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Collaborative resource allocation for Cloud of Things systems
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DOI：10.1016/j.jnca.2020.102592.png)
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Abstract
En 中文
The conceptual approach known as Fog/Edge Computing has recently emerged, aiming to move part of the computing and storage resources from the cloud to the edge of the network. The combination of IoT devices, edge nodes, and the Cloud gives rise to a three-tier Cloud of Things (CoT) architecture. In the complex and dynamic CoT ecosystems, a key issue is how to efficiently and effectively allocate resources to meet the demands of applications. Similar to traditional clouds, the goal of resource allocation in the CoT is to maximize the number of applications served by the infrastructure while ensuring a target operational cost. We propose a resource allocation algorithm for CoT systems that (i) supports heterogeneity of devices and applications, (ii) leverages the distributed nature of edge nodes to promote collaboration during the allocation process and (iii) provides an efficient usage of the system resources while meeting latency requirements and considering different priorities of IoT applications. Our algorithm follows a heuristic-based approach inspired on an economic model for solving the resource allocation problem in CoT. A set of simulations were performed, with promising results, showing that our collaborative resource allocation algorithm is more scalable, reduces the response time for applications and the energy consumption of end devices, in comparison to a two-tier, Cloud-based approach. Moreover, the network traffic between edge nodes, and between the Edge and Cloud tiers, is considerably smaller when using our collaborative solution, in comparison to other evaluated approaches.
Keywords:
Collaborative work
Edge computing
Internet of things
Resource allocation
Data freshness
Hierarchical
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