We study a wireless powered Internet-of-Things (IoT) network, which consists of spatially distributed energy harvesting (EH) nodes and a hybrid access point (HAP). The energy requirements of exponentially increasing IoT nodes could be fulfilled using the wireless EH. However, the spatiotemporal diversity may affect the performance of wireless EH networks due to the arbitrary information transmissions and varying amount of harvesting energy. In this article, we propose a new access control mechanism based on frame-slotted ALOHA considering the spatiotemporal diversity of nodes for distributed wireless powered IoT networks. In the proposed scheme, the nodes efficiently utilize the available time and power resources to enhance the achievable network throughput. The varying amount of harvested energy due to the harvesting duration and random distance from the power beacon (PB) affects the network performance. The contending nodes for a shared channel, randomly choose slots in a slotted frame, harvest energy, and transmit information using the harvested energy. We analyze the transmission probability of nodes affected by fading channel gains and formulate an optimization problem to find the optimal frame size for the contending number of nodes to maximize the achievable network throughput. The proposed scheme enhances the achievable throughput up to 12.5% and energy efficiency up to 20% over the conventional scheme.

Since the development of Smart Grid (SG), Home Energy Management (HEM) systems are emerged widely into it and consumers have an opportunity to schedule their smart appliances efficiently in smart homes. In this research, meta-heuristic techniques Harmony Search Algorithm (HSA), Pigeon Inspired Optimization (PIO) and our proposed Harmony Pigeon Inspired Optimization (HPIO) are adopted to efficiently schedule smart appliances in smart home. The aim of using the above proposed techniques is to reduce Electricity Cost (EC) and Peak-to-Average Ratio (PAR). HEM is proposed to further evaluate the performance of evaluated techniques. In this work, single home and multiple homes which consist of 10 ,30 and 50 homes are considered equipped with multiple smart appliances. These appliances are divided into three sets, which are thermostatically and non-thermostatically controllable, and non-controllable appliances under Time-ofUse (ToU) pricing scheme. Simulations are carried out on these parameters and results shows that proposed technique HPIO performed better than HSA and PIO in terms of minimizing waiting time and PAR. We have considered User Comfort (UC) in terms of waiting time.