Cloud Computing

Sustainable Load-Balancing Scheme for Inter-Sensor Convergence Processing of Routing Cooperation Topology

May 2016. By Young-Sik Jeong

Keyword: Sustainable load-balancing, Cloud computing, Convergence processing, Green communication

Figure 1. SLS architecture.

Recent advancements in Information Technology (IT) have sparked the creation of numerous and diverse types of devices and services. Manual data collection measurement methods have been automated through the use of various wireless or wired sensors. Single sensor devices are included in smart devices such as smartphones. Data transmission is critical for big data collected from sensor nodes, such as Mobile Sensor Nodes (MSNs), where sensors move dynamically according to sensor mobility, or Fixed Sensor Nodes (FSNs), where sensor locations are decided by the users. False data transfer processing of big data results in topology lifespan reduction and data transfer delays. Hence, a variety of simulators and diverse load-balancing algorithms have been developed as protocol verification tools for topology lifespan maximization and effective data transfer processing. However, those previously developed simulators have limited functions, such as an event function for a specific sensor or a battery consumption rate test for sensor deployment. Moreover, since the previous load-balancing algorithms consider only the general traffic distribution and the number of connected nodes without considering the current topology condition, the sustainable load-balancing technique that takes into account the battery consumption rate of the dispersed sensor nodes is required.

This research proposes the Sustainable Load-balancing Scheme (SLS), which maximizes the overall topology lifespan through effective and sustainable load-balancing of data transfer among the sensors. SLS is capable of maintaining an effective topology as it considers both the battery consumption rate of the sensors and the data transfer delay.