Abstract
Mobile edge-cloud computing environments appear as a novel computing paradigm to offer effective processing and storage solutions for delay sensitive applications. Besides, the container based virtualization technology becomes solicited due to its natural lightweight and portability as well as its small migration overhead that leads to seamless service migration and load balancing. However, with the mobility property, the users’ demands in terms of the backhaul bandwidth is a critical parameter that influences the delay constraints of the running applications. Accordingly, a Binary Integer Programming (BIP) optimization problem is formulated. It minimizes the users’ perceived backhaul delays and enhances the load-balancing degree in order to offer more chance to accept new requests along the network. Also, by introducing bandwidth constraints, the available user backhaul bandwidth after the placement are enhanced. Then, the adopted methodology to design two heuristic algorithms based on Ant Colony System (ACS) and Simulated Annealing (SA) is presented. The proposed schemes are compared using different metrics,and the benefits of the ACS-based solution compared to the SA-based as well as a genetic algorithm (GA) based solutions are demonstrated. Indeed, the normalized cost and the total backhaul costs are given by more optimal values using the ACS algorithm compared to the other solutions.
Highlights
Mobile Edge Computing (MEC) is an emerging distributed computing paradigm that can deliver timely services to mobile users [1], [2]
Reduce latency, preserve bandwidth and offer location-awareness, MEC enables computation and storage at the edge of the network using a set of edge nodes (EN)
The set of containers The set of edge-cloud servers The set of links The the total number of containers, servers, resources The set set of sufficient paths connecting servers sj and sj The bandwidth of path pk ∈ Pj,j The hop count of path pk ∈ Pj,j The backhaul bandwidth associated with container ci The operating parameters of container ci The ci demand in terms of resource rm The sj resource usage in terms of resource rm
Summary
Mobile Edge Computing (MEC) is an emerging distributed computing paradigm that can deliver timely services to mobile users [1], [2]. Reduce latency, preserve bandwidth and offer location-awareness, MEC enables computation and storage at the edge of the network using a set of edge nodes (EN) These nodes are resource-rich network cells or edge servers (ES) that are deployed in close proximity of the end-users and offer virtualized services to allow offloading of the mobile applications’ workloads [3]. The use of these applications leads to appear new constraints related to mobility, limited energy, limited computational capacity and short latency. Because of the limitation of the resources involved in the migration which accentuates the constraints and limits the number of possible solutions
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