Abstract
Smart Grid (SG) plays vital role in modern electricity grid. The data is increasing with the drastic increase in number of users. An efficient technology is required to handle this dramatic growth of data. Cloud computing is then used to store the data and to provide numerous services to the consumers. There are various cloud Data Centers (DC), which deal with the requests coming from consumers. However, there is a chance of delay due to the large geographical area between cloud and consumer. So, a concept of fog computing is presented to minimize the delay and to maximize the efficiency. However, the issue of load balancing is raising; as the number of consumers and services provided by fog grow. So, an enhanced mechanism is required to balance the load of fog. In this paper, a three-layered architecture comprising of cloud, fog and consumer layers is proposed. A meta-heuristic algorithm: Improved Particle Swarm Optimization with Levy Walk (IPSOLW) is proposed to balance the load of fog. Consumers send request to the fog servers, which then provide services. Further, cloud is deployed to save the records of all consumers and to provide the services to the consumers, if fog layer is failed. The proposed algorithm is then compared with existing algorithms: genetic algorithm, particle swarm optimization, binary PSO, cuckoo with levy walk and BAT. Further, service broker policies are used for efficient selection of DC. The service broker policies used in this paper are: closest data center, optimize response time, reconfigure dynamically with load and new advance service broker policy. Moreover, response time and processing time are minimized. The IPSOLW has outperformed to its counterpart algorithms with almost 4.89% better results.
Highlights
In the modern era, the traditional grid is converted into Smart Grid (SG) by integrating Information with Communication Technology (ICT) with it
CDC selects the Data Centers (DC), which is closest to the user to minimize latency; the selection of DC in ORT depends on the Response Time (RT); while RDL dynamically selects the DC, either considering distance or response time
This paper considers two different scenarios to evaluate meta-heuristic techniques and service broker policies
Summary
The traditional grid is converted into Smart Grid (SG) by integrating Information with Communication Technology (ICT) with it. To manage the load of PMs and to reduce the energy consumption of physical resources on a cloud, the game-based theory is applied in [5]. Fog computing is introduced by Computer Information System COmpany (CISCO), which is the intermittent layer between cloud and consumer layer [7] All these services are provided on the edge of the network which efficiently balances the load of a cloud. The objective of this paper is to balance the load and minimize the energy consumption of VMs and handle the user’s request efficiently. The open automated demand response protocol is proposed at the home-gateway level, which helps the consumers to manage their energy consumption. To tackle the aforementioned issues, this work is proposed to devise an integrated model for cloud and fog based computing in SG (using nature-inspired algorithm). The aim of this work is to minimize RT of DCs and PT of VMs along with the cost
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