Agent Based Job Classification and Resource Allocation in IoT
Daneshwari I. Hatti, Ashok V. Sutagundar · 2017
Internet of Things (IoT) is combination of things and Internet. Things in IoT communicate via Internet. IoT has several heterogeneous devices and results to many issues. In this work we have proposed agent based job classification and resource allocation in IoT. In the proposed methodology agent uses the Fuzzy Interference System. Agents are defined in two hierarchy namely at Local Processor Agency (LPA) and IoT Cloud Agency (ICA). Agents interact both for job classification and resource allocation. The jobs are classified and divided into subtasks at LPA. These tasks are allocated with sufficient resources available in devices and ICA facilitates resources if LPA does not have sufficient resources. To test the performance, the proposed work is simulated using C++. Some of the performance parameters considered are response time, energy consumption and bandwidth utilization.