etc. by the users has also drastically increased volume data that needs to be processed cloud servers. servers are very powerful and capable processing at once. However, being a centralized paradigm existence physical gap from IoT layer, it is incapable bulk thereby resulting in latency overhead, power consumption, service rate. This work proposes an energy-efficient method with introduction Fog...

In this work, a particle swarm optimisation (PSO) algorithm with chaotic mutation operator is proposed to solve flexible flow shop scheduling problems. Mutation, commonly used in genetic algorithm, has been introduced so that common problem of trapping solutions at local minima PSO can be avoided. Chaotic sequence using logistic mapping instead random numbers improve the diversity solution space. The performance schedules evaluated terms total completion time or makespan (Cmax). results are...