Energy-efficient deployment of edge dataenters for mobile clouds in sustainable iot

Sambit Kumar Mishra, Deepak Puthal, Bibhudatta Sahoo, Suraj Sharma, Zhi Xue, Albert Y. Zomaya

Research output: Contribution to journalArticlepeer-review

36 Scopus citations


Achieving quick responses with limited energy consumption in mobile cloud computing is an active area of research. The energy consumption increases when a user's request (task) runs in the local mobile device instead of executing in the cloud. Whereas, latency become an issue when the task executes in the cloud environment instead of the mobile device. Therefore, a tradeoff between energy consumption and latency is required in building sustainable Internet of Things (IoT), and for that, we have introduced a middle layer named an edge computing layer to avoid latency in IoT. There are several real-time applications, such as smart city and smart health, where mobile users upload their tasks into the cloud or execute locally. We have intended to minimize the energy consumption of a mobile device as well as the energy consumption of the cloud system while meeting a task's deadline, by offloading the task to the edge datacenter or cloud. This paper proposes an adaptive technique to optimize both parameters, i.e., energy consumption and latency by offloading the task and also by selecting the appropriate virtual machine for the execution of the task. In the proposed technique, if the specified edge datacenter is unable to provide resources, then the user's request will be sent to the cloud system. Finally, the proposed technique is evaluated using a real-world scenario to measure its performance and efficiency. The simulation results show that the total energy consumption and execution time decrease after introducing an edge datacenters as a middle layer.

Original languageBritish English
Article number8476590
Pages (from-to)56587-56597
Number of pages11
JournalIEEE Access
StatePublished - 2018


  • Cloud computing
  • Edge datacenter
  • Energy consumption
  • IoT
  • Latency
  • Mobile computing
  • Task scheduling


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