scheduling algorithms for heterogeneous cloud environment: main resource load balancing algorithm and time balancing algorithm

Cloud computing and internet of things (iot) are two of the most important technologies that have significantly changed human’s life. however, with the growing prevalence of cloud-iot paradigm, the load imbalance and higher sla lead to more resource wastage and energy consumption. although there are many researches that study cloud-iot from the perspective of offloading side, few of them have focused on how the offloaded workload are dealt with in cloud. this paper proposes two iot-aware multi-resource task scheduling algorithms for heterogeneous cloud environment namely main resource load balancing and time balancing. the algorithms aim to obtain better result of load balance, service-level agreement (sla) and iot task response time and meanwhile to reduce the energy consumption as much as possible. they both are devised to assign single task to a properly selected virtual machine (vm) each time. the task placed in a pre-processed queue is assigned sequentially each time. and the vm selection rule is carried out based on the newly inventive ideas called relative load or relative time cost. besides, two customized parameters that influence the result of pre-process tasks are provided for users or administrators to flexibly control the behavior of the algorithms. according to the experiments, the main resource load balancing performs well in terms of sla and load balance, while time balancing is good at saving time and energy. besides, both of them perform well in iot task response time.