As the sensor layer of Internet of Things (IOT), enormous amount of sensor nodes are densely deployed in a hostile environment to monitor and sense the changes in the physical space. Since sensor nodes are driven with limited power batteries, it is very difficult and expensive for wireless sensor networks (WSNs) to extend network lifetime. In order to achieve reliable data transmission in WSNs, energy efficient routing protocol is a crucial issue in extending the network lifetime of a network. However, traditional routing protocols usually propagate throughout the whole network to discover a reliable route or employ some cluster heads to undertake data transmission for other nodes, which both require large amount energy consumption. In this paper, to maximize the network lifetime of the WSN, we propose a novel energy efficient region source routing protocol (referred to ER-SR). In ER-SR, a distributed energy region algorithm is proposed to select the nodes with high residual energy in the network as source routing node dynamically. Then, the source routing nodes calculate the optimal source routing path for each common node, which enables partial nodes to participate in the routing process and balances the energy consumption of sensor nodes. Furthermore, to minimize the energy consumption of data transmission, we propose an effective distance-based ant colony optimization algorithm to search the global optimal transmission path for each node. Simulation results demonstrate that ER-SR exhibits higher energy efficiency, and has moderate performance improvements on network lifetime, packet delivery ratio, and delivery delay, compared with other routing protocols in WSNs.

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In dense Wireless Local Area Networks (WLANs), high-density Access Points (APs) bring severe interference that seriously affects the experience of users, resulting in lower throughput and poor connection quality. Due to the heavy computation workload raised by the sizable networking systems and the difficulty in estimating instantaneous Channel State Information (CSI), existing works are hard to solve interference problem. In this paper, we propose a Joint Power control and Channel allocation based on Reinforcement Learning (JPCRL) algorithm combining with statistical CSI to reduce interference adaptively. Firstly, we analyze the correlation between transmit power and channel, and formulate the interference optimization as a Mixed Integer Nonlinear Programming (MINLP) problem. Secondly, we use the statistical CSI method to take the power and channel state as the state and action space, the overall throughput increment as the reward function of Q-learning, and obtain the optimal joint optimization strategy through off-line training. Moreover, for the periodic reinforcement learning process leading to resource consumption, we design an event-driven mechanism of Q-learning, which triggers online learning to refresh the optimal policy by event-driven condition and the consumption of computing resources can be reduced. The evaluation results show that the proposed algorithm can effectively improve the throughput compared with the existing scheme. INDEX TERMS Interference, throughput, reinforcement learning, channel allocation, power control.

IEEE 802.11 wireless LAN is proliferating since the increased trend in the wireless network utilization on mobile devices. Accuracy, fast content delivery, and reliable mobility support are essential features of any network to support the changing trend in a wireless network. However, traditional architectures in wireless LAN (WLANs or WiFi) always endured from challenges such as the provision of consistent mobility, real-time packet flow, and seamless handoff. Generally, most of the WLAN only relies on signal strength for handoff which is not sufficient enough for fair selection of an access point (AP) and therefore causes imperfect performance of the network. We present a novel mobility management scheme for WLANs to deal with the mobility management issues, and load balancing by software-defined network (SDN) and network function virtualization (NFV) technologies. The proposed scheme is based on logical AP ( L AP) that keeps a connection with the user/mobile terminal (MT) during handoff triggered by either the user or the SDN controller for seamless mobility. It also involves the current state of each AP in addition to traditional parameters of WLAN. We implemented the proposed scheme on a real testbed in a WLAN environment. The evaluation results authenticate that our proposed scheme provides robust handover without throughput degradation and load imbalance among adjacent APs, and allocates the best AP in the neighboring region. Moreover, our proposed scheme is feasible to implement since it did not require any modification at the mobile terminal.

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