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The Function-as-a-Service (FaaS) execution model increases developer productivity by removing operational concerns such as managing hardware or software runtimes. Developers, however, still need to partition their applications into FaaS…

Application development in the Internet of Things (IoT) is challenging because it involves dealing with a wide range of related issues such as lack of separation of concerns, and lack of high-level of abstractions to address both the large…

Enhancements in technology always follow Consumer requirements. Consumer requires best of service with least possible mismatch and on time. Numerous applications available today are based on Web Services and Cloud Computing. Recently, there…

Edge-cloud collaborative computing (ECCC) has emerged as a pivotal paradigm for addressing the computational demands of modern intelligent applications, integrating cloud resources with edge devices to enable efficient, low-latency…

Modern applications increasingly span across cloud, fog, and edge environments, demanding orchestration systems that can adapt to diverse deployment contexts while meeting Quality-of-Service (QoS) requirements. Standard Kubernetes…

As computation shifts from the cloud to the edge to reduce processing latency and network traffic, the resulting Computing Continuum (CC) creates a dynamic environment where meeting strict Quality of Service (QoS) requirements and avoiding…

Function-as-a-Service (FaaS) is a promising paradigm for applications distributed across the edge-cloud continuum. FaaS functions are stateless by nature, leading to high elasticity and transparent invocation. Supporting stateful…

The Dynamic Scalability of resources, a problem in Infrastructure as a Service (IaaS) has been the hotspot for research and industry communities. The heterogeneous and dynamic nature of the Cloud workloads depends on the Quality of Service…

In FaaS, users invoke remote functions, which encapsulate service(s). These functions typically need to remotely access a persistent state via external services: this makes the paradigm less attractive in edge systems, especially for IoT…

In the present-day, distributed applications are commonly spread across multiple datacenters, reaching out to edge and fog computing locations. The transition away from single datacenter hosting is driven by capacity constraints in…

The serverless and functions as a service (FaaS) paradigms are currently trending among cloud providers and are now increasingly being applied to the network edge, and to the Internet of Things (IoT) devices. The benefits include reduced…

Internet of Things (IoT) has already proven to be the building block for next-generation Cyber-Physical Systems (CPSs). The considerable amount of data generated by the IoT devices needs latency-sensitive processing, which is not feasible…

Low-Latency IoT applications such as autonomous vehicles, augmented/virtual reality devices and security applications require high computation resources to make decisions on the fly. However, these kinds of applications cannot tolerate…

Motivated by the proliferation of Internet-of-Thing (IoT) devices and the rapid advances in the field of deep learning, there is a growing interest in pushing deep learning computations, conventionally handled by the cloud, to the edge of…

The concept of the Internet of Things (IoT) is a reality now. This paradigm shift has caught everyones attention in a large class of applications, including IoT-based video analytics using smart doorbells. Due to its growing application…

In the edge-cloud continuum, datacenters provide microservices (MSs) to mobile users, with each MS having specific latency constraints and computational requirements. Deploying such a variety of MSs matching their requirements with the…

A distributed application executing on a Network of Workstations (NOW) needs to be resource state aware to possibly adapt itself accordingly in order to keep satisfying the desired Quality of Service (QoS) demands throughout its lifespan.…

With the development of Internet of Things (IoT) and communication technology, the number of next-generation IoT devices has increased explosively, and the delay requirement for content requests is becoming progressively higher.…

Edge computing has become a promising computing paradigm for building IoT (Internet of Things) applications, particularly for applications with specific constraints such as latency or privacy requirements. Due to resource constraints at the…

Over the last decade, the cloud computing landscape has transformed from a centralised architecture made of large data centres to a distributed and heterogeneous architecture embracing edge and IoT units. This shift has created the…