Resource allocation mechanisms and approaches on the Internet of Things

Abstract

Internet of Things (IoT) as a novel paradigm is an environment with a vast number of connected things and applications. The IoT devices are used to generate data, which transforms into useable information and provides applied resources to end-users and this process is the main goal of IoT. Therefore, one of the important subjects in the IoT is resource allocation which aims is load balancing and minimizing operational cost, and power consuming. In addition, the resources should be allocated in such a way to be a balanced efficiency that can increase the system performance, Quality of Service (QoS) and Service Level Agreement (SLA). Although the resource allocation is very important in the IoT, there is no systematic review in this field. Therefore, in this paper, a Systematic Literature Review (SLR) is provided and the resources allocation methods in the IoT and used algorithms are investigated. Different classification, including cost-aware, context-aware, efficiency-aware, load-balancing-aware, power-aware, QoS-aware, SLA-based and utilization-aware resource allocation mechanisms are organized to investigate the resource allocation techniques. We present several parameters and describe them in each category. In addition, the used parameters in different articles are evaluated and the major developments in each category are surveyed and are outlined the new challenges. Furthermore, an SLR is provided in each of these eight categories. In this paper, a structure of different technical keys in the scope of resource allocation in the IoT and its platforms are presented and the important areas for improving the resource allocation methods in the future is highlighted and the open issues about resource allocation in IoT to achieve a better utilization of this technology are focused. The future direction is useful for academic researchers that work on IoT. This study shows that an independent technique does not exist to address all issues and challenges in resource allocation for IoT.