Multidimensional Knapsack Problem for Resource Allocation in a Distributed Competitive Environment Based on Genetic Algorithm

Internet of Things devices, Smart phones and smart cities have been expanding at wide rates which are highly computation resources demand. Classic cloud computing architecture, cannot continue provide the services requirements exploit by IoT services because of network latency, scalability, and network stability. Edge cloud computing had been introduced as a distributed edge cloud paradigm which provides an opportunity for users to obtain cloud resources over the internet. Services providers deploy the services in a distributed manner among the edge servers. However, the challenge is how to allocate the resources for users from different and distributed edge server. An intelligent strategy would provide a proper resource allocation on edge cloud architecture need to be addressed. In this paper, we consider edge computing architecture as an environment in which edge servers willing to invest their available resources and end-users want to utilize the services according to pay-asyou-go paradigm. Since edge servers need to maximize their profit by serving the maximum number of users. This paper present work-in-progress to overcome this challenge by formulating the problem as multi-dimensional knapsack, then genetic algorithm will proposed to get state of the art results and achieve our goal.