QoS-Based Elasticity for Service Chains in Distributed Edge Cloud Environments

Abstract

With the emerging IoT and Cloud-based networked systems that rely heavily on virtualization technologies, elasticity becomes a dominant system engineering attribute for providing QoS-aware services to their users. Although the concept of elasticity can introduce significant QoS and cost benefits, its implementation in real systems is full of challenges. Indeed, nowadays systems are mainly distributed, built upon several layers of abstraction, and with centralized control mechanisms. In such a complex environment, controlling elasticity in a centralized manner might strongly penalize scalability. To overcome this issue, we can conveniently split the system in autonomous subsystems that implement elasticity mechanisms and run control policies in a decentralized manner. To efficiently and effectively cooperate with each other, the subsystems need to communicate among themselves to determine elasticity decisions that collectively improve the overall system performance. This new architecture calls for the development of new mechanisms and efficient policies. In this chapter, we focus on elasticity in IoT and Cloud-based systems, which can be geo-distributed also at the edge of the networks, and discuss its engineering perspectives along with various coordination mechanisms. We focus on the design choices that may affect the elasticity properties and provide an overview of some decentralized design patterns related to the coordination of elasticity decisions.

SLedge: Scheduling and Load Balancing for a Stream Processing EDGE Architecture

“…With multiple control loops, we can work at different time scales and manage different resources or different kinds of resources. This pattern provides a layered separation of concerns to manage the elasticity of complex systems [28]. Such hierarchical design allows overcoming the system bottleneck represented by the centralized components of the MAPE loop in the master-slave pattern for its application to elastic data stream processing, especially when the system is composed of a multitude of processing entities scattered in a large-scale geo-distributed environment [29].…”

Landscape of Architecture and Design Patterns for IoT Systems

“…Fourteen papers [18], [21], [23], [26], [27], [35], [37], [39], [41]- [43], [46], [48], [49] only used non-IoT patterns. These results indicate that IoT systems and software are often designed via conventional architecture and design patterns that are not specific to IoT design.…”